bluuebunny/crossref_metadata_2025 huggingface dataset:
Sexual Dimorphism of Plasma and Tissue Proteomes in Human Calcific Aortic Valve Stenosis Pathogenesis
Authors: Clift Cassandra L. , Blaser Mark C. , Bartoli-Leonard Francesca , Schlotter Florian , Higashi Hideyuki , Kuraoka Shiori , Kasai Taku , Turner Mandy E. , Pham Tan , Perez Katelyn A. , Robson Simon C. , Body Simon C. , Muehlschlegel Jochen D. , Aikawa Masanori , Singh Sasha A. , Aikawa Elena
Published: January 2025

BACKGROUND

Calcific aortic valve stenosis (CAVS) is a global clinical burden, impacting around 2% of the population over 65 years of age. No pharmacotherapeutics exist, with surgical repair and transcatheter valve replacement being the only intervention. Females are underrepresented in studies of CAVS, leading to delay in timely intervention and increased mortality. Histopathology demonstrates female CAVS presents with decreased valvular calcification but increased fibrosis and severity of symptoms. We hypothesize that the underlying molecular mechanisms contributing to disease progression and fibrocalcific burden in AS differs between male and female patients. Our goal for this study is to use previously acquired proteomic datasets of a clinically-defined human AS cohort to examine sex disparities and underlying sex-specific disease signatures.

METHODS and RESULTS

Age-matched human AS tissue samples (n=4 females, n=14 males) were each segmented into non-diseased, fibrotic, and calcified disease stages and analyzed using LC-MS/MS proteomics and quantitative histopathology. CAVD plasma samples (n=20 females, n=30 males) were analyzed for circulating sex-specific biomarkers via LC-MS/MS. Unbiased principal component analysis shows sex- and stage-specific proteome clustering. AS pathogenesis drove sex-specific disparities in the valvular proteome: 338/1503 total proteins were differentially-enriched by sex across disease stages. Compared to sex-specific non-diseased controls, female fibrotic tissue resulted in 2.75-fold greater number of differentially-enriched proteins than did male fibrotic tissue (female: 42, male: 16; p<0.05 threshold). In contrast, female calcific tissue identified 2.473-fold less differentially-enriched proteins than male calcific tissue (female: 157, male 356; q<0.05 threshold). By Functional Enrichment Analysis revealed specific proteins responsible for the exacerbated valvular fibrosis signature in females, implicated adenosine phosphate metabolism as a potential male-specific driver of AS, and further reinforce the shared contribution of aberrant lipid and cholesterol activity to AS progression in both sexes.

CONCLUSIONS

We reveal a sexually-dimorphic AS proteome, including the novel overabundance of ECM remodeling pathways in female calcified aortic valve tissues. This analysis allows for identification of potential sex-specific protein drug targets implicated in AS pathobiology.
NOTCH1 S2513 is critical for the regulation of NICD levels impacting the segmentation clock in hiPSC-derived PSM cells and somitoids
Authors: Meijer Hedda A. , Hetherington Adam , Johnson Sara , Gallagher Rosie L. , Hussein Izzah N. , Rae Jess M. , Noordzij Tomas E.J.C. , Kalamara Margarita , Macartney Thomas J. , Davidson Lindsay , Martin David M.A. , Davies Paul , Sonnen Katharina F. , Murray Philip , Dale J. Kim
Published: January 2025

The segmentation clock is a molecular oscillator that regulates the timing of somite formation in the developing vertebrate embryo. NOTCH signalling is one of the key pathways required for proper functioning of the segmentation clock. Aberrant NOTCH signalling results in developmental abnormalities such as congenital scoliosis as well as diseases such as T-cell acute lymphoblastic lymphoma (T-ALL). In this study we analyse the effects of a mutation detected in T-ALL patients on somitogenesis using human iPS derived PSM cells and somitoids. Mutation of NOTCH1 Serine 2513 into Alanine compromises the interaction of Notch intracellular domain (NICD) with the F-box protein FBXW7 and consequently increases NICD stability and NICD levels in PSM cells. Moreover, the mutation impairs several aspects of clock gene oscillations and restricts the ability of somitoids to polarise, elongate and form paired somites. The data suggest a mechanism by which post-translational modification of a key segmentation clock component plays a crucial role in vertebrate axis segmentation.
Genomic divergence shaped the genetic regulation of meiotic homologous recombination inBrassicaallopolyploids
Authors: Pelé Alexandre , Falque Matthieu , Lodé-Taburel Maryse , Huteau Virginie , Morice Jérôme , Coriton Olivier , Martin Olivier C. , Chèvre Anne-Marie , Rousseau-Gueutin Mathieu
Published: January 2025

The tight regulation of meiotic recombination between homologs is disrupted inBrassicaAAC allotriploids, a genomic configuration that may have facilitated the formation of rapeseed (Brassica napusL.) ∼7,500 years ago. Indeed, the presence of the haploid C genome induces supernumerary crossovers between homologous A chromosomes with dramatically reshaped distribution. However, the genetic mechanisms driving this phenomenon and their divergence between nascent and established lineages remain unclear. To address these concerns, we generated hybrids carrying additional C chromosomes derived either from an established lineage of the allotetraploidB. napusor from its diploid progenitorB. oleracea. We then assessed recombination variation across twelve populations by mapping male meiotic crossovers using Single Nucleotide Polymorphism markers evenly distributed across the sequenced A genome. Our findings reveal that the C09 chromosome ofB. oleraceais responsible for the formation of additional crossovers near pericentromeric regions. Interestingly, its counterpart from an established lineage ofB. napusshows no significant effect on its own, despite having a similar content of meiotic genes. However, we showed that theB. napusC09 chromosome influences crossover formation through inter-chromosomal epistatic interactions with other specific C chromosomes. These results provide new insights into the genetic regulation of homologous recombination inBrassicaand emphasize the role of genomic divergence since the formation of the allopolyploidB. napus.
Tempo and mode of evolution across multiple traits in an adaptive radiation of birds (Vangidae)
Authors: Auerbach Anya Lilith Becker , Lim Euan Horng Jiunn , Reddy Sushma
Published: January 2025

An ongoing challenge in macroevolutionary research is identifying common drivers of diversification amid the complex interplay of many potentially relevant traits, ecological contexts, and intrinsic characteristics of clades. In this study, we used geometric morphometric and phylogenetic comparative methods to evaluate the tempo and mode of trait evolution in the adaptive radiation of Malagasy vangas and their mainland relatives. The Malagasy radiation is more diverse in both skull and foot shape. However, rather than following the classic “early burst” of diversification, trait evolution accelerated well after their arrival in Madagascar, likely driven by the evolution of new modes of foraging and especially of a few species with highly divergent morphologies. Each anatomical region showed differing evolutionary patterns, and the presence of morphological outliers impacted the results of some analyses, particularly of integration and modularity. Our results demonstrate that the adaptive radiation of Malagasy vangas has evolved exceptional ecomorphological diversity along multiple, independent trait axes, mainly driven by a late expansion in niche space due to key innovations. Our findings highlight the evolution of extreme forms as an overlooked feature of adaptive radiation warranting further study.
Carrying oversized loads may create pheromone “blind spots” in leafcutter ants
Authors: Porras-Brenes Katherine , Amador-Vargas Sabrina
Published: January 2025

Understanding animals’ sensorial abilities and cognitive processes while foraging helps explain why animals depart from theoretical optimal foraging. Here, we studied foraging decisions in leafcutter ants (Atta colombica), which form and follow pheromone foraging trails that workers smell by tapping the substrate with the antennae. Carrying oversized items transports more plant material in a single trip, but workers walk more slowly and can delay the nestmates walking behind them. We tested the hypothesis that balancing an oversized load limits the ability to tap the ground with the antennae, therefore reducing the ability to smell the foraging trail. As expected, we found that the number of antennae taps per step was (1) fewer in laden vs. unladen workers, (2) fewer as loads increased in area, but only for larger ants, and (3) unrelated to the load shape. Second, workers increased the antennae taps and speed after experimentally reducing standardized loads. Last, we evaluated the allometric relation between the antennae length and worker size, and found that it showed negative allometry. Hence, larger ants had proportionally shorter antennae, which could explain why larger workers are more impacted by oversized loads in the number of antennae taps. Overall, our results support that carrying an oversized load limits the ability of workers to tap the ground, analogous to the blind spots in a large truck. Our findings reveal a sensory limitation to foraging and reflect how foraging decisions in a social organism are adjusted to the individual capacities and the colony needs.
Causal disentanglement for single-cell representations and controllable counterfactual generation
Authors: Gao Yicheng , Dong Kejing , Shan Caihua , Li Dongsheng , Liu Qi
Published: January 2025

Conducting disentanglement learning on single-cell omics data offers a promising alternative to traditional black-box representation learning by separating the semantic concepts embedded in a biological process. We present CausCell, which incorporates the causal relationships among disentangled concepts within a diffusion model to perform disentanglement learning, with the aim of increasing the explainability, generalizability and controllability of single-cell data, including spatial and temporal omics data, relative to those of the existing black-box representation learning models. Two quantitative evaluation scenarios, i.e., disentanglement and reconstruction, are presented to conduct the first comprehensive single-cell disentanglement learning benchmark, which demonstrates that CausCell outperforms the state-of-the-art methods in both scenarios. Additionally, CausCell can implement controllable generation by intervening with the concepts of single-cell data when given a causal structure. It also has the potential to uncover biological insights by generating counterfactuals from small and noisy single-cell datasets.
miRScore: a rapid and precise microRNA validation tool
Authors: Vanek Allison , Griffiths-Jones Sam , Meyers Blake C. , Shahid Saima , Axtell Michael J.
Published: January 2025

MicroRNAs (miRNAs) are small non-protein-coding RNAs that regulate gene expression in many eukaryotes. Next-generation sequencing of small RNAs (small RNA-seq) has accelerated discovery and annotation of novel miRNAs. Newly discovered miRNAs are typically submitted to databases such as the miRBase microRNA registry following the publication of a peer-reviewed study. However, genome-wide scans using small RNA-seq data often yield high rates of false-positive miRNA annotations, highlighting the need for more robust validation methods. miRScore was developed as an independent and efficient tool for evaluating miRNA annotations using sRNA-seq data. miRScore combines structural and expression-based analyses to provide rapid and reliable validation of miRNA annotations. By providing users with detailed metrics and visualization, miRScore enhances the ability to assess confidence in novel and existing miRNA annotations. miRScore has the potential to advance the overall quality of miRNA annotations by improving accuracy of new submissions to miRNA databases and serving as a resource for re-evaluating existing annotations.
PepMSND: Integrating Multi-level Feature Engineering and Comprehensive Databases to Enhance in vivo/in vitro Peptide Blood Stability Prediction
Authors: Haomeng Hu , Zhang Chengyun , Zhenyu Xu , Duan Hongliang
Published: January 2025

Deep learning technology has revolutionized the field of peptides, but key questions such as how to predict the blood stability of peptides remain. While such a task can be accomplished by experiments, it requires much time and cost. Here, to address this challenge, we collect extensive experimental data on peptide stability in blood from public databases and literature and construct a database of peptide blood stability that includes 635 samples. Based on this database, we develop a novel model called PepMSND, integrating KAN, Transformer, GAT and SE(3)-Transformer to make multi-level feature engineering to make peptide stability prediction. Our model can achieve the ACC of 0.8672 and the AUC of 0.9118 on average and outperforms the baseline models. This work can facilitate the development of novel peptides with strong stability, which is crucial for their therapeutic use in clinical applications.
A questionnaire for a conceptual framework and interdisciplinary public health research using the Delphi technique – development and validation
Authors: Alaze Anita , Finne Emily , Batram-Zaantvoort Stephanie , Razum Oliver , Miani Céline
Published: January 2025

Background

The Delphi technique has become established in public health research, yet there is a lack of methodological standards in questionnaire development. We here demonstrate how the Delphi technique can be used in an interdisciplinary public health topic for framework development, and we highlight methodological challenges and possible solutions.

Methods

We developed the questionnaire through a comprehensive literature review and the generation of an item pool based on the rules of item construction. We used cognitive interviews, Delphi experts’ assessment and group discussions to refine the questionnaire and to ensure content validity. Finally, we pre-tested the online questionnaire on LimeSurvey.

Results

The questionnaire consists of three main sections, namely gender (norms), the social environment and the mental health of adolescents, and another section on the expert’s characteristics. The questionnaire comprises a total of 32 questions and includes rating and ranking questions, contentrelated and comment questions, open and closed questions as well as questions on personal characteristics and evaluation questions.

Conclusion

Interdisciplinary researchers need to be involved in the development process of the questionnaire to address challenges related to interdisciplinarity. Researchers using the Delphi technique should consider certain aspects of the development process, such as comprehensively preprocessing the content, disentangling the theoretical concepts, reducing the complexity, providing more structure and clarity, and ensuring that the length of the questionnaire is manageable. Future research should focus on developing methodological guidelines and testing their applicability for different objectives of the Delphi technique (e.g. framework development).
Immunohistochemical Profiling of Histone Modification Biomarkers Identifies Subtype-Specific Epigenetic Signatures and Potential Drug Targets in Breast Cancer
Authors: Huo Zirong , Zhang Sitong , Su Guodong , Cai Yu , Chen Rui , Jiang Mengju , Yang Dongyan , Zhang Shengchao , Xiong Yuyan , Zhang Xi
Published: January 2025

Background:Breast cancer (BC) subtypes exhibit distinct epigenetic landscapes, with triple-negative breast cancer (TNBC) lacking effective targeted therapies. This study investigates histone biomarkers and therapeutic vulnerabilities across BC subtypes.Methods:Immunohistochemical profiling of >20 histone biomarkers, including histone modifications, modifiers and oncohistone mutations was conducted on a discovery cohort and a validation cohort of BC tissues, healthy controls and cell line models. Transcriptomic and cell growth analyses were conducted to evaluate the effects of the small-molecule G9a inhibitor in diverse BC models.Results:Key histone biomarkers, including H3K9me2, H3K36me2, and H3K79me, were differentially expressed across BC subtypes. H3K9me2 emerged as an independent predictor for distinguishing TNBC from other less aggressive BC subtypes, with elevated expression correlating with higher tumor grade and stage. G9a inhibition impaired cell proliferation and modulated epithelial-mesenchymal transition pathways, with the strongest impact in basal-like TNBC. Disruption of oncogene and tumor suppressor regulation (e.g., TP53, SATB1) was observed in TNBC.Conclusion:This study highlights G9a’s context-dependent roles in BC, supporting its potential as a therapeutic target. Findings provide a foundation for subtype-specific epigenetic therapies to improve outcomes in aggressive BC subtypes.

Clinical Perspective

This study was undertaken to explore the epigenetic landscape of breast cancer subtypes, focusing on histone modifications and their therapeutic potential, particularly through targeting G9a, a histone methyltransferase.

The study identified subtype-specific histone biomarkers, with H3K9me2 emerging as a key marker distinguishing TNBC from other less aggressive subtypes. G9a inhibition demonstrated robust anti-cancer effects, including cell proliferation impairment and disruption of oncogenic pathways, particularly in TNBC models.

These findings provide compelling evidence for the development of subtype-specific epigenetic therapies targeting G9a and similar regulators, highlighting their potential to reshape the treatment landscape for TNBC and improve patient outcomes.
Insular cortex encodes task alignment
Authors: Niediek Johannes , Jankowski Maciej M. , Polterovich Ana , Kazakov Alexander , Nelken Israel
Published: January 2025

Animals can learn complex behaviors. Animal behavior in the lab has traditionally been studied via summary statistics such as trial-based success rates. However, animal behavior is much more fine-grained: a trial in an experiment often consists of multiple actions, and more than one strategy can lead to a successful completion of a trial. To understand how the brain controls behavior, a fine-grained yet compact description of behavior is necessary.

We describe here an approach for estimating the strategies animals use for a large family of tasks from first principles. Using reinforcement learning with informational constraints on policies, we compute a rich set of candidate policies with a small number of meaningful parameters, and match observed behavior to these policies. In a sample rat task, our approach revealed ongoing learning for more than 100 days after the saturation of success rates. Moreover, we showed that many neurons in the insular cortex of rats track the instantaneous task engagement of the rats with a resolution of a few minutes.

Due to its generic formulation in reinforcement learning terminology, our work is directly applicable to the majority of animal tasks in use today.
Bees flexibly adjust learning strategies to information content in a foraging task
Authors: Spaethe Johannes , Hutzenthaler Selma , Dietz Alexander , Gehrig Karl , Foster James , Stöckl Anna
Published: January 2025

When making decisions, humans and animals often rely on multiple sensory cues simultaneously. These provide complementary sources of information, which can help overcome ambiguity and noise, and increase the accuracy of decisions. While most studies have focused on the benefits of multimodal and within-mode integration for learning and decision making, their costs have received less attention. Processing, learning and memorizing multiple inputs requires more neural resources than for single cues, and might also require more time. In this study, we tested whether insects trade off the costs and benefits of learning multiple cues in a foraging task, using the buff-tailed bumblebeeBombus terrestris. To maximize comparability between cues, we presented combinations of visual-only features, as found on natural flowers: colours of varying discriminability, paired with shapes or patterns. We found that the bees relied exclusively on colours when these were easy to discriminate, and did not learn pattern or shape features presented simultaneously. With harder to discriminate colours, the bees learned both colour and shape or pattern features. Our results demonstrate that bumblebees flexibly adjust their learning strategies when presented with visual features of varying discriminability, to balance the costs and benefits of multi-cue learning. Our analysis of the learning rates of the bees with multi- and single attribute stimuli suggests that blocking could serve as a mechanism to implement this strategy switch. These results shed light on trade-offs in learning and decision making with multiple cues, and can directly be compared to studies in other insects, animals and humans.

Significance Statement

When making decisions, animals often rely on multiple sensory cues simultaneously. These complementary sources of information can increase decision accuracy. Unlike the benefits of cue integration, their costs have received less attention. In this study, we tested whether insects trade off the costs and benefits of learning multiple cues in a foraging task. We trained buff-tailed bumblebees,Bombus terrestris, to feature combinations of natural flowers. Bees flexibly switched from linear integration to winner-takes-all decision strategies depending on the sensory information available, thereby balancing accuracy and time investment in the task. We find that this switch can be explained by the cognitive phenomenon of blocking; providing the ground for future investigations into the underlying neural mechanisms of flexible decision strategies.
Notch signaling maintains a progenitor-like subclass of hepatocellular carcinoma
Authors: Seidel Kerstin , Piskol Robert , Thao Nguyen Thi Thu , Shelton Amy , Cottonham Charisa , de la Cruz Cecile C. , Castillo Joseph , Garcia Jesse , Segal Udi , Merchant Mark , Yang Yeqing Angela , Chen Jasmine , Ahmed Musa , Scherl Alexis , Vij Rajesh , Mosteiro Lluc , Wu Yan , Modrusan Zora , Metcalfe Ciara , Siebel Chris
Published: January 2025

Hepatocellular carcinomas (HCCs) constitute one of the few cancer indications for which mortality rates continue to rise. While Notch signaling dictates a key progenitor lineage choice during development, its role in HCC has remained controversial. Using therapeutic antibodies targeting Notch ligands and receptors to screen over 40 patient-derived xenograft models, we here identify progenitor-like HCCs that crucially depend on a tumor-intrinsic JAG1-NOTCH2 signal. Inhibiting this signal induces tumor regressions by triggering progenitor-to-hepatocyte differentiation, the same cell fate-switch that Notch controls during development. Transcriptomic analysis places the responsive tumors within the well-characterized progenitor subclass, a poor prognostic group of highly proliferative tumors, providing a diagnostic method to enrich for Notch-dependent HCCs. Furthermore, single-cell RNA sequencing uncovers a heterogeneous population of tumor cells and reveals how Notch inhibition shifts cells from a mixed cholangiocyte-hepatocyte lineage to one resembling mature hepatocytes. Analyzing the underlying transcriptional programs brings molecular detail to this process by showing that Notch inhibition de-represses expression of CEBPA, which enables the activity of HNF4α, a hepatocyte lineage factor that is otherwise quiescent. We thus describe a compelling and targetable dependency in a poor-prognosis class of HCCs.
Accelerometer-derived classifiers for early detection of degenerative joint disease in cats
Authors: Montout A.X. , Maniaki E , Burghardt T. , Hezzell M. J. , Blackwell E. , Dowsey A.W.
Published: January 2025

Decreased mobility is a clinical sign of degenerative joint disease (DJD) in cats, which is highly prevalent, with 61% of cats aged six years or older showing radiographic evidence of DJD. Radiographs can reveal morphological changes and assess joint degeneration, but they cannot determine the extent of pain experienced by cats. Additionally, there is no universal objective assessment method for DJD-associated pain in cats. Developing an accurate evaluation model could enable earlier treatment, slow disease progression, and improve cats’ well-being.

This study aimed to predict early signs of DJD in cats using accelerometers and machine learning techniques. Cats were restricted to indoors or limited outdoor access, including being walked on a lead or allowed into enclosed areas for short periods. Fifty-six cats were fitted with collar-mounted sensors that collected accelerometry data over 14 days, with data from 51 cats included in the analysis. Cat owners assessed their cats’ mobility and assigned condition scores, validated through clinical orthopaedic examinations. The study group comprised 24 healthy cats (no owner-reported mobility changes) and 27 unhealthy cats (owner-reported mobility changes, suggestive of early DJD). Data were segmented into 60-second windows centred around peaks of high activity. Using a Support Vector Machine (SVM) algorithm, the model achieved 78% (confidence interval: 0.65, 0.88) area under the curve (AUC), with 68% sensitivity (0.64, 0.77) at 75% specificity (0.68, 0.79).

These results demonstrate the potential of accelerometry and machine learning to aid early DJD diagnosis and improve management, offering significant advances in non-invasive diagnostic techniques for cats.
Postural control in an upright snake
Authors: Hoffmann Ludwig A. , Bryde Petur , Davenport Ian C. , Prasath S Ganga , Jayne Bruce C. , Mahadevan L
Published: January 2025

Posture and its control are fundamental aspects of animal behavior that capture the complex interplay between sensorimotor activity driven by muscular forces and mediated by environmental feedback. An extreme example of this is seen in brown tree snakes and juvenile pythons, which can stand almost upright, with 70% of their body length in the air. We quantify experimental observations of this behavior and present a minimal theoretical framework for postural stability by modeling the snake as an active elastic filament whose shape is controlled by muscular forces. We explore two approaches to characterize the musculature needed to achieve a specific posture: proprioceptive feedback (whereby the snake senses and reacts to its own shape) and a control-theoretic optimization approach (whereby the snake minimizes the expended energy to stand up), and also analyze the dynamic stability of the snake in its upright pose. Our results lead to a three-dimensional postural stability diagram in terms of muscle extent and strength, and gravity, consistent with experimental observations. In addition to general predictions about posture control in animals, our study suggests design principles for robotic mimics.
Random connectivity generates inhibitory microcircuits that decorrelate adaptation in visual cortex
Authors: Kosiachkin Y. , Hinojosa A. J. , Dominiak S.E. , Evans B. , Lagnado L.
Published: January 2025

Inhibitory neurons are fundamental to sensory processing in the cortex but the rules governing their connections with excitatory neurons are unclear. Are pyramidal cells with different functions generated through specific or random connections? We used two-photon imaging, optogenetics and modelling to investigate opposing forms of adaptation in layer 2/3 of mouse visual cortex. We find that a slow modulatory drive acts differentially depending on the relative strength of inputs that individual pyramidal cells receive from parvalbumin-positive and somatostatin-positive interneurons. The number of depressing and sensitizing pyramidal cells could be explained quantitatively by the simplest connectivity rule – all inhbitory synapses made randomly. The functional heterogeneity of the pyramidal cell population therefore begins with general statistics of the connectome - interneurons are much sparser and connect with probabilities far less than one. The resulting “patchwork” of inhibitory microcircuits causes modulatory inputs to strongly decorrelate pyramidal cells on the behavioural time-scale of seconds.
Early-life adversity mediates a thalamo-amgydalar circuit dysfunction underlying chronic pain and anxiety
Authors: Borruto Anna Maria , Kohlund Tabea , von Renesse Martin , Rettig Lukas , Leonhardt Nikolas , Calpe-López Claudia , Benn Luca , Friederich Hans-Christoph , Kuner Rohini , Kuner Thomas , Spanagel Rainer , Wieland Sebastian
Published: January 2025

Childhood adversity increases the risk of developing a vicious cycle of chronic pain and comorbid anxious avoidance, yet the underlying biological mechanisms remain unclear. Here, we investigated the role of a brain circuit from the paraventricular thalamus (PVT) to the central amygdala (CeA) in mediating hyperalgesia and comorbid anxiety following early life stress. Using a vulnerability-stress model, we exposed both male and female mice to early social isolation (vulnerability) followed by nerve injury (stress) and showed increased hyperalgesia and anxious avoidance behavior in nerve-injured female mice following early adversity. Chemogenetic, electrophysiological, and optophysiological analyses revealed a causal contribution of a hyperexcitable PVT-CeA circuit dysfunction to chronic hyperalgesia and anxiety in nerve-injured female mice after early life stress. Our findings reveal a neural mechanism linking childhood adversity to chronic pain and anxiety, and suggest that reprogramming this pathway may reverse the impact of childhood adversity.
Advances in culturing of the sea starPatiria miniata
Authors: Barone Vanessa , Coronado Luisa , Ismail Deka , Fiaz Sareen , Lyons Deirdre C.
Published: January 2025

The use of the sea starPatiria miniataas a model system has produced groundbreaking advances in a disparate set of biomedical research fields, including embryology, immunology, regeneration, cell biology and evolution of development. Nonetheless, the life cycle ofP. miniatahas not yet been closed in the laboratory, precluding the generation of stable transgenic and mutant lines, which would greatly expand the toolset for experimentation with this model system. RearingP. miniatain the laboratory has been challenging due to limited knowledge about metamorphosis cues, feeding habits of juveniles and their relatively long generation time. Here we report protocols to rearP. miniataembryos through sexual maturity in a laboratory setting. We provide detailed staging of early embryonic development at different temperatures, and show that larvae can be raised to competence in as little as 15 days. We find that retinoic acid induces metamorphosis effectively and present methods to rear juveniles on commercially available foods. We show that in a flow-through system, juveniles double in size every 2 months and reach sexual maturity in approximately 2 years. We report the first example ofP. miniataraised through sexual maturity in a laboratory setting, paving the way for the generation of stable mutant sea star lines.
Exploring simultaneous production of polyhydroxybutyrate and exopolysaccharides in cyanobacteria-rich microbiomes
Authors: Altamira-Algarra Beatriz , García Joan , Torres Cristiana A. V. , Reis Maria A.M. , Gonzalez-Flo Eva
Published: January 2025

The aim of this study was to explore the viability of the dual production of polyhydroxybutyrate (PHB) and exopolysaccharides (EPS) by seven microbiomes rich in cyanobacteria. Our initial experiments involved to screen for EPS-producing candidates and examine the impact of salinity and acetate on EPS synthesis. Salinity’s known influence on EPS production and acetate’s role in enhancing PHB production guided our parameter selection. Surprisingly, neither the introduction of an external carbon source (acetate) nor exposure to an abiotic stressor (salt) significantly altered EPS synthesis rates, which ranged from 25 to 150 mg·L-1, or its composition, with glucose being the dominant sugar component. Scaling up to a 3 L photobioreactor, we achieved simultaneous biopolymer production, reaching up to 205 mg·L-1EPS and 87 mg·L-1PHB. Additionally, the presence of uronic acid in the EPS facilitated biomass flocculation, streamlining the separation process, and potentially reducing associated time and costs.
Kinetic-model-guided engineering of multipleS. cerevisiaestrains improvesp-coumaric acid production
Authors: Narayanan Bharath , Jiang Wei , Wang Shengbao , Sáez-Sáez Javier , Weilandt Daniel , Barcon Maria Masid , Hesselberg-Thomsen Viktor , Borodina Irina , Hatzimanikatis Vassily , Miskovic Ljubisa
Published: January 2025

The use of kinetic models of metabolism in design-build-learn-test cycles is limited despite their potential to guide and accelerate the optimization of cell factories. This is primarily due to difficulties in constructing kinetic models capable of capturing the complexities of the fermentation conditions. Building on recent advances in kinetic-model-based strain design, we present the rational metabolic engineering of anS. cerevisiaestrain designed to overproducep-coumaric acid (p-CA), an aromatic amino acid with valuable nutritional and therapeutic applications. To this end, we built nine kinetic models of an already engineeredp-CA-producing strain by integrating different types of omics data and imposing physiological constraints pertinent to the strain. These nine models contained 297 mass balances involved in 303 reactions across four compartments and could reproduce the dynamic characteristics of the strain in batch fermentation simulations. We used constraint-based metabolic control analysis to generate combinatorial designs of 3 enzyme manipulations that could increase p-CA yield on glucose while ensuring that the resulting engineering strains did not deviate far from the reference phenotype. Among 39 unique designs, 10 proved robust across the phenotypic uncertainty of the models and could reliably increasep-CA yield in nonlinear simulations. We implemented these top 10 designs in a batch fermentation setting using a promoter-swapping strategy for down-regulations and plasmids for up-regulations. Eight out of the ten designs produced higherp-CA titers than the reference strain, with 19 – 32% increases at the end of fermentation. Importantly, these eight designs also maintained at least 90% of the growth of the reference strain; this indicates the importance of the phenotypic constraint. The high success rate of our in-silico designs in an experimental setting demonstrates the potential and utility of kinetic-model-based strain design. This work sets the foundation for accelerated design-build-test-learn cycles using large-scale kinetic models as a scaffold.
Refining Muscle Morphometry Through Machine Learning and Spatial Analysis
Authors: Ono Daisuke , Kawai Honami , Kuwahara Hiroya , Yokota Takanori
Published: January 2025

Aims

Muscle morphology provides important information in differentiating the disease aetiology, but its measurement remains challenging due to the lack of an efficient and objective method. This study aimed to quantitatively refine the morphological features of muscle fibres in neuromuscular diseases using machine learning.

Methods

This retrospective study analysed muscle biopsy specimens on hematoxylin and eosin-staining. A machine learning-based software was developed to segment muscle fibre contours and perform automated muscle morphometry and subsequent graph theory-based spatial analysis of atrophied fibre grouping. A decision tree-based framework, LightGBM, was trained to predict underlying aetiologies based on the morphometric and spatial variables.

Results

The study included 100 muscle samples, including 20 normal muscles, 49 myopathies, and 19 neuropathies. The fine-tuned segmentation model, YOLOv8, achieved a mask average precision of 0.819. The muscle morphometry revealed the significance of fibre circularity. The mean circularity was higher in the myopathy group, and the SD of circularity was elevated in the neuropathy group. Although most cases were consistent with textbook findings, atypical presentations, such as dermatomyositis with angular atrophy and amyotrophic lateral sclerosis with round atrophy, were objectively documented. Spatial analysis quantified grouped atrophy, showing the potential to feature specific atrophy patterns. The LightGBM model successfully predicted the final clinical diagnosis of the myopathies and neuropathies with an accuracy of 0.852, which exceeded that of 0.808 by human annotation.

Conclusion

Automated muscle morphometry and spatial analysis provided the quantification of muscle morphology and atrophy patterns, which will facilitate objective and efficient investigation of neuromuscular diseases.

Key Points

This study aimed to quantitatively refine the morphological features of muscle fibres in neuromuscular diseases using machine learning-based software.

Automated muscle morphometry successfully characterised myopathies and neuropathies, presenting the utility of circularity for their differentiation.

Spatial analysis based on graph theory proposed quantitative definitions for grouped atrophy and perifascicular atrophy, which showed the potential to feature the grouping patterns of atrophic fibres.

This open-source tool will facilitate objective and efficient investigation of neuromuscular diseases.
Two-week supplementation ofBifidobacterium adolescentisiVS-1 reduces fecal urgency and diarrhea and enhances overall lactose tolerance in lactose maldigesters
Authors: Ramakrishnan Monica , Cross Tzu-Wen L. , Wilcox Anne K. , Organski Anna Clapp , Rhine Robin L. , Saiprasad Sindusha Mysore , Simpson Abigayle M. R. , Tancredi Daniel J. , Van Haute Mallory J. , Christensen Chloe M. , Lewis Zachery T. , Auchtung Thomas A. , Walter Jens , Hutkins Robert , Savaiano Dennis A.
Published: January 2025

Probiotic supplements containing high β-galactosidase-producing bacteria may aid in the management of lactose intolerance. We previously isolated a strain ofBifidobacterium adolescentis, iVS-1, from the fecal sample of a human donor after consumption of galactooligosaccharides (GOS), a prebiotic derived from lactose. Therefore, it was hypothesized that iVS-1 might reduce symptoms associated with lactose maldigestion. Compared to other probiotic strains, iVS-1 had high β-galactosidase activity and reduced gas formation by fecal communities during in vitro fermentations of lactose or milk. A randomized placebo-controlled clinical trial was then conducted with 21 lactose maldigesters, randomized to receive eitherB. adolescentisiVS-1 (n = 11) or placebo (n = 10) daily for two weeks. Compared to the two-week run-in period, iVS-1 abundance was higher at the end of the treatment period (p = 0.0005) and after the two week post-treatment period (p = 0.045). The iVS-1 group experienced less overall daily symptoms during the treatment period when compared to placebo (p = 0.032) and had significant improvement for fecal urgency (p = 0.033) and diarrhea (p = 0.006). The metabolism of lactose, reduction of gas, and improvement of multiple gastrointestinal symptoms suggestsB. adolescentisiVS-1 may be an effective treatment for lactose intolerance.

Trial Registration

The trial is registered atClinicalTrials.gov(https://clinicaltrials.gov/study/NCT05668468).
Impact of Surgeon cadre, theatre location, and presence of intern healthcare professionals on decision-to-delivery interval in women undergoing emergency caesarean section in Northern Uganda: a historical cohort study
Authors: Ochola Henry , Omoro Ronnie , Buga Paul , Odong Emintone Ayella , Ocaya Oscar , Kajabwangu Rogers , Ochola Emmanuel , Atim Nelly , Akello Harriet , Acayo Judith Praiselyn , Ekwem Doris , Namuddu Jovia , Mukurasi Derrick , Lukyamuzi Enock , Onen Hudson , Lenia Maurine , Gimono Martha , Webb Emily , Campbell Oona , Komata Ronald , Okot Jerom , Ojara Sande
Published: January 2025

Introduction

Emergency caesarean sections (CS) are crucial for preventing life-threatening complications. The Decision-to-Delivery Interval (DDI), the time between decision and actual delivery, impacts maternal and neonatal outcomes. While the World Health Organization recommends a DDI of < 30 minutes, achieving this in low-resource settings remains challenging. This study examines the impact of surgeon’s cadre, operating theatre location, and presence of intern healthcare professionals on DDI and whether these associations vary by CS indication.

Methods

This historical cohort study was conducted at St. Mary’s Hospital Lacor, a tertiary hospital in Northern Uganda, involving 760 women who underwent emergency CS between 6thSeptember 2022 and 1stJune 2024. We assessed the association of prolonged DDI (≥60 minutes) with surgeon cadre, operating theatre location, and intern presence using logistic regression, adjusting for key confounders and investigated interaction with the indication for emergency CS.

Results

The median DDI was 51 minutes (IQR: 36-67), with 36.0% of cases classified as prolonged (≥ 60 minutes). Emergency CS performed by junior doctors had twice the odds of prolonged DDI compared to senior doctors (adjusted OR: 2.07; 95% CI: 1.38-3.10). Theatre location showed no effect on DDI (OR: 0.89; 95% CI: 0.61-1.28). The presence of interns was weakly associated, with slightly lower odds of prolonged DDI when interns were absent (OR: 0.71; 95% CI: 0.51-1.02). No significant variations were found based on the indication for emergency CS.

Conclusion

Surgeon’s cadre is a key factor in reducing prolonged DDI, highlighting the importance of training and supervision for junior doctors. While theatre location did not significantly impact DDI, improving theatre readiness and coordination remains essential. The weak association with intern presence suggests further investigation into their role in emergency CS. These findings highlight the importance of addressing system-level delays to improve timely emergency obstetric care in resource-limited settings.
DIYNAFLUOR: An Affordable DIY Plug-and-Play Nucleic Acid Fluorometer for eDNA Quantification in Resource Limited Settings
Authors: Anderson Will , Antaw Fiach , Kenny Sophie , Rupani Harshita , Khamis Ramlah , Constantin Nicolas , Kumar Vinay , Gemmell Anna , Bell Craig , Trau Matt , Korbie Darren
Published: January 2025

Nucleic Acid (NA) fluorometry is widely employed for quantifying environmental DNA (eDNA) samples and their downstream DNA sequencing libraries, owing to its sensitivity, accuracy, and speed. However, the high cost of NA fluorometers presents a barrier to eDNA sequencing in resource limited settings (RLSs). For instance, at ∼$1.5-3.3k USD, current NA fluorometers present a greater capital cost than ONT’s $1k USD portable MinION third-generation Nanopore sequencing platform. The collapse of international scientific device and consumable supply chains during the COVID-19 pandemic also highlighted the need for distributed manufacturing of molecular research tools to mitigate the impact of increased pricing to RLSs. To address these challenges, we have developed the “DIYNAFLUOR” (DIY Nucleic Acid FLUORometer), a portable, open-source, <$40 USD NA fluorometer, designed using readily available off-the-shelf components, simple 3D-printed parts, and plug-and-play, solder-free assembly. The DIYNAFLUOR was primarily designed to be compatible with the popular DNA-centric Qubit High Sensitivity (HS) and Broad Range (BR) assay kits. Notably, the DIYNAFLUOR demonstrated an ‘in-assay’ Limit of Detection with the Qubit HS kit of 0.0028 ng/μL, and an average absolute bias of 0.018 ng/μL across a 0–10 ng/μL working range using a 2-point linear calibration methodology. Device verification was performed by comparative measurements with a Qubit 4 fluorometer in a busy biotechnology laboratory, and build instructions were validated through assembly and qualification of three DIYNAFLUOR devices by researchers outside the primary design team. We also describe a custom “extreme”low-cost assay, <13¢ USD per-measurement, that uses SYBR Safe dye to quantify DNA across a working range of 0-0.5 ng/μL. This assay reports a lower sensitivity and accuracy than commercial kits but may be of use to RLSs in times of extreme resource constraints or as a teaching tool for STEM educators. To demonstrate its practical application for field-based eDNA analysis in RLSs, the DIYNAFLUOR was used to perform all quality control measurements throughout the preparation of a 16S and 18S metabarcoding library generated from eDNA extracted from Australian lake water, leading to the successful identification of Australian fauna via Nanopore sequencing. Finally, configurations of the DIYNAFLUOR for RNA and Protein quantification are briefly described.

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ScHiCAtt: Enhancing Single-Cell Hi-C Resolution Using Attention-Based Models
Authors: Menon Rohit , Chowdhury H. M. A. Mohit , Oluwadare Oluwatosin
Published: January 2025

The spatial organization of chromatin is fundamental to gene regulation and essential for proper cellular function. The Hi-C technique remains the leading method for unraveling 3D genome structures; however, limited resolution, data sparsity, and incomplete coverage in single-cell Hi-C data pose significant challenges for comprehensive analysis. Traditional CNN-based models often suffer from blurring and loss of fine details, while GAN-based methods encounter difficulties in maintaining diversity and generalization. Moreover, existing algorithms perform poorly in cross-cell line generalization, where a model trained on one cell type is used to enhance high-resolution data in another cell type. To address these limitations, we propose ScHiCAtt (Single-cell Hi-C Attention-Based Model), which leverages attention mechanisms to capture both long-range and local dependencies in Hi-C data, significantly enhancing resolution while preserving biologically meaningful interactions. We implement this mechanism and check its validity on data from different cells of the same organisms and data of different organisms. By dynamically focusing on regions of interest, attention mechanisms effectively mitigate data sparsity and enhance model performance in low-resolution contexts. Extensive experiments on Human and Drosophila single-cell Hi-C data demonstrate that ScHiCAtt consistently outperforms existing methods in terms of computational and biological reproducibility metrics across different downsampling ratios, especially under extreme downsampling conditions. The model is publicly available at https://github.com/OluwadareLab/ScHiCAtt.