bluuebunny/crossref_metadata_2025 huggingface dataset:
A Spatiotemporal Atlas of Mouse Gastrulation and Early Organogenesis to Explore Axial Patterning and ProjectIn VitroModels ontoIn VivoSpace
Authors: Harland Luke TG , Lohoff Tim , Koulena Noushin , Pierson Nico , Pape Constantin , Ameen Farhan , Griffiths Jonathan , Theeuwes Bart , Wilson Nicola K , Kreshuk Anna , Reik Wolf , Nichols Jennifer , Cai Long , Marioni John C , Gottgens Berthold , Ghazanfar Shila
Published: December 2024

At the onset of murine gastrulation, pluripotent epiblast cells migrate through the primitive streak, generating mesodermal and endodermal precursors, while the ectoderm arises from the remaining epiblast. Together, these germ layers establish the body plan, defining major body axes and initiating organogenesis. Although comprehensive single cell transcriptional atlases of dissociated mouse embryos across embryonic stages have provided valuable insights during gastrulation, the spatial context for cell differentiation and tissue patterning remain underexplored. In this study, we employed spatial transcriptomics to measure gene expression in mouse embryos at E6.5 and E7.5 and integrated these datasets with previously published E8.5 spatial transcriptomics1and a scRNA-seq2atlas spanning E6.5 to E9.5. This approach resulted in a comprehensive spatiotemporal atlas, comprising over 150,000 cells with 88 refined cell type annotations as well as genome-wide transcriptional imputation during mouse gastrulation and early organogenesis. The atlas facilitates exploration of gene expression dynamics along anterior-posterior and dorsal-ventral axes at cell type, tissue, and organismal scales, revealing insights into mesodermal fate decisions within the primitive streak. Moreover, we developed a bioinformatics pipeline to project additional scRNA-seq datasets into a spatiotemporal framework and demonstrate its utility by analysing cardiovascular models of gastrulation3. To maximise impact, the atlas is publicly accessible via a user-friendly web portal empowering the wider developmental and stem cell biology communities to explore mechanisms of early mouse development in a spatiotemporal context.
Who said that? Deciphering Complex Coral Reef Soundscapes with Spatial Audio and 360° Video
Authors: Dantzker Marc S. , Duggan Matthew T. , Berlik Erika , Delikaris-Manias Symeon , Bountourakis Vasileios , Pulkki Ville , Rice Aaron N.
Published: December 2024

Coral reef soundscapes hold an untapped wealth of biodiversity information. While they are easy to record, they are nearly impossible to decipher because we know very little about which sound is made by which species. With identified fish sounds, acoustic monitoring can directly measure biodiversity, detect key or invasive species, identify behavioral events and frequencies, and estimate abundance, all at temporal and spatial scales not possible with methods like eDNA or visual surveys. Using a novel approach to visualize underwater sound, we present the most extensive collection of identified natural sounds from reef-associated Atlantic fishes. These sounds were all ascribed to speciesin situon a crowded Caribbean coral reef. The soundfield analysis technique combines visualizations of spatial audio with 360° video recordings, a method not previously accomplished underwater. We used these species identifications to decipher a representative section of a soundscape recording from a separate recording device. We have collected our identified recordings into a growing open-access resource to catalyze passive acoustic monitoring research, enabling a species-specific resolution of coral reef soundscape dynamics and providing critical validated information for developing machine learning models required to analyze an ever-expanding collection of long-term recordings.
Opioid use disorder and brain health: observational and genetic associations
Authors: Javidnia Sara , Roe James M. , Karhunen Ville , Gill Dipender , Bell Steven , Deak Joseph , Levey Daniel , Cronje Toinet , Burgess Stephen , Gelernter Joel , Ebmeier Klaus P. , Topiwala Anya
Published: December 2024

Background

The long-term impact of opioid use disorder (OUD) on brain health has been little explored although of potentially high public health importance.

Objectives

To investigate the potential causal impact of OUD on later life brain health outcomes, including dementia, stroke and brain structure.

Methods

Observational and Mendelian randomization (MR) analyses were conducted. Participants included in observational analyses were enrolled in the US Million Veteran Program (MVP). Cox proportional hazards were used to examine the association between electronic health record (EHR)-derived diagnoses of OUD and incident dementia in European and African ancestry populations. Two-sample MR was applied to explore the association between genetic predisposition to OUD and dementia, as well as key endophenotypes including brain structure. Several analyses were used for insight into aetiological pathways, including cis-MR to assess the impact of genetically-proxied opioid receptor perturbation, Bayesian colocalization, and polygenic risk score analyses of longitudinal brain changes in non-opioid users from the Lifebrain project (n=229).

Results

Amongst 222,518 MVP participants, 8397 developed dementia during follow up. Participants with OUD (n=9,399) were younger and more likely to be male. In observational analyses, OUD was associated with a higher risk of incident all-cause dementia (hazard ratio [HR]=1.56, 95% confidence interval [CI] [1.39,1.76];p=2.23×10-13), Alzheimer’s [HR=1.40[1.04,1.87]; p=0.02) and vascular dementia (HR=1.49[1.19,1.86];p=0.0004). In the genetic analysis, genetically-proxied OUD also associated with higher dementia risk. A doubling in genetically-proxied OUD prevalence was associated with a 77% increase in odds of dementia (IVW OR=1.77[1.43,2.19];p=1.69×10⁻⁷). Variation in μ-opioid receptor genes were strongly associated with dementia risk. No significant associations were observed with brain structure in non-opioid users, nor in lower powered non-European ancestry groups.

Conclusions

These findings suggest a potential causal impact of opioid use disorder on dementia. Genetic analyses supported an aetiological role of μ-opioid receptor pathways. Further pharmacovigilance and investigation into the long-term effects of opioids on brain health are warranted.
Detecting Clinically Relevant Topological Structures in Multiplexed Spatial Proteomics Imaging Using TopKAT
Authors: Samorodnitsky Sarah , Campbell Katie , Little Amarise , Ling Wodan , Zhao Ni , Chen Yen-Chi , Wu Michael C.
Published: December 2024

Novel multiplexed spatial proteomics imaging platforms expose the spatial architecture of cells in the tumor microenvironment (TME). The diverse cell population in the TME, including its spatial context, has been shown to have important clinical implications, correlating with disease prognosis and treatment response. The accelerating implementation of spatial proteomic technologies motivates new statistical models to test if cell-level images associate with patient-level endpoints. Few existing methods can robustly characterize the geometry of the spatial arrangement of cells and also yield both a valid and powerful test for association with patient-level outcomes. We propose a topology-based approach that combines persistent homology with kernel testing to determine if topological structures created by cells predict continuous, binary, or survival clinical endpoints. We term our method TopKAT (Topological Kernel Association Test) and show that it can be more powerful than statistical tests grounded in the spatial point process model, particularly when cells arise along the boundary of a ring. We demonstrate the properties of TopKAT through simulation studies and apply it to two studies of triple negative breast cancer where we show that TopKAT recovers clinically relevant topological structures in the spatial distribution of immune and tumor cells.
The impact of introducing meningococcal C/ACWY booster vaccination among adolescents in Germany: a dynamic transmission modelling study
Authors: Günther Felix , Reinacher Ulrich , Chisholm Sarah , Griskaitis Matas , Höhle Michael , Scholz Stefan , Schönfeld Viktoria , Wichmann Ole , Harder Thomas , Sandmann Frank G.
Published: December 2024

Background

In Germany, primary vaccination against invasive meningococcal disease (IMD) serogroup C aims to reduce the highest burden of IMD in infants aged 12-23 month. Due to another IMD-peak in adolescents, we modelled the potential impact of introducing adolescent boosters with conjugate meningococcal C or ACWY (MenC/MenACWY) vaccines.

Methods

We built an age- and serogroup-structured dynamic-transmission model for Germany, which we calibrated to national surveillance data in 2005-2019. We simulated five vaccination scenarios of either continuing with the current MenC primary vaccination (scenario 1), or additionally introducing MenC or MenACWY boosters at age 13 years (scenarios 2-3) or 16 years (scenarios 4-5). We performed comprehensive sensitivity analyses, including on the protection against carriage and serotype replacement.

Results

The calibrated model projected for scenario 1 an annual mean of 243 (95%-uncertainty interval: 220-258) expected IMD cases over a 10-year period. Introducing the MenC booster prevented an estimated 5 (3.9-6.7) and the MenACWY booster 8 (6.7-9.1) IMD cases per year on average (scenario 2 and 3). The number-needed-to-vaccinate (NNVs) to prevent one IMD case were 140,000 (100,000-180,000) and 91,000 (76,000-100,000), respectively. To prevent one sequela or death, NNVs were higher (i.e., less efficient). Results were broadly similar for scenarios 4-5. Simulations suggested relevant serotype replacement starting eight-to-ten years after introducing the MenACWY booster.

Conclusions

Introducing adolescent MenC or MenACWY boosters marginally reduces the expected IMD burden in Germany. Effectiveness and efficiency of evaluated strategies depend on future incidence. The magnitude of future serotype replacement for the MenACWY vaccine is highly uncertain.
Tumor-associated macrophages enhance tumor innervation and spinal cord repair
Authors: Dolci Sissi , Mannino Loris , Campanelli Alessandra , Rossi Eros , Bottani Emanuela , Ciarpella Francesca , Karkossa Isabel , Setten Elisa , Savino Benedetta , Pruonto Giulia , Piazza Nicola , Gianoli Stefano , Amenta Alessia , Busetto Giuseppe , Pezzotta Alex , Di Chio Marzia , Castagna Alessandra , Martinelli Nicolò , Barone Ilaria , Boschi Federico , Doherty Adam , Scupoli Maria Teresa , Cavallini Chiara , Malpeli Giorgio , Malik Zulkifal , Sagripanti Ludovica , Silani Vincenzo , Cristofori Patrizia , Scanziani Eugenio , Sandri Marco , Pistocchi Anna , Bossolasco Patrizia , Endrizzi Marco , Schubert Kristin , Fumagalli Guido Francesco , Locati Massimo , Bifari Francesco , Decimo Ilaria
Published: December 2024

Abstract

Tumor-associated macrophages (TAM) enhance cancer progression by promoting angiogenesis, extracellular matrix (ECM) remodeling, and immune suppression. Nerve infiltration is a hallmark of various cancers and is known to directly contribute to tumor growth. However, the role of TAM in promoting intratumoral nerve growth remains poorly understood. In this study, we demonstrate that TAM expressed a distinct “neural growth” gene signature. TAM actively enhance neural growth within tumors and directly promote neurites outgrowth. We identify secreted phosphoprotein 1 (Spp1) as a key mediator of TAM-driven neural growth activity, which triggers neuronal mTORC2 signaling.

Leveraging this new neural growth function, which added to the TAM wound healing properties, we explored TAM potential to repair central nervous system. Adoptive transfer ofin vitro-generated TAM in a severe complete-compressive-contusive spinal cord injury (scSCI) model, not only repaired the damaged neural parenchyma by improving tissue oxygenation, ECM remodeling, and dampening chronic inflammation, but also resulted in neural regrowth and partial functional motor recovery. Proteomic analysis and subsequent functional validation confirmed that TAM-induced spinal cord regeneration is mediated through the activation of neural mTORC2 signaling pathways.

Collectively, our data unveil a previously unrecognized role of TAM in tumor innervation, neural growth, and neural tissue repair.
Non-invasive diagnosis of early chronic colitis cancerization via amplified sensing of miRNA-21 in NIR-IIb window
Authors: Zhai Fuheng , Yun Baofeng , Ming Jiang , Li Benhao , Yu Tianyu , Liu Xiao , Wang Xusheng , Chen Zi-Han , Song Changfeng , Zhao Mengyao , Li Jiyu , Liang Aibin , Zhang Fan
Published: December 2024

Early diagnosis of the colitis-associated colorectal cancer (CRC) is of great significance for improving prognosis and survival rates. However, the clinical used colonoscopy and biopsy methods are invasive and lack of sensitivity at early stage of cancerization. Herein, we present an amplified sensing strategy in the second near-infrared b (NIR-IIb, 1500-1700 nm) window for non-invasive in situ visualization of early cancerization biomarker miRNA-21. A CRC nanosensor composed of Er3+doped lanthanide nanoparticles, DNAzyme, and IR820 dye is designed as a NIR-IIb ratiometric luminescence reporter, providing rapid feedback and high sensitive miRNA-21 detection with limit of detection (LOD) of 1.26 pM. This strategy enables a non-invasive detection of colitis-associated cancerization up to ∼4 weeks ahead of the clinically used biopsy analysis, providing a promising alternative for early diagnosis of chronic colitis cancerization and guidance for therapeutic management.
MultiNMRFit: A software to fit 1D and pseudo-2D NMR spectra
Authors: Millard Pierre , Le Grégam Loïc , Dubiley Svetlana , Gosselin-Monplaisir Thomas , Lippens Guy , Charlier Cyril
Published: December 2024

Nuclear Magnetic Resonance (NMR) is widely used for quantitative analysis of metabolic systems. Accurate extraction of NMR parameters – such as chemical shift, intensity, coupling constants, and linewidth – is essential for obtaining information on the structure, concentration, and isotopic composition of metabolites. We present MultiNMRFit, an open-source software designed for high-throughput analysis of one-dimensional NMR spectra, whether acquired individually or as pseudo-2D experiments. MultiNMRFit extracts signal parameters (e.g. intensity, area, chemical shift, and coupling constants) by fitting the experimental spectra using built-in or user-defined signal models that account for multiplicity, providing high flexibility along with robust and reproducible results. The software is accessible both as a Python library and via a graphical user interface, enabling intuitive use by end-users without computational expertise. We demonstrate the robustness and flexibility of MultiNMRFit on datasets collected in metabolomics and isotope labeling studies.

Availability and Implementation

MultiNMRFit is implemented in Python 3 and was tested on Unix, Windows, and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license athttps://github.com/NMRTeamTBI/MultiNMRFit/.

Supplementary data

Supplementary data are available online.
Stereochemical Insights into Sarpagan and Akuammiline Alkaloid Biosynthesis
Authors: Alexander Mann Scott Galeung , Paz-Galeano Malina , Shahsavarani Mohammadamin , Perley Jacob Owen , Guo Jun , Oswaldo Garza-Garcia Jorge Jonathan , Qu Yang
Published: December 2024

The Apocynaceae family produces a remarkable diversity of monoterpenoid indole alkaloids (MIAs), many of which possess significant pharmaceutical value. Among these, sarpagan and akuammiline alkaloids represent distinct subclasses characterized by their intricate stereochemical frameworks, derived through enzymatically controlled cyclization and rearrangement of the key precursor geissoschizine. In this study, we systematically investigated the products and stereochemical outcomes of sarpagan bridge enzymes (SBEs) and rhazimal synthases (RHS), key enzymes involved in geissoschizine cyclization and MIA diversification. Using two previously characterized enzymes alongside five newly identified enzymes from six plant species, we demonstrate that RHS enzymes fromAlstonia scholaris,Vinca minor, andAmsonia tabernaemontanaexclusively produce the 16Rrhazimal stereoisomer. In contrast, SBEs fromCatharanthus roseus,Vinca minor,Tabernaemontana elegans, andRauvolfia serpentinagenerate both 16Sakuammidine aldehyde and 16Rpolyneuridine aldehyde diastereomers in varying ratios. Remarkably, downstream esterases and deformylases epimerize and alter the stereochemical configuration, yielding naturally occurring alkaloids bearing distinct C16 stereochemistry in different species. These findings are supported by both in vitro assays andin plantasilencing of the newly identifiedC. roseusCrSBE, after we redirected the MIA flux to the otherwise muted sarpagan pathway. Our results provide a comprehensive understanding of the enzymatic control over C16 stereochemistry during SBE-mediated and RHS-mediated transformations. By elucidating how diastereomeric intermediates contribute to sarpagan MIA biosynthesis, this work addresses long-standing questions surrounding the stereochemical dynamics and enzymatic diversification of MIAs in nature.
Formal and informal mental health support in young adults with recurrently depressed parents
Authors: Jones Rhys Bevan , Weavers Bryony , Lomax Tessa , Meilak Emma , Eyre Olga , Powell Victoria , Mars Becky , Rice Frances
Published: December 2024

Background

A family history of mental illness, particularly parental depression, is a risk factor for mental health difficulties in young people, with this heightened risk extending into adulthood. Evidence suggests low rates of formal mental health support in children/adolescents with depressed parents, but it is unknown whether this pattern persists into adulthood and applies to informal support.

Aims

We examined the prevalence of formal and informal mental health support accessed by young adults with recurrently depressed parents. We identified factors associated with access to different support, reported satisfaction with support and identified potential facilitators/barriers to access.

Methods

A mixed-method study comprising 144 young adults (mean age=23 years, range=18-28 years) who completed psychiatric assessments and reported on their use of mental health support. Regression analyses explored predictors for support. A focus group examined facilitators and barriers.

Results

Young adults accessed a range of formal (29%) and informal (56%) support. Among those with psychiatric disorder, nearly half had not accessed formal support and one-fifth had not accessed any support. Predictors of support included psychiatric disorder, severity indicators (e.g. self-harm/suicidal thoughts, impairment), and demographic factors (e.g. education, gender).

Predictors varied by type of support. Most participants reported satisfaction with support. Facilitators included role models, public mental health discussions, and practitioner training. Barriers included identifying difficulties, stigma, service limitations, and family/friends’ experiences.

Conclusions

Young adults at high risk of mental disorders accessed various mental health support. However, many did not access/receive support when needed. Further work is required to improve access to tailored support.
Automated Interpretation of Fundus Fluorescein Angiography with Multi-Retinal Lesion Segmentation
Authors: Zhao Ziwei , Huang Shoujin , Zhang Weiyi , Song Fan , Lu Yan , Shang Xianwen , He Mingguang , Shi Danli
Published: December 2024

Purpose

Fundus fluorescein angiography (FFA) is essential for diagnosing and managing retinal vascular diseases, while its evaluation is time-consuming and subject to inter-observer variability. We aim to develop a deep-learning-based model for accurate multi-lesion segmentation for these diseases.

Methods

A dataset comprising 428 standard 55° and 53 ultra-wide-field (UWF) FFA images was labeled for various lesions, including non-perfusion areas (NPA), microaneurysms (MA), neovascularization (NV) and laser spots. A U-net-based network was trained and validated (80%) to segment FFA lesions and then tested (20%), with performance assessed via Dice score and Intersection over Union (IoU).

Results

Our model achieved Dice scores for NPA, MA, NV, and Laser on 55° FFA images at 0.65±0.24, 0.70±0.13, 0.73±0.23 and 0.70±0.17, respectively. UWF results were slightly lower for NPA (0.48±0.21, p=0.02), MA (0.58±0.19, p=0.01), NV (0.50±0.34, p=0.14), but similar for Laser (0.74±0.03, p=0.90). Notably, NV segmentation in choroidal neovascularization achieved a high Dice score of 0.90±0.09, surpassing those in DR (0.68±0.22) and RVO (0.62±0.28), p<0.01. In RVO, NPA segmentation outperformed that in DR, scoring 0.77±0.25 versus 0.59±0.22, p<0.01, while in DR, MA segmentation was superior to that in RVO, with scores of 0.70±0.18 compared to 0.53±0.20,p<0.01. Moreover, NV segmentation was significantly stronger in venous phase (0.77±0.17) and late phase (0.75±0.24) compared to arteriovenous phase (0.50±0.32), p<0.05.

Conclusion

This study has established a model for precise multi-lesion segmentation in retinal vascular diseases using 55° and UWF FFA images. This multi-lesion segmentation model has the potential to expand databases, ease grader burden and standardize FFA image interpretation, thereby improving disease management. Furthermore, it enhances interpretable AI, fostering the development of sophisticated systems and promoting cross-modal image generation for medical applications.

Synopsis

We developed deep-learning models for segmenting multiple retinal lesions in both normal and ultra-field FFA images; the satisfactory performances set the foundation for quantifiable clinical biomarker assessment and building interpretable generative artificial intelligence.
Neurodevelopmental deviations in schizophrenia: Evidences from multimodal connectome-based brain ages
Authors: Fan Yun-Shuang , Yang Pengfie , Zhu Yucheng , Jing Wenfeng , Xu Yong , Guo Jing , Huang Wei , Chen Huafu
Published: December 2024

Background

Pathologic schizophrenia process originate early in brain development, leading to detectable brain alterations via structural and functional magnetic resonance imaging (MRI). Recent MRI studies have sought to characterize disease effects from a brain age perspective, but developmental deviations from the typical brain age trajectory in youths with schizophrenia remain unestablished.

Aim

This study investigated brain development deviations in early-onset schizophrenia (EOS) patients by applying machine learning algorithms to structural and functional MRI data.

Methods

Multimodal MRI data, including T1-weighted MRI (T1w-MRI), diffusion MRI, and resting-state functional MRI (rs-fMRI) data, were collected from 80 antipsychotic-naive first-episode EOS patients and 91 typically developing (TD) controls. The morphometric similarity connectome (MSC), structural connectome (SC), and functional connectome (FC) were separately constructed by using these three modalities. According to these connectivity features, eight brain age estimation models were first trained with the TD group, the best of which was then used to predict brain ages in patients. Individual brain age gaps (BAGs) were assessed as brain ages minus chronological ages.

Results

Both the SC and MSC features performed well in brain age estimation, whereas the FC features did not. Compared with the TD controls, the EOS patients presented widened structural BAGs, with opposite trends between childhood and adolescence. These increased absolute BAG scores for EOS patients were positively correlated with the severity of their clinical symptoms.

Conclusion

These findings from a multimodal brain age perspective suggest that advanced BAGs exist early in youths with schizophrenia.
Aggregation promoting sequences rather than phosphorylation are essential for Tau-mediated toxicity inDrosophila
Authors: Cooper Amber , Richardson Bradley , Ruiz Ortega Eva , Zhang Yongrui , Batchelor Ben , Vaikakkara Chithran Aarya , Liu Jie , Lian Tianshun , Ramírez Moreno Miguel , Boehme Benjamin , Abtahi Leila , Devitt George , Sivanantharajah Lovesha , Skoulakis Efthimios M. C. , Allan Douglas W. , Mudher Amritpal
Published: December 2024

Background

Disease-modifying therapies for tauopathies like Alzheimer’s disease have targeted Tau hyperphosphorylation and aggregation, as both pathological manifestations are implicated in Tau-mediated toxicity. However, the relative contributions of these pathology-linked changes to Tau neurotoxicity remain unclear.

Methods

Leveraging the genetic tractability ofDrosophila, we generated multiple inducible human Tau transgenes with altered phosphorylation status and/or aggregation propensity. Their individual and combined impact was testedin vivoby quantifying Tau accumulation and neurodegenerative phenotypes in the aging fly nervous system.

Results

We report that phospho-mimicking Tau (hTau2N4RE14) induced profound neurodegeneration, supporting a neurotoxic role for phosphorylation. However, when we rendered hTau2N4RE14aggregation incompetent, by deleting the306VQIVYK311motif in the microtubule-binding region, neurotoxicity was abolished. Moreover, a peptide inhibitor targeting this motif efficaciously reduced Tau toxicity in agingDrosophila.

Conclusion

Neurodegeneration mediated by Tau hyperphosphorylation is gated via at least one aggregation-mediating motif on the protein. This highlights the primacy of blocking Tau aggregation in therapy, perhaps without the need to clear phosphorylated species.
Crystal structure of Fatty Acid Thioesterase A bound by 129 fragments provides diverse development opportunities
Authors: Kot Ekaterina , Ferla Matteo P. , Hollinshead Patricia H. , Tomlinson Charlie W.E. , Fearon Daren , Aschenbrenner Jasmin C. , Koekemoer Lizbé , Winokan Max , Fairhead Michael , Ni Xiaomin , England Katherine S. , Ortega Varga Laura , Montgomery Mark G. , Mulholland Nicholas P. , von Delft Frank
Published: December 2024

To alleviate the growing issue of herbicide resistance, diversification of the herbicide portfolio is necessary. A promising yet underutilised mode of action (MoA) are Fatty Acid Thioesterases (Fat), which terminatede novofatty acid (FA) biosynthesis by releasing fatty acids from acyl carrier protein (ACP) cofactors. These enzymes impact plant growth and sterility by determining the amount and length of FAs present. To find novel chemical matter targeting this MoA we have solved the crystal structure ofArabidopsis thalianaFatA to 1.5Å and conducted a crystallographic fragment screen which identified 141 hits. Our fragments recapitulated interactions made by current herbicides, but also targeted novel regions, namely the active site and the dimer interface. Ten fragments demonstrated on-scale potency, two of those exploiting different interactions to known herbicides. The screen also revealed large conformational changes exploited by some fragments, including stabilisation of a loop and shifts in the ACP-binding lid domain. These changes alter the accessibility of the substrate binding site by reducing the size of the apparent substrate access channel. Finally, the fragments readily lend themselves to designing compounds that both merge motifs and allow catalogue-based SAR exploration. Elaboration of one of the fragments resulted in an improvement of affinity from ∼20 μM to ∼90nM KD. Thus our data may facilitate accelerated early discovery of alternative inhibitors that are novel in both chemical scaffolds and modes of interaction.
eDNA provides accurate and precise estimates of abundance by integrating bioenergetics and particle mass-balance
Authors: Beaulieu J , Yates MC , Fraser DJ , Cristescu ME , Derry AM
Published: December 2024

Anthropogenic activities have led to an unprecedented crisis in freshwater biodiversity loss. The capacity to monitor the abundance of wild populations is critical to conserving biodiversity, but conventional physical specimen collection methods are invasive, costly, and labour-intensive. Environmental DNA (eDNA) offers a promising alternative, being easy to sample, with studies under controlled laboratory conditions showing consistent correlations between eDNA concentration and abundance. However, applying eDNA to monitor abundance remains contentious, as eDNA particle dynamics and the ecology of eDNA production can decouple this relationship in natural ecosystems. To address this, we integrated bioenergetics and mass-balance frameworks to relate eDNA concentrations to freshwater fish populationabundanceestimated through conventional mark-recapture in Brook Trout (Salvelinus fontinalis) across nine Rocky Mountains lakes, five of which underwent size-selectively harvest over two years. Our integrated framework improved the variance explained in eDNA concentrations from 24% to 71%. The integrated model accurately distinguished most abundance estimates across populations and sampling periods, detecting both natural and harvest-induced reductions in abundance within several populations. This study is the first to empirically integrate the DNA production ecology and particle dynamics, demonstrating that properly accounting for ‘the ecology of eDNA’ enables rapid, accurate abundance quantification. We also discuss future research and applications of eDNA in light of these results.

Significance statement

Addressing the unprecedented freshwater biodiversity crisis requires cost- and time-effective methods for estimating abundance and biomass. Our study empirically demonstrates the potential of eDNA for rapid and accurate assessment of abundance in natural populations by integrating hydrology, chemistry and bioenergetics into a mass-balance modelling framework. Through a replicated whole-ecosystem experiment, we show that eDNA not only detects differences in fish abundance and biomass across populations, but also captures natural and experimentally induced abundance changes within populations. Our modeling approach enables eDNA to generate abundance and biomass estimates comparable in precision and accuracy to high-quality mark-recapture methods.
Hindering memory suppression by perturbing the right dorsolateral prefrontal cortex
Authors: Stramaccia Davide F. , Bergmann Frederik , Lingelbach Katharina , Numssen Ole , Hartwigsen Gesa , Benoit Roland G.
Published: December 2024

A reminder of the past can trigger the involuntary retrieval of an unwanted memory. Yet, we can intentionally stop this process and thus prevent the memory from entering awareness. Such suppression not only transiently hinders the retrieval of the memory, it can also induce forgetting. Neuroimaging has implicated the right dorsolateral prefrontal cortex (dlPFC) in initiating this process. Specifically, this region seems to downregulate activity in brain systems that would otherwise support the reinstatement of the memory. We here probed the causal contribution of the right dlPFC to suppression by combining the Think/No-Think task with repetitive transcranial magnetic stimulation (rTMS). Participants first learned pairs of cue and target words, and then repeatedly recalled some of the targets (think condition) and suppressed others (no-think condition). We applied 10 Hz rTMS bursts to the right dlPFC during the suppression of half the no-think items, and to the contralateral primary motor area (M1) as an active control site during the other half. As hypothesized, participants experienced less success at keeping the memories out of awareness with concurrent dlPFC than M1 stimulation. Similarly, a memory test yielded evidence for suppression-induced forgetting (SIF) following M1 but not dlPFC stimulation. However, the difference in forgetting between the stimulation conditions was not significant. The study thus provides causal evidence for the role of the dlPFC in preventing retrieval. Future work will need to conclusively establish the relationship between this transient effect and suppression-induced forgetting.
Performance Evaluation of Ciprofloxacin loaded Micellar Bioconjugate Carrier for Eradication of Bacterial Biofilms
Authors: Gupta Chandrika , Ghosh Sudip Kumar , Sen Ramkrishna
Published: December 2024

This study reports the utilization of a Curcumin-Exopolysaccharide (Cur-EPS) micellar bioconjugate comprising acid-labile ester bond as a carrier for ciprofloxacin (Cip) to improve its ability to eradicate mature bacterial biofilms. The most significant attributes of Cip-loaded Cur-EPS micelles, including hydrodynamic particle size, polydispersity index (PDI), and encapsulation efficiency (EE), were statistically optimized to be 305.43 ± 1.47 nm, 0.38 ± 1.23, and 84.50 ± 2.01 %, respectively. At an acidic pH of 5.6, the pH-responsive release of Cip from Cur-EPS micelles was 82.51 ± 2.95 % over a duration of 100 h, but it was reduced to 39.10 ± 1.55 % at a pH of 7.4 over the same period. This pH-dependent Cip release may be attributed to the destabilisation of Cur-EPS micelles due to hydrolysis of the succinic acid linker in the acidic pH range. Thus, the acidic pH microenvironment of biofilms formed by pathogenic bacterial strains, such as methicillin resistantStaphylococcus aureus(MRSA) andPseudomonas aeruginosa, enhances the pH-responsive release of Cip from Cur-EPS micelles, thereby leading to the eradication of mature biofilms. This enhanced antibiofilm effect of Cip-Cur-EPS, in contrast to the free form of Cip, was evident from the significant decrease in the biofilm biomass. Furthermore, mature biofilms that formed on the surface of the urinary catheter were almost eradicated when treated in vitro with Cip-Cur-EPS for 72 h in the presence of artificial urine media (AUM). Moreover, Cip-Cur-EPS could also eradicate the biofilms formed byP. aeruginosaand MRSA in a catheterized bladder model employing recirculated artificial urine. Overall, this study demonstrated the antibiofilm potential of Cip-Cur-EPS micelles, rendering them suitable therapeutic agents for addressing biofilm-associated infections in clinical settings.

Graphical abstract
Unraveling the Genetic Complexity of InvasiveLoniceraspp.: Evidence of Hybridization from Nuclear and Chloroplast Genome Analysis
Authors: Osier Michael V. , Borrego Eli J. , Tran Samantha V. , Hudson André O.
Published: December 2024

Members of theLoniceragenus, commonly known as honeysuckles, encompass both native and invasive species in North America, the latter posing significant ecological challenges. Invasive honeysuckles can disrupt native ecosystems by outcompeting local flora, altering habitats, and affecting wildlife populations. Effective management and control of these species are critical but hindered by the difficulty of accurate identification due to overlapping morphological traits. Traditional control measures recommended by government agencies, such as cutting, burning, and chemical treatments, have proven only partially effective, sometimes complicated by misidentification of species.

The morphological identification of invasive honeysuckles is notoriously challenging. Key distinguishing features are often subtle, variable, and sometimes only discernible during specific developmental stages, complicating field identification efforts. This taxonomic ambiguity underscores the urgent need for more precise identification methods that transcend conventional morphological assessments.

In this study, we explore the molecular identity of a Lonicera isolate collected from the Finger Lakes region of Western New York. Through detailed genetic analysis, we demonstrate that the specimen likely possesses maternal inheritance fromLonicera tataricawhile the majority of its nuclear genome is associated withLonicera insulara. Both species are prevalent in the region and known for their invasive potential.

Our findings highlight the utility of molecular techniques as a complementary tool for species identification within the Lonicera genus. By providing a clearer genetic framework for distinguishing between morphologically similar species, this approach can enhance conservation strategies, inform management decisions, and improve ecological restoration efforts. As invasive species continue to threaten biodiversity, integrating molecular diagnostics with traditional methods offers a promising path toward more effective environmental stewardship.
Long-Term Reactivation of Multiple Sub-Assemblies in the Hippocampus and Prefrontal Cortex
Authors: Tatsuno Masami , Fellous Jean-Marc
Published: December 2024

In resting or sleep periods following a task, neurons in various parts of the brain become reactivated, with firing patterns often similar to that during the task. This reactivation plays an essential role in memory consolidation. However, detecting these reactivating episodes has been challenging because not all neurons recorded may be directly relevant to the memory being consolidated. Here, we propose a novel spike train clustering (STC) method for detecting groups of neurons (clusters) with partial synchronous firing. From a mechanistic standpoint, the correlated activity of an ensemble can arise from neuronal interactions within the recorded local ensemble, common external inputs, or both. To quantify these contributions, we propose to use information geometry (IG) by taking advantage of its capacity for orthogonal decomposition of neural interactions. We analyzed simultaneous single unit activity from rat medial prefrontal cortex (mPFC) and area CA1 of the hippocampus when animals explored novel objects and when they slept before and after the exploration. We demonstrate that multiple reactivations by different subsets of neurons (clusters) occurred. Those reactivations could extend over 11 hours, the entire recording duration of post-task rest after the exploration epoch. Long-lasting reactivation was not detected when all neurons were included as a single cluster in the analysis. We also showed that pairwise interactions in reactivating clusters tended to be more strongly modified than in non-reactivating ones. In addition, the pairwise interactions of the reactivating clusters in CA1 were strongly modulated by the task experience but not in the mPFC. These results indicate that hippocampal reactivation following novel experience is likely to be induced within the hippocampal circuits. In contrast, mPFC reactivation is likely to be driven by external inputs, possibly in part from the hippocampus.
Periplasmic serine protease Prc is responsible for amyloid subunit CsgA degradation and proteostasis inEscherichia coli
Authors: Sugimoto Shinya , Terasawa Yurika , Tani Naoki , Yamanaka Kunitoshi , Kinjo Yuki
Published: December 2024

Escherichia colisynthesizes curli amyloid fibers extracellularly during biofilm formation and host colonization. The proteostasis network regulates the major curli subunit, CsgA, to prevent intracellular amyloid aggregation, yet the degradation mechanism remains elusive. Here, through a comprehensive investigation employing genetically engineeredE. coli, multi-copy-suppressor screening, and biochemical analyses, we identify periplasmic serine protease Prc as a key player in CsgA degradation. Prc directly degrades CsgA through internal cleavage, differing from canonical tail-specific proteases. Although the bacterial HtrA homologs DegP and DegQ exhibit limited CsgA degradation activity in vitro in the presence of the suicide activator YjfN, deletion of these proteases did not affect native CsgA degradation in vivo. Instead, Prc, in coordination with the periplasmic chaperone CsgC, prevents the periplasmic accumulation of CsgA amyloid-like aggregates. Additionally, disruptions in secretion efficiency and proteolytic systems reducecsgoperon expression through activation of the Rcs and Cpx two-component systems. These findings reveal a dual-layered strategy employed byE. colito prevent intracellular accumulation of extracellular amyloids at both protein degradation and transcriptional regulation levels. This study provides insights into the mechanisms ensuring cellular homeostasis during curli biogenesis.
KAT8 facilitates the proliferation of cancer cells through enhancing E7 function in HPV-associated cervical cancer
Authors: Xu Anli , Yang Xiaoming , Zhao Junwei , Kong Shujun , Tang Qing , Li Xiangzhi , Qu Hongmei , Wang Guoyun
Published: December 2024

Persistent human papillomavirus (HPV) infection serves as the principal etiological factor in cervical cancer, with the oncoprotein E7, encoded by the virus, playing a key role in tumorigenesis. Despite this, targeted therapeutic strategies against E7 remain underexplored. KAT8, a lysine acetyltransferase, significantly contributes to oncogenesis through the regulation of transcription. However, its involvement in cervical cancer remains inadequately characterized. This study employs HPV18-positive HeLa and HPV16-positive SiHa cell lines to investigate how KAT8 modulates E7 expression and function in cervical cancer cells. Upon KAT8 knockdown, a marked reduction in cell viability is observed, alongside a downregulation of E7 expression. This is associated with elevated levels of retinoblastoma protein (pRb) and decreased E2F1 expression, indicating that KAT8 depletion inhibits E7 expression, resulting in E2F1 inactivation and cell cycle arrest. Furthermore, KAT8 is found to directly bind to the promoter regions of the HPV18 LCR, enhancing transcription of the HPV18 E7 gene. This study also demonstrates that KAT8 is essential for the acetylation of E7, and plays a critical role in facilitating the interaction between pRb/E2F1 and E7 in cervical cancer cells. In conclusion, these results highlight KAT8 as a key driver of cervical cancer progression, promoting HPV E7 expression and its associated oncogenic signaling pathways.
Fluctuation-Driven Synergy, Redundancy, Signal to Noise Ratio and Error Correction in Protein Allostery
Authors: Erman Burak
Published: December 2024

This study explores the relationship between residue fluctuations and molecular communication in proteins, emphasizing the role of these dynamics in allosteric regulation. We employ computational tools including the Gaussian Network Model, mutual information, and interaction information, to analyze how stochastic interactions among residues contribute to functional interactions while also introducing noise. Our approach is based on the postulate that residues experience continuous stochastic bombardment from impulses generated by their neighbors, forming a complex network characterized by small-world scaling topology. By mapping these interactions through the Kirchhoff matrix framework, we demonstrate how conserved correlations enhance signaling pathways and provide stability against noise-like fluctuations. Notably, we highlight the importance of selecting relevant eigenvalues to optimize the signal-to-noise ratio in our analyses, a topic that has yet to be thoroughly investigated in the context of residue fluctuations. This work underscores the significance of viewing proteins as adaptive information processing systems, and emphasizes the fundamental mechanisms of biological information processing. The basic idea of this paper is the following: Given two interacting residues on an allosteric path, what are the contributions of the remaining residues on this interaction. This naturally leads to the concept of synergy, redundancy and noise in proteins, which we analyze in detail for three proteins CheY, Tyrosine Phosphatase and β-Lactoglobulin.
Quantum vacuum amplification in time-varying media with arbitrary temporal profiles
Authors: Ganfornina-Andrades A. , Vázquez-Lozano J. E. , Liberal I.
Published: December 2024

In this work we address quantum vacuum amplification effects in time-varying media with an arbitrary time-modulation profile. To this end, we propose a theoretical formalism based on the concept of conjugated harmonic oscillators, evaluating the impact on the transition time in temporal boundaries, shedding light into the practical requirements to observe quantum effects at them. In addition, we find nontrivial effects in pulsed modulations, where the swiftest and strongest modulation does not lead to the highest photon production. Thus, our results provide key insights for the design of temporal modulation sequences to enhance quantum phenomena.

Published by the American Physical Society
2024
Machine learning the operator content of the critical self-dual Ising-Higgs lattice gauge theory
Authors: Oppenheim Lior , Koch-Janusz Maciej , Gazit Snir , Ringel Zohar
Published: December 2024

Understanding critical phenomena is of central importance to condensed-matter and high-energy physics. Such an understanding is reflected in our ability to sort observables based on their degeneracy, symmetries, and power-law decays. Here, we study such critical properties of the Ising-Higgs gauge theory in (2+1)D along the self-dual line which have recently been a subject of debate. Using machine learning techniques, we determine the low-energy operator content of the associated field theory. Our approach enables us to largely refute the existence of an emergent current operator and with it the standing conjecture that this transition is of the XY* universality class. We contrast these results with the ones obtained for the (2+1)D Ashkin-Teller transverse field Ising model where we find the expected current operator. Our numerical technique extends the recently proposed real-space mutual information allowing us to extract subleading nonlinear operators. This allows a controlled and computationally scalable approach to target the conformal field theory spectrum. and discern universality classes beyond (1+1)D from Monte Carlo data.

Published by the American Physical Society
2024
Designs from Local Random Quantum Circuits with
SU(d)
Symmetry
Authors: Li Zimu , Zheng Han , Liu Junyu , Jiang Liang , Liu Zi-Wen
Published: December 2024

The generation of k-designs (pseudorandom distributions that emulate the Haar measure up to k moments) with local quantum circuit ensembles is a problem of fundamental importance in quantum information and physics. Despite the extensive understanding of this problem for ordinary random circuits, the crucial situations in which symmetries or conservation laws are in play are known to pose fundamental challenges and remain little understood. Here, we construct explicit local unitary ensembles that can achieve high-order unitary k-designs under transversal continuous symmetry, in the particularly important SU(d) case. Specifically, we define the convolutional quantum alternating (CQA) group generated by 4-local SU(d)-symmetric Hamiltonians as well as associated 4-local SU(d)-symmetric random unitary circuit ensembles and prove that they form and converge to SU(d)-symmetric k-designs, respectively, for all k<n(n−3)/2, with n being the number of qudits. A key technique that we employ to obtain the results is the Okounkov-Vershik approach to Sn representation theory. To study the convergence time of the CQA ensemble, we develop a numerical method using the Young orthogonal form and the Sn branching rule. We provide strong evidence for a subconstant spectral gap and certain convergence time scales of various important circuit architectures, which contrast with the symmetry-free case. We also provide comprehensive explanations of the difficulties and limitations in rigorously analyzing the convergence time using methods that have been effective for cases without symmetries, including Knabe’s local gap threshold and Nachtergaele’s martingale methods. This suggests that a novel approach is likely necessary for understanding the convergence time of SU(d)-symmetric local random circuits.

Published by the American Physical Society
2024