bluuebunny/crossref_metadata_2025 huggingface dataset:
Acquisition and reversal of glioblastoma chemoresistance are mediated by the Rho GTPase pathway
Authors: Magalhaes Yuli Thamires , Boell Viktor Kalbermatter , Forti Fabio Luis
Published: October 2024

Glioblastoma (GBM) are highly aggressive tumors treated mainly with surgery, radiotherapy, and chemotherapy. Innovative multimodal therapies are needed, targeting the immune system, tumor metabolism, and cell signaling. Our research focuses on the role of the actin cytoskeleton and Rho GTPases in modulating DNA damage repair and therapeutic sensitivity in GBM cells. We developed GBM sublines resistant to temozolomide (TMZ) and cisplatin (CP), and assessed actin stress fiber organization, Rho pathway activity, and resistance phenotype. TMZ-resistant clones exhibited increased Rho pathway activity, elevated p53 and DNA double-strand break (DSB) repair pathways, but reduced MMR protein levels. Importantly, Rho GTPase inhibition restored TMZ-resistant clones’ sensitivity to TMZ and CP, counteracting chemoresistance. While both drugs reduced DNA repair capacity in normal GBM cells—exacerbated by Rho inhibition—TMZ-resistant clones with overactivated Rho pathways did not show this effect. This response was p53-wild-type dependent, as p53-mutant GBM cells were unresponsive to Rho inhibition. However, p53-mutant cells treated with PRIMA-1 showed restored sensitivity to chemotherapeutics with Rho inhibition. Furthermore, modulation of the actin cytoskeleton and Rho GTPases affected sensitivity and viability in GBM spheroid models exposed to chemotherapy. In summary, Rho pathway activity and actin cytoskeleton dynamics are critical for both the development and reversal of chemoresistance in GBM tumors.

STATEMENT OF SIGNIFICANCE

Chemoresistance in glioblastomas modulates the Rho GTPases pathway and actin cytoskeleton, while negatively affecting DNA repair. Downmodulating the actin circuitry in resistant GBMs sensitizes them to TMZ and CP drugs.
Probing DNA damage sites reveals context-dependent and novel DNA damage response factors
Authors: da Silva Richard Cardoso , Recchia Davide C. , Portegijs Vincent , Sanchez Maria Cristina Trueba , Stecker Kelly E. , van den Heuvel Sander , Baubec Tuncay
Published: October 2024

DNA damage is a constant threat to genome integrity and function. Diminished capacity for DNA repair is linked to many human diseases, therefore understanding the molecular pathways responding to DNA damage is key for developing novel therapies. Lack of unbiased probes to report DNA damage dynamics and the associated proteins in living cells and animals limit our current efforts to completely understand DNA repair processes. In this study we overcome these limitations by engineering protein probes containing the tandem-BRCT domain of MCPH1, which we show to have a specific affinity for the DNA-damage-associated histone mark γH2AX. We employ these probes to track DNA damage dynamics in living cells exposed to a panel of different genotoxic insults and to visualize programmed double strand breaks during gametogenesis in living animals. We further utilize the binding selectivity of our probe to tether TurboID biotin ligases to chromatin and identify the DNA damage-associated proteome via proximity ligation. By comparing five different DNA damaging agents, we reveal the proteome associated with specific lesions, and identify multiple novel proteins with potential implications in damage response and repair. Among these novel proteins, we characterize the ubiquitin ligase UBE3A, the methyl-binding and proteasome-recruiting protein L3MBTL3, and the spliceosomal factor U2SURP, as previously uncharacterized effectors of DNA damage response. These functional datasets reveal the DNA damage-dependent proteomes and reveal novel insights into DNA damage response.
Utilizing data imbalance to enhance compound-protein interaction prediction models
Authors: Lin Wei , Fung Chi Chung Alan
Published: October 2024

Identifying potential compounds for target proteins is crucial in drug discovery. Current compound-protein interaction prediction models concentrate on utilizing more complex features to enhance capabilities, but this often incurs substantial computational burdens. Indeed, this issue arises from the limited understanding of data imbalance between proteins and compounds, leading to insufficient optimization of protein encoders. Therefore, we introduce a sequence-based predictor named FilmCPI, designed to utilize data imbalance to learn proteins with their numerous corresponding compounds. FilmCPI consistently outperforms baseline models across diverse datasets and split strategies, and its generalization to unseen proteins becomes more pronounced as the datasets expand. Notably, FilmCPI can be transferred to unseen protein families with sequence-based data from other families, exhibiting its practicability. The effectiveness of FilmCPI is attributed to different optimization speeds for diverse encoders, elucidating optimization imbalance in compound-protein prediction models. Additionally, these advantages of FilmCPI do not depend on increasing parameters, aiming to lighten model design with data imbalance.
How the Structure of Signaling Regulation Evolves: Insights from an Evolutionary Model
Authors: Asgari Danial , Tate Ann T.
Published: October 2024

To remain responsive to environmental changes, signaling pathways attenuate their activity with negative feedback loops (NFLs), where proteins produced upon stimulation downregulate the response. NFLs function both upstream of signaling to reduce input and downstream to reduce output. Unlike upstream NFLs, downstream NFLs directly regulate gene expression without the involvement of intermediate proteins. Thus, we hypothesized that downstream NFLs evolve under more stringent selection than upstream NFLs. Indeed, genes encoding downstream NFLs exhibit a slower evolutionary rate than upstream genes. Such differences in selective pressures could result in the robust evolution of downstream NFLs while making the evolution of upstream NFLs more sensitive to changes in signaling proteins and stimuli. Here, we test these assumptions within the context of immune signaling. Our minimal model of immune signaling predicts robust evolution of downstream NFLs to changes in model parameters. This is consistent with their critical role in regulating signaling and the conservative rate of evolution. Furthermore, we show that the number of signaling steps needed to activate a downstream NFL is influenced by the cost of signaling. Our model predicts that upstream NFLs are more likely to evolve under a shorter half-life of signaling proteins, absence of host-pathogen co-evolution, and a high infection rate. Although it has been proposed that NFLs evolve to reduce the cost of signaling, we show that a high cost does not necessarily predict the evolution of upstream NFLs. The insights from our model have broad implications for understanding the evolution of regulatory mechanisms across signaling pathways.
Evolutionary-Scale Enzymology Enables Biochemical Constant Prediction Across a Multi-Peaked Catalytic Landscape
Authors: Muir Duncan F. , Asper Garrison P. R. , Notin Pascal , Posner Jacob A. , Marks Debora S. , Keiser Michael J. , Pinney Margaux M.
Published: October 2024

Quantitatively mapping enzyme sequence-catalysis landscapes remains a critical challenge in understanding enzyme function, evolution, and design. Here, we expand an emerging microfluidic platform to measure catalytic constants—kcatandKM—for hundreds of diverse naturally occurring sequences and mutants of the model enzyme Adenylate Kinase (ADK). This enables us to dissect the sequence-catalysis landscape’s topology, navigability, and mechanistic underpinnings, revealing distinct catalytic peaks organized by structural motifs. These results challenge long-standing hypotheses in enzyme adaptation, demonstrating that thermophilic enzymes are not slower than their mesophilic counterparts. Combining the rich representations of protein sequences provided by deep-learning models with our custom high-throughput kinetic data yields semi-supervised models that significantly outperform existing models at predicting catalytic parameters of naturally occurring ADK sequences. Our work demonstrates a promising strategy for dissecting sequence-catalysis landscapes across enzymatic evolution and building family-specific models capable of accurately predicting catalytic constants, opening new avenues for enzyme engineering and functional prediction.
IntelliProfiler: a novel analytic tool for behavior dynamics of multiple animals in a home cage
Authors: Ochi Shohei , Inada Hitoshi , Osumi Noriko
Published: October 2024

There is a growing demand for sophisticated behavioral analysis systems that minimize bias in multi-animal and semi-natural environments. We present “IntelliProfiler,” an advanced system using radio frequency identification (RFID) technology to enable fully automated behavior analyses of multiple mice within a home cage. IntelliProfiler continuously monitors up to 16 mice, capturing both locomotor activity and social dynamics over extended periods. Our findings revealed that male mice maintain broader social distances than females, with group size playing a key role in shaping male social network dynamics. Furthermore, aging in males significantly impacts both locomotor activity and social interaction in a group size-dependent manner. With its ability to provide in-depth analysis of individual and group behaviors, IntelliProfiler offers a novel approach for exploring complex social interactions and group dynamics, advancing the field of behavioral science.
Single-nucleus transcriptional and chromatin accessibility analyses of maturing mouse Achilles tendon uncover the molecular landscape of tendon stem/progenitor cells
Authors: Tsutsumi Hiroki , Chiba Tomoki , Fujii Yuta , Matsushima Takahide , Kimura Tsuyoshi , Kanai Akinori , Kishida Akio , Suzuki Yutaka , Asahara Hiroshi
Published: October 2024

Tendons and ligaments are crucial connective tissues linking bones and muscles, yet achieving full functional recovery after injury remains challenging. We investigated the characteristics of tendon stem/progenitor cells (TSPCs) by focusing on the declining tendon repair capacity with growth. Using single-cell RNA sequencing on Achilles tendon cells from 2- and 6-week-old mice, we identifiedCd55andCd248as novel surface antigen markers for TSPCs. Combining single-nucleus ATAC and RNA sequencing analyses revealed thatCd55andCd248positive fractions in tendon tissue are TSPCs, with this population decreasing at 1 weeks. We also identified candidate upstream transcription factors regulating these fractions. Functional analyses of isolated CD55/CD248 positive cells demonstrated high clonogenic potential and tendon differentiation capacity, forming functional tendon-like tissuein vitro. This study establishes CD55 and CD248 as novel TSPC surface antigens, potentially advancing tendon regenerative medicine and contributing to the development of new treatment strategies for tendon and ligament injuries.
Algorithms to reconstruct past indels: the deletion-only parsimony problem
Authors: Moutet Jordan , Rivals Eric , Pardi Fabio
Published: October 2024

Ancestral sequence reconstruction is an important task in bioinformatics, with applications ranging from protein engineering to the study of genome evolution. When sequences can only undergo substitutions, optimal reconstructions can be efficiently computed using well-known algorithms. However, accounting for indels in ancestral reconstructions is much harder. First, for biologically-relevant problem formulations, no polynomial-time exact algorithms are available. Second, multiple reconstructions are often equally parsimonious or likely, making it crucial to correctly display uncertainty in the results.

Here, we consider a parsimony approach where any indel event has the same cost, irrespective of its size or the branch where it occurs. We thoroughly examine the case where only deletions are allowed, while addressing the aforementioned limitations. First, we describe an exact algorithm to obtain all the optimal solutions. The algorithm runs in polynomial time if only one solution is sought. Second, we show that all possible optimal reconstructions for a fixed node can be represented using a graph computable in polynomial time. While previous studies have proposed graph-based representations of ancestral reconstructions, this result is the first to offer a solid mathematical justification for this approach. Finally we discuss the relevance of the deletion-only case for the general case.

Author summary

An exciting frontier in evolutionary biology is the ability to reconstruct DNA or protein sequences from species that lived in the distant past. By analyzing sequences from present-day species, we aim to infer the sequences of their common ancestors —a process known as ancestral sequence reconstruction. This task has far-reaching applications, such as resurrecting ancient proteins and studying the biology of extinct organisms. However, a significant challenge remains: the lack of well-established methods for inferring past deletions and insertions —–mutations that remove or add segments of genetic code. In this paper, we present algorithms that lay the groundwork for addressing this gap. We show that finding the reconstructions involving only deletion events, while minimizing their number, can be done efficiently. Additionally, we show that all optimal solutions can be represented using specialized graphs. While previous studies have proposed graph-based representations of ancestral reconstructions, we are the first to provide a rigorous mathematical foundation for the use of these graphs.
An IFN-STAT1-CYBB Axis Defines Protective Plasmacytoid DC to Neutrophil Crosstalk During Aspergillus fumigatus Infection.
Authors: Guo Yahui , Aufiero Mariano A. , Mills Kathleen A.M. , Grassmann Simon A. , Kim Hyunu , Zumbo Paul , Gjonbalaj Mergim , Billips Audrey , Mar Katrina B. , Yu Yao , Betel Doron , Sun Joseph C. , Hohl Tobias M.
Published: October 2024

Aspergillus fumigatus is the most common cause of invasive aspergillosis (IA), a devastating infection in immunocompromised patients. Plasmacytoid dendritic cells (pDCs) regulate host defense against IA by enhancing neutrophil antifungal properties in the lung. Here, we define the pDC activation trajectory during A. fumigatus infection and the molecular events that underlie the protective pDC - neutrophil crosstalk. Fungus-induced pDC activation begins after bone marrow egress and results in pDC-dependent regulation of lung type I and type III IFN levels. These pDC-derived products act on type I and type III IFN receptor-expressing neutrophils and control neutrophil fungicidal activity and reactive oxygen species production via STAT1 signaling in a cell-intrinsic manner. Mechanistically, neutrophil STAT1 signaling regulates the transcription and expression of Cybb, which encodes one of five NADPH oxidase subunits. Thus, pDCs regulate neutrophil-dependent immunity against inhaled molds by controlling the local expression of a subunit required for NADPH oxidase assembly and activity in the lung.
Composition of saliva metabolome is significantly associated with SARS-CoV2 infection and with severity of COVID-19 disease
Authors: Larios-Serrato Violeta , Vázquez-Manjarrez Natalia , Resendis-Antonio Osbaldo , Rios-Sarabia Nora , Meza-Marquez Beatriz , Fiehn Oliver , Torres Javier
Published: October 2024

Background

The metabolome of COVID-19 patients has been studied sparsely, with most research focusing on a limited number of plasma metabolites or small cohorts. This is the first study to test saliva metabolites in COVID-19 patients in a comprehensive way, revealing significant changes linked to disease severity and highlighting saliva is potential as a non-invasive diagnostic tool.

Methods

We included 30 asymptomatic subjects with no prior COVID-19 infection or vaccination, 102 patients with mild SARS-CoV-2 infection, and 61 hospitalized patients with confirmed SARS-CoV-2 status. Saliva samples were analyzed using hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS/MS) in positive and negative ionization modes.

Results

Significant changes in metabolites were identified in COVID-19 patients, with distinct patterns based on disease severity. Healthy individuals exhibited a well-regulated bacterial network, while severe cases showed disordered microbial networks. Elevated dipeptides such as Val-Glu and Met-Gln in moderate cases suggest specific protease activity related to SARS-CoV-2. Increased acetylated amino acids like N-Acetylserine and N-Acetylhistidine indicate potential biomarkers for stress and disease severity. Bacterial metabolites, including muramic acid and indole-3-carboxaldehyde, were higher in mild-moderate cases, indicating oral microbiota changes. In severe cases, polyamines and organ damage-related metabolites, such as N-acetylspermine and 3-methylcytidine, were significantly increased. Interestingly, metabolites reduced in moderate cases were elevated in severe cases.

Conclusions

Saliva metabolomics offers insight into disease progression and potential biomarkers for COVID-19.
Monocytes-derived cxcl12 guides a directional migration of blood vessels in zebrafish
Authors: Lu Xiaofeng , Wang Xiaoning , Li Bowen , Wang Xin , Duan Xuchu , Liu Dong
Published: October 2024

Background

Sprouting blood vessels, reaching the aimed location, and establishing the proper connections are vital for building vascular networks. Such biological processes are subject to precise molecular regulation. So far, the mechanistic insights into understanding how blood vessels grow to the correct position are limited. In particular, the guiding cues and the signaling-originating cells remain elusive.

Methods

Live imaging analysis was used to observe the vascular developmental process of zebrafish. Whole-mount in situ hybridization and fluorescent in situ hybridization were used to detect the expression profiles of the genes. Single-cell sequencing analysis was conducted to identify the guiding protein and its originating cells.

Results

Taking advantage of live imaging analysis, we described a directional blood vessel migration in the vascularization process of zebrafish pectoral fins. We demonstrated that pectoral fin vessel c (PFVc) migrated over long distances and was anastomosed with the second pair of intersegmental vessels (ISVs). Furthermore, we found the cxcl12a-cxcr4a axis specifically guided this long-distance extension of PFVc-ISV, and either inhibition or over-expression of cxcl12a-cxcr4a signaling both mislead the growth of PFVc to ectopic areas. Finally, based on an analysis of single-cell sequencing data, we revealed that a population of monocytes expresses the Cxcl12a, which guides the migration of the vascular sprout.

Conclusions

Our study identified Cxcl12a as the signaling molecule for orchestrating organotypic-specific long-distance migration and anastomosis of the pectoral fin vessel and ISVs in zebrafish. We discovered a specific cluster of gata1-positive monocytes that are responsible for expressing Cxcl12a. The findings offer novel insights into the mechanisms underlying organotypic vascularization in vertebrates.
Multisensory integration in Peripersonal Space indexes consciousness states in sleep and disorders of consciousness
Authors: Bertoni Tommaso , Ricci Giulia , Johr Jane , Donno Brunella , Cataldi Jacinthe , Fellrath Julia , Stephan Aurelie , Foglia Carolina , Lecci Sandro , Dauvin Florian , Lopez Da Silva Marina , Galigani Mattia , Pozeg Polona , Dunet Vincent , De Lucia Marzia , Noel Jean Paul , Magosso Elisa , Diserens Karin , Siclari Francesca , Serino Andrea
Published: October 2024

Conscious experience encompasses not only the awareness of external objects, but also a phenomenal representation of the embodied subject of the experience. The latter is mediated by the integration of multisensory stimuli between the body and the environment, a process mediated by the Peripersonal Space (PPS) system. Here we thus tested the hypothesis that a neural marker of PPS representation may index the presence of conscious experience. Using high-density EEG in awake participants, we identified a PPS index, characterized by high-beta oscillations in centroparietal regions during the integration of audiotactile stimuli presented near versus far from the body. We then examined this marker across two models of altered consciousness, i.e., sleep and disorders of consciousness. The PPS index persisted during dreaming and waking conscious states but was absent during dreamless, unconscious states. Moreover, the same index predicted behavioural measures of consciousness and clinical outcome in patients recovering from disorders of consciousness. These results suggest that multisensory integration within the PPS is tightly linked to the presence of conscious experience.
Syntaxin11 Deficiency Inhibits CRAC Channel Priming To Suppress Cytotoxicity And Gene Expression In FHLH4 Patient T Lymphocytes
Authors: Datta Sritama , Gupta Abhikarsh , Jagetiya Kunal Mukesh , Tiwari Vikas , Yamashita Megumi , Ammann Sandra , Shahrooei Mohammad , Yande Atharva Rahul , Sowdhamini Ramanathan , Dani Adish , Prakriya Murali , Vig Monika
Published: October 2024

CRAC channels enable calcium entry from the extracellular space in response to a variety of stimuli and are crucial for gene expression and granule exocytosis in lymphocytes. Here we find that Syntaxin11, a Q-SNARE, associated with FHLH4 disease in human patients, directly binds Orai1, the pore forming subunit of CRAC channels. Syntaxin11 depletion strongly inhibited SOCE, CRAC currents, IL-2 expression and cytotoxicity in cell lines and FHLH4 patient T lymphocytes. Constitutively active H134 Orai1 mutant completely reconstituted calcium entry in Syntaxin11 depleted cells and the defects of granule exocytosis as well as gene expression could be bypassed by ionomycin induced calcium influx in FHLH4 T lymphocytes. Our data reveal a Syntaxin11 induced pre-activation state of Orai which is necessary for its subsequent coupling and gating by the endoplasmic reticulum resident Stim protein. We propose that ion channel regulation by specific SNAREs is a primary and conserved function which may have preceded their role in vesicle fusion.
A Three Dimensional Immunolabeling Method with Peroxidase-fused Nanobodies and Fluorochromized Tyramide-Glucose Oxidase Signal Amplification
Authors: Yamauchi Kenta , Koike Masato , Hioki Hiroyuki
Published: October 2024

Three dimensional immunohistochemistry (3D-IHC), immunolabeling of 3D tissues, reveals the spatial organization of molecular and cellular assemblies in the context of the tissue architecture. Deep and rapid penetration of antibodies into 3D tissues and highly sensitive detection are critical for high-throughput imaging analysis of immunolabeled 3D tissues. Here, we report a nanobody (nAb)-based 3D-IHC, POD-nAb/FT-GO 3D-IHC, for high-speed and high-sensitive detection of targets within 3D tissues. Peroxidase-fused nAbs (POD-nAbs) enhanced immunolabeling depth and allowed for highly sensitive detection by combined with a fluorescent tyramide signal amplification system, Fluorochromized Tyramide-Glucose Oxidase (FT-GO). Multiplex labeling was implemented to the 3D-IHC by quenching POD with sodium azide. Using the 3D-IHC technique, we successfully visualized somata and processes of neuronal and glial cells in millimeter-thick mouse brain tissues within three days. Given its high-speed and high-sensitive detection, our 3D-IHC protocol, POD-nAb/FT-GO 3D-IHC, would provide a useful platform for histochemical analysis in 3D tissues.
Three-dimensional memory of nuclear organization through cell cycles
Authors: Fujishiro Shin , Sasai Masaki
Published: October 2024

The genome in the cell nucleus is organized by a dynamic process influenced by structural memory from mitosis. In this study, we develop a model of human genome dynamics through cell cycles by extending the previously developed whole-genome model to cover the mitotic phase. With this extension, we focus on the role of mitotic and cell cycle memory in genome organization. The simulation progresses from mitosis to interphase and the subsequent mitosis, leading to successive cell cycles. During mitosis, our model describes microtubule dynamics, showing how forces orchestrate the assembly of chromosomes into a rosette ring structure at metaphase. The model explains how the positioning of chromosomes depends on their size in metaphase. The memory of the metaphase configuration persists through mitosis and into interphase in dimensions perpendicular to the cell division axis, effectively guiding the distribution of chromosome territories over multiple cell cycles. At the onset of each G1 phase, phase separation of active and inactive chromatin domains occurs, leading to A/B compartmentalization. Our cycling simulations show that the compartments are unaffected by structural memory from previous cycles and are consistently established in each cell cycle. The genome model developed in this study highlights the interplay between chromosome dynamics and structural memory across cell cycles, providing insights for the analyses of cellular processes.
Social Experience Shapes Fighting Strategies for Reproductive Success
Authors: Gao Can , Ma Mingze , Chen Jie , Ji Xiaoxiao , Peng Qionglin , Pan Yufeng
Published: October 2024

Social isolation generally increases aggression but decreases mating competition, resulting in an intricate and ambiguous relationship between social experience, aggression, and reproductive success. In maleDrosophila, aggression is often characterized by lunging, a frequent and comparatively gentle combat behavior. Here, we establish a behavioral paradigm for studying a less frequent but more vigorous fighting form known as tussling. We discover that while social enrichment decreases lunging, aligning with past observations, it heightens the more forceful tussling behavior. These two forms of aggression rely on different olfactory receptor neurons, specifically Or67d for lunging and Or47b for tussling. We further identify three pairs of central pC1 neurons that specifically promote tussling. Moreover, shifting from lunging to tussling in socially enriched males facilitates better territory control and mating success, mitigating the disadvantages associated with aging. These findings reveal how social experience shapes fighting strategies to optimize reproductive success.
Understanding the epidemiology and pathogenesis ofMycobacterium tuberculosiswith non-redundant pangenome and population genetics
Authors: Zhou Yang , Anthony Richard , Wang Shengfen , Xia Hui , Ou Xichao , Zhao Bing , Song Yuanyuan , Zheng Yang , He Ping , Liu Dongxin , Zhao Yanlin , van Soolingen Dick
Published: October 2024

Tuberculosis is a major public health threat demanding more than one million lives every year. Many challenges exist to defeat this deadly infectious disease which address the importance of a thorough understanding of the biology of the causative agentMycobacterium tuberculosis(MTB). We generated a non-redundant pangenome of 420 epidemic MTB strains from China. We estimate that MTB strains have a pangenome of 4,278 genes encoding 4,183 proteins, of which 3,438 of which are core genes. However, due to 99,694 interruptions in 2,447 coding genes, only 1,651 may be translated in all samples, which dramatically reduces the number of active core genes. Of these interruptions, 67,315 (67.52%) could be classified by various genetic variations detected by currently available tools, and more than half of them are due to structure variations, mostly small indels. We further describe differential evolutionary patterns of genes under the influences of selective pressure, population structure and background selection. While selective pressure is ubiquitous among these coding genes, evolutionary adaptations primarily occur in 1,313 genes. Genes located in the cell wall and membrane region are under the strongest selective pressure, while biological processes including regulation of transcription, translation and regulation of growth are under strongest background selection in MTB. The metabolism of fatty acids may be an outstanding example of evolutionary adaption for MTB under current selective pressure. This study provides a comprehensive view on the genetic diversity and evolution patterns of coding genes in MTB which may deepen our understanding of its epidemiology and pathogenicity.
Dopamine transmission in the anterior insula shapes the neural coding of anxiety
Authors: Couderc Yoni , Reddy Tanmai Dhani , Vardiero Giovanni , Garg Archi , Ricci Daria , d’Almeida Marion , Nicolas Céline , Habchi Tina , Wu Yue K. , Gjorgjieva Julijana , Li Yulong , Valjent Emmanuel , Beyeler Anna
Published: October 2024

The insular cortex (or insula), and particularly its anterior region, plays a crucial role in the control of emotional valence and anxiety (Etkin & Wager, 2007; Méndez-Ruette et al., 2019; Nicolas et al., 2023). While dopamine neurotransmission is known to modulate anxiety levels in humans (Hjorth et al., 2021) and animal models (de la Mora et al., 2010; Bananej et al., 2012; Zarrindast & Khakpai, 2015; DeGroot et al., 2020; Godino et al., 2023), its regulatory effects on the anterior insula remained unexplored. Here, using a multifaceted approach, we uncovered how dopamine shapes anterior insula function in anxiety and valence processing. First, we revealed a high density of neurons expressing type-1 dopamine receptors (D1) in the insula, particularly important in the anterior insula, and seven times greater than the density of neurons expressing type-2 dopamine receptors (D2). Few neurons co-expressedDrd1 and Drd2mRNAs in the anterior and posterior insula, and the density ofDrd1+neurons in the anterior insula was twice higher among inhibitory neurons than excitatory neurons. Second, we found that pharmacological activation of D1 in the anterior insula is anxiogenic, suggesting a direct link between insular dopamine signaling and anxiety-related behaviors. Using fiber-photometry recordings, we identified that the amplitude of dopamine release onto D1+ neurons in the anterior insula while mice were in anxiogenic spaces or receiving mild foot shocks was both positively correlated with mice level of trait anxiety. Population dynamics and deep-learning analyses of anterior insula single-unit recordings uncovered distinct coding patterns of anxiety-provoking and safe environments, as well as tastants of positive and negative valence. Remarkably, systemic D1 activation, which heightens anxiety- related behaviors, dampens this coding dichotomy by increasing coding variability for protected spaces while increasing the coding reliability for anxiogenic spaces. Interestingly, the coding reliability of anxiogenic areas was positively correlated with mice level of trait anxiety, and we observed a trend towards a positive correlation between the coding reliability of a negative tastants, and mice level of anxiety. Altogether, our findings provide a new model of neural population coding of anxiety and emotional valence and unravel D1-dependent coding mechanisms in the mouse anterior insula.
Hydrothermally treated yeast cell wall suppresses the growth of MCF7 cells under isolated conditions
Authors: Kitagawa Takanori
Published: October 2024

Traditionally, yeast cell wall (YCW) has limited applications because of their low solubility. To overcome this, a novel method was developed using a hydrothermal reaction to enhance its solubility and decrease its viscosity; this resulted in the production of a soluble form of YCW, known as the YCW treated with hydrothermal reaction (YCW-H), with broader chemical composition. Therefore, in the present study, we aim to investigate YCW-H, a hydrothermally treated YCW product with enhanced solubility, for the inhibition of cancer cell proliferation. YCW-H promotes plant growth by effectively regulating soil microspheres. YCW-H inhibited the growth of MCF-7 breast cancer cells even after complete physical separation from the cells. This suggests the presence of a diffusible cytotoxic factor in YCW-H, a phenomenon not observed in the presence of untreated YCW. Since YCW-H possess reactive carbon species (RCS), we hypothesized that the reactive radical species generated during the hydrothermal treatment of YCW are responsible for this effect. The addition of Fe(III) ions to YCW-H further amplified the production of RCS and its inhibitory activity across the plastic barrier, correlating with the increased RCS levels. The radicals migrated to the water in wells adjacent to YCW-H, indicating that RCS generation is a key determinant of the inhibition of cancer cell growth. Moreover, compounds containing RCS were confirmed to exhibit cytotoxicity. Thus, our findings underscore the RCS-containing compounds from YCW-H as promising candidates for developing novel medical devices for cancer treatment.
Sex Differences in Contextual Extinction Learning After Single Binge-Like EtOH Exposure in Adolescent C57BL/6J Mice
Authors: Cardona-Jordan Kiara M. , Lay-Rivera Xiany X. , Cartagena-López Eliezer , Bracho-Rincón Dina L. , González-Bermejo Ruth , Alvarado-Monefeldt Gerardo L. , Gonzalez Del Toro Jovangelis P. , Esquilín-Rodríguez Christian J. , Lloret-Torres Mario , Velázquez-Marrero Cristina
Published: October 2024

The relationship between chronic heavy drinking and post-traumatic stress disorder (PTSD) is well-documented; however, the impact of more common drinking patterns, such as a single episode leading to a blood alcohol concentration (BAC) of 0.09 g/dL (moderate intoxication), remains underexplored. Given the frequent co-occurrence of PTSD and alcohol misuse, it is essential to understand the biological and behavioral factors driving this comorbidity. We hypothesize that alcohol’s immediate sedative effects are coupled with the development of persistent molecular alcohol tolerance, which may disrupt fear extinction learning. To investigate this, we employed aSingleEpisodeEthanol(SEE)in-vivoexposure to mimic binge-like alcohol consumption over a 6-hour period, following contextual conditioning trials. Extinction trials were conducted 24 hours later to assess the effects on extinction learning. Our findings reveal a significant deficit in fear extinction learning in alcohol-treated adolescent male mice compared to saline-treated controls, with no such effects observed in female adolescent mice. These results suggest that even non-chronic alcohol exposure may contribute to the development of trauma- and stress-related disorders, such as PTSD, in males. Additionally, histological analysis revealed significant alterations in FKBP5, β-catenin, and GSK-3β levels in the hippocampus, striatum, and basolateral amygdala of alcohol-treated mice following extinction. The insights gained from this study could reshape our understanding of the risk factors for PTSD and open new avenues for prevention and treatment, targeting the molecular mechanisms that mediate alcohol tolerance.

STATEMENT OF SIGNIFICANCE

This study investigates the impact of binge-like alcohol exposure on context extinction learning, aiming to identify previously unrecognized risks associated with this common drinking pattern and the development of trauma- and stress-related disorders, such as PTSD. Our findings reveal that binge-like alcohol exposure impairs extinction learning in male adolescent mice by disrupting molecular mechanisms within fear memory circuits, suggesting novel therapeutic and preventive targets. Dysregulated candidates include the canonical Wnt/β-catenin signaling proteins, β-catenin and GSK-3β, along with FKBP5, a key player in glucocorticoid signaling and part of a gene network linked to PTSD. These alterations, found in the dorsal hippocampus (dHPC), basolateral amygdala (BLA), striatum, and nucleus accumbens (NAc) core and shell, may serve as promising targets for future pharmacological intervention.
Heavy Metal and Antibiotic Co-resistance in Bacteria Isolated from Poultry Samples in Bangladesh: An Emerging Environmental Threat
Authors: Sarker Amily , Haque Nabila , Ayaz Mohammad , Antu Umme Samia , Mou Taslin Jahan , Dey Shuvra Kanti , Parvez Md.Anowar Khasru
Published: October 2024

The excessive use of heavy metals and antibiotics as additives in livestock feed may significantly contribute to bacterial resistance in poultry environments by exerting selective pressure. This study aimed to comprehensively analyze bacterial isolates from poultry farms across Bangladesh, focusing on their resistance to heavy metals and antibiotics. Through microbial phenotypic screening, 23 cadmium-resistant and 28 chromium-resistant bacterial isolates were identified. The minimum inhibitory concentrations (MICs) for cadmium and chromium in metal-resistant bacterial isolates varied significantly, ranging from 200 μg/ml to 1600 μg/ml. All cadmium-resistant isolates were fully resistant to cefixime and ceftazidime, while chromium-resistant isolates showed 90% resistance to tetracycline. The cadmium resistance gene, such asczc, was detected in 26% (6/23) of cadmium-resistant isolates, and the chromium reductase genechrRwas detected in 18% (5/28) of chromium-resistant isolates. Among the chromium-reductase isolates, 40% (2/5) exhibited co-resistance and harbored thechrRgene, beta-lactam resistance genes (bla-TEM,bla-NDM), and the colistin resistance gene (mcr-2). A significant association (p = 0.026) was observed between the presence of thechrRgene and these antibiotic resistance genes. However, no co-resistance was found in cadmium-resistant isolates. Mobile genetic elements, specifically Class 1 integrons, were found in 33.33% (2/6) of the isolates carrying the cadmium resistance gene (czc) and in 100% (5/5) of the isolates containing the chromium reductase gene (chrR). These findings underscore poultry environments in Bangladesh as significant reservoirs for bacteria with dual resistance to heavy metals and antibiotics, emphasizing the need for further investigation into the genetic mechanisms driving microbial resistance and its implications for public health.
µPIX: Leveraging Generative AI for Enhanced, Personalized and Sustainable Microscopy
Authors: Bon Gabriel , Sapède Daniel , Matthews Cédric , Daian Fabrice
Published: October 2024

Fluorescence microscopy is a critical tool in bio-cellular research, enabling the visualization of biological tissues and cellular structures. However, the inevitable aging of microscopes can degrade their performance posing challenges for long-term scientific investigations. In this study, we introduceµPIX, a personalized deep learning workflow based on a Generative Adversarial Network (GAN) utilizing a Pix2Pix architecture. The network is trained in a supervised manner to denoise images, optimize pre-processing for binary segmentation, and compensate for equipment aging. Our results, evaluated using standard image quality and binary segmentation metrics, demonstrate thatµPIXoutperforms popular deep learning architectures based on convolutional auto-encoder networks for similar tasks. Additionally, our generative model effectively rejuvenates older detectors to perform on par with newer ones, not only by improving image quality but also by preserving resolution in depth and maintaining a near-linear response between original and generated images in terms of pixel intensity (crucial for quantitative imaging). These findings suggest that generative deep learning approaches can significantly contribute to more sustainable, cost-effective microscopy, fostering continued innovation and discovery in biological research.
Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing
Authors: Chang Jessie J-Y , Yang Xuan , Teng Haotian , Reames Benjamin , Corbin Vincent , Coin Lachlan
Published: October 2024

Polyadenylation is a dynamic process which is important in cellular physiology. Oxford Nanopore Technologies direct RNA-sequencing provides a strategy for sequencing the full-length RNA molecule and analysis of the transcriptome and epi-transcriptome. There are currently several tools available for poly(A) tail-length estimation, including well-established tools such astailfindrandnanopolish, as well as two more recent deep learning models:DoradoandBoostNano. However, there has been limited benchmarking of the accuracy of these tools against gold-standard datasets. In this paper we evaluate four poly(A) estimation tools using synthetic RNA standards (Sequins), which have known poly(A) tail-lengths and provide a valuable approach to measuring the accuracy of poly(A) tail-length estimation. All four tools generate mean tail-length estimates which lie within 12% of the correct value. Overall,Doradois recommended as the preferred approach due to its relatively fast run times, low coefficient of variation and ease of use with integration with base-calling.
Clinical characteristics, drug-resistance genes and virulence analysis of carbapenem-resistant Klebsiella pneumoniae
Authors: He Junning , Zhang Peilin , Li Cheng , Xie Ning , Yin Yijie , Wang Guixia , Liang Xianting , Liu Yongfang
Published: October 2024

OBJECTIVE

The aim was to investigate the clinical infection characteristics, risk factors and convergence of carbapenem-resistant and hypervirulent Klebsiella pneumoniae(hv-CRKP) in our hospital, in order to provide scientific basis for the rational use of antibiotics in the clinic.

METHODS

CRKP strains were isolated from clinical specimens of 44 patients in central intensive care unit (CICU), neurosurgery intensive care unit (NICU) and emergency intensive care unit (EICU) of our hospital in 41 months. The clinical manifestations of the patients were analyzed, and the hypermucoviscous phenotype was defined by string test. The drug resistance gene, virulence gene and capsular specific serotype of the isolated strains were detected by polymerase chain reaction (PCR) technology, and the gene of CRKP producing KPC enzyme was sequence.

RESULTS

The incidence of sepsis in 44 patients with CRKP infection was 25.0%, and the overall treatment failure rate was 38.6%. All the 44 strains of CRKP produced KPC enzyme, and all of them were blaKPC-2(100%);14 strains (31.8%) were positive in string test; 23 strains (52.3%) were found to have virulence related genes, including 10 strains (22.7%) of rmpA, 16 strains (36.4%) of iucA and 19 strains (43.2%) of peg-344. 5 strains (11.4%) were capsule-specific serotypes and 13 strains (29.5%) were identified as hv-CRKP.

CONCLUSION

The mechanism of CRKP resistance in our hospital isblaKPC-2, the detection rates of virulence gene, string test positive and hypervirulent capsular specific serotype are all relatively high in CRKP, there are not a few Klebsiella pneumoniae with carbapenem-resistant and hypervirulent.
Dysfunction of the episodic memory network in the Alzheimer’s disease cascade
Authors: Lattmann-Grefe René , Vockert Niklas , Machts Judith , Suksangkharn Yanin , Yakupov Renat , Schütze Hartmut , Glanz Wenzel , Incesoy Enise , Butryn Michaela , Lüsebrink Falk , Schmid Matthias , Stark Melina , Kleineidam Luca , Spottke Annika , Coenjaerts Marie , Brosseron Frederic , Fliessbach Klaus , Schneider Anja , Dechent Peter , Hetzer Stefan , Scheffler Klaus , Ramirez Alfredo , Laske Christoph , Sodenkamp Sebastian , Altenstein Slawek , Schneider Luisa-Sophie , Gref Daria , Spruth Eike Jakob , Lohse Andrea , Schott Björn H. , Wiltfang Jens , Kilimann Ingo , Goerss Doreen , Rostamzadeh Ayda , Priller Josef , Peters Oliver , Hellmann-Regen Julian , Teipel Stefan , Jessen Frank , Maass Anne , Ziegler Gabriel , Düzel Emrah
Published: October 2024

Alzheimer’s disease (AD) is a major cause of dementia and cognitive decline. Here we assessed how episodic memory circuit dysfunction, a hallmark of AD, is related to the longitudinal cascade of AD biomarkers, neurodegeneration and cognition using data from the DZNE Longitudinal Cognitive Impairment and Dementia study. This data set is unique by including over 1000 longitudinal functional magnetic resonance imaging (fMRI) measurements during episodic memory encoding. We leveraged a disease progression model (DPM) to obtain AD progression scores. Voxel-wise analyses revealed widespread loss of deactivation (hyperactivation) and activation (hypoactivation) with increasing disease stage. Hyperactivation trajectories were nonlinear and visually preceded trajectories of cognition. Overall, hyperactivation was independently associated with co-occurrence of amyloid- and tau-positivity and neurodegeneration, suggesting synaptic dysfunction and neurodegeneration as two independent drives of cognitive decline. Our results therefore provide evidence for a critical time window in which pharmacological treatments targeting the synapse may improve cognition.
Principles and Operation of Virtual Brain Twins
Authors: Hashemi Meysam , Depannemaecker Damien , Saggio Marisa , Triebkorn Paul , Rabuffo Giovanni , Fousek Jan , Ziaeemehr Abolfazl , Sip Viktor , Athanasiadis Anastasios , Breyton Martin , Woodman Marmaduke , Wang Huifang , Petkoski Spase , Sorrentino Pierpaolo , Jirsa Viktor
Published: October 2024

Current clinical methods often overlook individual variability by relying on population-wide trials, while mechanism-based trials remain underutilized in neuroscience due to the brain's complexity. A Virtual Brain Twin (VBT) is a personalized digital replica of an individual's brain, integrating structural and functional brain data into advanced computational models and inference algorithms. By bridging the gap between molecular mechanisms, whole-brain dynamics, and imaging data, VBTs enhance the understanding of (patho)physiological mechanisms, advancing insights into both healthy and disordered brain function. Central to VBT is the network modeling that couples mesoscopic representation of neuronal activity through white matter connectivity, enabling the simulation of brain dynamics at a network level. This transformative approach provides interpretable predictive capabilities, supporting clinicians in personalizing treatments and optimizing interventions. This manuscript outlines the key components of VBT development, covering the conceptual, mathematical, technical, and clinical aspects. We describe the stages of VBT construction--from anatomical coupling and modeling to simulation and Bayesian inference--and demonstrate their applications in resting-state, healthy aging, epilepsy, and multiple sclerosis. Finally, we discuss potential extensions to other neurological disorders, such as Parkinson's disease, and explore future applications in consciousness research and brain-computer interfaces, paving the way for advancements in personalized medicine and brain-machine integration.