bluuebunny/crossref_metadata_2025 huggingface dataset:
Tossing the coin of extended-spectrum β-lactamase: prevalence of extended-spectrum β-lactamase-producing Klebsiella pneumoniae isolated from patients with sepsis
Authors: Achan Beatrice , Luggya Tonny , Ebwongu Robert Innocent , Sekyanzi Simon , Kajumbula Henry
Published: February 2025

Background.
Klebsiella pneumoniae is part of the ESKAPE (Enterococcus faecium, Staphylococcus aureus, K. pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp.) group of multidrug-resistant (MDR) pathogens. K. pneumoniae is the leading cause of antimicrobial resistance-associated mortality and the second leading cause of nosocomial bloodstream infections (BSIs), globally and in sub-Saharan Africa. Therefore, it was aimed to determine the antibiotic resistance patterns of K. pneumoniae isolated from blood cultures of patients with features of sepsis at Mulago National Referral Hospital, Uganda.

Methods. The cross-sectional study on patients with features of sepsis utilized K. pneumoniae (n=30) isolated from positive blood culture specimens. The antibiotic resistance profile was determined by the Clinical and Laboratory Standards Institute’s Kirby–Bauer disc diffusion method, which was used to classify the isolates as susceptible, intermediate and resistant. K. pneumoniae isolates that were resistant to third-generation cephalosporins were subjected to extended-spectrum β-lactamase (ESBL) screening and confirmation using the double-disc synergy test using cefotaxime, ceftazidime, ceftriaxone, cefotaxime–clavulanic acid and ceftazidime–clavulanic acid. The results were analysed for frequencies.

Results.
K. pneumoniae isolates showed emerging resistance to imipenem at 13% (4 out of 30) followed by amikacin at 17% (5 out of 30). There was intermediate resistance to gentamycin at 60% (18 out of 30). However, K. pneumoniae showed the highest resistance to piperacillin at 100% (30 out of 30) followed by sulphamethoxazole-trimethoprim and cefepime, both showing a percentage of 97% (29 out of 30). Up to 16 out of 30 (53.3%) of K. pneumoniae were positive for ESBL production, whilst 14 out of 30 (46.7%) were negative.

Conclusion. There was a high prevalence of antibiotic-resistant ESBL-producing K. pneumoniae isolates from BSI of patients with features of sepsis in Uganda’s Mulago National Referral Hospital.
Phenotypic and genetic heterogeneity of Acinetobacter baumannii in the course of an animal chronic infection
Authors: Bednarczuk Léa , Chassard Alexandre , Plantade Julie , Charpentier Xavier , Laaberki Maria-Halima
Published: February 2025

Acinetobacter baumannii is a nosocomial pathogen associated with various infections, including urinary tract infections (UTIs). In the course of an infection, A. baumannii is known to rapidly become resistant to antibiotic therapy, but much less is known about possible adaptation without antibiotic pressure. Through a retrospective study, we investigated within-host genetic diversity during a subclinical 5-year UTI in an animal–patient after withdrawal of colistin treatment. We conducted whole-genome sequencing and phenotypic assays on 17 clonally related isolates from the Sequence Type 25 lineage. Phylogenomic analysis revealed their proximity with animal and human strains from the same country suggesting zoonotic transmission (France). In this case study, the clonally related strains presented variations in genome sizes and nucleotide sequences. Over the course of the infection, A. baumannii underwent genome reduction through insertion sequence (IS) recombination, phage excision or plasmid curing. Alongside this global genome reduction, we observed an expansion of IS17, initially located on the endogenous large plasmid. Genetic variations were mainly located in biofilm formation and metabolism genes. We observed repeated variations affecting three biofilm genes and two adhesion operons associated with weak biofilm-forming capacity. Conversely, only two metabolic genes were recurrently affected, and phenotypic assays indicated a rather stable metabolism profile between the isolates suggesting minor adaptations to its host. Lastly, an overall decreased antibiotic resistance – expected in the absence of antibiotic treatment – contrasted with a conserved colistin resistance due to a pmrB mutation among the isolates.
GraphMatch: Knowledge Graphs for Allogeneic Stem Cell Matching
Authors: Kunau Timothy M.
Published: February 2025

Allogeneic bone marrow and umbilical cord stem cell transplants often provide the best hope for curing many patients with leukemia, lymphoma, and over 70 other diseases. Matching patients to unrelated donors requires flexible and timely searches as matching criteria change. Matching systems should scale to accommodate the diversity in patient and donor typing resolution and the growing number of donors.

We developed GraphMatch (GM), a scalable graph database solution for storing and searching variable-resolution HLA genotype markers. As a test set, we expanded the World Marrow Donor Association (WMDA) validation set based on the IPD-IMGT/HLA Database version 2.16 to create a synthetic production data set of 1 million patients and 10 million donors.

Single-patient identity search times range from 218.5 milliseconds per patient for 2 million donors to 1201.4 milliseconds per patient for 10 million donors. Search performance timing remained linear with the number of edges, even at a production scale.

In general, GM demonstrates the usefulness of graph databases as a flexible platform for scalable matching solutions.
Massive Chromosome Fission and Speciation in Asian River Chub: Integrating Kinetochore Reproduction Theory with Transposable Element Dynamics
Authors: Tai Jui-Hung , Wang Tzi-Yuan , Ma Gwo-Chin , Wu Yu-Wei , Yu Tsung-Han , Wang Chen-Fan , Liao Te-Yu , Huang Shih-Pin , Wang Feng-Yu , Terai Yohey , Wu Tsung-Han , Hsu Chun-Hua , Yu Hon-Tsen , Shao Kwang-Tsao , Chaw Shu-Miaw , Wang Hurng-Yi
Published: February 2025

Chromosome rearrangements significantly influence speciation, but the role of chromosome fission is paradoxical due to its link with unbalanced segregation. The kinetochore reproduction theory suggests that fissions from kinetochore duplication should allow normal segregation, though empirical support remains scarce. In the Opsariichthyini tribe (Asian river chub), chromosome number vary from 2N=48 in most genera to 76-78 inOpsariichthysdue to 15 fission events.Opsariichthysharbors over 15 species, substantially surpassing the typical three to four species in other genera. This exceptional diversity, coupled with dramatic chromosome fission, makes the Opsariichthyini as an ideal model for studying speciation driven by chromosome fission. We sequenced and annotated genomes from five representative species, finding that significant transposable element (TE) accumulation in centromeres likely contributes to centromeric DNA expansion. This, in turn, may have facilitated neokinetochore formation, potentially leading to chromosome fissions. The fissioned chromosomes showed lower migration rates and higher genetic divergence between species than their intact counterparts, highlighting their role as reproductive barriers that promote speciation. Our findings offer unprecedented support for the kinetochore reproduction theory and elucidate the complex interplay between TE activities, genomic structure, and speciation.
Examining Perinatal Regionalization in Practice: A Network Analysis of Maternal Transport in Georgia
Authors: Li Jingyu , Radke Stephanie M. , Steimle Lauren N.
Published: February 2025

Objective

The primary objective was to use network analysis to characterize maternal transport patterns in the state of Georgia and compare them with the state’s designated perinatal regions (DPRs).

Study Design

Using 2017-2022 birth records in Georgia, we constructed network graphs of maternal transport routes among obstetric facilities. We used multivariate logistic regression to identify factors associated with inter-DPR transports. We applied a community-detection algorithm to cluster facilities and compared the clusters to Georgia’s DPRs.

Results

Among 774 639 deliveries, 2 757 (0.36%) involved transports among obstetric facilities. 8 facility clusters were identified and strongly aligned with DPRs (p < 0.001). Inter-DRP transports tended to occur between neighboring DPRs and between facilities belonging to the same healthcare system (p < 0.001).

Conclusion

Network analysis reveals patterns of maternal transports among obstetric facilities. States can improve the design of perinatal regionalization systems by formalizing existing partnership among obstetric facilities.
Predicting age-related determinants of heterogeneous outcomes to COVID-19 mRNA vaccines through mathematical modelling
Authors: Deng Xiaoyan , Farhang-Sardroodi Suzan , Craig Morgan
Published: February 2025

Older adults tend to exhibit weaker vaccine-elicited responses to mRNA COVID-19 immunization than younger people. This is a public health concern, as older individuals are more likely to experience severe COVID-19. To better understand the mechanisms of this age-related disparity, we developed a mathematical model of the post-vaccination humoral immune response. Through calibration to clinical data from 32 healthcare workers (HCWs) and 27 seniors who received the primary vaccine series (two priming doses and one booster), our model predicted that repeated vaccinations consistently enhanced antibody responses in both groups. While seniors were estimated to experience an accelerated decay in T follicular helper cells compared to HCWs, a larger booster dose effectively compensated for this weakened antibody response. Furthermore, we linked antibody and neutralization levels and used this relationship to predict post-vaccination neutralization, thus serving as a proxy for vaccine efficacy. By studying various combinations of mixed doses sizes in the primary vaccination series, our model predicted that administering a full-dose booster significantly enhances immunization outcomes, irrespective of the initial vaccine dose size. Further, a biannual half booster strategy was found to be more effective than one with an annual full booster, especially for seniors. Overall, our findings highlight the importance of tailoring vaccination strategies to different age groups to provide robust and long-lasting immunity against SARS-CoV-2 infections.
Adjuvants to improve efficacy of miticides in managed honey bee (Apis mellifera) colonies to control Varroa destructor
Authors: Shannon Brandon , Zhang Rui , Marsh Lucas , Johnson Reed M.
Published: February 2025

Beekeepers must manage Varroa destructor mites to maintain colony health. Large-scale beekeepers often use chemical treatments (miticides) to manage this pest. Miticide resistance drives a need for compounds with alternative modes of toxic action that can be used in a rotation as part of a Varroa management plan. This research aimed to determine the efficacy of oxalic acid, clove oil, and fenpyroximate when delivered in glycerin soaked in strips and combined with a range of bee-safe adjuvants. Adjuvants are a group of compounds used in plant pesticide applications to increase the spreading and penetration of a pesticide. Laboratory cage trials tested a miticidal active ingredient (oxalic acid, clove oil, or fenpyroximate) and an adjuvant (Ecostep BC-12®, Ecostep SE-11®, Ecostep AE-13®, Ecostep CE-13®, or Silwet L-7500®) in glycerin-soaked strips; field trials evaluated oxalic acid combined with Ecostep BC-12® adjuvant in glycerin-soaked strips. Field trials with oxalic acid and adjuvant in glycerin caused a significant decrease in Varroa in year 1 and a significant reduction in Varroa, relative to the solvent control, in year 2. On the other hand, field trials with oxalic acid alone did not reduce Varroa loads in colonies relative to the solvent control. Additionally, mite drop data indicate increased speed for the miticidal effect when an adjuvant is included with oxalic acid. This research informs formulation chemistries for oxalic acid and other miticides to help beekeepers maintain healthy hives.
Communication pathway analysis within protein-nucleic acid complexes
Authors: Bheemireddy Sneha , González-Alemán Roy , Bignon Emmanuelle , Karami Yasaman
Published: February 2025

Inter-residue communication forms a vast and intricate network that underpins essential biological processes such as catalysis, gene expression, and cell signaling. Allostery, a crucial phenomenon where distant regions of a macromolecule are energetically coupled to elicit functional responses, operates through these intricate communication networks within macromolecular complexes. Despite the pivotal role of nucleic acids in these networks, their contributions to allostery remain largely overlooked. To address this gap, we developed ComPASS, a large-scale computational method designed to study communication networks in protein-protein and protein-nucleic acid complexes. Recognizing the significance of dynamics in the communication of macromolecules, our approach leverages molecular dynamics (MD) simulation data to extract inter-residue key properties, including dynamical correlations, interactions, and distances. These properties are integrated to construct a weighted communication network that comprehensively represents dependencies among amino acids and nucleotides. Using ComPASS, we uncovered distinct mechanisms of signal transmission in diverse macromolecular systems. In Cysteinyl-tRNA synthetase, the central domain was found to mediate the coordination between substrate recognition and enzymatic activity, ensuring functional precision. In the LacI repressor, allosteric communication occurs through interface pathways within the dimer, effectively linking ligand sensing to DNA binding. For the Type IIF restriction endonuclease Bse634I, structural communication across dimer and tetramer interfaces was crucial for specific DNA recognition. In the liver X receptor, a key helical region was identified as a bridge connecting ligand-binding events to DNA interactions. Finally, our analysis with ComPASS aligned with previous literature, confirmed the role of H2A L1 loops in mediating communication across histone interfaces and coordinating interactions between structural domains in nucleosome complexes. ComPASS is available as an open-source tool, maintained athttps://github.com/yasamankarami/compass. By offering an integrated framework for studying communication networks, ComPASS advances our understanding of conformational dynamics, particularly within protein-nucleic acid complexes.
MARTi: a real-time analysis and visualisation tool for nanopore metagenomics
Authors: Peel Ned , Martin Samuel , Heavens Darren , Yu Douglas W , Clark Matthew D , Leggett Richard M
Published: February 2025

The emergence of nanopore sequencing technology has the potential to transform metagenomics by offering low-cost, portable, and long-read sequencing capabilities. Furthermore, these platforms enable real-time data generation, which could significantly reduce the time from sample collection to result, a crucial factor for point-of-care diagnostics and bio-surveillance. However, the full potential of real-time metagenomics remains largely unfulfilled due to a lack of accessible, open-source bioinformatic tools.

We present MARTi (Metagenomic Analysis in Real-Time), an innovative open-source software designed for the real-time analysis, visualisation, and exploration of metagenomic data. MARTi supports various classification methods, including BLAST, Centrifuge, and Kraken2, letting users customise parameters and utilise their own databases for taxonomic classification and antimicrobial resistance analysis. With a user-friendly, browser-based graphical interface, MARTi provides dynamic, real-time updates on community composition and AMR gene identification.

MARTi’s architecture and operational flexibility make it suitable for diverse research applications, ranging from in-field analysis to large-scale metagenomic studies. Using both simulated and real-world data, we demonstrate MARTi’s performance in read classification, taxon detection, and relative abundance estimation. By bridging the gap between sequencing and actionable insights, MARTi marks a significant advance in the accessibility and functionality of real-time metagenomic analysis.
Climate-driven warming disrupts the symbiosis of bobtail squidEuprymna scolopesand the luminous bacteriumVibrio fischeri
Authors: Otjacques E. , Jatico B. , Marques T.A. , Xavier J.C. , Ruby E. , McFall-Ngai M. , Rosa R.
Published: February 2025

Under the current climate crisis, marine heatwaves (MHW) are expected to intensify and become more frequent in the future, leading to adverse effects on marine life. Here, we aimed to investigate the impact of environmental warming on the symbiotic relationship between the Hawaiian bobtail squid (Euprymna scolopes) and the bioluminescent bacteriumVibrio fischeri. We exposed eggs ofE. scolopesto three different temperatures during the embryogenesis, namely: i) 25 °C (yearly average), ii) 27 °C (average summer), or iii) 30 °C (category IV MHW), followed by a colonisation assay under the same conditions. Decreased hatching success and reduced developmental time were observed across warmer conditions compared to 25 °C. Moreover, exposure to the category IV MHW led to a significant decrease in survival after 48 hours. With increasing temperature, bobtail squids required more bacteria in the surrounding seawater for successful colonisation. When colonised, the regression of the light organ’s appendages was not dependent on temperature, but the opposite was found in non-colonised bobtail squids. Furthermore, the capacity to maintain the symbiosis diminished significantly with temperature. Finally, the capacity for crypt 3 formation in the squid’s light organ, which is crucial for enhancing resilience under stress, also declined with warming conditions. This study emphasises the critical need to study the dynamics of microbial symbiosis under the projected conditions for the ocean of tomorrow.
Accuracy of the Lotka-Volterra Model fails in strongly coupled microbial consumer-resource systems
Authors: Mustri Michael , Duan Quqiming , Pawar Samraat
Published: February 2025

The generalized Lotka-Volterra (GLV) model is a cornerstone in theoretical ecology for modeling the dynamics emerging from pairwise species interactions within complex ecological communities. The GLV is also increasingly being used to infer species interactions and predict dynamics from empirical data on microbial communities in particular. However, despite its widespread use, the accuracy of the GLV’s pairwise interaction structure in capturing the unseen dynamics of microbial consumer-resource interactions—arising from resource competition and metabolite exchanges—remains unclear. Here, we rigorously quantify how well the GLV can represent the dynamics of a general mathematical model that encapsulates key consumer-resource processes in microbial communities. We find that the GLV significantly misrepresents the feasibility, stability, and reactivity of microbial communities above a threshold, biologically feasible level of consumer-resource coupling because it omits higher-order nonlinear interactions. We show that the probability of the GLV making inaccurate predictions can be quantified by a simple, empirically accessible measure of timescale separation between consumers and resources. These insights advance understanding of the temporal dynamics in resource-mediated microbial interactions and provide a method to gauge the GLV’s reliability under various empirical and theoretical scenarios.
Integrative Analysis of Single-cell and Bulk RNA Sequencing Reveals Macrophage Heterogeneity in Lyme Arthritis
Authors: Dong Yan , Luo Yanshuang , Liu Meng , Chen Yantong , Song Chao , Liu Xiaorong , Yang Fusong , Liang Zhi , Zi Liye , Gao Hongbing , Cao Zhichao , Gao Fucun , Chen Xuesong , Zhou Guozhong
Published: February 2025

Introduction

Lyme arthritis (LA) is a chronic inflammatory joint disease caused byBorrelia burgdorferiinfection, with approximately 10-20% of patients developing antibiotic resistance. Macrophages in the synovial microenvironment play a crucial role in disease progression, but their precise regulatory mechanisms remain unclear.

Methods

scRNA-seq data of synovial tissue from LA patients was obtained from the GEO database (GSE233850) and integrated with transcriptome data from our research team’s LA mouse model and the GSE125503 dataset. Multiple analytical strategies, including cell clustering, differential gene analysis, GO and KEGG enrichment analysis, pseudotime trajectory analysis, and cell-cell communication analysis, were employed to systematically investigate macrophage characteristics in LA. In vitro experiments using RAW cell lines were conducted to validate the role of key genes in response toBorrelia burgdorferiinfection.

Results

Through single-cell transcriptome analysis of 78,015 cells in the GSE233850 dataset, we identified and annotated 27,843 macrophages, further classifying them into 4 functional subgroups. Differential expression analysis revealed 387 macrophage-specific genes. Cell-cell communication network analysis showed that macrophages interact with other immune cells, including T cells and B cells, through multiple signaling pathways. GO and KEGG enrichment analyses indicated that these differentially expressed genes were mainly enriched in biological processes such as inflammatory response regulation, pathogen recognition, and cytokine signaling. By integrating transcriptome data from our team’s LA mouse model and the GSE125503 dataset, we screened and validated three potential diagnostic marker genes (SIRPB1C, FABP5, and PEPD). In vitro experiments using the RAW264.7 macrophage cell line showed significant expression changes in these genes followingBorrelia burgdorferistimulation (P< 0.05).

Conclusion

This study provides the first systematic characterization of macrophage transcriptome in the LA synovial microenvironment, revealing their functional heterogeneity and identifying potential diagnostic markers, offering new targets for targeted therapeutic strategies.
GerNA-Bind: Geometric-enhanced RNA-ligand Binding Specificity Prediction with Deep Learning
Authors: Xia Yunpeng , Li Jiayi , Chu Yi-Ting , Rao Jiahua , Chen Jing , Hua Chenqing , Yu Dong-Jun , Chen Xiu-Cai , Zheng Shuangjia
Published: February 2025

RNA molecules are essential regulators of biological processes and promising therapeutic targets for various diseases. Discovering small molecules that selectively bind to specific RNA conformations remains challenging due to RNA’s structural complexity and the limited availability of high-resolution data. Herein, we introduce GerNA-Bind, a geometric deep learning framework to predict RNA-ligand binding specificity by integrating multi-state RNA-ligand representations and interactions. GerNA-Bind achieves state-of-the-art performance on multiple benchmark datasets and excels in predicting interactions for low-homology RNA-ligand pairs. It achieves a 20.8% improvement in precision for binding site prediction compared to AlphaFold3. Furthermore, it offers informative, well-calibrated predictions with built-in uncertainty quantification. In a large-scale virtual screening application, GerNA-Bind identified 18 structurally diverse compounds targeting the oncogenic MALAT1 RNA, with experimentally confirmed submicromolar affinities. Among them, one lead compound selectively binds the MALAT1 triple-helix, reduces its transcript levels, and inhibits cancer cell migration. These findings highlight GerNA-Bind’s potential as a powerful tool for RNA-focused drug discovery, offering both accuracy and biological insight.
Occupational fall incidence associated with heated tobacco product smoking and lifestyle behaviors: a nationwide cross-sectional study in Japan
Authors: Tsushima Saki , Watanabe Kazuhiko , Hirohashi Sora , Yoshimi Tomohiro , Fujino Yoshihisa , Tabuchi Takahiro , Zaitsu Masayoshi
Published: February 2025

Objectives

To identify the association between heated tobacco product (HTP) smoking and occupational falls, particularly combined with other lifestyle variables, including sleeping duration and comorbidities.

Methods

This web-based nationwide cross-sectional study (September–November 2023) involved 18,440 current workers (mean age, 43 years; women, 43.9%) in Japan. The primary outcome was occupational fall incidence in the past year. The secondary outcome was fall-related fractures. Smoking status was categorized as never, former, or current smokers; current smokers further classified into exclusive cigarette, exclusive HTP, and dual smokers (both cigarettes and HTPs). Other behavioral factors and covariates included alcohol consumption, sleep duration, physical activity, comorbidities, body mass index, hypnotics/anxiolytics use, and sociodemographic variables. Incidence ratios (IRs) and 95% confidence intervals (CIs) for occupational falls were estimated using multilevel Poisson regression with robust variance.

Results

Occupational falls and fall-related fractures were reported by 7.3% and 2.8% participants, respectively, in the past year. Younger workers were more likely to experience occupational falls. Compared with never smokers, current smokers had higher occupational fall incidence (IR = 1.36, 95% CI: 1.20–1.54), with exclusive HTP (IR = 1.78) and dual smokers (IR = 1.64) showing particularly elevated incidences. Similar patterns were observed for fall-related fractures. Elevated IRs were also observed for other lifestyle variables, including short sleep duration and diabetes, with the strongest associations found among younger workers.

Conclusions

Current smoking, particularly HTP use, and lifestyle behaviors were significantly associated with occupational falls in Japan. These findings highlight the importance of lifestyle modifications to prevent occupational falls.

KEY MESSAGES

What is already known on this topic

Individual lifestyle behaviors, including physical activity, sedentary behaviors, and sleep quality, are associated with the risk of falls. However, the association between the risk of falls and smoking habits, including heated tobacco product (HTP) use, which has emerged as a public health concern in Japan, remains poorly understood.

What this study adds

Current smoking, particularly HTP use, is associated with occupational falls.

How this study might affect research, practice or policy

Smoking cessation can be considered a modifiable behavior for occupational fall prevention. Further studies are needed to investigate the relationship between smoking and the incidence of falls.
Robust single-trial estimates of electrocortical generalized aversive conditioning: Validation of a Bayesian multilevel learning model
Authors: Farkas Andrew H. , Escobar Judith Cediel , Gilbert Faith E. , Ding Mingzhou , Keil Andreas
Published: February 2025

Aversive conditioning changes visuocortical responses to conditioned cues, and the generalization of these changes to perceptually similar cues may provide mechanistic insights into anxiety and fear disorders. Yet, neuroimaging conditioning paradigms are challenged by poor single-trial signal-to-noise ratios (SNR), missing trials, and inter-individual differences in learning. Here, we address these issues with the validation of a steady-state visual evoked potential (ssVEP) generalization paradigm in conjunction with a Rescorla-Wagner inspired Bayesian multilevel learning model. A preliminary group of observers (N=24) viewed circular gratings varying in grating orientation, with only one orientation paired with an aversive outcome (noxious electric pulse). Gratings were flickered at 15 Hz to evoke ssVEPs recorded with 31 channels of EEG in an MRI scanner. The multilevel structure of the Bayesian model learning model informs and constrains estimates per participant providing an interpretable generative model. It led to superior cross-validation accuracy and insights into individual participant dynamics than simpler models. It also isolates the generalized effects of conditioning, providing improved statistical certainty. Lastly, the present report demonstrates that missing trials are interpolated and weighted appropriately using the full model’s structure. This is a critical aspect for single-trial analyses of simultaneously recorded physiological measures, because each added measure will typically increase the number of trials missing a complete set of observations. The present technical report validates a limited version of a learning model to illustrate the utility of this analytical framework. It shows how models may be iteratively built and compared in a modern Bayesian workflow. Future models may use different conceptualizations of learning, allow integration of clinically relevant factors, and enable the fusion of different simultaneous physiological recordings.
Precision measurements of brain oxygen utilization with positron emission tomography
Authors: Lee John J. , Shimony Joshua S , Metcalf Nicholas , Vlassenko Andrei G , Goyal Manu S
Published: February 2025

Oxygen utilization is important for studies of brain metabolism, alongside other measurements such as for glucose metabolism. Oxygen and other measurements with [15O] tracers and PET, however, are significantly more challenging than measurements of [18F]fluorodeoxyglucose, the standard for probing tissue glucose metabolism in vivo, in part due to the much shorter radioactive half-life of [15O]. This work examines details of precision measurement of [15O] tracers and their kinetics. Investigations of arterial input functions (AIFs) and image-derived input functions (IDIFs) have figured prominently for PET, but [15O] tracers are rarely studied given the small numbers of PET facilities equipped to work with these tracers, particularly in their inhaled form. Estimates of IDIFs and AIFs for [15O] tracers have demonstrably distinct characteristics arising from instrumentation as well as circulatory physiology. To reconcile IDIFs and AIFs, we developed a generalizable model for bolus tracer transport, corrected for known effects of instrumentation for measuring IDIFs and AIFs, and found intravascular[15O]CO to be especially suited for constructing a robust recovery coefficient for IDIFs compared against AIFs. Within a Bayesian framework for posterior estimation and estimating data evidence, IDIFs provide parameter estimates compatible with AIFs in the setting of biological variability. IDIFs also provide data evidence that exceeds that of results from AIFs. These suggest that scalar recovery coefficients may be adequate to estimate partial volume effects, and that the circulatory consistency of internal carotid IDIFs with brain tissue perfusion provides greater precision than what can be estimated using radial artery AIFs, which exhibit greater variability of recirculation wave forms.
Neutralizing antibodies elicited by Nipah virus G-head nanoparticle target diverse sites and inhibit receptor binding and fusion
Authors: Zhou Dan , Wang Yong , Yao Yanfeng , Kuang Wenhua , Cheng Rao , Zhang Gan , Liu Hang , Li Xin , Chiu Sandra , Deng Zengqin , Zhao Haiyan
Published: February 2025

Nipah virus (NiV) and Hendra virus (HeV), two highly pathogenic Henipaviruses (HNVs), pose a significant public health threat. The attachment glycoprotein (G) plays a crucial role in viral attachment and entry, making it an attractive target for vaccine and therapeutic antibody development. However, the antigenic landscape and neutralization sensitivity of the G protein remain poorly defined. Here, we systematically characterize 27 monoclonal antibodies (mAbs) elicited by NiV G head (GH) nanoparticle-immunized mice. Among these, 25 mAbs exhibit neutralizing activity against two major NiV strains, NiV-Malaysia and NiV-Bangladesh, with five mAbs also cross-inhibiting HeV infection. Although all mAbs target GH, they inhibit viral infection through distinct mechanisms, either by blocking receptor ephrin-B2 engagement with the G protein or by preventing viral membrane fusion. Notably, mAbs from two distinct groups conferred complete protection to hamsters against lethal NiV-Malaysia infection. Structural analysis of NiV GHin complex with four representative Fabs reveals four non-overlapping epitopes, including two novel antigenic sites and one shared protective epitope identified across species. Our study provides a comprehensive map of the antigenic determinants of NiV GH, elucidates the relationship between epitopes, neutralization mechanisms, and protection, and offers new insights and opportunities for antibody-based therapies and vaccine development.

Highlights

Most mAbs induced in G head nanoparticle-immunized mice are potent neutralizers MAbs recognizing the G head block receptor binding or viral fusion

Structural analysis shows mAbs target four distinct epitopes on G head protein

Receptor competition site on G head is a shared protective antigenic site in human and multiple animals
Efficient Inference of Macrophylogenies: Insights from the Avian Tree of Life
Authors: Zhao Min , Thom Gregory , Faircloth Brant C. , Andersen Michael J. , Barker F. Keith , Benz Brett W. , Braun Michael J. , Bravo Gustavo A. , Brumfield Robb T. , Chesser R. Terry , Derryberry Elizabeth P. , Glenn Travis C. , Harvey Michael G. , Hosner Peter A. , Imfeld Tyler S. , Joseph Leo , Manthey Joseph D. , McCormack John E. , McCullough Jenna M. , Moyle Robert G. , Oliveros Carl H. , Carreiro Noor D. White , Winker Kevin , Field Daniel J. , Ksepka Daniel T. , Braun Edward L. , Kimball Rebecca T. , Smith Brian Tilston
Published: February 2025

The exponential growth of molecular sequence data over the past decade has enabled the construction of numerous clade-specific phylogenies encompassing hundreds or thousands of taxa. These independent studies often include overlapping data, presenting a unique opportunity to build macrophylogenies (phylogenies sampling > 1,000 taxa) for entire classes across the Tree of Life. However, the inference of large trees remains constrained by logistical, computational, and methodological challenges. The Avian Tree of Life provides an ideal model for evaluating strategies to robustly infer macrophylogenies from intersecting datasets derived from smaller studies. In this study, we leveraged a comprehensive resource of sequence capture datasets to evaluate the phylogenetic accuracy and computational costs of four methodological approaches: (1) supermatrix approaches using concatenation, including the “fast” maximum likelihood (ML) methods, (2) filtering datasets to reduce heterogeneity, (3) supertree estimation based on published phylogenomic trees, and (4) a “divide-and-conquer” strategy, wherein smaller ML trees were estimated and subsequently combined using a supertree approach. Additionally, we examined the impact of these methods on divergence time estimation using a dataset that includes newly vetted fossil calibrations for the Avian Tree of Life. Our findings highlight that recently developed fast tree search approaches offer a reasonable compromise between computational efficiency and phylogenetic accuracy, facilitating inference of macrophylogenies.
Neural and Behavioral Adaptation to Listening with a Unilateral Cochlear Implant (CI)
Authors: Wöstmann Malte , Meineke Hannah Marie , Schönweiler Rainer , Hollfelder Daniela , Bruchhage Karl-Ludwig , Leichtle Anke , Obleser Jonas
Published: February 2025

The human auditory system must encode sounds and separate relevant input from noise. Hearing loss hurts both processes, but profound hearing loss and deafness can be treated with a Cochlear Implant (CI). Here, we probe the human brain’s adaptation to electrical hearing with a CI in unilaterally implanted CI users with normal or aided contralateral hearing, in the first and seventh month after CI activation. In addition to clinical measures of speech comprehension, electroencephalography (EEG) recordings during passive listening to amplitude-modulated (AM) sounds and an active spatial listening task with competing talkers were analyzed. We demonstrate that, first, adaptation to hearing with a CI is accompanied by decreasing cortical overrepresentation and increasing auditory temporal coding fidelity: After six month of CI use, auditory phase-locking during passive listening relatively decreased for 4-Hz AM sounds but increased for 40-Hz AM sounds. Second, strongest benefits of listening with the CI (i.e., CI on vs. off) in the spatial-listening task occurred when the CI ear was primarily exposed to target sound. Here, the power of lateralized alpha oscillations (∼10 Hz) served as a robust signature of spatial attention, independent of time (1stvs 7thmonth) and listening modality (with vs. without CI). Stronger lateralized alpha modulation in the hemisphere contralateral to the non-implanted ear suggests asymmetrical allocation of auditory spatial attention, operating preferentially on the input to the non-implanted ear. These findings highlight CI-related plasticity in auditory perception and a persistent attentional bias toward the non-implanted ear, emphasizing the need to consider bilateral auditory input in CI rehabilitation.
Quantification of SARM1 activity in human peripheral blood mononuclear cells
Authors: Dabill Lila , Shen Ivana , Brazill Jennifer , Neiner Alicia , Sasaki Yo , Scheller Erica L
Published: February 2025

SARM1 (sterile α and TIR motif-containing protein-1) is an NADase enzyme that has been identified as the central executioner of Wallerian axon degeneration. Given this, SARM1 is of high interest as a candidate therapeutic target and SARM1 inhibitors are currently in clinical trials for prevention and treatment of neurodegeneration. Beyond neuroscience, emerging studies reveal that SARM1 activation may also drive aspects of bone fragility, liver pathology, adipose tissue expansion, and insulin resistance in settings of metabolic disease. However, we lack methods to quantify SARM1 activation in humans using clinical isolates to better define patients at high risk of SARM1-mediated tissue damage, informing the future clinical application of SARM1 inhibitors. Unlike neurons, peripheral blood mononuclear cells (PBMCs) represent an easily accessible population of cells for clinical screening. We hypothesized that by pairing activators and inhibitors of SARM1 with analysis of downstream changes in cellular metabolites, we could quantify both the basal SARM1 activity and the SARM1 activation potential of human PBMCs. Our results reveal that SARM1 agonist pyrinuron, also known as Vacor, activates a dose-dependent increase in cAPDR and the cADPR:ADPR ratio that is arrested when paired with SARM1 inhibitor DSRM-3716. Various changes in secondary metabolites were also characterized and reported herein. Overall, these findings demonstrate that human PBMCs have detectable SARM1 activation potential and could be leveraged as a clinical readout of SARM1 expression and activity across diverse disease contexts.
Neuromodulation in neural organoids with shell MEAs
Authors: Acha Chris , George Derosh , Diaz Lauren C. , Ouyang Ziwei , Alam El Din Dowlette-Mary M. , Surlekar Hrishikesh , Moghadas Babak , Loftus Eva , Mangalvedhekar Gandhali M. , Rayasam Pratyush Sai R. , Lai Yu-Chiao , Smirnova Lena , Caffo Brian S. , Johnson Erik C. , Gracias David H.
Published: February 2025

Neural organoids (NOs) have emerged as important tissue engineering models for brain sciences and biocomputing. Establishing reliable relationships between stimulation and recording traces of electrical activity is essential to monitor the functionality of NOs, especially as it relates to realizing biocomputing paradigms such as reinforcement learning or stimulus discrimination. While researchers have demonstrated neuromodulation in NOs, they have primarily used 2D microelectrode arrays (MEAs) with limited access to the entire 3D contour of the NOs. Here, we report neuromodulation using tiny mimics of macroscale EEG caps or shell MEAs. Specifically, we observe that stimulating current within a specific range (20 to 30 µA) induced a statistically significant increase in neuron firing rate when comparing the activity five seconds before and after stimulation. We observed neuromodulatory behavior using both three– and 16-electrode shells and could generate 3D spatiotemporal maps of neuromodulatory activity around the surface of the NO. Our studies demonstrate a methodology for investigating 3D spatiotemporal neuromodulation in organoids of broad relevance to biomedical engineering and biocomputing.

One-Sentence Summary

Neuromodulation, an essential intelligence feature, was observed using 3D stimulation and recording from neural organoids.
Mapping the regulatory effects of common and rare non-coding variants across cellular and developmental contexts in the brain and heart
Authors: Marderstein Andrew R. , Kundu Soumya , Padhi Evin M. , Deshpande Salil , Wang Austin , Robb Esther , Sun Ying , Yun Chang M. , Pomales-Matos Diego , Xie Yilin , Nachun Daniel , Jessa Selin , Kundaje Anshul , Montgomery Stephen B.
Published: February 2025

Whole genome sequencing has identified over a billion non-coding variants in humans, while GWAS has revealed the non-coding genome as a significant contributor to disease. However, prioritizing causal common and rare non-coding variants in human disease, and understanding how selective pressures have shaped the non-coding genome, remains a significant challenge. Here, we predicted the effects of 15 million variants with deep learning models trained on single-cell ATAC-seq across 132 cellular contexts in adult and fetal brain and heart, producing nearly two billion context-specific predictions. Using these predictions, we distinguish candidate causal variants underlying human traits and diseases and their context-specific effects. While common variant effects are more cell-type-specific, rare variants exert more cell-type-shared regulatory effects, with selective pressures particularly targeting variants affecting fetal brain neurons. To prioritizede novomutations with extreme regulatory effects, we developed FLARE, a context-specific functional genomic model of constraint. FLARE outperformed other methods in prioritizing case mutations from autism-affected families near syndromic autism-associated genes; for example, identifying mutation outliers nearCNTNAP2that would be missed by alternative approaches. Overall, our findings demonstrate the potential of integrating single-cell maps with population genetics and deep learning-based variant effect prediction to elucidate mechanisms of development and disease–ultimately, supporting the notion that genetic contributions to neurodevelopmental disorders are predominantly rare.
Deep exploration of transcriptomic cellular identities over evolutionary time
Authors: Xu Ying , Gatt Catherine , Kaymak Esra , Kikuchi Kensei , Bourguignon Thomas , Zanini Fabio
Published: February 2025

Whole-organism cell atlases have painted the cellular landscapes of individual species, however comparing cells across the tree of life remains challenging. Most cross-species analyses are restricted to orthologous genes, while the complexity of atlas data constitutes an access barrier for many researchers. We developed a computational strategy to accelerate the exploration of cellular identities at scale. We integrated 30 atlases detailing the expression of 861,013 genes by 2,645,508 animal and plant cells and trained a universal model of cellular transcriptomes to track cell type diversification over evolutionary times. A derived model could identify cell types of a new species within minutes on both mammals and ade novoconstructed atlas of the insectCryptocercus punctulatus. We then reduced the footprint of atlases by 100 times while retaining crucial information and developed interfaces to answer 26 query types within two seconds, accelerating atlas exploration by ∼50,000 times.
Low-spin ground state of the giant single-molecule magnets
{Mn70}
and
{Mn84}
Authors: Rausch Roman , Karrasch Christoph
Published: February 2025

The single-molecule magnets {Mn70} and {Mn84} are characterized by a 14-site unit cell with S=2 spin sites arranged in a circular geometry. Experimentally, these systems exhibit a magnetic ground state with a notably low total spin Stot=5–7. Up to now, this low-spin ground state has been up difficult to describe theoretically due to the complexity of the quantum Heisenberg model for such a large system. In this paper, we fill this gap and demonstrate that the ground state of {Mn70} and {Mn84} is in fact governed by a small, finite Stot in quantitative agreement with the experiment. We employ accurate, large-scale SU(2)-symmetric density-matrix renormalization group calculations for a quantum Heisenberg model with previously published exchange parameters obtained by density-functional theory. We do not find a low-spin state for the same parameters and S=1 and thus propose that frustrated systems with S≥2 are inherently prone to weak ferromagnetic interactions. This could account for the prevalence of similar low-spin Mn-based single-molecule magnets. Finally, we compute the full magnetization curve and find wide plateaus at 10/14, 11/14, 12/14, and 13/14 of the saturation, which can be traced back to nearly independent three-site clusters with broken intercluster bonds.

Published by the American Physical Society
2025
Optimizing entanglement and Bell inequality violation in top antitop events
Authors: Cheng Kun , Han Tao , Low Matthew
Published: February 2025

A top quark and an antitop quark produced together at colliders have correlated spins. These spins constitute a quantum state that can exhibit entanglement and violate Bell’s inequality. In realistic collider experiments, most analyses allow the axes, as well the Lorentz frame, to vary event by event, thus introducing a dependence on the choice of event-dependent basis leading us to adopt “fictitious states,” rather than genuine quantum states. The basis dependence of fictitious states allows for an optimization procedure, which makes the usage of fictitious states advantageous in measuring entanglement and Bell inequality violation. In this work, we show analytically that the basis that diagonalizes the spin-spin correlations is optimal for maximizing spin correlations, entanglement, and Bell inequality violation. We show that the optimal basis is approximately the same as the fixed beam basis (or the rotated beam basis) near the tt¯ production threshold, while it approaches the helicity basis far above threshold. Using this basis, we present the sensitivity for entanglement and Bell inequality violation in tt¯ events at the Large Hadron Collider (LHC) and a future e+e− collider. Since observing Bell inequality violation appears to be quite challenging experimentally, and requires a large dataset in collider experiments, choosing the optimal basis is crucially important to observe Bell inequality violation. Our method and general approach are equally applicable to other systems beyond tt¯, including interactions beyond the Standard Model.

Published by the American Physical Society
2025
Constructive fermionic matrix product states for projected Fermi sea
Authors: Li Kangle , Zhang Yan-Bai , Po Hoi Chun
Published: February 2025

Projected wave functions offer a means of incorporating local correlation effects in gapless electronic phases of matter, like metals. Although such wave functions can be readily specified formally, computing their associated physical observables is challenging. Tensor network approaches offer a modern numerical method for this task. In this paper, we develop and demonstrate a constructive tensor-network approach for obtaining physical quantities, like fermion two-point functions and density-density correlation functions, for one-dimensional projected Fermi sea states. We benchmark our method against exact analytical results for spin-1/2 electrons subjected to the Gutzwiller projection, and then present results on spinless fermions with nearest-neighbor repulsion. For a state with two pairs of Fermi points, we reveal a correlation-dependent tuning of the characteristic wave vector of the charge density modulation in the system.

Published by the American Physical Society
2025