bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aromatase-independent estrogenesis: Wood-Ljungdahl pathway likely contributed to the emergence of estrogens in the biosphere
Authors: Wang Po-Hsiang , Wu Tien-Yu , Chen Yi-Lung , Gicana Ronnie G. , Lee Tzong-Huei , Chen Mei-Jou , Hsiao Tsun-Hsien , Jade Lu Mei-Yeh , Lai Yi-Li , Wang Tzi-Yuan , Li Jeng-Yi , Chiang Yin-Ru 
Published: October 2024

AbstractAndrogen and estrogen, key sex hormones, were long thought to be exclusively produced by vertebrates. The O2-dependent aromatase that converts androgen to estrogen (estrogenesis) has never been identified in any prokaryotes. Here, we report the discovery of anaerobic estrogenesis in a Peptococcaceae bacterium (strain TUW77) isolated from the gut of the great blue-spotted mudskipper (Boleophthalmus pectinirostris). This strain exhibits unprecedented testosterone fermentation pathways, transforming testosterone into estrogens and androstanediol under anaerobic conditions. Physiological experiments revealed that strain TUW77 grows exclusively on testosterone, utilizing the androgenic C-19 methyl group as both the carbon source and electron donor. The genomic analysis identified three copies of a polycistronic gene cluster,abeABC(anaerobicbacterialestrogenesis), encoding components of a classic cobalamin-dependent methyltransferase system. These genes, highly expressed under testosterone-fed conditions, show up to 57% protein identity to the characterized EmtAB from denitrifyingDenitratisomaspp., known for methylating estrogen into androgen (the reverse reaction). Tiered transcriptomic and proteomic analyses suggest that the removed C-19 methyl group is completely oxidized to CO2viathe oxidative Wood-Ljungdahl pathway, while the reducing equivalents (NADH) fully reduce remaining testosterone to androstanediol. Consistently, the addition of anthraquinone-2,6-disulfonate, an extracellular electron acceptor, to testosterone-fed TUW77 cultures enabled complete testosterone conversion into estrogen without androstanediol accumulation (anaerobic testosterone oxidation). This discovery of aromatase-independent estrogenesis in anaerobic bacteria suggests that the ancient Wood-Ljungdahl pathway may have contributed to the emergence of estrogens in the early biosphere.SignificanceUsing a testosterone-grown anaerobic bacterium as a model organism, we characterized this unusual anaerobic estrogenesis at the molecular level. Our findings challenge the long-held belief that estrogen production is exclusive to aromatase-containing vertebrates, expanding our understanding of steroid hormone biosynthesis across domains of life. The involvement of ancient strictly anaerobic Peptococcaceae members and the Wood-Ljungdahl pathway suggests that bacterial estrogenesis may predate O2-dependent estrogenesis in vertebrates. Furthermore, the identification of estrogen-producing bacteria in animal guts opens new avenues for potential microbiome-based hypoestrogenism therapies to supplement estrogen in menopausal or ovariectomized females, offering an innovative alternative to current hormone replacement strategies.
Deterministic colonization arises early during the transition of soil bacteria to the phyllosphere and is shaped by plant-microbe interactions
Authors: Mayer Teresa , Teutloff Erik , Unger Kerstin , Lehenberger Pamela , Agler Matthew T. 
Published: October 2024

AbstractBackgroundUpon seed germination, soil bacteria are activated to transition to the plant and eventually colonize mature tissues like leaves. These bacteria are poised to significantly influence plant health, but we know little about their colonization routes. We studied the mechanisms of the transition of soil bacteria to germinating plants and leaves by experimentally manipulating inoculation times and usingin-plantaisolation to understand bacteria that can make the complex soil-to-leaf transition. Using a trackable, labeledPseudomonas viridiflava(Pv3D9) amended to soil, we tested how plant-microbe-microbe interactions shape assembly mechanisms in natural soil communites.ResultsWe found that the stages of the transition of bacteria from soil to leaves before true leaf emergence were important in establishing uniquely diverse leaf bacteriomes. A wide diversity of leaf-associated taxa can individually make this transition, but most are still shaped by stochastic processes. Interestingly, deterministic processes drove some important taxa only when they transitioned from soil to leaves, but not when they were inoculated later. The opportunistic pathogenPv3D9 promoted plant growth in a natural soil, likely by activating plant immunity. These effects in turn strongly affected the soil-to-leaf transition of almost strictly taxa that colonized deterministically, demonstrating the important role of plant-microbe-microbe interactions in controlling deterministic processes.ConclusionsDiverse, well-adapted bacterial taxa make the soil-to-leaf transition during natural colonization resulting in characteristic diversity in healthy leaf microbiomes. The domination of stochastic mechanisms during this colonization indicates that many taxa must strongly compete to establish their niche. During this complex transition, however, specific important taxa emerge that are driven by deterministic processes, suggesting they occupy unique niches. The malleability of these processes suggests that they may be controlled, for example by targeted soil manipulations. This finding is significant given the important roles of these bacteria in plant health and offers directions forward for engineering beneficial plant microbiomes.
Synaptic input architecture of visual cortical neurons revealed by large-scale synapse imaging without backpropagating action potentials
Authors: Kondo Satoru , Kikuta Kohei , Ohki Kenichi 
Published: October 2024

ABSTRACTHow neurons integrate thousands of synaptic inputs to compute sharply tuned outputs is a critical question in sensory information processing. To answer this question, it is essential to record the location and activity of synaptic inputsin vivo. However, back-propagating action potential (BAP) calcium signals invade dendrites and spines, making accurate recording of spine responses difficult. In this study, we first developed a new method to record spine calcium responses without BAP signals. Using this method, we performed large-scale imaging of visually evoked spine activity from layer 2/3 pyramidal neurons and revealed three patterns of dendritic functional architectures of synaptic inputs: dendrites with clusters of spines of similar responses, dendrites with spines of diverse responses, and dendrites with spines where the majority of them show no visual response. Our model suggests that only a small fraction of spines on dendrites of clustered architectures are sufficient to generate sharply tuned output.
TFAM as a sensor of UVC-induced mitochondrial DNA damage
Authors: King Dillon E. , Beard Emily E. , Satusky Matthew J. , Ryde Ian , George Alex , Johnson Caitlin , Dolan Emma L. , Zhang Yuning , Zhu Wei , Wilkins Hunter , Corden Evan , Murphy Susan K. , Erie Dorothy , Gordân Raluca , Meyer Joel N. 
Published: October 2024

AbstractMitochondria lack nucleotide excision DNA repair; however, mitochondrial DNA (mtDNA) is resistant to mutation accumulation following DNA damage. These observations suggest additional damage sensing or protection mechanisms. Transcription Factor A, Mitochondrial (TFAM) compacts mtDNA into nucleoids. As such, TFAM has emerged as a candidate for protecting DNA or sensing damage. To examine these possibilities, we used live-cell imaging, cell-based assays, atomic force microscopy, and high-throughput protein-DNA binding assays to characterize the binding properties of TFAM to UVC-irradiated DNA and cellular consequences of UVC irradiation. Our data indicate an increase in mtDNA degradation and turnover, without a loss in mitochondrial membrane potential that might trigger mitophagy. We identified a reduction in sequence specificity of TFAM associated with UVC irradiation and a redistribution of TFAM binding throughout the mitochondrial genome. Our AFM data show increased compaction of DNA by TFAM in the presence of damage. Despite the TFAM-mediated compaction of mtDNA, we do not observe any protective effect on DNA damage accumulation in cells orin vitro. Taken together, these studies indicate that UVC-induced DNA damage promotes compaction by TFAM, suggesting that TFAM may act as a damage sensor, sequestering damaged genomes to prevent mutagenesis by direct removal or suppression of replication.Graphical Abstract
Proteomic associations with cognitive variability as measured by the Wisconsin Card Sorting Test in a healthy Thai population: A machine learning approach
Authors: Chen Chen , Khanthiyong Bupachad , Thaweetee-Sukjai Benjamard , Charoenlappanit Sawanya , Roytrakul Sittiruk , Surit Phrutthinun , Phoungpetchara Ittipon , Thanoi Samur , Reynolds Gavin P , Nudmamud-Thanoi Sutisa 
Published: October 2024

AbstractCognitive function is the term for the higher-order mental processes in the brain that gather and process information, and it mirrors brain activity. Cognitive function in adults exhibits variability as a result of genetic and environmental components such as gender, age[1], and lifestyle factors to name a few. Interindividual variability in cognitive trajectories has been observed in community-dwelling older adults across different cognitive domains. Inter-individual variations in cognitive response to identical physical exercise are also evident. This study aimed to explore the association between serum protein expression profiles and one measure of cognitive variability, as measured by the Wisconsin Card Sorting Test (WCST), in a healthy Thai population using a machine learning approach. This study included 199 healthy Thai subjects, ranging in age from 20 to 70 years. Cognitive performance was measured by the WCST, and the WCST % Errors was used to define the lower and higher cognitive ability groups. Serum protein expression profiles were studied by the label-free proteomics method. The Linear Model for Microarray Data (LIMMA) approach in R was utilized to assess differentially expressed proteins (DEPs) between groups; subsequently bioinformatic analysis was performed for the functional enrichment and interaction network analysis of DEPs. A random forest model was built to classify subjects from the lower and higher cognitive ability groups. Cross-validation was used for model performance evaluation. The results showed that, there were 213 DEPs identified between the poor and higher cognition groups, with 155 DEPs being upregulated in the poor cognition group. Those DEPs were significantly enriched in the IL-17 signaling pathway. Furthermore, the analysis of protein-protein interaction (PPI) network revealed that most of the selected DEPs were linked to neuroinflammation-related cognitive impairment. The random forest model achieved a test classification accuracy of 81.5%. The model’s sensitivity (true positive rate) was estimated to be 65%, and the specificity (true negative rate) was 85.9%. The AUC (0.79) indicates good binary classification performance. The results suggested that a measure of poor WCST performance in healthy Thai subjects might be attributed to higher levels of neuroinflammation.
Loop Feynman integration on a quantum computer
Authors: Martínez de Lejarza Jorge J. , Cieri Leandro , Grossi Michele , Vallecorsa Sofia , Rodrigo Germán 
Published: October 2024

This work investigates in detail the performance and advantages of a new quantum Monte Carlo integrator, dubbed quantum Fourier iterative amplitude estimation (QFIAE), to numerically evaluate for the first time loop Feynman integrals in a near-term quantum computer and a quantum simulator. In order to achieve a quadratic speedup, QFIAE introduces a quantum neural network (QNN) that efficiently decomposes the multidimensional integrand into its Fourier series. For a one-loop tadpole Feynman diagram, we have successfully implemented the quantum algorithm on a real quantum computer and obtained a reasonable agreement with the analytical values. One-loop Feynman diagrams with more external legs have been analyzed in a quantum simulator. These results thoroughly illustrate how our quantum algorithm effectively estimates loop Feynman integrals and the method employed could also find applications in other fields such as finance, artificial intelligence, or other physical sciences.

Published by the American Physical Society
2024
Data-driven computation of adjoint sensitivities without adjoint solvers: An application to thermoacoustics
Authors: Ozan Defne E. , Magri Luca 
Published: October 2024

Adjoint methods have been the pillar of gradient-based optimization for decades. They enable the accurate computation of a gradient (sensitivity) of a quantity of interest with respect to all system parameters in one calculation. When the gradient is embedded in an optimization routine, the quantity of interest can be optimized for the system to have the desired behavior. Adjoint methods, however, require the system's governing equations and their Jacobian. In this paper, we propose a computational strategy to infer the adjoint sensitivities from data when the governing equations might be unknown (or partly unknown), and noise might be present. The key component of this strategy is an echo state network, which learns the dynamics of nonlinear regimes with varying parameters, and it evolves dynamically via a hidden state. Although the framework does not make assumptions on the dynamical system, we focus on thermoacoustics, which are governed by nonlinear and time-delayed systems. First, we show that a parameter-aware echo state network (ESN) infers the parametrized dynamics. Second, we derive the adjoint of the ESN to compute two types of sensitivity: (i) parameter sensitivity, which is the gradient of a time-averaged cost functional with respect to physical or design parameters of the system, and (ii) initial condition sensitivity, which is the gradient of a cost functional of the final state with respect to the initial condition. Third, we propose the thermoacoustic echo state network (T-ESN), which embeds the physical knowledge in the network architecture for improved generalization. Fourth, we apply the framework to a variety of nonlinear thermoacoustic regimes of a prototypical system. We show that the T-ESN accurately infers the correct adjoint sensitivities of the acoustic energy with respect to the flame parameters and initial conditions. The results are robust to noisy data, from periodic, through quasiperiodic, to chaotic regimes. The inferred adjoint sensitivities are employed to suppress an instability via steepest descent. We show that a single network predicts the nonlinear bifurcations on unseen scenarios, which allows it to converge to the minimum of the acoustic energy. This work opens new possibilities for gradient-based data-driven design optimization.

Published by the American Physical Society
2024
P-type Schottky-barrier-free contact to
MoS2
via layer-number-assisted interface engineering
Authors: Zhao Xiao-Lin , Wang Nie-Wei , Zhang Yue-Jiao , Gao Yu-Meng , Gong Peng-Lai , Jin Chen-Dong , Zheng Xiaohong , Wang Jiang-Long , Shi Xing-Qiang 
Published: October 2024

Bilayer and few-layer MoS2 show intrinsically higher electronic quality and substantially improved device performance than monolayer, and high-quality MoS2 wafers with controlled layer number have been grown. In addition, MoS2 has different polymorphs such as the semiconducting H phase and semimetallic distorted T (dT) phase, and vertically stacked dT-/H-MoS2 metal-semiconductor junctions (MSJs) have been synthesized. However, the contact mechanism of dT-/H (few layer)-MoS2 MSJs remains to be elucidated, and p-type ohmic contact to MoS2 is difficult to realize due to the high ionization energy of MoS2. In the current work, we reveal a mechanism of two-dimensional (2D) semiconductors (2DSCs) layer-number-assisted metal-semiconductor (SC) interface engineering for Schottky barrier height (SBH) reduction and p-type ohmic contact is achieved based on this mechanism; 2DSCs here mean H (few layer)-MoS2 and metal-SC interfaces are the dT-/H-MoS2 interfaces with increasing 2DSC layers. Specifically speaking, the mechanism is as follows: (1) two competing effects coexist, namely, the interface dipole (ΔV) at the metal-SC interface and the quasibonding (QB) between all adjacent layers, with ΔV (QB) increasing (decreasing) SBH; (2) the effect of QB beats ΔV and hence the overall effect is decreasing SBH at the metal-SC interface; and (3) the SBH reduction effect increases with increasing 2DSC layers. The mechanism of 2DSC layer-number-assisted metal-SC interface engineering should apply also for other 2DSCs with a suitable metal and hence our current work paves an avenue for ohmic contact to few-layer 2DSCs by the accumulated interlayer QBs that widely present in 2DSCs.

Published by the American Physical Society
2024
How influencers can enhance consumer responses by value co-creation
Authors: Zhang Jin , Cai Lingkui , Zheng Xiaoying 
Published: October 2024

Purpose
This paper aims to explore whether, how and when influencers’ value co-creation behavior in a post – influencers investing operant resources to enhance the value gained from using the product – shapes consumers’ responses toward an influencer’s recommendation. Based on value co-creation theory and consumer inference, this paper proposes that consumers infer influencers have more expertise with and more favorable attitude toward the product from value co-creation. Consequently, such behavior can foster consumer engagement and favorable attitude toward the recommended product.

Design/methodology/approach
The authors collected real-world data and conducted four sets of experimental studies. In the experimental studies, the presence of an influencer’s value co-creation behavior (i.e. co-creation vs. control) was manipulated to test the causal effect and mechanisms of co-creation on engagement and product attitude.

Findings
Results show that influencers’ value co-creation behavior positively affects consumers’ engagement and attitudes toward the product. These effects are driven by perceived influencer’s expertise with and favorability toward the product (Studies 1 and 2). Co-creating utilitarian value is more effective than co-creating hedonic value (Studies 3A and 3B). In addition, influencers with a larger number of followers benefit more from co-creation behavior than those with fewer followers (Study 4).

Research limitations/implications
This research adds to the literature on value co-creation by investigating how, why and when influencers’ value co-creation enhances consumer responses to the post. Our investigation concretizes value co-creation behavior in the context of influencer marketing and demonstrates its signaling effect with nuanced role of value type in shaping the effect. The findings provide a novel cue that influencers can use to enhance consumer responses to their posts.

Practical implications
Brands should encourage influencers to focus on value-in-use co-creation when promoting their products. While emphasizing value co-creation in influencer partnership, brands should also carefully consider the type and size of influencers they collaborate with based on the nature of their products and target audience. The research findings also provide practical implications for influencers, offering guidance on how they can optimize their content creation strategies and enhance their effectiveness in influencer marketing collaborations.

Originality/value
This research enriches understanding of value co-creation in the context of influencer marketing and the role of content specifics in influencers’ posts. The findings provide a novel cue that influencers can use to enhance consumer responses to their posts.
Exploring value relevance of EVA over different stages of business lifecycle
Authors: Tripathi Manju , Ghalke Avinash , Kashiramka Smita 
Published: October 2024

Purpose
This study aims to determine whether the financial ecosystem is reliable for evaluating a company’s financial performance at various lifecycle stages or whether value-based performance metrics like Economic Value Added (EVA) are the most comprehensive indicators regardless of the company’s lifecycle stage. The evaluation will analyse the importance of value-based and accounting performance benchmarks (EVA, Return on Capital Employed, Return on Equity and Earnings per Share) in creating shareholder value, as measured by market value added, throughout the company’s lifecycle.

Design/methodology/approach
This study is based on a robust empirical analysis of 228 Indian firms listed on the National Stock Exchange Nifty 500 Index from 2006 to 2023. By considering firms of different sizes and ages, the authors aim to capture and analyse any distinct impact across various stages of their lifecycles. Using quantile regression for analysis equips the authors to effectively address extreme events such as the 2008 global financial crisis and the COVID-19 pandemic, making the method particularly suitable for conditionally distributed samples based on size and age.

Findings
The research reveals that various performance indicators are crucial at different stages of a company’s lifecycle for generating wealth for shareholders. However, considering the significance of the EVA measure, it is recommended that policymakers standardize the calculation of EVA and mandate its disclosure.

Originality/value
The authors comprehensively analysed the economic value addition relative to a company’s size and age, going beyond previous studies that focused solely on specific size categories. This offers managers valuable insights into aligning business performance measures with the various stages of the business lifecycle.
Fractal momentum investment strategies based on liquidity non-linear fluctuations in Chinese stock market
Authors: Yan Ruzhen , Zhu Xin , Wang Kun , Ma Fanming , Wu Xu 
Published: October 2024

Purpose
This paper aims to the relationship between liquidity fluctuation trends and stocks’ expected returns.

Design/methodology/approach
The authors use the multi-fractal detrended fluctuation analysis to study the liquidity non-linear multi-fractal characteristics of stock market and predict the future volatility trend of market liquidity with the help of potential entropy dimensional model and also consider the non-linear volatility trend of liquidity, construct a fractal momentum strategy under different sorting periods and holding periods, to test the liquidity momentum effects of Chinese stock market and, finally, compare with the traditional price momentum strategy.

Findings
The result suggests that: Chinese stock market liquidity has obvious non-linear multi-fractal characteristics; the trend entropy dimensional model can accurately predict the future volatility trend of market liquidity; significant liquidity trend momentum effects persist in the Chinese stock market, while price momentum effects exist only in the short term; a significant liquidity premium exists in the Chinese equity market; the fractal momentum strategy constructed in this paper achieves higher returns and less risk than the price momentum strategy.

Originality/value
Based on the above analysis, this paper will further construct a momentum strategy incorporating liquidity trends, i.e. fractal momentum strategy (LMP strategy), with the realistic background that Chinese stock market liquidity has non-linear multi-fractal characteristics – the main contribution of this paper is to overcome the shortcomings of existing momentum strategies, which seldom combine the trend of future liquidity fluctuations with momentum strategies, and to incorporate the real characteristics of the market.