bluuebunny/crossref_metadata_2025 huggingface dataset:
S.O.S: Shape, orientation, and size tune solvation in electrocatalysis
Authors: Serva Alessandra , Pezzotti Simone
Published: March 2024

Current models to understand the reactivity of metal/aqueous interfaces in electrochemistry, e.g., volcano plots, are based on the adsorption free energies of reactants and products, which are often small hydrophobic molecules (such as in CO2 and N2 reduction). Calculations played a major role in the quantification and comprehension of these free energies in terms of the interactions that the reactive species form with the surface. However, solvation free energies also come into play in two ways: (i) by modulating the adsorption free energy together with solute–surface interactions, as the solute has to penetrate the water adlayer in contact with the surface and get partially desolvated (which costs free energy); (ii) by regulating transport across the interface, i.e., the free energy profile from the bulk to the interface, which is strongly non-monotonic due to the unique nature of metal/aqueous interfaces. Here, we use constant potential molecular dynamics to study the solvation contributions, and we uncover huge effects of the shape and orientation (on top of the already known size effect) of small hydrophobic and amphiphilic solutes on their adsorption free energy. We propose a minimal theoretical model, the S.O.S. model, that accounts for size, orientation, and shape effects. These novel aspects are rationalized by recasting the concepts at the base of the Lum–Chandler–Weeks theory of hydrophobic solvation (for small solutes in the so-called volume-dominated regime) into a layer-by-layer form, where the properties of each interfacial region close to the metal are explicitly taken into account.
A new random walk method for simulating heat flow and temperature distribution in three-dimensional discontinuous systems
Authors: Maruyama Yutaka
Published: March 2024

Numerical methods for analyzing diffusion phenomena involving strong discontinuities and complicated interfaces are of great scientific and technical importance. In this paper, we extend the existing step-balanced random walk, which overcomes the problem of detailed balance of a random walker in three-dimensional (3D), diffusion-tensor discontinuous systems, to particle density (ρ) discontinuous systems, and introduce volumetric heat capacity C and temperature T by considering ρ as heat density, i.e., ρ=CT, to apply it to thermal problems. Two types of thermophysical simulations are demonstrated: one is steady-state heat flow due to a temperature difference at the end surfaces on a two-phase slab model unit cell with periodic boundary conditions; the other is the time variation of temperature distribution due to heat diffusion from a point heat source in a repeated two-phase slab model with no periodic boundary conditions. We see the correct behavior of heat and temperature expected in 3D discontinuous systems composed of two phases with anisotropic thermal conductivity. The applicability to problems other than pure diffusion and the limitations of the method are also discussed.
Early detection of thermoacoustic instability in an O2/CH4 single-injector rocket combustor using analysis of chaos and deep learning models
Authors: Wang Zhiyu , Lin Wei , Tong Yiheng , Guo Kangkang , Chen Peng , Nie Wansheng , Huang Weidong
Published: March 2024

Thermoacoustic instability (TAI) presents a critical challenge for lean-burning combustors and rocket engines. The early detection of instability is crucial, and to address this, a data-driven prediction framework has been established for TAI in a sub-scale rocket combustor with variable chamber length. Nonlinear combustion features are generated from time series of dynamic pressure using recurrence matrices. Deep learning models are then utilized to train these features and predict the proximity of impending TAI. The performance of the proposed method is investigated through cross-validations of 12 groups of hot-fire test datasets. Remarkably, the prediction performances are in good agreement with measured experimental data, with most instabilities being predicted dozens of milliseconds in advance. This capability paves the way for the early implementation of active control systems in full-scale combustors in the future. The prediction performances are also compared with state-of-the-art TAI prediction methods.
Upscaling mass adsorption and momentum transport in the crown of trees
Authors: Valdés-Parada F. J. , Sánchez-Vargas J.
Published: March 2024

Airborne chemical species transport and adsorption in the crown of trees are relevant processes with many crucial environmental consequences. This multiphase and multiscale process requires incorporation of momentum transport both in the air and in the solid phases composing the biomass (leaves and branches) and coupling with species mass transport. In this work, an upscaled model for momentum transport and adsorption of chemical species in tree crowns is derived using the method of volume averaging. The model comprises four effective-medium equations, namely: the macroscopic balance equation for momentum transport in the air, which has a Darcy-like structure; the macroscopic equations for total mass and momentum transport, considering the air and deformable leaves and branches; and an unsteady upscaled equation for species mass (diffusive and convective) transport and adsorption at the surface of leaves and branches. These equations are written in terms of effective-medium coefficients that capture the essential microscale information by solving ancillary closure problems in periodic unit cells in the Laplace domain. This allowed evaluating the dynamic functionality of the unsteady adsorption and dispersion coefficients in terms of the Reynolds number, the solid velocity and the adsorption rate. The macroscopic model predictions of the average chemical species concentration were found to be in excellent agreement with direct numerical simulations (i.e., with a relative percent difference smaller than 1%), thus providing a first validation of the upscaled model. Extensions to other systems are briefly discussed.
Research on mining high performance path rules for new energy enterprises from the perspective of social responsibility—Empirical data from China
Authors: Zhang Chao , Wang Jun , Hu Shu , Wu Yong , Zhu Weidong
Published: March 2024

The high-quality development of new energy enterprises is of great significance to promote carbon peak and carbon neutrality and cope with the global warming crisis. However, with the increasing intensity of market competition and the appropriate weakening of the expected future subsidies, how to improve their performance through the fulfillment of the social responsibility of stakeholders has become a key scientific problem to be solved. Given the features of the new energy industry, including substantial initial investment, formidable technical barriers, and a pronounced reliance on policy support, this paper takes 182 new energy concept enterprises listed in China's A-shares in 2011–2020 as the research object. Employing qualitative comparative analysis, we extract four key rules for achieving high performance in new energy enterprises from the perspective of value co-creation of core stakeholders, including capital stakeholders (shareholders and creditors), technical stakeholders (employees), policy stakeholders (government and society), and upstream and downstream stakeholders (suppliers and customers). Then, we explore the performance improvement rules of typical cases. Our findings reveal that within the realm of new energy enterprises, capital-intensive enterprises with cost leadership and tax incentives, energy-manufacturing enterprises with suppliers dependence and saving environmental input, technology-innovation enterprises with cost leadership and talents dependence, and comprehensive-mature enterprises with suppliers dependence and tax incentives are more likely to achieve high performance. The findings can better guide management practice and promote the high-quality development of new energy enterprises.
Liquid sheet formation and spray characterization of N-heptane spray jet from a swirl atomizer: Numerical analysis and validation
Authors: Sun Yaquan , Vegad Chetankumar S. , Li Yongxiang , Dreßler Louis , Renou Bruno , Nishad Kaushal , Demoulin François-Xavier , Hasse Christian , Sadiki Amsini
Published: March 2024

This paper analyzes the liquid atomization mechanisms of an N-heptane spray jet emerging from a swirl simplex atomizer using numerical and experimental techniques. In particular, a direct seamless coupled Volume of Fluid and Lagrangian Particle Tracking approach together with adaptive mesh refinement within the Large Eddy Simulation framework offers a suitable way to accurately simulate the complex behavior of spray atomization, spray evolution, and droplet dispersion as a whole while using manageable computational cost. The achieved simulation results are first presented in terms of qualitative properties, characteristics of liquid sheet, air core generation, flow recirculation zones, and vortex patterns. For validation purposes, the numerical results are then compared with detailed experimental data obtained by a two-component Phase Doppler Anemometry technique. The assessment includes especially droplet statistics which strongly determine subsequent possible spray combustion process and related product and species emissions. The overall reported agreement demonstrates the capability of the adopted methodology in predicting and comprehensively investigating the complex phenomena associated with a pressure swirl fuel atomizer. In particular, it is found out that the normalized number-based probability density function of droplet size fits well with a lognormal distribution.
Observation of novel in-gap states on alkali metal dosed Ti2O3 film
Authors: Ran Pengxu , Lin Bing , Hong Caiyun , Wang Baokai , Xie Xiaopeng , Jiang Congying , Tanaka K. , He Rui-Hua
Published: March 2024

Alkali metal dosing has nowadays been extensively used in angle-resolved photoemission spectroscopy (ARPES) for the in situ surface electron doping of materials to provide access to the unoccupied states. This technique also gives rise to nontrivial physical phenomena, such as the appearance of quantum well states and effects due to alkali metal intercalation. Here, we uncovered a previously unobserved type of electronic behavior induced by alkali metal dosing. By employing ARPES to study the evolution of the electronic structure of the Ti2O3 thin film upon rubidium (Rb) dosing, we found that the electron chemical potential of the system remains unchanged throughout the process. Interestingly, a series of electron-like band dispersions first appear with Rb dosing. A further increase in the Rb dosage leads to the eventual disappearance of the electron-like bands and the emergence of a set of hole-like bands. Our finding enriches the phenomenology brought about by alkali metal surface dosing, suggesting a novel functionality of this popular surface doping technique.
Engineering crystal structure transformation from layered perovskite-like to pyrochlore for electrostatic energy storage
Authors: An W. , Song D. P. , Zhang Y. , Zhou A. X. , Yang J.
Published: March 2024

The pyrochlore phase in ferroelectric materials has long been unaccepted as a negative factor. Therefore, every effort was made to eliminate it. Here, based on electrostatic energy storage capacitors, we provide a counter view to evaluate its effects on ferroelectric properties, i.e., the electrostatic energy storage properties of ferroelectric thin films can be significantly improved by a deliberately designed pyrochlore phase. By adjusting the components and annealing temperature to control crystal structure transformation, an energy storage density of 69 J/cm3 and an efficiency of 70.1% were achieved as a pyrochlore-dominated film, along with good temperature and fatigue stability. It is attribute to its relatively low loss and linear ferroelectric polarization behavior, which enhances the breakdown field while reducing the remnant polarization. These results will provide a versatile strategy for the development of ferroelectric thin film energy storage capacitors with high energy storage density, high efficiency, and good fatigue resistance based on crystal structure transformation.
Dynamic large-array terahertz imaging display based on high-performance 1D/2D tellurium homojunction modulators
Authors: Zhang Pujing , Hao Xue , Zhou Qingli , She Guangwei , Chen Jinyu , Zhang Xuteng , Liang Wanlin , Deng Yuwang , Ning Tingyin , Shi WenSheng , Zhang Liangliang , Zhang Cunlin
Published: March 2024

Mixed-dimensional van der Waals systems could improve terahertz modulators’ performance by utilizing the advantages of different dimensional materials. However, the reported available mixed-dimensional heterojunctions using two-dimensional (2D) and three-dimensional materials usually sacrifice the modulation speed to realize a higher modulation depth. Here, we creatively integrate one-dimensional (1D) nanowires with 2D nanofilms to construct the novel mixed-dimensional tellurium (Te) homojunction and achieve optimal indices with an ultrahigh modulation depth and a shorter carrier lifetime. In addition, a Te-based large-array imaging element was fabricated to successfully reproduce the painting colors under specific pump conditions as well as the dynamic multicolor display. Further measurements with the introduction of metamaterials prove that the required energy consumption can be significantly reduced by one order of magnitude. Our proposed 1D/2D integration strategy opens a new way to build high-performance terahertz functional devices and greatly expands the application fields of Te nanomaterials.
Fluorinated organic ammonium salt passivation for high-efficiency and stable inverted CsPbI2Br perovskite solar cells
Authors: Liu Xin , She Xingchen , Wang Lang , Li Wei , Zhang Wen , Wang Shu , Wangyang Peihua , Wang Zhijun , Li Jie , Cui Xumei , Lan Mu , Liu Liqin , Sun Hui , Zhang Jun , Yang Dingyu
Published: March 2024

All-inorganic CsPbI2Br inverted perovskite solar cells (PSCs) have drawn increasing attention because of their outstanding thermal stability and compatible process with tandem cells. However, relatively low open circuit voltage (Voc) has lagged their progress far behind theoretical limits. Herein, we introduce phenylmethylammonium iodide and 4-trifluoromethyl phenylmethylammonium iodide (CFPMAI) on the surface of a CsPbI2Br perovskite film and investigate their passivation effects. It is found that CFPMAI with a –CF3 substituent significantly decreases the trap density of the perovskite film by forming interactions with the under-coordinated Pb2+ ions and effectively suppresses the non-radiative recombination in the resulting PSC. In addition, CFPMAI surface passivation facilitates the optimization of energy-level alignment at the CsPbI2Br perovskite/[6,6]-phenyl C61 butyric acid methyl ester interface, resulting in improved charge extraction from the perovskite to the charge transport layer. Consequently, the optimized inverted CsPbI2Br device exhibits a markedly improved champion efficiency of 14.43% with a Voc of 1.12 V, a Jsc of 16.31 mA/cm2, and a fill factor of 79.02%, compared to the 10.92% (Voc of 0.95 V) efficiency of the control device. This study confirms the importance of substituent groups on surface passivation molecules for effective passivation of defects and optimization of energy levels, particularly for Voc improvement.
Air stability and composition evolution in van der Waals Fe3GeTe2
Authors: Xie Weiran , Zhang Jie , Bai Yue , Liu Yingjie , Wang Hangtian , Yu Peiyuan , Li Jing , Chang Hao , Wang Zili , Gao Fan , Wei Guodong , Zhao Weisheng , Nie Tianxiao
Published: March 2024

Layered two-dimensional ferromagnetic materials have emerged as a promising platform for spintronic applications, owing to their extraordinary physical properties. Remarkably, the representative two-dimensional ferromagnet Fe3GeTe2 has been extensively investigated due to its high Curie temperature and strong perpendicular magnetic anisotropy, which are beneficial for high-density storage at room temperature. However, there are few reports on its stability in the air and the surface oxidation products, which may prohibit its future application. Here, we report the natural oxidation process of Fe3GeTe2 films grown by molecular beam epitaxy evolved in the atmosphere, which was studied by x-ray photoelectron spectroscopy measurements and transmission electron microscopy. Our research shows that the surface of the Fe3GeTe2 film is oxidized quickly when exposed to air and shows two obviously evolving stages in the whole oxidation process. In the first stage, metallic Ge atoms are almost completely oxidized to form Ge–O bonds in GeO2, while partial metallic Fe and Te atoms are oxidized into Fe2O3 and TeO2, respectively. The second stage of oxidation is dominated by changes in the valence state of the Fe element, where Fe2O3 is reduced to FeCO3 through the participation of carbon adsorbed on the surface with the final oxidation product of FeCO3 · GeO2 · TeO2. Our findings provide insight into the subsequent growth and protection of Fe3GeTe2 thin films, which is of great significance for in-depth study and further application of spintronic devices in two-dimensional limits.
Antiferromagnetic and nutation resonance frequencies of antiferromagnets at an arbitrary strength of the applied dc field
Authors: Titov Sergei V. , Dowling William J. , Titov Anton S. , Fedorov Andrey S.
Published: March 2024

Nutation and precession resonances in an antiferromagnet subjected to a dc magnetic field are investigated by employing coupled linearized inertial Landau–Lifshitz–Gilbert equations describing the dynamics of magnetizations of antiferromagnet sublattices with uniaxial magnetocrystalline anisotropy. Analytical expressions for the eigenfrequencies of such an antiferromagnet are obtained for the longitudinal and transverse directions of the external dc field and for different ranges of its strength. The effect of inertia on the values of the resonant frequencies is shown for all possible states of the antiferromagnet in both the longitudinal and transverse directions of the external field. The estimated resonant frequencies are compared with those obtained from the numerical solution of the system of undamped inertial Landau–Lifshitz–Gilbert equations for closed trajectories of sublattice magnetizations. The good agreement of both independent estimations is demonstrated.
The roar of a rocket
Authors: Gee Kent L. , Lubert Caroline P. , James Michael M.
Published: March 2024

During a rocket’s liftoff, its extreme sound levels can damage launch structures, payload electronics, and even the rocket itself.
Manhattan Project astrophysics
Authors: Wiescher Michael , Langanke Karlheinz
Published: March 2024

After World War II, scientists applied the knowledge and experience they gained from nuclear weapons to nuclear astrophysics.
How a mineral that’s always wet gets wetter
Authors: Sieben Jennifer
Published: March 2024

Potassium-rich feldspar is a hydrophilic mineral that accelerates ice nucleation in the atmosphere. For the first time, the atomic surface structure has been observed.
What makes blueberries blue?
Authors: Sieben Jennifer
Published: March 2024

A new study reveals how the berries and some other waxy fruits look blue despite a lack of blue pigment.
Algorithmic power and scientific knowledge
Authors: Signorini Inês
Published: March 2024

This paper critically revisits traditional perspectives on technology within academic and scientific writing
studies. It aims to comprehend the intricate, emerging, and dynamic sociotechnical configurations that underlie contemporary
scientific practices. These practices increasingly involve language, text, and literacy practices, seen as products of the
collaboration between humans and machines. The paper draws on empirical research on influential institutional metadiscourses in
high-impact scientific writing produced and/or disseminated by public universities and a research institute in the State of São
Paulo (Brazil), whose local policies of globalization are driven by international university rankings. I use a qualitative content
analysis approach grounded in socio-anthropological, socio-semiotic, and pragmatic studies of linguistic ideologies to shed light
on how ideological and socio-semiotic processes support the metapragmatics of scientific writing in university policy documents.
This metapragmatics is utterly alien to the role of performative sociotechnical infrastructures in the production, distribution,
and hierarchization of scientific texts. Additionally, these documents do not account for the diverse conditions and restrictions
that shape the production and circulation of academic knowledge in geopolitically marginal and equally diverse regions within the
country, including those within São Paulo.
Gromov–Hausdorff variational principles and measure stability
*
Authors: Lee Keonhee , Morales C A , Nguyen Ngocthach
Published: March 2024

Variational formulae for the Gromov–Hausdorff distances of compact metric spaces and their continuous maps are obtained. Also, a notion of µ-topological GH-stability on metric-measure spaces with probability µ is given. We prove that every expansive map with the weak µ-shadowing property (Lee and Rojas 2022 Russ. J. Nonlinear Dyn.
18 297–307) is µ-topologically GH-stable.
Spin-fluctuation-induced sign reversal of the spin Hall angle in Pt100−x
Co
x
alloys near the Curie temperature
Authors: Chang Yuhan , Wang Ruoshui , Ga Yonglong , Cui Baoshan , Xie Hongfei , Zhang Xu , Zhang Jianrong , Yan Ze , Cao Yang , Guo Xi , Xu Hengyi , Zuo Yalu , Jia Chenglong , Yang Hongxin , Xue Desheng , Xi Li
Published: March 2024

The spin Hall effect (SHE), typically emerging in non-magnetic metals with strong spin-orbit couplings, has attracted significant attention for its ability to convert a charge current into a spin current, a key feature in power-efficient spintronic devices. Recently, an enhanced SHE has been detected in the magnetic alloys, where the spin Hall conductivity is strongly modified by the dynamical and thermal spin fluctuations. We find that the spin Hall angle (

θ

SH

) in Pt100−x
Co
x
alloys dramatically changes at the Curie temperature, which is positive in the paramagnetic phase akin to Pt, while negative in the ferromagnetic phase. Such intriguing behavior of

θ

SH

stemming from individual and collective fluctuations in the magnetic moments is further substantiated with the full-fledged Monte Carlo simulations. Our work broadens insights into the SHE and highlights the importance of spin fluctuations for the spin-current generation near the ferromagnetic instability point of magnetic alloys.
Detecting the quantum phase transition from the perspective of quantum information in the Aubry–André model
Authors: Wei 韦 Geng-Biao 庚彪 , Ye 叶 Liu 柳 , Wang 王 Dong 栋
Published: March 2024

We investigate the effectiveness of entropic uncertainty, entanglement and steering in discerning quantum phase transitions (QPTs). Specifically, we observe significant fluctuations in entropic uncertainty as the driving parameter traverses the phase transition point. It is observed that the entropic uncertainty, entanglement and quantum steering, based on the electron distribution probability, can serve as indicators for detecting QPTs. Notably, we reveal an intriguing anticorrelation relationship between entropic uncertainty and entanglement in the Aubry–André model. Moreover, we explore the feasibility of detecting a QPT when the period parameter is a rational number. These observations open up new and efficient avenues for probing QPTs.
Tunable superconducting resonators via on-chip control of local magnetic field
Authors: Wang 王 Chen-Guang 晨光 , Yue 岳 Wen-Cheng 文诚 , Tu 涂 Xuecou 学凑 , Chi 迟 Tianyuan 天圆 , Guo 郭 Tingting 婷婷 , Lyu 吕 Yang-Yang 阳阳 , Dong 董 Sining 思宁 , Cao 曹 Chunhai 春海 , Zhang 张 Labao 蜡宝 , Jia 贾 Xiaoqing 小氢 , Sun 孙 Guozhu 国柱 , Kang 康 Lin 琳 , Chen 陈 Jian 健 , Wang 王 Yong-Lei 永磊 , Wang 王 Huabing 华兵 , Wu 吴 Peiheng 培亨
Published: March 2024

Superconducting microwave resonators play a pivotal role in superconducting quantum circuits. The ability to fine-tune their resonant frequencies provides enhanced control and flexibility. Here, we introduce a frequency-tunable superconducting coplanar waveguide resonator. By applying electrical currents through specifically designed ground wires, we achieve the generation and control of a localized magnetic field on the central line of the resonator, enabling continuous tuning of its resonant frequency. We demonstrate a frequency tuning range of 54.85 MHz in a 6.21-GHz resonator. This integrated and tunable resonator holds great potential as a dynamically tunable filter and as a key component of communication buses and memory elements in superconducting quantum computing.
Mass suppression effect in QCD radiation and hadron angular distribution in jet*
Authors: Jiang 蒋 Chuan-Hui 传辉 , Li 李 Hai Tao 海涛 , Li 李 Shi-Yuan 世渊 , Si 司 Zong-Guo 宗国
Published: March 2024

The finite mass of the heavy quark suppresses the collimated radiations; this is generally referred to as the dead cone effect. In this paper, we study the distribution of hadron multiplicity over the hadron opening angle with respect to the jet axis for various jet flavors. The corresponding measurement can be the most straightforward and simplest approach to explore the dynamical evolution of the radiations in the corresponding jet, which can expose the mass effect. We also propose a transverse energy-weighted angular distribution, which sheds light on the interplay between perturbative and non-perturbative effects in the radiation. Through Monte-Carlo simulations, our calculations show that the dead cone effect can be clearly observed by finding the ratio between the b and light-quark (inclusive) jets; this is expected to be measured at the LHC in the future.
B − L model with D
4 × Z
4 × Z
2 symmetry for fermion mass hierarchies and mixings*
Authors: Vien V. V.
Published: March 2024

We constructed a gauge

model with

symmetry to explain the quark and lepton mass hierarchies and their mixings with realistic CP phases via the type-I seesaw mechanism. Six quark mases, three quark mixing angles, and the CP phase in the quark sector take the central values whereas Yukawa couplings in the quark sector are diluted in a range of difference of three orders of magnitude by the perturbation theory at the first order. Concerning the neutrino sector, a small neutrino mass is achieved by the type-I seesaw mechanism. Both inverted and normal neutrino mass hierarchies are consistent with the experimental data. The predicted sum of neutrino masses for normal and inverted hierarchies, the effective neutrino masses, and the Dirac CP phase are also consistent with recently reported limits.
Gas gains over 104 and optimisation using 55Fe X-rays in low pressure SF6 with a novel Multi-Mesh ThGEM for directional dark matter searches
Authors: McLean A.G. , Spooner N.J.C. , Crane T. , Eldridge C. , Ezeribe A.C. , Marcelo Gregorio R.R. , Scarff A.
Published: March 2024

The Negative Ion Drift (NID) gas SF6 has favourable properties for track reconstruction in directional Dark Matter (DM) searches utilising low pressure gaseous Time Projection Chambers (TPCs). However, the electronegative nature of the gas means that it is more difficult to achieve significant gas gains with regular Thick Gaseous Electron Multipliers (ThGEMs). Typically, the maximum attainable gas gain in SF6 and other Negative Ion (NI) gas mixtures, previously achieved with an 55Fe X-ray source or electron beam, is on the order of 103 [1,2,3,4]; whereas electron drift gases like CF4 and similar mixtures are readily capable of reaching gas gains on the order of 104 or greater [5,9,7,8,6]. In this paper, a novel two stage Multi-Mesh ThGEM (MMThGEM) structure is presented. The MMThGEM was used to amplify charge liberated by an 55Fe X-ray source in 40 Torr of SF6. By expanding on previously demonstrated results [10], the device was pushed to its sparking limit and stable gas gains up to ˜50000 were observed. The device was further optimised by varying the field strengths of both the collection and transfer regions in isolation. Following this optimisation procedure, the device was able to produce a maximum stable gas gain of ˜90000. These results demonstrate an order of magnitude improvement in gain with the NID gas over previously reported values and ultimately benefits the sensitivity of a NITPC to low energy recoils in the context of a directional DM search.
Ion entropy and accurate entropy-based FDR estimation in metabolomics
Authors: An Shaowei , Lu Miaoshan , Wang Ruimin , Wang Jinyin , Jiang Hengxuan , Xie Cong , Tong Junjie , Yu Changbin
Published: March 2024

Accurate metabolite annotation and false discovery rate (FDR) control remain challenging in large-scale metabolomics. Recent progress leveraging proteomics experiences and interdisciplinary inspirations has provided valuable insights. While target–decoy strategies have been introduced, generating reliable decoy libraries is difficult due to metabolite complexity. Moreover, continuous bioinformatics innovation is imperative to improve the utilization of expanding spectral resources while reducing false annotations. Here, we introduce the concept of ion entropy for metabolomics and propose two entropy-based decoy generation approaches. Assessment of public databases validates ion entropy as an effective metric to quantify ion information in massive metabolomics datasets. Our entropy-based decoy strategies outperform current representative methods in metabolomics and achieve superior FDR estimation accuracy. Analysis of 46 public datasets provides instructive recommendations for practical application.
Biolinguistic graph fusion model for circRNA–miRNA association prediction
Authors: Guo Lu-Xiang , Wang Lei , You Zhu-Hong , Yu Chang-Qing , Hu Meng-Lei , Zhao Bo-Wei , Li Yang
Published: March 2024

Emerging clinical evidence suggests that sophisticated associations with circular ribonucleic acids (RNAs) (circRNAs) and microRNAs (miRNAs) are a critical regulatory factor of various pathological processes and play a critical role in most intricate human diseases. Nonetheless, the above correlations via wet experiments are error-prone and labor-intensive, and the underlying novel circRNA–miRNA association (CMA) has been validated by numerous existing computational methods that rely only on single correlation data. Considering the inadequacy of existing machine learning models, we propose a new model named BGF-CMAP, which combines the gradient boosting decision tree with natural language processing and graph embedding methods to infer associations between circRNAs and miRNAs. Specifically, BGF-CMAP extracts sequence attribute features and interaction behavior features by Word2vec and two homogeneous graph embedding algorithms, large-scale information network embedding and graph factorization, respectively. Multitudinous comprehensive experimental analysis revealed that BGF-CMAP successfully predicted the complex relationship between circRNAs and miRNAs with an accuracy of 82.90% and an area under receiver operating characteristic of 0.9075. Furthermore, 23 of the top 30 miRNA-associated circRNAs of the studies on data were confirmed in relevant experiences, showing that the BGF-CMAP model is superior to others. BGF-CMAP can serve as a helpful model to provide a scientific theoretical basis for the study of CMA prediction.
Inference of differential gene regulatory networks using boosted differential trees
Authors: Galindez Gihanna , List Markus , Baumbach Jan , Völker Uwe , Mäder Ulrike , Blumenthal David B , Kacprowski Tim
Published: March 2024

Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel nonparametric approaches. We develop a new ensemble method called BoostDiff (boosted differential regression trees) to infer a differential network discriminating between two conditions. BoostDiff builds an adaptively boosted (AdaBoost) ensemble of differential trees with respect to a target condition. To build the differential trees, we propose differential variance improvement as a novel splitting criterion. Variable importance measures derived from the resulting models are used to reflect changes in gene expression predictability and to build the output differential networks. BoostDiff outperforms existing differential network methods on simulated data evaluated in four different complexity settings. We then demonstrate the power of our approach when applied to real transcriptomics data in COVID-19, Crohn’s disease, breast cancer, prostate adenocarcinoma, and stress response in Bacillus subtilis. BoostDiff identifies context-specific networks that are enriched with genes of known disease-relevant pathways and complements standard differential expression analyses.

Availability and implementation

BoostDiff is available at https://github.com/scibiome/boostdiff_inference.
AutoGVP: a dockerized workflow integrating ClinVar and InterVar germline sequence variant classification
Authors: Kim Jung , Naqvi Ammar S , Corbett Ryan J , Kaufman Rebecca S , Vaksman Zalman , Brown Miguel A , Miller Daniel P , Phul Saksham , Geng Zhuangzhuang , Storm Phillip B , Resnick Adam C , Stewart Douglas R , Rokita Jo Lynne , Diskin Sharon J
Published: March 2024

With the increasing rates of exome and whole genome sequencing, the ability to classify large sets of germline sequencing variants using up-to-date American College of Medical Genetics—Association for Molecular Pathology (ACMG-AMP) criteria is crucial. Here, we present Automated Germline Variant Pathogenicity (AutoGVP), a tool that integrates germline variant pathogenicity annotations from ClinVar and sequence variant classifications from a modified version of InterVar (PVS1 strength adjustments, removal of PP5/BP6). This tool facilitates large-scale, clinically focused classification of germline sequence variants in a research setting.

Availability and implementation

AutoGVP is an open source dockerized workflow implemented in R and freely available on GitHub at https://github.com/diskin-lab-chop/AutoGVP.
MolFeSCue: enhancing molecular property prediction in data-limited and imbalanced contexts using few-shot and contrastive learning
Authors: Zhang Ruochi , Wu Chao , Yang Qian , Liu Chang , Wang Yan , Li Kewei , Huang Lan , Zhou Fengfeng
Published: March 2024

Motivation

Predicting molecular properties is a pivotal task in various scientific domains, including drug discovery, material science, and computational chemistry. This problem is often hindered by the lack of annotated data and imbalanced class distributions, which pose significant challenges in developing accurate and robust predictive models.

Results

This study tackles these issues by employing pretrained molecular models within a few-shot learning framework. A novel dynamic contrastive loss function is utilized to further improve model performance in the situation of class imbalance. The proposed MolFeSCue framework not only facilitates rapid generalization from minimal samples, but also employs a contrastive loss function to extract meaningful molecular representations from imbalanced datasets. Extensive evaluations and comparisons of MolFeSCue and state-of-the-art algorithms have been conducted on multiple benchmark datasets, and the experimental data demonstrate our algorithm’s effectiveness in molecular representations and its broad applicability across various pretrained models. Our findings underscore MolFeSCues potential to accelerate advancements in drug discovery.

Availability and implementation

We have made all the source code utilized in this study publicly accessible via GitHub at http://www.healthinformaticslab.org/supp/ or https://github.com/zhangruochi/MolFeSCue. The code (MolFeSCue-v1-00) is also available as the supplementary file of this paper.
Uncertainty-aware single-cell annotation with a hierarchical reject option
Authors: Theunissen Lauren , Mortier Thomas , Saeys Yvan , Waegeman Willem
Published: March 2024

Motivation

Automatic cell type annotation methods assign cell type labels to new datasets by extracting relationships from a reference RNA-seq dataset. However, due to the limited resolution of gene expression features, there is always uncertainty present in the label assignment. To enhance the reliability and robustness of annotation, most machine learning methods address this uncertainty by providing a full reject option, i.e. when the predicted confidence score of a cell type label falls below a user-defined threshold, no label is assigned and no prediction is made. As a better alternative, some methods deploy hierarchical models and consider a so-called partial rejection by returning internal nodes of the hierarchy as label assignment. However, because a detailed experimental analysis of various rejection approaches is missing in the literature, there is currently no consensus on best practices.

Results

We evaluate three annotation approaches (i) full rejection, (ii) partial rejection, and (iii) no rejection for both flat and hierarchical probabilistic classifiers. Our findings indicate that hierarchical classifiers are superior when rejection is applied, with partial rejection being the preferred rejection approach, as it preserves a significant amount of label information. For optimal rejection implementation, the rejection threshold should be determined through careful examination of a method’s rejection behavior. Without rejection, flat and hierarchical annotation perform equally well, as long as the cell type hierarchy accurately captures transcriptomic relationships.

Availability and implementation

Code is freely available at https://github.com/Latheuni/Hierarchical_reject and https://doi.org/10.5281/zenodo.10697468.
A rapid and accurate method for evaluating the degradation of pan-Akt in cells by PROTACs using NanoLuc luciferase
Authors: Ji Xiaojun , Miao Lei , Wu Yebin , Zhao Tingli , Si Yaxuan , Tan Xiaoyun , Zhou Qiuhua , Zuo Rui , Pei Junjie , Wu Jian , Ma Changyou , Ma Zhongjun , Xu Dan
Published: March 2024

Proteolysis targeting chimera (PROTAC) is a protein degradation technique that has been increasingly used in the development of new drugs in recent years. Akt is a classical serine/threonine kinase, and its role outside of the kinase has gradually gained attention in recent years, making it one of the proteins targeted by PROTACs. Currently, there are many methods used for the evaluation of intracellular protein degradation, but each has its own advantages or disadvantages. This study aimed to investigate the feasibility of evaluating the degradation of pan-Akt proteins in cells by PROTACs (MS21 and MS170) using the NanoLuc luciferase method. After conducting a thorough comparison between this method and the classical western blot assay in various cells, as well as testing the stability of the experiments between multiple batches, we found that NanoLuc luciferase is a highly accurate, stable, low-cost and easy-to-operate method for the evaluation of intracellular pan-Akt degradation by PROTACs with a short cycle time and high cellular expandability. Given the numerous advantages of this method, it is hypothesized that it could be extended to evaluate the degradation of more target proteins of PROTACs. In summary, the NanoLuc luciferase is a suitable method for early protein degradation screening of PROTAC compounds.
Cementoplasty to cryoablation: review and current status
Authors: Tan Jin Rong , Yan Yet Yen , Sheikh Adnan , Ouellette Hugue , Mallinson Paul , Munk Peter L
Published: March 2024

Recent advances in percutaneous image-guided techniques have empowered interventional radiologists with diverse treatment options for the management of musculoskeletal lesions. Of note, there is growing utility for cementoplasty procedures, with indications ranging from stabilization of bone metastases to treatment of painful vertebral compression fractures. Likewise, cryoablation has emerged as a viable adjunct in the treatment of both primary and secondary bone and soft tissue neoplasms. These treatment options have been progressively incorporated into the multidisciplinary approach to holistic care of patients, alongside conventional radiotherapy, systemic therapy, surgery, and analgesia. This review article serves to outline the indications, technical considerations, latest developments, and evidence for the burgeoning role of cementoplasty and cryoablation in the musculoskeletal system, with an emphasis on pain palliation and tumour control.
The lysosomal β-glucocerebrosidase strikes mitochondria: implications for Parkinson’s therapeutics
Authors: Rubilar Juan Carlos , Outeiro Tiago Fleming , Klein Andrés D
Published: March 2024

Parkinson’s disease is a neurodegenerative disorder primarily known for typical motor features that arise due to the loss of dopaminergic neurons in the substantia nigra. However, the precise molecular aetiology of the disease is still unclear. Several cellular pathways have been linked to Parkinson’s disease, including the autophagy-lysosome pathway, α-synuclein aggregation and mitochondrial function. Interestingly, the mechanistic link between GBA1, the gene that encodes for lysosomal β-glucocerebrosidase (GCase), and Parkinson’s disease lies in the interplay between GCase functions in the lysosome and mitochondria. GCase mutations alter mitochondria-lysosome contact sites. In the lysosome, reduced GCase activity leads to glycosphingolipid build-up, disrupting lysosomal function and autophagy, thereby triggering α-synuclein accumulation. Additionally, α-synuclein aggregates reduce GCase activity, creating a self-perpetuating cycle of lysosomal dysfunction and α-synuclein accumulation. GCase can also be imported into the mitochondria, where it promotes the integrity and function of mitochondrial complex I. Thus, GCase mutations that impair its normal function increase oxidative stress in mitochondria, the compartment where dopamine is oxidized. In turn, the accumulation of oxidized dopamine adducts further impairs GCase activity, creating a second cycle of GCase dysfunction. The oxidative state triggered by GCase dysfunction can also induce mitochondrial DNA damage which, in turn, can cause dopaminergic cell death. In this review, we highlight the pivotal role of GCase in Parkinson’s disease pathogenesis and discuss promising examples of GCase-based therapeutics, such as gene and enzyme replacement therapies, small molecule chaperones and substrate reduction therapies, among others, as potential therapeutic interventions.
Small fibre integrity and axonal pathology in the rat model of experimental autoimmune neuritis
Authors: Renk Pia , Sgodzai Melissa , Klimas Rafael , Blusch Alina , Grüter Thomas , Motte Jeremias , Pedreiturria Xiomara , Gebel Jeannette , Gobrecht Philipp , Fischer Dietmar , Gold Ralf , Pitarokoili Kalliopi
Published: March 2024

Experimental autoimmune neuritis is a common animal model for acute human immune–mediated polyneuropathies. Although already established in 1955, a number of pathophysiological mechanisms remain unknown. In this study, we extensively characterize experimental autoimmune neuritis progression in Lewis rats, including new insights into the integrity of small nerve fibres, neuropathic pain and macrophage activation. Acute experimental autoimmune neuritis was induced with P253–78 peptide and consequently investigated using the gait analysis system CatWalk XT, electrophysiological and histopathological analyses, quantitative polymerase chain reaction (PCR), dorsal root ganglia outgrowth studies, as well as the von Frey hair and Hargreaves tests. For the longitudinal setup, rats were sacrificed at Day (d) 10 (onset), d15 (peak), d26 (recovery) and d29 (late recovery). We confirmed the classical T-cell and macrophage-driven inflammation and the primarily demyelinating nature of the experimental autoimmune neuritis. The dual role of macrophages in experimental autoimmune neuritis is implicated by the high number of remaining macrophages throughout disease progression. Furthermore, different subpopulations of macrophages based on Cx3-motif chemokine receptor 1 (Cx3cr1), platelet factor 4 (Pf4) and macrophage galactose-type lectin-1 (Mgl1) expressions were identified. In addition, modulation of the sensory system in experimental autoimmune neuritis was detected. An outgrowth of small fibres in the plantar skin at the onset and peak of the experimental autoimmune neuritis was evident parallel to the development of acute hyperalgesia mediated through transient receptor potential vanilloid 1 modulation. Our data depict experimental autoimmune neuritis as a primary demyelinating disease with implicated axonal damage, a small unmyelinated fibre impairment throughout the disease progression course, and underline the pivotal role of macrophages in the effector and during the recovery stage.
In vivo PET classification of tau pathologies in patients with frontotemporal dementia
Authors: Kubota Manabu , Endo Hironobu , Takahata Keisuke , Tagai Kenji , Suzuki Hisaomi , Onaya Mitsumoto , Sano Yasunori , Yamamoto Yasuharu , Kurose Shin , Matsuoka Kiwamu , Seki Chie , Shinotoh Hitoshi , Kawamura Kazunori , Zhang Ming-Rong , Takado Yuhei , Shimada Hitoshi , Higuchi Makoto
Published: March 2024

Frontotemporal dementia refers to a group of neurodegenerative disorders with diverse clinical and neuropathological features. In vivo neuropathological assessments of frontotemporal dementia at an individual level have hitherto not been successful. In this study, we aim to classify patients with frontotemporal dementia based on topologies of tau protein aggregates captured by PET with 18F-florzolotau (aka 18F-APN-1607 and 18F-PM-PBB3), which allows high-contrast imaging of diverse tau fibrils in Alzheimer’s disease as well as in non–Alzheimer’s disease tauopathies. Twenty-six patients with frontotemporal dementia, 15 with behavioural variant frontotemporal dementia and 11 with other frontotemporal dementia phenotypes, and 20 age- and sex-matched healthy controls were included in this study. They underwent PET imaging of amyloid and tau depositions with 11C-PiB and 18F-florzolotau, respectively. By combining visual and quantitative analyses of PET images, the patients with behavioural variant frontotemporal dementia were classified into the following subgroups: (i) predominant tau accumulations in frontotemporal and frontolimbic cortices resembling three-repeat tauopathies (n = 3), (ii) predominant tau accumulations in posterior cortical and subcortical structures indicative of four-repeat tauopathies (n = 4); (iii) amyloid and tau accumulations consistent with Alzheimer’s disease (n = 4); and (iv) no overt amyloid and tau pathologies (n = 4). Despite these distinctions, clinical symptoms and localizations of brain atrophy did not significantly differ among the identified behavioural variant frontotemporal dementia subgroups. The patients with other frontotemporal dementia phenotypes were also classified into similar subgroups. The results suggest that PET with 18F-florzolotau potentially allows the classification of each individual with frontotemporal dementia on a neuropathological basis, which might not be possible by symptomatic and volumetric assessments.