bluuebunny/crossref_metadata_2025 huggingface dataset:
Autophagy: a critical mechanism of N6-methyladenosine modification involved in tumor progression and therapy resistance
Authors: Wang Feiyang , Liao Qiudi , Qin Zihao , Li Jingyi , Wei Qingqing , Li Mengna , Deng Hongyu , Xiong Wei , Tan Ming , Zhou Ming
Published: October 2024

N6-Methyladenosine (m6A) is an evolutionarily highly conserved epigenetic modification that affects eukaryotic RNAs, especially mRNAs, and m6A modification is commonly linked to tumor proliferation, progression, and therapeutic resistance by participating in RNA metabolism. Autophagy is an intracellular degradation and recycling biological process by which cells remove damaged organelles, protein aggregates, and other intracellular wastes, and release nutrients to maintain cell survival when energy is scarce. Recent studies have shown that m6A modification plays a critical role in the regulation of autophagy, affecting the initiation of autophagy, the formation and assembly of autophagosomes, and lysosomal function by regulating critical regulatory molecules involved in the process of autophagy. Moreover, autophagy can also affect the expression of the three types of regulators related to m6A, which in turn affects the levels of their target genes via m6A modification. Thus, m6A modification and autophagy form a sophisticated regulatory network through mutual regulation, which plays an important role in tumor progression and therapeutic resistance. In this manuscript, we reviewed the effects of m6A modification on autophagy as well as the effects of autophagy on m6A modification and the roles of the m6A-autophagy axis in tumor progression and therapy resistance. Additionally, we summarized the value and application prospects of key molecules in the m6A-autophagy axis in tumor diagnosis and therapy.
RAB4A is a master regulator of cancer cell stemness upstream of NUMB–NOTCH signaling
Authors: Karthikeyan Subbulakshmi , Casey Patrick J. , Wang Mei
Published: October 2024

Cancer stem cells (CSCs) are a group of specially programmed tumor cells that possess the characteristics of perpetual cell renewal, increased invasiveness, and often, drug resistance. Hence, eliminating CSCs is a major challenge for cancer treatment. Understanding the cellular programs that maintain CSCs, and identifying the critical regulators for such programs, are major undertakings in both basic and translational cancer research. Recently, we have reported that RAB4A is a major regulator of epithelial-to-mesenchymal transition (EMT) and it does so mainly through regulating the activation of RAC1 GTPase. In the current study, we have delineated a new signaling circuitry through which RAB4A transmits its control of cancer stemness. Using in vitro and in vivo studies, we show that RAB4A, as the upstream regulator, relays signal stepwise to NUMB, NOTCH1, RAC1, and then SOX2 to control the self-renewal property of multiple cancer cells of diverse tissue origins. Knockdown of NUMB, or overexpression of NICD (the active fragment NOTCH1) or SOX2, rescued the in vitro sphere-forming and in vivo tumor-forming abilities that were lost upon RAB4A knockdown. Furthermore, we discovered that the chain of control is mostly through transcriptional regulation at every step of the pathway. The discovery of the novel signaling axis of RAB4A–NUMB–NOTCH–SOX2 opens the path for further expansion of the signaling chain and for the identification of new regulators and interacting proteins important for CSC functions, which can be explored to develop new and effective therapies.
Chromatic covalent organic frameworks enabling in-vivo chemical tomography
Authors: Wang Song , Han Yangyang , Reddy Vaishnavi Amarr , Ang Mervin Chun-Yi , Sánchez-Velázquez Gabriel , Saju Jolly Madathiparambil , Cao Yunteng , Khong Duc Thinh , Jayapal Praveen Kumar , Cheerlavancha Raju , Loh Suh In , Singh Gajendra Pratap , Urano Daisuke , Rajani Sarojam , Marelli Benedetto , Strano Michael S.
Published: October 2024

Covalent organic frameworks designed as chromatic sensors offer opportunities to probe biological interfaces, particularly when combined with biocompatible matrices. Particularly compelling is the prospect of chemical tomography – or the 3D spatial mapping of chemical detail within the complex environment of living systems. Herein, we demonstrate a chromic Covalent Organic Framework (COF) integrated within silk fibroin (SF) microneedles that probe plant vasculature, sense the alkalization of vascular fluid as a biomarker for drought stress, and provide a 3D in-vivo mapping of chemical gradients using smartphone technology. A series of Schiff base COFs with tunable pKa ranging from 5.6 to 7.6 enable conical, optically transparent SF microneedles with COF coatings of 120 to 950 nm to probe vascular fluid and the surrounding tissues of tobacco and tomato plants. The conical design allows for 3D mapping of the chemical environment (such as pH) at standoff distances from the plant, enabling in-vivo chemical tomography. Chromatic COF sensors of this type will enable multidimensional chemical mapping of previously inaccessible and complex environments.
Protective effect of TCR-mediated MAIT cell activation during experimental autoimmune encephalomyelitis
Authors: Walkenhorst Mark , Sonner Jana K. , Meurs Nina , Engler Jan Broder , Bauer Simone , Winschel Ingo , Woo Marcel S. , Raich Lukas , Winkler Iris , Vieira Vanessa , Unger Lisa , Salinas Gabriela , Lantz Olivier , Friese Manuel A. , Willing Anne
Published: October 2024

Mucosal-associated invariant T (MAIT) cells express semi-invariant T cell receptors (TCR) for recognizing bacterial and yeast antigens derived from riboflavin metabolites presented on the non-polymorphic MHC class I-related protein 1 (MR1). Neuroinflammation in multiple sclerosis (MS) is likely initiated by autoreactive T cells and perpetuated by infiltration of additional immune cells, but the precise role of MAIT cells in MS pathogenesis remains unknown. Here, we use experimental autoimmune encephalomyelitis (EAE), a mouse model of MS, and find an accumulation of MAIT cells in the inflamed central nervous system (CNS) enriched for MAIT17 (RORγt+) and MAIT1/17 (T-bet+RORγt+) subsets with inflammatory and protective features. Results from transcriptome profiling and Nur77GFP reporter mice show that these CNS MAIT cells are activated via cytokines and TCR. Blocking TCR activation with an anti-MR1 antibody exacerbates EAE, whereas enhancing TCR activation with the cognate antigen, 5-(2-oxopropylideneamino)−6-D-ribitylaminouracil, ameliorates EAE severity, potentially via the induction of amphiregulin (AREG). In summary, our findings suggest that TCR-mediated MAIT cell activation is protective in CNS inflammation, likely involving an induction of AREG.
Formaldehyde initiates memory and motor impairments under weightlessness condition
Authors: Mei Tianhao , Chen Ying , Gao Yajuan , Zhao Hang , Lyu Xingzhou , Lin Jing , Niu Tianye , Han Hongbin , Tong Zhiqian
Published: October 2024

During space flight, prolonged weightlessness stress exerts a range of detrimental impacts on the physiology and psychology of astronauts. These manifestations encompass depressive symptoms, anxiety, and impairments in both short-term memory and motor functions, albeit the precise underlying mechanisms remain elusive. Recent studies have revealed that hindlimb unloading (HU) animal models, which simulate space weightlessness, exhibited a disorder in memory and motor function associated with endogenous formaldehyde (FA) accumulation in the hippocampus and cerebellum, disruption of brain extracellular space (ECS), and blockage of interstitial fluid (ISF) drainage. Notably, the impairment of the blood-brain barrier (BBB) caused by space weightlessness elicits the infiltration of albumin and hemoglobin from the blood vessels into the brain ECS. However, excessive FA has the potential to form cross-links between these two proteins and amyloid-beta (Aβ), thereby obstructing ECS and inducing neuron death. Moreover, FA can inhibit N-methyl-D-aspartate (NMDA) currents by crosslinking NR1 and NR2B subunits, thus impairing memory. Additionally, FA has the ability to modulate the levels of certain microRNAs (miRNAs) such as miRNA-29b, which can affect the expression of aquaporin-4 (AQP4) so as to regulate ECS structure and ISF drainage. Especially, the accumulation of FA may inactivate the ataxia telangiectasia-mutated (ATM) protein kinase by forming cross-linking, a process that is associated with ataxia. Hence, this review presents that weightlessness stress-derived FA may potentially serve as a crucial catalyst in the deterioration of memory and motor abilities in the context of microgravity.
When combinations of humans and AI are useful: A systematic review and meta-analysis
Authors: Vaccaro Michelle , Almaatouq Abdullah , Malone Thomas
Published: October 2024

Inspired by the increasing use of artificial intelligence (AI) to augment humans, researchers have studied human–AI systems involving different tasks, systems and populations. Despite such a large body of work, we lack a broad conceptual understanding of when combinations of humans and AI are better than either alone. Here we addressed this question by conducting a preregistered systematic review and meta-analysis of 106 experimental studies reporting 370 effect sizes. We searched an interdisciplinary set of databases (the Association for Computing Machinery Digital Library, the Web of Science and the Association for Information Systems eLibrary) for studies published between 1 January 2020 and 30 June 2023. Each study was required to include an original human-participants experiment that evaluated the performance of humans alone, AI alone and human–AI combinations. First, we found that, on average, human–AI combinations performed significantly worse than the best of humans or AI alone (Hedges’ g = −0.23; 95% confidence interval, −0.39 to −0.07). Second, we found performance losses in tasks that involved making decisions and significantly greater gains in tasks that involved creating content. Finally, when humans outperformed AI alone, we found performance gains in the combination, but when AI outperformed humans alone, we found losses. Limitations of the evidence assessed here include possible publication bias and variations in the study designs analysed. Overall, these findings highlight the heterogeneity of the effects of human–AI collaboration and point to promising avenues for improving human–AI systems.
Dynamic of bifurcation, chaotic structure and multi soliton of fractional nonlinear Schrödinger equation arise in plasma physics
Authors: Alazman Ibtehal , Alkahtani Badr Saad Thaar , Mishra Manvendra Narayan
Published: October 2024

In this study, we examine the third-order fractional nonlinear Schrödinger equation (FNLSE) in $$(1+1)$$-dimensional, by employing the analytical methodology of the new extended direct algebraic method (NEDAM) alongside optical soliton solutions. In order to better understand high-order nonlinear wave behaviors in such systems, the researched model captures the physical and mathematical properties of nonlinear dispersive waves, with applications in plasma physics and optics. With the aid of above mentioned approach, we rigorously assess the novel optical soliton solutions in the form of dark, bright–dark, dark–bright, periodic, singular, rational, mixed trigonometric and hyperbolic forms. Additionally, stability assessments using conserved quantities, such as Hamiltonian property, and consistency checks were used to validate the solutions. The dynamic structure of the governing model is further examined using chaos, bifurcation, and sensitivity analysis. With the appropriate parameter values, 2D, 3D, and contour plots can all be utilized to graphically show the data. This work advances our knowledge of nonlinear wave propagation in Bose–Einstein condensates, ultrafast fibre optics, and plasma physics, among other areas with higher-order chromatic effects.
A generic self-learning emotional framework for machines
Authors: Hernández-Marcos Alberto , Ros Eduardo
Published: October 2024

In nature, intelligent living beings have developed emotions to modulate their behavior as a fundamental evolutionary advantage. However, researchers seeking to endow machines with this advantage lack a clear theory from cognitive neuroscience describing emotional elicitation from first principles, namely, from raw observations to specific affects. As a result, they often rely on case-specific solutions and arbitrary or hard-coded models that fail to generalize well to other agents and tasks. Here we propose that emotions correspond to distinct temporal patterns perceived in crucial values for living beings in their environment (like recent rewards, expected future rewards or anticipated world states) and introduce a fully self-learning emotional framework for Artificial Intelligence agents convincingly associating them with documented natural emotions. Applied in a case study, an artificial neural network trained on unlabeled agent’s experiences successfully learned and identified eight basic emotional patterns that are situationally coherent and reproduce natural emotional dynamics. Validation through an emotional attribution survey, where human observers rated their pleasure-arousal-dominance dimensions, showed high statistical agreement, distinguishability, and strong alignment with experimental psychology accounts. We believe that the framework’s generality and cross-disciplinary language defined, grounded on first principles from Reinforcement Learning, may lay the foundations for further research and applications, leading us toward emotional machines that think and act more like us.
Effects of neighbourhood characteristics on the distribution of vacant houses in Toda city, a satellite city of Tokyo metropolis of japan
Authors: Liu Qiyuan , Sho Kojiro , Corcoran Jonathan , Ando Naomi
Published: October 2024

As Japan faces a growing crisis of vacant housing, this study investigates the underexplored relationship between vacant house distribution and neighbourhood characteristics in Toda City, a satellite city of the Tokyo metropolis located in Saitama Prefecture. We selected 10 community features, including living convenience, housing supply, and policy support, to explore their influence on vacancy rates. Using a comprehensive dataset primarily derived from the PLATEAU data, we employed a two-step method combining global and local Moran’s I analyses to assess the spatial distribution normality of vacant houses. We then compared traditional statistical data analysis with spatial data analysis through multiscale geographically weighted regression to evaluate their effectiveness and identify the factors most closely associated with vacancy rates. Our findings reveal that spatial data analysis provides superior insights compared to traditional statistical methods. Both approaches consistently indicate a significant positive correlation between the supermarket area ratio and vacancy rates, and a significant negative correlation between road adjacency and vacancy rates. This study demonstrates the feasibility of using spatial data to analyse neighbourhood characteristics in the context of declining vacancy rates in satellite cities. The insights gained offer theoretical support for selecting data and methodologies in future research and policymaking that are aimed at mitigating the growth of vacant houses.
Mathematical modeling predicts that endemics by generalist insects are eradicated if nearly all plants produce constitutive defense
Authors: Chakraborty Suman , Dwivedi Shalu , Schuster Stefan
Published: October 2024

Plants with constitutive defense chemicals exist widely in nature. The phenomenon is backed by abundant data from plant chemical ecology. Sufficient data are also available to conclude that plant defenses act as deterrent and repellent to attacking herbivores, particularly deleterious generalist insects. In the wild, generalist species are usually not endemic, meaning they are not restricted to certain plant species in a region. Therefore, our objective is to inspect theoretically whether evolution of chemical defenses in all plant species eradicate an endemic by any generalist species. The objective is addressed by developing deterministic ordinary differential equations under the following conditions: Plants without constitutive defenses are susceptible to oviposition by generalist insects, while they become defended against generalists by storing chemical defenses. From the models, we explicitly obtain that a generalist-free stable state is only possible if the vast majority of all plant individuals have chemical defenses. The model also allows one to predict the highest possible percentage of undefended plant individuals, which may be considered as free-riders.
Rationalised experiment design for parameter estimation with sensitivity clustering
Authors: Chhajer Harsh , Roy Rahul
Published: October 2024

Quantitative experiments are essential for investigating, uncovering, and confirming our understanding of complex systems, necessitating the use of effective and robust experimental designs. Despite generally outperforming other approaches, the broader adoption of model-based design of experiments (MBDoE) has been hindered by oversimplified assumptions and computational overhead. To address this, we present PARameter SEnsitivity Clustering (PARSEC), an MBDoE framework that identifies informative measurable combinations through parameter sensitivity (PS) clustering. We combined PARSEC with a new variant of Approximate Bayesian Computation-based parameter estimation for rapid, automated assessment and ranking of experiment designs. Using two kinetic model systems with distinct dynamical features, we show that PARSEC-based experiments improve the parameter estimation of a complex system. By its inherent formulation, PARSEC can account for experimental restrictions and parameter variability. Moreover, we demonstrate that there is a strong correlation between sample size and the optimal number of PS clusters in PARSEC, offering a novel method to determine the ideal sampling for experiments. This validates our argument for employing parameter sensitivity in experiment design and illustrates the potential to leverage both model architecture and system dynamics to effectively explore the experimental design space.
Dynamics of the human bile acid metabolome during weight loss
Authors: Schmid Andreas , Liebisch Gerhard , Burkhardt Ralph , Belikan Hannah , Köhler Sebastian , Steger Daniel , Schweitzer Leonie , Pons-Kühnemann Jörn , Karrasch Thomas , Schäffler Andreas
Published: October 2024

Bile acids (BA) are supposed to cause metabolic alterations after bariatric surgery (BS). Here we report the longitudinal dynamics of the human BA metabolome by LC–MS/MS after BS versus low calory diet (LCD) in two obesity cohorts over 12 months. Rapid and persistent oscillations of 23 BA subspecies could be identified with highly specific patterns in BS vs. LCD. TCDCA, GLCA, and TLCA represent most promising candidates for drug development.
Exploring the potential of biosurfactants produced by fungi found in soil contaminated with petrochemical wastes
Authors: Mahmoud Yehia A.-G. , El-Halmouch Yasser H. , Nasr Ebtsam E. , Al-Sodany Yassin M. , El-Nogoumy Baher A. , Ali Sameh S.
Published: October 2024

Biosurfactants are a diverse group of compounds derived from microorganisms, possessing various structures and applications. The current study was seeking to isolate and identify a new biosurfactant-producing fungus from soil contaminated with petrochemical waste. The bioprocess conditions were optimized to maximize biosurfactant production for Aspergillus carneus OQ152507 using a glucose peptone culture medium with a pH of 7.0 and a temperature of 35 °C. The carbon source was glucose (3%), and ammonium sulfate (0.25%) was utilized as the nitrogen source. For Aspergillus niger OQ195934, the optimized conditions involved a starch nitrate culture medium with a pH of 7.0 and a temperature of 30 °C. The carbon source used was sucrose (3.5%), and ammonium sulfate (0.25%) served as the nitrogen source. The phenol-H2SO4 and phosphate tests showed that the biosurfactants that were extracted did contain glycolipid and/or phospholipid molecules. They showed considerable antimicrobial activity against certain microbes. The obtained biosurfactants increased the solubility of tested polyaromatic hydrocarbons, including fluoranthene, pyrene, anthracene, and fluorine, and successfully removed the lubricating oil from contaminated soil and aqueous media surface tension reduction. Based on the obtained results, A. carneus and A. niger biosurfactants could be potential candidates for environmental oil remediation processes.
Machine learning to improve the understanding of rabies epidemiology in low surveillance settings
Authors: Keshavamurthy Ravikiran , Boutelle Cassandra , Nakazawa Yoshinori , Joseph Haim , Joseph Dady W. , Dilius Pierre , Gibson Andrew D. , Wallace Ryan M.
Published: October 2024

In low and middle-income countries, a large proportion of animal rabies investigations end without a conclusive diagnosis leading to epidemiologic interpretations informed by clinical, rather than laboratory data. We compared Extreme Gradient Boosting (XGB) with Logistic Regression (LR) for their ability to estimate the probability of rabies in animals investigated as part of an Integrated Bite Case Management program (IBCM). To balance our training data, we used Random Oversampling (ROS) and Synthetic Minority Oversampling Technique. We developed a risk stratification framework based on predicted rabies probabilities. XGB performed better at predicting rabies cases than LR. Oversampling strategies enhanced the model sensitivity making them the preferred technique to predict rare events like rabies in a biting animal. XGB-ROS classified most of the confirmed rabies cases and only a small proportion of non-cases as either high (confirmed cases = 85.2%, non-cases = 0.01%) or moderate (confirmed cases = 8.4%, non-cases = 4.0%) risk. Model-based risk stratification led to a 3.2-fold increase in epidemiologically useful data compared to a routine surveillance strategy using IBCM case definitions. Our study demonstrates the application of machine learning to strengthen zoonotic disease surveillance under resource-limited settings.
Overdamping of vibration resonances by liquid crystal elastomers
Authors: Elmadih Waiel , Terentjev Andrew , Liang Hsin-Ling , Terentjev Eugene
Published: October 2024

This work aims to compare the capability of vibration attenuation by standard elastomeric polymers, and by the new anomalously damping nematic liquid crystal elastomer. We use the most mainstream materials in both categories, and design two testing platforms: the ASTM-standard constrained layer plate resonance geometry, and the attenuation of resonances in a commercial device (electric drill) where the damping polymers were inserted into the casing. In the standard plate resonance testing, we find that LCE outperforms all standard damping materials, moreover, it brings the vibrating plate into the overdamped condition, which is unique for a non-fluid dissipative system. In the attenuation of high-frequency vibrations of a device, we also found LCE dissipates these vibrations much better, although we did not find the optimal insertion configuration for the damping polymer, and did not reach overdamping.
Phenological response to climatic change depends on spring warming velocity
Authors: Guralnick Robert , Crimmins Theresa , Grady Erin , Campbell Lindsay
Published: October 2024

Climatic change is dramatically altering phenology but generalities regarding tempo and mode of response remain limited. Here we present a general model framework incorporating spring temperature, velocity of spring warming, and species’ thermal requirements for predicting phenological response to warming. A key prediction of this framework is that species active earlier in the season and located in warmer regions where spring temperature velocity is lowest show strongest sensitivity to climatic change and greatest advancement in response to warming. We test this prediction using plant phenology datasets collected in the 1850s and 2010s. Our results strikingly confirm model predictions, showing that while temperature sensitivity is higher in regions with low temperature velocity, the greatest realized change in phenological onset is northern areas where warming rates have been fastest. Our framework offers enhanced utility for predicting phenological sensitivity and responsiveness in temperate regions and across multiple plant species and potentially other groups.
Human PC4 supports telomere stability and viability in cells utilizing the alternative lengthening of telomeres mechanism
Authors: Salgado Sara , Abreu Patricia L , Moleirinho Beatriz , Guedes Daniela S , Larcombe Lee , Azzalin Claus M
Published: October 2024

Cancer cells with an activated Alternative Lengthening of Telomeres (ALT) mechanism elongate telomeres via homology-directed repair. Sustained telomeric replication stress is an essential trigger of ALT activity; however, it can lead to cell death if not properly restricted. By analyzing publicly available data from genome-wide CRISPR KO screenings, we have identified the multifunctional protein PC4 as a novel factor essential for ALT cell viability. Depletion of PC4 results in rapid ALT cell death, while telomerase-positive cells show minimal effects. PC4 depletion induces replication stress and telomere fragility primarily in ALT cells, and increases ALT activity. PC4 binds to telomeric DNA in cells, and its binding can be enhanced by telomeric replication stress. Finally, a mutant PC4 with partly impaired single stranded DNA binding activity is capable to localize to telomeres and suppress ALT activity and telomeric replication stress. We propose that PC4 supports ALT cell viability, at least partly, by averting telomere dysfunction. Further studies of PC4 interactions at ALT telomeres may hold promise for innovative therapies to eradicate ALT cancers.
Deep quantification of substrate turnover defines protease subsite cooperativity
Authors: Gudipati Rajani Kanth , Gaidatzis Dimos , Seebacher Jan , Muehlhaeusser Sandra , Kempf Georg , Cavadini Simone , Hess Daniel , Soneson Charlotte , Großhans Helge
Published: October 2024

Substrate specificity determines protease functions in physiology and in clinical and biotechnological applications, yet quantitative cleavage information is often unavailable, biased, or limited to a small number of events. Here, we develop qPISA (quantitative Protease specificity Inference from Substrate Analysis) to study Dipeptidyl Peptidase Four (DPP4), a key regulator of blood glucose levels. We use mass spectrometry to quantify >40,000 peptides from a complex, commercially available peptide mixture. By analyzing changes in substrate levels quantitatively instead of focusing on qualitative product identification through a binary classifier, we can reveal cooperative interactions within DPP4’s active pocket and derive a sequence motif that predicts activity quantitatively. qPISA distinguishes DPP4 from the related C. elegans DPF-3 (a DPP8/9-orthologue), and we relate the differences to the structural features of the two enzymes. We demonstrate that qPISA can direct protein engineering efforts like the stabilization of GLP-1, a key DPP4 substrate used in the treatment of diabetes and obesity. Thus, qPISA offers a versatile approach for profiling protease and especially exopeptidase specificity, facilitating insight into enzyme mechanisms and biotechnological and clinical applications.
Controlled Drug Analysis
Authors: Cole Michael D , Gautam Lata , Grela Agatha
Published: October 2024

Development of new techniques and methods for analysis of controlled substances brings a different way of considering drug analysis which is articulated for the first time in this new text. In addition to a modern treatment of the widely known drugs (e.g. cannabis, heroin, cocaine, amphetamines, ring substituted amphetamines) and pharmaceuticals which are used as recreational drugs (e.g. barbiturates, benzodiazepines), the book will consider prominent drug classes that have not yet received systematic treatment in a textbook (for example synthetic cannabinoids, piperazines, cathinones, fentanyls). Aimed at undergraduate and postgraduate taught programmes, the book includes methods for drug analysis and comparison using physical, biologically based, comparative and numerical techniques. It will also serve as a reference point for research students and practising forensic scientists. It introduces statistical methods for drug sample comparison and the appropriateness of some of the statistical techniques for drug analysis and examines their use. It also considers newly developed analytical methods and significant legislative changes.

Aimed at academics delivering forensic science courses in particular, it could also be used by chemistry, biochemistry, criminalistics, criminology and law and policing students on MSc forensic science courses and postgraduate research candidates.
A Cu-based metal–organic framework synthesized via a green method exhibits unique catecholase-like activity for epigallocatechin gallate detection in teas
Authors: Kulandaivel Sivasankar , Wang Yu-Meng , Chen Sung-Fang , Lin Chia-Her , Yeh Yi-Chun
Published: October 2024

Green-synthesized Cu-PyC NH4+ MOF nanozyme demonstrates selective catecholase activity, distinct from typical oxidase nanozymes, enabling epigallocatechin gallate detection in tea samples.
Agent-based learning of materials datasets from the scientific literature
Authors: Ansari Mehrad , Moosavi Seyed Mohamad
Published: October 2024

An AI Agent for autonomous development of materials dataset from scientific literature.
Unsupervised learning and pattern recognition in alloy design
Authors: Bhat Ninad , Birbilis Nick , Barnard Amanda S.
Published: October 2024

Metal alloys are important for a variety of industrial applications but occupy large combinatorial design spaces. Pattern recognition provides unique opportunities to group and simplify alloy data prior to property prediction.
Topotactic transformation of zeolitic imidazolate frameworks into high-performance battery type electrodes for supercapattery application
Authors: Sharma Jatin , Alagar Srinivasan , Aashi  , Kaur Rajdeep , Gaur Ashish , Krishankant  , Pundir Vikas , Upreti Deepak , Rani Rekha , Arun K. , Bagchi Vivek
Published: October 2024

This work provides the development of a highly efficient HSCs by topotactically converting extremely porous metal organic framework into energy storage devices.
Depressing charge recombination in hybrid perovskites by introducing a dynamic electron/energy relay couple towards enhanced photocatalytic hydrogen production
Authors: Liu Jiaqi , Xie Yuxin , Jiao Yongxin , Zhang Hefeng , Wang Junhui , Gao Yuying , Zong Xu
Published: October 2024

Extraordinary photocatalytic hydrogen evolution is achieved on methylammonium lead iodide perovskites by introducing a dynamic Cu/(CuI2)− couple as the electron/energy relay station and the Pt co-catalyst as the charge/energy-releasing promotor.
Flexible spacer-block multi-component copolymerized donors enable resilient organic solar cells with over 40% crack-onset strain
Authors: Lin Congqi , Chen Zhenyu , Peng Ruixiang , Song Wei , Gao Jiangwei , Yu Xueliang , Feng Tingting , Bai Yongqi , Ge Ziyi
Published: October 2024

A series of novel block donors were synthesized, achieving excellent PCE of 19.57% in rigid OSCs and 18.03% in f-OSCs, along with an outstanding crack-onset strain value of 40.29%.
meso-Substituted AB3-type phenothiazinyl porphyrins and their indium and zinc complexes photosensitising properties, cytotoxicity and phototoxicity on ovarian cancer cells
Authors: Balázs Brém , Stoean (Vasile) Bianca , Molnár Éva , Fischer-Fodor Eva , Bălăcescu Ovidiu , Borlan Raluca , Focsan Monica , Grozav Adriana , Achimaş-Cadariu Patriciu , Gál Emese , Gaina Luiza
Published: October 2024

New meso-substituted AB3-type phenothiazinyl porphyrins and ferrocenylvinyl phenothiazinyl porphyrin were synthesised by Suzuki–Miyaura and Mizoroki–Heck cross-coupling reactions, respectively.
Supramolecular chirality in self-organised systems and thin films
Authors: Giancane G. , Bettini S. , Valli L.
Published: October 2024

Gabriele Giancane, Simona Bettini and Ludovico Valli introduce the Nanoscale Advances themed collection on Supramolecular chirality in self-organised systems and thin films.
Fabrication of palladium-enriched metallic structures by direct focused He+ and Ne+ beam nanowriting from organometallic thin films: a comparison with Ga+ and e− beams
Authors: Herrer Lucía , Salvador-Porroche Alba , Hlawacek Gregor , Cea Pilar , De Teresa José María
Published: October 2024

A direct nanowriting method using He+ and Ne+ ion beams with spin-coated palladium acetate thin films enables the fabrication of metallic structures in a single and fast step, showcasing versatility with the four most commonly used focused ion beams.
Current progress and frontiers in three-dimensional macroporous carbon-based aerogels for electromagnetic wave absorption: a review
Authors: Ding Han , Hu Bo , Wang Yu , Du Yunchen
Published: October 2024

This article provides a timely review on the construction of three-dimensional macroporous carbon-based aerogels and their application in the field of electromagnetic absorption.
Synergetic antibacterial nanosheet based on Ti3C2Tx photothermal therapy and cationic polymer to eradicate drug-resistant bacterial biofilms
Authors: Pang Chuming , Tan Yingxin , Ling Jiahao , Hong Liangzhi
Published: October 2024

The BPG nanosheets, based on Ti3C2Tx MXene and cationic bornyl-guanidine polymers, exhibited broad-spectrum antibacterial activity and antibiofilm ability under near-infrared irradiation.
Development of an ultra-sensitive laser stimulated fluorescence system for simultaneous detection of amino acids
Authors: Naik Megha , Patil Ajeetkumar
Published: October 2024

An in-house developed ultra-sensitive high-performance liquid chromatography coupled laser stimulated fluorescence system for qualitative and quantitative assessment of amino acids in biological fluids.
Intact quantitation and evaluation of a PEG-glycosulfopeptide as a therapeutic P-selectin antagonist
Authors: Park Diane D. , Park Simon S. , Dai Erbin , Haller Carolyn A. , Wong Daniel J. , Wever Walter J. , Cummings Richard D. , Chaikof Elliot L.
Published: October 2024

Peptide-based therapeutics are recognized as potent and selective molecules but are often limited by short circulating half-lives, instability towards enzymatic degradation, and immunogenicity.
Molecular dynamics study of the trans-grain extension behavior of crack tips under synergistic effects
Authors: Zhou Jinjie , Zhang Tianyu , Shen Jinchuan
Published: October 2024

In this paper, the trans-grain extension behavior of crack tips is investigated.
Co-deposition of Ni–Mo alloy film catalysts for hydrogen evolution from an ethylene glycol system
Authors: He Xinkuai , Li Yiren , Yang Jingjing , Zeng Genfa , Wu Luye
Published: October 2024

The electrochemical behaviors of nickel and molybdenum ions in ethylene glycol were studied. Moreover, it was found that the alloy films exhibited excellent electrocatalytic performance for hydrogen evolution (η10 = 74 mV).
Ionic resorcinarenes as drug solubilization agents in water
Authors: Osei Frank Boateng , Twum Kwaku , Manfredi Barbara , Fatohi Mariana , Bessem Ojong Yvonne , Washington Valance , Beyeh Ngong Kodiah
Published: October 2024

Two ionic, cavity-containing, water-soluble resorcinarenes are shown to bind to and enhance the aqueous solubility of three hydrophobic drugs: isoniazid, caffeine, and griseofulvin. The macrocycles are non-toxic at experimental concentrations.
Crosslinked polymeric networks of TiO2–polymer composites: a comprehensive review
Authors: Arif Muhammad , Javed Mohsin , Akhter Toheed
Published: October 2024

The crosslinked network of TiO2–organic polymer composites has gained considerable attention over the past few years.
Bioinspired self-healing nickel coating
Authors: Bellah Masum , Nosonovsky Michael , Church Benjamin , Rohatgi Pradeep
Published: October 2024

A self-healing anticorrosive nickel coating using poly(urea-formaldehyde) (PUF) shell microcapsules containing linseed oil triggers a self-healing response to damage similar to mechanisms observed in nature.
Design and performance evaluation of low-volatility and low-viscosity absorbents for CO2 capture
Authors: Ma Ning , Yang Liu , Fang Zhenchang , Jiang Kaijia , Li Xinling , Huang Zhen
Published: October 2024

This study synthesized a novel homogeneous non-aqueous absorbent and analyzed hydrogen bonds and viscosities, which were rarely studied before.
Investigating students' expectations and engagement in general and organic chemistry laboratory courses
Authors: Vaughan Elizabeth B. , Tummuru Saraswathi , Barbera Jack
Published: October 2024

Students’ expectations for their laboratory coursework are theorized to have an impact on their learning experiences and behaviors, such as engagement. Before students’ expectations and engagement can be explored in different types of undergraduate chemistry laboratory courses, appropriate measures of these constructs must be identified, and evidence of validity and reliability for the data collected with these instruments must be investigated. This study collected evidence related to response process validity, internal structure validity, and single administration reliability for version 2 of the Meaningful Learning in the Laboratory Instrument (MLLIv2) and a measure of student engagement in the undergraduate chemistry laboratory. Additionally, evidence of consequential validity was assessed through measurement invariance, providing support for the comparison of latent means between the groups. Differences in students’ expectations and engagement were found based on course-level (general vs. organic chemistry) and pedagogical style (cookbook vs. inquiry-based).
Aging iridium oxide catalyst inks: a formulation strategy to enhance ink processability for polymer electrolyte membrane water electrolyzers
Authors: Khandavalli Sunilkumar , Park Jae Hyung , Rice Robin , Zhang Diana Y. , Berlinger Sarah A. , Bender Guido , Myers Deborah J. , Ulsh Michael , Mauger Scott A.
Published: October 2024

Steady-shear rheology showing evolution of the microstructure of iridium oxide catalyst inks of PEM water electrolyzers with aging time.
Recent progresses in the synthesis and strategic designs of sustainable carbon-based fibrous electrodes for flexible batteries
Authors: Thomas Susmi Anna , Cherusseri Jayesh , Rajendran Deepthi N.
Published: October 2024

A detailed review on carbon fiber (CF)-based flexible electrodes for application in rechargeable batteries is reported. Various preparation methods for flexible electrodes based on CFs are reviewed, along with their performance evaluations.
Efficient single-component nickel catalysts with tetradentate aminopyridine ligands for cycloaddition reactions of CO2 and epoxides under mild conditions
Authors: Zhang Congcong , Shi Minghui , Yu Ning , Zhang Bowen , Han Feng , Miao Chengxia
Published: October 2024

A series of single-component nickel catalysts with tetradentate aminopyridine ligands exhibited excellent capabilities and selectivity for the synthesis of cyclic carbonates from epoxides and CO2, even under 1 atm CO2 and 0.5 mol% of the catalyst.
Crystal structure, stability and Li superionic conductivity of pyrochlore-type solid electrolyte Li2−xLa(1+x)/3Nb2O6F: a first-principles calculation study
Authors: Jalem Randy , Takada Kazunori , Onodera Hitoshi , Yoshida Shuhei
Published: October 2024

Recently, a new oxide-type solid electrolyte (SE) for all-solid-state Li ion batteries, pyrochlore-type Li2−xLa(1+x)/3Nb2O6F (LLNOF), was reported to exhibit a Li+ superionic conductivity of 3.9 × 10−3 S cm−1 at room temperature.
Pilot spoofing attack detection and channel estimation for secure massive MIMO
Authors: Liu Delong , Wang Wei , Huang Yang
Published: October 2024

Pilot spoofing attack (PSA) is an active eavesdropping attack in massive multiple‐input multiple‐output systems, where the eavesdroppers transmit the same pilot sequence as the legitimate user does to the base station to confuse the normal channel estimation during the uplink channel training phase. With the contaminated channel estimations, more information will be leaked to eavesdroppers in the downlink transmission phase. However, it is a challenging issue to detect the PSA attack due to the similarity of the received signals and the variations of the wireless channels. Here, a new PSA detection scheme by using the difference of two different estimators is presented, that is, the least square estimator and the minimum mean square error estimator, without requiring any priori of eavesdroppers. Following that, a new data‐aided channel estimation scheme is proposed to eliminate the PSA effect. Simulation results demonstrate that the proposed PSA detection scheme outperforms the conventional energy detector, and more accurate legitimate channel estimation and higher sum secrecy rates can be obtained with the proposed scheme.
Resilience‐oriented load restoration method for power‐gas‐water systems considering public safety impact
Authors: Wan Haiyang , Liu Wenxia , Zhang Shuai , Shi Qingxin , Cheng Rui , Feng Wei
Published: October 2024

Focusing solely on enhancing the resilience of power systems at a systemic level would lead to a significant underestimation of the actual impact of extreme disasters. Equally vital is the assurance of livelihood security amidst such extreme conditions, which is crucial for the development of a truly resilient power system. Hence, this paper attempts to incorporate quantifiable metrics assessing public safety impacts into resilience enhancement works, thereby guiding the precise allocation of funds. Considering that the residents' intuitive feelings are the most direct reflection of the severity of the disaster, this paper employs the modified prospect theory to formulate functions representing residents' psychological risk perception and risk‐taking willingness to tolerate risks during disruptions in power, gas, and water supplies. Meanwhile, in order to accurately calculate the energy loss duration for each residential customer, a resilience enhancement method for post‐disaster collaborative dispatch of electricity‐gas‐water systems is proposed. With the objective of minimizing the public safety and economic impact of disasters, the optimal multi‐source collaborative emergency restoration strategy is developed. The significant necessity and efficiency of the proposed strategy are verified with exhaustive case studies. Numerical results evince the resilience enhancement by considering the livelihood security in the post‐disaster restoration stage.
Neutron-rich clustering investigation at LNS with FARCOS detectors
Authors: Risitano Fabio , Gnoffo Brunilde , Trimarchi Marina , Acosta Luis , Cardella Giuseppe , De Filippo Enrico , Dell’Aquila Daniele , Geraci Elena , Lombardo Ivano , Maiolino Concetta , Martorana Nunzia Simona , Pagano Angelo , Pagano Emanuele Vincenzo , Papa Massimo , Pirrone Sara , Politi Giuseppe , Quattrocchi Lucia , Rizzo Francesca , Russotto Paolo , Zagami Cristina
Published: October 2024

The physics of clusters in heavy neutron-rich ions is a topic of constant interest in the worldwide scientific community. In recent times, many interesting phenomena have been investigated especially thanks to the development of new radioactive beam production facilities. One example is the clustering of α particles in neutron-rich isotopes of self-conjugated nuclei, such as10Be or16C, exhibiting even very large nuclear deformations. At Laboratori Nazionali del Sud of INFN, a study was carried out on the topic of α clustering, employing the CHIMERA and FARCOS detectors. Radioactive ions of interest, such as10Be,13B and16C, were produced in a cocktail beam through the In-Flight fragmentation technique by the FRIBs@LNS facility. Particularly important for this study was the employment of four FARCOS detectors, offering high angular and energetic resolutions. Several calibration and analysis techniques have been exploited and developed in this experiment for the analysis of the data collected by FARCOS. Finally, some preliminary results on the analysis of10Be and16C spectroscopy will be shown, in relation to some results already collected in the literature.
Investigation on surface tension of CaF2–CaO–SiO2 (–MgO–Al2O3) melts
Authors: Lao Yigui , Gao Yunming , Wang Qiang , Li Guangqiang
Published: October 2024

In this work, the surface tension of CaF2–CaO–SiO2 melt with high CaF2 contents was measured by pulling cylinder method at 1773 K. The effects of CaF2 content, basicity, and the addition of MgO and Al2O3 on the surface tension were also investigated by considering the change in the melt structure. It was observed that as the CaF2 content increased from 30 to 80 mass%, there was no further depolymerizing effect on the silicate structure of the melt, maintaining a constant basicity of 1. However, the surface tension of the melts decreased from 397 to 325 mN/m due to the surface-active effect of CaF2. With the increase of basicity from 0.5 to 3, the surface tension of the melt initially increased from 342 mN/m to a maximum value of 390 mN/m, then decreased to 368 mN/m. The maximum value occurred at a basicity of 2. Furthermore, at constant basicity, the addition of MgO from 0 to 10 mass% led to a decrease in the surface tension of the melt decreased from 358 to 326 mN/m. Similarly, with the basicity ranging from 1 to 3, the addition of 10 mass% Al2O3 resulted in a decrease in the surface tension of the melt.
Energy conversion and transport in molecular-scale junctions
Authors: Zhang Haixin , Zhu Yunxuan , Duan Ping , Shiri Mehrdad , Yelishala Sai Chandra , Shen Shaocheng , Song Ziqi , Jia Chuancheng , Guo Xuefeng , Cui Longji , Wang Kun
Published: October 2024

Molecular-scale junctions (MSJs) have been considered the ideal testbed for probing physical and chemical processes at the molecular scale. Due to nanometric confinement, charge and energy transport in MSJs are governed by quantum mechanically dictated energy profiles, which can be tuned chemically or physically with atomic precision, offering rich possibilities beyond conventional semiconductor devices. While charge transport in MSJs has been extensively studied over the past two decades, understanding energy conversion and transport in MSJs has only become experimentally attainable in recent years. As demonstrated recently, by tuning the quantum interplay between the electrodes, the molecular core, and the contact interfaces, energy processes can be manipulated to achieve desired functionalities, opening new avenues for molecular electronics, energy harvesting, and sensing applications. This Review provides a comprehensive overview and critical analysis of various forms of energy conversion and transport processes in MSJs and their associated applications. We elaborate on energy-related processes mediated by the interaction between the core molecular structure in MSJs and different external stimuli, such as light, heat, electric field, magnetic field, force, and other environmental cues. Key topics covered include photovoltaics, electroluminescence, thermoelectricity, heat conduction, catalysis, spin-mediated phenomena, and vibrational effects. The review concludes with a discussion of existing challenges and future opportunities, aiming to facilitate in-depth future investigation of promising experimental platforms, molecular design principles, control strategies, and new application scenarios.