Kim, Ah Young · Kim, Jin Su · Ko, Jung Yun · et al.

3 files · 307 KB · pdf, xlsxdeclared

This dataset contains the source data associated with the manuscript entitled "Overexpression of SlMPBQMT (VTE3) enhances α-tocopherol accumulation and reduces oxidative stress in tomato." The uploaded files include the original experimental data used to generate the figures and analyses presented in the manuscript, including: HPLC quantification of α-tocopherol. Plant phenotype measurements. qRT-PCR expression data. DAB and NBT staining quantification data. These data are provided to ensure transparency, reproducibility, and compliance with the data availability policy of BMC Plant Biology .

Bell, Peter

2 files · 14 MB · pdf, zipdeclared

This working paper asks how Canada should assess strategic resource infrastructure that may not earn a commercial return on its own. A road, port, power system, pipeline, smelter, or processing plant can appear uneconomic when evaluated as an individual asset while still enabling new production, preserving difficult-to-replace processing capacity, supporting several users, or improving security of supply. The paper develops a framework for deciding when public support for such an asset may be justified. Its central rule is that an asset-level loss is defensible only when it produces wider benefits that are specific, measurable, and subject to effective public oversight. The analysis draws on Canadian wartime industrial mobilization, concentration in critical-mineral supply chains, proposed support for processing capacity at Trail, current infrastructure and northern development programs, and cautionary cases involving mining subsidies, managed decline, remote transport, and major-project governance. The paper converts the argument into a twelve-question approval test and a measurement framework for tracking public cost, avoided closure, new production, secure supply, shared infrastructure use, and signs of failure. It does not recommend a particular project and does not argue that all loss-making assets deserve public support. Its purpose is to distinguish infrastructure that creates durable public value from subsidy, bailout, or white-elephant risk.

Anazawa, Katsuro

1 files · 11 MB · pdfdeclared

The authorship of the Pauline epistles, particularly the Pastoral Epistles (1 and 2 Timothy and Titus), remains contested in biblical scholarship. Quantitative stylometry can contribute to this debate, but supervised approaches risk circular reasoning when they depend on predefined "core Pauline" labels, and lexical measures risk topic bias when distinctive vocabulary reflects subject matter rather than authorial style. This study proposes a transparent, sensitivity-oriented workflow for examining stylistic boundaries within the New Testament corpus. Using lemmatized Greek texts, it combines BM25 weighting, principal component analysis, hierarchical and k-means clustering, sensitivity analysis across alternative definitions of the Core Pauline letters, function-word-only analysis, and SHAP-based model interpretation. The results show that the Pastoral Epistles consistently occupy a region of stylometric space distinct from the Core Pauline letters; Deutero-Pauline letters tend to occupy a more intermediate position, while the Pastorals remain in the lowest tier of relative Core-likeness across core definitions. The pattern persists when content vocabulary is removed, suggesting that the observed divergence is not solely attributable to a topic-specific lexicon. The study does not claim to determine historical authorship definitively, especially given the absence of an externally verified Pauline stylome. Instead, it provides convergent quantitative evidence for a stable stylistic boundary that any historical account of the Pastorals-single-author, amanuensis-mediated, Pauline-school, or pseudonymous-must explain. The workflow illustrates how explainable machine learning can support transparent and reproducible stylometric analysis in small historical corpora. An earlier extended version is available at https://doi.org/10.5281/zenodo.18503648.

Dr. Ratheeswari K · Prof. Vasimalairaja M

1 files · 256 KB · pdfdeclared

Mobile learning apps have become a significant tool in modern education, especially for high school students. This study examines the influence of mobile learning apps on the academic performance of high school students in Dindigul District, considering factors such as gender, locality, school management type, and medium of instruction. A sample of 400 students was selected, comprising 180 males and 220 females, 220 from urban areas and 180 from rural areas, 190 from government schools and 210 from private schools, and 185 Tamil-medium and 215 English-medium students. The findings suggest that mobile learning apps positively impact academic performance, with variations observed across different demographic groups. The study highlights the potential of mobile learning in bridging educational gaps and recommends tailored approaches to maximize its benefits.

Anokhina, Tetiana · Годинчук, С. В.

1 files · 392 KB · pdfdeclared

Культурно-специфічні метафори в художньому перекладі є відображенням національних традицій, історичного досвіду та ментальних особливостей народу, що зумовлює труднощі їх інтерпретації іншою мовою. Питання взаємозв'язку мови, культури та метафори досліджували Джордж Лейкофф та Пітер Ньюмарк. На основі їхніх праць можна виокремити основні способи перекладу культурно маркованих метафор: пряме відтворення, адаптацію до культури реципієнта, заміну аналогічним образом, описовий переклад і нейтралізацію образності, що забезпечує збереження смислової та стилістичної цілісності тексту.

Fidelis Edonyabo · Onofere Princewill Okereka Ph.d · Akpomuvire Mukoro Ph.d

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Abstract: The study examined the role of job autonomy in enhancing employee performance in Delta State government hospitals. The study adopted Self-Determination Theory as theoretical framework for this study. The study utilized both qualitative and quantitative sources of data. The study revealed that participation in decision-making emerged as another significant predictor of employee performance, as it fosters a sense of ownership, accountability, and commitment to organisational goals. Moreover, clear work criteria, which outline performance expectations and task priorities, were shown to enhance employee confidence and consistency, leading to better outcomes in healthcare service delivery. In conclusion, the study highlights the transformative potential of job autonomy in enhancing employee performance, offering actionable strategies for improving public healthcare systems in Nigeria and beyond. The study recommended that to boost morale and enhance employee commitment, hospital management should involve staff in decision-making processes, especially in areas directly affecting their work. Structured mechanisms, such as staff committees or regular feedback sessions, should be established to gather input on scheduling, resource allocation, and patient care strategies. Hospital administrators should ensure that work criteria are well-defined and effectively communicated to employees. These criteria should outline performance expectations, task priorities, and quality standards to guide staff in their daily operations.

inquantio

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Published in Nature Astronomy, this study demonstrates a novel pathway where polyglycine peptide chains spontaneously form through the condensation of atomic carbon, skipping the stage of amino acid formation, by simulating the environment of interstellar clouds in space. The polymerization could occur spontaneously in a cryogenic environment of about 10 K because quantum chemical calculations revealed that this is a barrierless reaction requiring no external energy. By revealing that polymers can be formed through the combination of carbon monoxide (CO), atomic carbon (C), and ammonia (NH₃) without water or irradiation, this research presents disruptive evidence for astrobiology and the study of the origin of life. [Quantum Biology Society] How protein peptide chains, the fundamental building blocks of life, could spontaneously form in the extreme environment of space prior to the emergence of life has long been an unsolved mystery. This is because for molecules to combine and undergo polymerization, a certain level of activation energy is required, and overcoming this energy barrier has been considered thermodynamically impossible in interstellar molecular clouds where the temperature is a mere 10 K. The paper titled "A pathway to peptides in space through the condensation of atomic carbon," published as open access in the international journal Nature Astronomy, experimentally proves that this classical limitation has been completely overcome through a chemical mechanism known as a barrierless reaction. S. A. Krasnokutski and a joint research team from the Max Planck Institute for Astronomy in Germany led this innovative study. ■ The Pathway to Life Synthesis in Space Opened by Barrierless Chemical Reactions The research team conducted experiments in an ultrahigh vacuum chamber at cryogenic temperatures to precisely mimic the surface environment of cold solid particles (cosmic dust) in space. The experimental results confirmed that three of the most abundant species present in star-forming molecular clouds—carbon monoxide (CO), atomic carbon (C), and ammonia (NH₃)—react to form isomeric polyglycine monomers (aminoketene molecules). According to quantum chemical calculations, this is surprisingly a barrierless reaction, meaning there is no activation energy barrier to overcome. As a result, the molecules could undergo spontaneous chemical reactions at a cryogenic temperature of 10 K without the aid of external thermal energy. ■ A Revolutionary Mechanism Skipping the Amino Acid Stage The most revolutionary aspect of this mechanism is that, unlike traditional protein synthesis pathways, it entirely skips the stage of amino acid formation. The researchers demonstrated that without irradiation or the presence of water, aminoketene molecules formed under cryogenic conditions can encounter each other and polymerize highly efficiently to produce peptide chains of various lengths. This strongly supports the possibility that biopolymers spontaneously formed in the space environment could have been delivered to rocky planets in the habitable zone, acting as a crucial seed for the origin of life. This study is evaluated as a monumental astrobiological achievement, showing that the quantum chemically proven barrierless reaction is a core driving force leading the macroscopic origin of life even in extreme space environments. #QuantumBiology #OriginOfLife #Astrobiology #PeptideFormation #AtomicCarbon #BarrierlessReaction #Astrochemistry #InterstellarMedium #ExtremeEnvironment #Biophysics https://www.nature.com/articles/s41550-021-01577-9

inquantio

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A study published on bioRxiv proposes the paradigm of 'Particle Biology', moving beyond classical mechanics to explain the extreme efficiency of living organisms. Biological binding, such as ligand-receptor interactions, is reinterpreted not as a classical geometric lock-and-key model, but as a complex 'quantum many-body system'. The state of all biological systems is defined by the Unified Biological Hamiltonian equation (Ĥ_bio), which includes the interactions of electronic states, nuclear structures, coupling, and thermal fluctuations. [Quantum Biology Society] The extreme efficiency demonstrated by living organisms is difficult to fully explain through classical mechanics alone. Quantum tunneling, superposition, and coherence observed in core biological processes like enzyme catalysis and energy conversion are not mere environmental noise; rather, they are core driving mechanisms honed through a long evolutionary process. Recently, a study that presents a new perspective of 'Particle Biology', aiming to understand biological phenomena at the particle level, has been published, drawing significant attention from academia. The paper titled "Particle Biology: A Perspective on a First-Principles Theory of Life" , published in the preprint repository bioRxiv, proposes an integrative paradigm that explains biology through the fundamental principles of physics. A joint research team, including Peng Wang, Yanlei Ge, and Guogui Sun from Hebei Medical University and North China University of Science and Technology in China, established this innovative theoretical framework. ■ 'Quantum Many-Body System' Beyond the Lock-and-Key Model According to this new paradigm, biological binding processes, such as ligand-receptor complex formation, are not simply classical and geometric 'lock-and-key' puzzles. They must be understood as a complex 'quantum many-body system' where numerous particles interact through molecular orbital overlap and quantum superposition. The researchers explain that this perspective opens a new path to controlling life phenomena at the subatomic level, overcoming the limitations of conventional biochemical pathway modulation. ■ Declaration of the Unified Biological Hamiltonian (Ĥ_bio) This study introduces a Unified Biological Hamiltonian equation (Ĥ_bio = Ĥ_electronic + Ĥ_nuclear + Ĥ_coupling + Ĥ_environment) that can fundamentally describe the dynamic state of all biological systems. It suggests that biological functions emerge from the continuous quantum interactions among electronic states (Ĥ_electronic), nuclear structures (Ĥ_nuclear), vibronic coupling between them (Ĥ_coupling), and stochastic thermal fluctuations (Ĥ_environment), as represented in this equation. This provides a crucial theoretical foundation that integratively explains biological binding and mechanisms through the first principles of physics. #ParticleBiology #FirstPrinciplesOfLife #BiologicalHamiltonian #QuantumBiology #QuantumPhysics #Biophysics #LifePhenomena #QuantumDynamics #UnifiedTheory #KoreanQuantumBiologySociety https://www.biorxiv.org/content/10.64898/2026.05.17.725705v1

inquantio

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A study published on bioRxiv demonstrates for the first time the technique of treating protein sequences like sentences in natural language processing (NLP) and parsing them into parameterized quantum circuits using the Quantum Natural Language (QNLP) framework. It establishes a scheme that converts protein sequences into tensor networks represented by wires and boxes, and maps them onto actual quantum circuits through semantic functors. By generating protein syntax trees with a neural network-based parser and converting them into string diagrams optimized for quantum processor execution, the study proves that 'Quantum Tensor Networks (QTN)' achieve overwhelming computational accuracy in classifying vast protein sequences. [Quantum Biology Society] An innovative approach has been proposed to decode protein sequences—the most fundamental and complex codes of living organisms—by converting them into a natural language that quantum computers can comprehend. The paper titled "Application of Quantum Tensor Networks for Protein Classification" , published in the preprint repository bioRxiv, introduces a groundbreaking pipeline that applies Quantum Natural Language Processing (QNLP) technology to protein sequence classification, opening a new horizon for next-generation bioinformatics. A research team from Pennsylvania State University, including Debarshi Kundu, Jian Wang, Archisman Ghosh, and Nikolay Dokholyan, led this innovative study. ■ QNLP: Reading Protein Sequences as Sentences The researchers introduced a unique perspective of treating protein sequences, which are arrays of amino acids, as if they were sentences composed in human language. To achieve this, they adopted the 'Quantum Natural Language (QNLP)' framework, which combines state-of-the-art computational natural language processing (NLP) techniques with quantum computing. Within this framework, protein sequences are parsed into syntax trees with grammatical structures through a neural network-based parser, laying the foundation for their direct conversion into parameterized quantum circuits. ■ Transformation into Tensor Networks and String Diagrams In this process, protein sequences are converted into a tensor network scheme, geometrically represented by wires and boxes. The researchers defined a sophisticated semantic function (functor) that perfectly maps this abstract network to the operational structure of actual quantum circuits. The generated syntax trees are ultimately transformed into string diagrams, a format optimized for execution on quantum processors. Consequently, the constructed Quantum Tensor Networks (QTN) demonstrated overwhelming computational accuracy in machine learning tasks that involve extracting features and functionally classifying highly diverse and complex protein sequences, even in environments with a limited number of available qubits. This demonstration is highly significant as it establishes a powerful workflow in drug discovery and biotechnology, enabling rapid and accurate analysis of massive genomic data and protein interaction structures through quantum algorithms, transcending the limits of conventional classical computers. #QuantumTensorNetworks #QNLP #ProteinClassification #QuantumMachineLearning #QuantumLanguageModel #ProteinSequenceAnalysis #QuantumBiology #Biophysics #ArtificialIntelligence #KoreanQuantumBiologySociety https://www.biorxiv.org/content/10.1101/2024.03.11.584501v1

TAN, Kwan Hong

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Many firms adopt artificial intelligence as a tool while failing to redesign capabilities around it. This paper develops an original Artificial Intelligence Capability Architecture for Asian service firms. Using integrative theory building, it synthesizes dynamic capabilities, resource-based advantage, organizational learning, and responsible technology governance. The study proposes five mutually reinforcing capabilities including data discipline, workflow recomposition, human judgment orchestration, trust governance, and adaptive learning. The framework explains how firms convert artificial intelligence investment into defensible business value while reducing implementation drift, employee resistance, and governance risk.

Yoonsu Lee

1 files · 24 MB · pdfdeclared

Recent work in quantum gravity has revealed that closed universes appear to admit only a one-dimensional Hilbert space, implying zero information content. The leading resolution by Harlow, Usatyuk, and Zhao (arXiv:2501.02359, January 2025), featured in Quanta Magazine (November 2025), introduces observers as external additions to restore complexity. We demonstrate that this approach is self-contradictory: it resolves a closed universe problem by opening the universe, introducing boundaries in a system defined by their absence. We present a fundamentally different resolution. By proving that the open/closed distinction is itself a declaration and establishing observer-universe equivalence (O ≡ U), we derive the Totality Theorem: T = O + U = 1. The one-state result is not a paradox but a correct description of completeness: Shannon entropy H = 0 indicates full knowledge, not emptiness. We show that dimensionality itself is an artifact of partition, not a feature of reality. From three relations alone - T = 1, O ≡ U, dO = -dU - and a single structural principle (the Law of Identity A = A generates the binary partition A + ¬A = 1 with unique fixed point A = ¬A = 0.5), we resolve problems across every foundational domain: the unification of the four laws of thermodynamics as facets of a single identity, the black hole information paradox, the cosmological constant discrepancy, the Collatz and twin prime conjectures, Wigner's 67-year mystery of mathematical effectiveness, and the dissolution of Gödel's incompleteness as a property of notation rather than truth. All results derive from A = A.

inquantio

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A study published on bioRxiv demonstrates the first hybrid quantum computing framework combining classical Hamming distance filtering with the Grover quantum search algorithm to overcome bottlenecks in massive genomic data analysis. Utilizing the IBM Qiskit 27-qubit simulator, researchers rapidly and flawlessly identified a 50-nucleotide target sequence of a Cas9-like nuclease within a Brazilian biome metagenome database, even under conditions allowing up to a 30% mismatch. The study lays a revolutionary foundation for synthetic genome design by completing simulations that precisely insert a "BioBloQu" (quantum biological block)—composed of a promoter, an RBS, an enzyme, and a terminator—into the explored scar regions of the minimal genome M. mycoides JCVI-Syn3B. [Quantum Biology Society] Modern life sciences are pouring out genomic sequencing data at an exponential rate. However, due to the immense complexity of biological data, existing classical computing methods are facing severe computational bottlenecks in analyzing and manipulating it. To break through these limitations, a disruptive study recently published on the preprint repository bioRxiv, titled "Genetic Engineering with Quantum Circuits: creating codes and studying BioBloQu genetic elements," has brought quantum computers to the forefront of genetic engineering. A joint research team led by Professor Elibio Rech from the Brazilian Agricultural Research Corporation (Embrapa) Genetic Resources and Biotechnology and the Federal University of Rio Grande do Sul (UFRGS) presented this innovative research. ■ Scanning Massive Genomic Databases with Qubits Using the core quantum mechanical principles of superposition and entanglement as the foundation for information processing, the research team developed a hybrid quantum framework that combines classical Hamming distance filtering with the Grover quantum search algorithm. Powered by IBM's Qiskit 27-qubit simulator, this algorithm was used to search for a 50-nucleotide target sequence of a Cas9-like nuclease within a Brazilian biome metagenome database. As a result, the team successfully and swiftly identified the massive genetic data through amplitude amplification, filtering out the sequence perfectly even under conditions allowing up to a 30% mismatch rate. This proves that vast amounts of genetic data, which are unmanageable for classical computers, can be analyzed in a flash through quantum parallel processing. ■ The Era of Synthetic Genome Design Opened by BioBloQu Furthermore, the researchers successfully completed a quantum circuit simulation that accurately inserts a synthetic genetic construct called "BioBloQu" (quantum biological block) into the identified target regions. In the genome of M. mycoides JCVI-Syn3B, an artificially synthesized minimal genome model, the quantum algorithm first identified two 20-nucleotide "scar" regions—which are traces of gene editing. Then, it precisely integrated a tandem genetic block (BioBloQu) composed of a promoter, a ribosome binding site (RBS), an enzyme sequence, and a terminator into that location. This innovative approach goes beyond simply cutting and pasting existing genes physicochemically; it opens up the possibility of designing and assembling novel synthetic genomes from the ground up under the control of quantum algorithms equipped with overwhelming computational power. By directly applying the computational power of quantum mechanics to biotechnology, this research is expected to serve as the starting point for a massive revolution in next-generation quantum-bio data manipulation, customized gene therapy, and synthetic biology. #QuantumComputing #GeneticRecombination #BioBloQu #QuantumAlgorithm #GroverAlgorithm #Metagenome #SyntheticBiology #GenomeDesign #QuantumBiology #KoreanQuantumBiologySociety https://www.biorxiv.org/content/10.1101/2025.05.02.651535v2

inquantio

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A study published on bioRxiv proposes quantum and classical graph neural networks that address the issues of parameter compression and temporal changes in protein-ligand geometry—factors previously overlooked by existing machine learning (ML) models for predicting drug dissociation kinetics (k_off). Demonstrated a significant improvement in predictive accuracy through temporal integration by introducing a 2-timestep GCN+GRU model that actively learns structural changes before and after a short molecular dynamics simulation. Proved that quantum structures act as a powerful lever for the advancement of kinetic ML models in drug design by using variational quantum circuits to compress the model head, eliminating 66% of parameters while perfectly maintaining expressive power. [Quantum Biology Society] In the field of drug design, dissociation kinetics ($k_{off}$)—the duration a drug remains bound to its target protein—is increasingly recognized as a much more critical indicator of in vivo efficacy than simple binding affinity. However, existing machine learning (ML) models have largely overlooked the dynamic, temporal changes in protein-ligand geometric structures and the fundamental computational requirement to represent complex spatial interactions with fewer parameters. A study recently published on the preprint repository bioRxiv, titled "Quantum and Classical Graph Convolutional Neural Networks for Protein Ligand Dissociation Constant Prediction," opens new horizons by extending state-of-the-art Spatial Graph Neural Networks (Spatial GNNs) in two innovative directions to break through these classical limitations. A research team at the University of Cincinnati—comprising Azamat Salamatov, Jun Bai, Gowtham Atluri, and Chaowen Guan—led this disruptive research. ■ Combining 2-Timestep Learning and Variational Quantum Circuits The first innovation introduced by the research team is the integration of temporal flow. By adopting a 2-timestep GCN+GRU model that actively learns structural changes before and after a short molecular dynamics simulation, they have elevated the accuracy of kinetic predictions to the next level. The second key innovation is groundbreaking parameter optimization utilizing quantum technology. By compressing the model head using variational quantum circuits, the researchers successfully eliminated 66% of unnecessary parameters while completely preserving the complex expressive power of the existing fully classical model. Results from the PDBbind-koff-2020 benchmark test revealed the remarkable achievement of this quantum compressed model: it perfectly matched the predictive accuracy of the heavy, fully classical model while exponentially reducing the model size. This study clearly proves that temporal kinetics and quantum neural network structures serve as a powerful, disruptive lever to break the massive computational bottlenecks that occur in future drug candidate screening processes, propelling kinetic ML models a significant leap forward. #DrugScreening #DissociationKinetics #QuantumMachineLearning #GraphNeuralNetworks #ProteinLigand #QuantumComputing #DrugDevelopment #MolecularDynamics #ArtificialIntelligence #KoreanQuantumBiologySociety https://www.biorxiv.org/content/10.1101/2025.11.20.689635v2.full

inquantio

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Published in the international journal PLOS Computational Biology, this study models for the first time the decrease in adult hippocampal neurogenesis in a hypomagnetic field using the 'Radical Pair Mechanism'. It establishes a theoretical mathematical model that explains the cognitive decline and reduction in reactive oxygen species (ROS) levels observed in previous mouse experiments through changes in the singlet-triplet spin dynamics of radical pairs consisting of flavin and superoxide. It demonstrates that the formation of neural networks and metabolic processes in the mammalian brain are not merely simple macroscopic biochemical reactions, but are directly governed by a microscopic quantum phenomenon: the spin dynamics of ROS electrons that depend on external magnetic fields. [Korean Society of Quantum Biology, Reporter Hak-Jin Kim] Could the radical pair mechanism—the principle by which birds sense the Earth's magnetic field to navigate—also be deeply involved in mammalian brain development and cognitive function? Recently, a theoretical study offering a clear physical answer to this remarkable quantum biological question has been published. The paper, titled "Radical pairs may explain reactive oxygen species-mediated effects of hypomagnetic field on neurogenesis," published in the international journal PLOS Computational Biology, uncovers that neurogenesis is intricately linked to a purely quantum mechanical process. The research team, led by Rishabh Rishabh and Professor Christoph Simon from the University of Calgary in Canada, spearheaded this innovative study. ■ Hypomagnetic Field Environment and the Decrease in ROS Levels According to recently published biological experimental results, mice exposed to a hypomagnetic field environment—where the geomagnetic field is largely shielded—showed significantly attenuated neurogenesis in the hippocampal region of the adult brain, resulting in a distinct decline in cognitive abilities. Surprisingly, the fundamental cause of this cognitive decline and suppressed neurogenesis was revealed to be a decrease in intracellular reactive oxygen species (ROS) levels. The University of Calgary research team mathematically analyzed the cause of this phenomenon through the lens of quantum mechanics. ■ Electron Spin Dynamics Governing Brain Development The research team constructed a radical pair model of 'flavin' and 'superoxide', which are responsible for intracellular ROS production, and simulated their spin dynamics. As a result, they found that when the external magnetic field decreases from the geomagnetic field level (approx. 50 μT) to a hypomagnetic field (approx. 0 μT), the yield of the singlet-triplet interconversion changes dramatically due to alterations in the internal hyperfine interactions of the radical pair. The mathematically calculated extent of the decrease in product yield was consistent with the reduction rate of ROS observed in actual experiments. In other words, the sophisticated formation of neural networks and metabolic processes in mammals are not simply macroscopic chemical reactions, but are directly governed by an extremely microscopic quantum phenomenon: the electron spin dynamics occurring within molecules. This research is a monumental achievement that mathematically proves the causal entanglement between the macroscopic geomagnetic environment of the Earth and the quantum spin states within living organisms. It is expected to provide a revolutionary paradigm for developing technologies that utilize magnetic fields to treat degenerative brain diseases and promote neurogenesis in the future. #QuantumBiology #RadicalPairMechanism #Magnetoreception #Neurogenesis #ReactiveOxygenSpecies #HypomagneticField #SpinDynamics #QuantumMechanics #BrainScience #KoreanSocietyOfQuantumBiology https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010198

inquantio

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A study published in the international journal PCCP (Physical Chemistry Chemical Physics) models the proton transfer pathways and quantum tunneling rates during Watson-Crick tautomerism in DNA A-T and G-C base pairs, utilizing Density Functional Theory (DFT) and a machine learning-based Nudged Elastic Band (ML-NEB) algorithm. The research physically demonstrates that proton transfer in A-T base pairs is highly unstable due to an extremely low reverse-reaction barrier, making the occurrence of mutations during the replication process highly improbable. In G-C base pairs, a high quantum tunneling correction value was observed, providing the first physical proof that the mutant form (G-C) possesses a biological lifespan sufficient to be misread as an error by the human DNA replication machinery (replisome). [Korean Society of Quantum Biology, Reporter Hak-Jin Kim] The phenomenon wherein protons shift positions within the hydrogen bonds of DNA—the carrier of an organism's genetic information—can induce transient but lethal point mutations. Known as tautomerism, this process has long been identified as a potential root cause of genetic variation and oncogenesis. A recent study published in Physical Chemistry Chemical Physics (PCCP) has combined pure quantum mechanical modeling (DFT) with machine learning techniques to precisely calculate the energy barriers of double proton transfer occurring within A-T and G-C base pairs. This significant physicochemical research was conducted by L. Slocombe, J. S. Al-Khalili, and M. Sacchi of the University of Surrey, UK. ■ Instantly Collapsing A-T Tautomers vs. Surviving G-C Tautomers The research team analyzed the energy landscape as the hydrogen bond structure shifts from the standard (amino-keto) to the mutant (imino-enol) form, using Density Functional Theory (DFT) and a machine learning-based Nudged Elastic Band (ML-NEB) algorithm. The results revealed that in A-T base pairs, although a quantum tunneling effect transitioning toward the mutant A*-T* state was observed, the reverse-reaction barrier was virtually nonexistent. Consequently, the state could not be maintained and immediately collapsed back into its original standard form. The situation was different for G-C base pairs. Beyond the classical reaction where protons cross the barrier using only thermal energy at room temperature, it was confirmed that wave-like movement via quantum tunneling contributes decisively to the formation of mutant populations. The team mathematically proved that the G-C mutant (G*-C*), which showed a significantly high tunneling correction value, possesses a lifespan long enough to reach the human replisome, suggesting a high probability of solidifying into a permanent point mutation. ■ Genetic Stability Governed by Physical Laws This study is a landmark achievement, demonstrating that complex DNA mutations occurring during the most critical replication processes of life are not merely the result of random thermal fluctuations, but are substantially controlled and shaped by the microscopic physical laws of quantum tunneling dynamics. By providing objective data on how the wave-like nature of protons physically threatens the fidelity of genetic information replication, this study underscores the importance of a quantum biological approach in future research regarding DNA damage and mutation-related diseases. #DNAPointMutation #ProtonTransfer #QuantumTunneling #WatsonCrickTautomerism #BasePair #QuantumBiology #Biophysics #GeneticMutation #MolecularDynamics #KoreanSocietyOfQuantumBiology https://pubs.rsc.org/en/content/articlehtml/2021/cp/d0cp05781a

inquantio

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A study published on arXiv provides a structured narrative evidence map of the three complementary directions where quantum science and biology intersect: 'quantum in biology', 'quantum for biology', and 'biology for quantum'. It highlights hydrogen tunneling in enzymes and the radical-pair mechanism for magnetoreception as representative cases of quantum in biology. For quantum for biology, it analyzes how quantum sensing and imaging tools can improve biological inference. It also illuminates biology for quantum, which utilizes biomolecular self-assembly to enhance the performance of quantum devices, and presents a comprehensive benchmark to compare the current evidence and alternatives in each area. [Korean Society of Quantum Biology, Reporter Hak-Jin Kim] As we enter the 21st century, the convergence of quantum physics and the life sciences is moving beyond mere curiosity to establish itself as a substantial scientific paradigm. A recent paper published on the preprint repository arXiv, titled "Quantum in Biology, Quantum for Biology, and Biology for Quantum: Mapping the Evidence and the Road Ahead," clearly defines the three core areas where these two disciplines intersect. It provides a first-of-its-kind structured narrative evidence map that compiles the technological claims and experimental evidence of each field. A multinational collaborative research team led by Professor Travis J. A. Craddock of the University of Waterloo in Canada and Professor Francesco Petruccione of Stellenbosch University in South Africa published this extensive review. ■ Quantum in Nature and Quantum Tools Illuminating Biology The first pillar presented in this paper, 'Quantum in biology', deals with instances where quantum mechanics directly intervenes in the natural biological phenomena of living organisms. The most scientifically mature evidence highlighted includes the quantum tunneling of hydrogen in enzyme catalysis and the radical-pair spin chemistry mechanism that enables magnetoreception in birds. The second pillar, 'Quantum for biology', explores the application of cutting-edge quantum tools to the life sciences. The core question analyzed in this area is whether quantum technologies—such as quantum computing, quantum sensing, and quantum imaging—can provide significantly more precise biological inference and resolution beyond existing classical baselines, even under realistic biological constraints. ■ Living Organisms as the Foundation for Quantum Technology The final third pillar, 'Biology for quantum', is an innovative approach that utilizes biological systems in reverse to develop quantum technologies. The paper evaluates that the strongest claims in this field arise when the sophisticated structure or self-assembly capabilities unique to biomolecules are used to measurably improve the fabrication, integration, and robustness of artificial quantum devices. This monumental review paper holds great significance as it presents a macroscopic roadmap for the emerging interdisciplinary field of quantum biology. It establishes a powerful benchmark that allows for the at-a-glance comparison and verification of the current evidence levels and competitive alternative models in each specific subfield. #QuantumBiology #QuantumScience #LifeScience #InterdisciplinaryConvergence #EvidenceMap #QuantumSensing #QuantumLifeScience #QuantumTools #FutureScience #KoreanSocietyOfQuantumBiology https://arxiv.org/abs/2605.00205

inquantio

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Published in the journal Frontiers in Photonics, this study designs an aptamer-based platform to detect the clinically relevant dengue NS1 protein, completely reinterpreting it from the perspective of a quantum-biological interface. Moving beyond classical approaches, the research demonstrates that electrochemical capacitance systems can be treated based on the quantum characteristics of electron transport, confirming that biomolecular interactions directly modulate quantum parameters such as the density of states (DOS) of the interface. By integrating quantum-scale concepts into bioelectrochemical sensing, the analytical capability is dramatically improved, achieving high sensitivity and a broad linear range of 0.01 to 1,000 ng/mL even in complex biological matrices like commercial human serum. [Reporter Hak-Jin Kim, Korean Society of Quantum Biology] Electrochemical biosensors are promising tools for clinical diagnostics, but technical challenges have remained in maximizing stability and sensitivity for target proteins within extremely complex biological matrices like human serum. Recently, an open-access study published in the international journal Frontiers in Photonics titled "Quantum-biological interface in biosensor design: detecting proteins with electrochemical aptasensor" , presented a groundbreaking paradigm to overcome these challenges by directly introducing quantum mechanics—the physical laws of the microscopic world—into sensor design. A research team led by Leonardo Peres Chiaradia Costa and Professor Marcelo Mulato from the University of São Paulo, Brazil, spearheaded this disruptive study. ■ Beyond Classical Accumulation: Quantum Capacitance The researchers constructed a self-assembled monolayer (SAM) composed of single-stranded DNA aptamers and a spacer molecule, 6-mercapto-1-hexanol (MCH), on a gold (Au) electrode surface, and measured the binding of the dengue NS1 protein using non-Faradaic electrochemical capacitance spectroscopy (ECS). The most prominent innovation lies in the shift in how this system is interpreted. While existing models described the sensor using the classical capacitance of an electric double layer where charge accumulates geometrically, this study reinterpreted the interaction between the molecular layer and the electrode as an intrinsic electron transport characteristic known as quantum capacitance ($C_q$). This means that the interaction between the protein molecule and the aptamer goes beyond simple physicochemical docking; it directly modulates the density of electronic states (DOS) of the sensor interface and the discrete energy levels of individual molecules, thereby controlling the quantum tunneling and transfer mechanisms of electrons. ■ Overwhelming Analytical Performance Driven by Quantum Control Based on this quantum-biological interface model, the research team precisely optimized the ratio of aptamer to MCH molecules on the sensor surface to 1:50. The optimized platform successfully maintained a broad linear response ranging from 0.01 ng/mL to 1,000 ng/mL, not only in simple laboratory buffers (PBS) but also in commercial human serum entangled with complex ions and proteins. In particular, this aptasensor recorded an outstanding limit of detection (LoD) of 25.8 ng/mL in a human serum environment, clearly demonstrating how an understanding of quantum characteristics can serve as powerful leverage to break through existing biochemical limitations and design highly sensitive diagnostic devices. This study will serve as a crucial starting point for completely restructuring future protein detection and disease diagnosis technologies from the perspective of microscopic quantum dynamics rather than macroscopic chemical reactions. #QuantumBiology #Biosensor #Aptasensor #ProteinDetection #ElectrochemicalSensor #QuantumCapacitance #UltrasensitiveDiagnostics #Nanotechnology #Biophysics #KoreanSocietyOfQuantumBiology https://www.frontiersin.org/journals/photonics/articles/10.3389/fphot.2026.1714572/full

inquantio

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Published in the American Chemical Society journal ACS Omega, the study represents hemoglobin with the FePIm (iron–porphyrin–imidazole) model and uses spin-polarized density functional theory (DFT) to track, at the atomic level, how the spin state changes over the course of oxygen binding. It shows that O2 binding proceeds as a multi-step spin crossing running from the triplet, through the quintet, to the singlet. This spin crossing dramatically lowers the binding activation barrier from 0.82 eV to 0.02 eV, accelerating the reaction. It identifies the position of the iron (Fe) atom relative to the porphyrin plane as the key indicator governing oxygen affinity, and it raises the possibility of applying the system as an oxygen-reduction catalyst in fuel cells. [Quantum Biology Society] The oxygen molecule (O2) in the air we inhale is, in its ground state, a triplet carrying two unpaired electrons. The oxygen bound to hemoglobin—oxyhemoglobin—is, by contrast, a singlet with no unpaired electrons, a fact already established in 1936 when Linus Pauling observed the diamagnetism of oxyhemoglobin. Yet a fundamental principle of quantum mechanics poses a puzzle here. In a chemical reaction, a transition in which the total spin of the reactants and products differs is forbidden by the spin selection rule (spin-forbidden) and should therefore proceed only very slowly. The direct conversion of triplet oxygen into a singlet complex is exactly such a case. How, then, does our body carry out this forbidden reaction so quickly and reversibly with every breath? A 2018 study published in the ACS journal ACS Omega, "Spin-Dependent O2 Binding to Hemoglobin," answers this question through quantum-mechanical calculations. Daiichi Kurokawa, Jessiel Siaron Gueriba, and Wilson Agerico Diño of Osaka University in Japan simplified hemoglobin's active site to the FePIm model (iron Fe, porphyrin P, imidazole Im) and used spin-polarized DFT to trace, step by step, how the system's spin state changes along the oxygen-binding pathway. They showed that O2 binding is a spin-crossing process in which the system switches successively between several spin states—and that this very process is the key that unlocks the forbidden reaction. ■ As Oxygen Approaches, the Spin Shifts Step by Step The researchers narrowed the distance (R) between the iron atom and the oxygen molecule from 7.21 angstroms (Å) in the deoxy state down to 1.84 Å in the oxy state, calculating the system's total magnetization (spin multiplicity) at each point. In the deoxyhemoglobin state, with O2 not yet bound, the entire system (FePIm plus the separated O2 molecule) was a triplet (multiplicity 3), and the iron atom protruded 0.18 Å out of the porphyrin plane. As oxygen drew closer, the spin state did not change all at once but shifted in stages. At a point about 4 Å from the iron, the electrons in oxygen's antibonding (π*) orbital flipped their spin, raising the system to a septet (multiplicity 7)—a state nearly degenerate in energy with the triplet. Then, around R = 2.4 Å, it changed to a quintet (multiplicity 5), a shift accompanied by a lengthening of the bond between the two oxygen atoms within the O2 molecule. Finally, in the oxyhemoglobin state at R = 1.84 Å, oxygen formed a sigma (σ) bond between the iron's dz² orbital and its own π* orbital and stabilized as a singlet (multiplicity 1). In short, the system's total spin multiplicity traced a path from the triplet (degenerate with the septet), through the quintet, to the singlet. ■ The Key That Unlocks the Forbidden Reaction: Spin Crossing Why this multi-step spin transition matters becomes clear from the activation-barrier analysis. When the researchers fixed the system's spin state as a septet, the activation barrier for oxygen binding was a substantial 0.82 eV. But when the system was allowed to cross from the septet to the singlet—spin crossing—the binding barrier fell sharply to 0.02 eV. A single spin crossing lowered the barrier roughly fortyfold. The spin transition, in other words, is not an obstacle blocking oxygen binding but rather the passage that makes the forbidden reaction possible. Instead of directly connecting two states of different total spin (triplet oxygen and the singlet complex), the system detours through intermediate high-spin states, bypassing the spin selection rule and finding a low-energy path. For reference, a minimum-energy-path calculation with the atomic positions fully optimized (CINEB) yielded a binding barrier of 0.38 eV and an oxygen-release barrier of 0.92 eV. The researchers concluded that this spin crossing is the key factor governing the activation barrier. ■ The Switch for Oxygen Affinity: Iron Out of the Plane The researchers identified one more important indicator: how far the iron atom sits out of the porphyrin plane (d). In the oxygen-free deoxy state the iron protruded 0.18 Å out of the plane, but in the oxygen-bound oxy state it settled almost within the plane, at 0.01 Å. This agrees well with the crystal structure determined by experiment. Behind this movement lies an interaction between orbitals. In the deoxy state, the iron's dxy orbital interacts antibondingly with the nitrogen atoms of the porphyrin, pushing the iron out of the plane. But as oxygen binds and the electron in the dxy orbital flips its spin and moves to the dyz orbital, the dxy orbital empties and this antibonding interaction vanishes. As a result, the iron is drawn back into the porphyrin plane. The researchers concluded that, together with the iron–oxygen distance (R), this iron out-of-plane distance (d) is one of the two key reaction coordinates controlling oxygen affinity. ■ Significance and Outlook The greatest significance of this study lies in its concrete explanation, in the language of quantum mechanics, of breathing—the most basic activity of life. Life performs the oxygen-binding reaction, forbidden under the spin selection rule, quickly and reversibly by way of a spin crossing that switches successively through several spin states. In a sense, we harness a quantum-mechanical spin transition with every breath. The work also points to potential applications. The lengthening of the bond between the two oxygen atoms during an intermediate stage of binding suggests that the FePIm system could function as a catalyst that splits the oxygen molecule. The researchers noted the possibility of using the system as a cathode-electrode catalyst in polymer electrolyte fuel cells (PEFCs), where the oxygen reduction reaction takes place, while also pointing out that the challenge of overcoming the high activation barrier accompanying the reaction remains. By confronting head-on how life resolves the forbidden reaction of triplet oxygen binding to the heme iron, this study offers a solid starting point for further discussion from the standpoint of the quantum mechanics of respiration. #QuantumBiology #Hemoglobin #Respiration #OxygenBinding #SpinCrossing #QuantumMechanics #Porphyrin #DFT #FuelCellCatalyst #TripletOxygen https://pubs.acs.org/doi/10.1021/acsomega.8b00879

inquantio

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Published in the Elsevier journal Plant Stress, this review synthesizes the field by extending the scope of plant quantum biology beyond the traditional territory of photosynthesis and magnetosensing to enzyme catalysis and stress responses (light, oxidative, temperature, and biotic stress). It offers a broad survey of how four quantum phenomena—quantum coherence, entanglement, the radical pair mechanism, and quantum tunneling—may be involved in light-harvesting efficiency, magnetic-field sensing, and enzyme reaction rates. It projects that understanding and controlling these quantum effects could be harnessed for sustainable agriculture, such as developing stress-tolerant crops, while also pointing to the challenges posed by biological complexity and experimental limitations. [Quantum Biology Society] Plant biology has traditionally explained stress responses in the language of classical physics and biochemistry. But as evidence accumulates that quantum phenomena once thought to be the exclusive province of the microscopic world are in fact involved in the activities of life, quantum biology—which explores what role quantum mechanics (QM) plays in core functions such as photosynthesis, light perception, and stress responses—is emerging as a new field. Concepts like superposition, entanglement, tunneling, and coherence are its central tools. A review recently published in the Elsevier journal Plant Stress, "Plant quantum biology: The quantum dimension of plant responses to stress," surveys this field broadly. Massimo E. Maffei of the University of Turin in Italy extends the scope of plant quantum biology—until now discussed largely in terms of photosynthesis and magnetosensing—to enzyme catalysis, stress responses, and, further still, agricultural applications. At the same time, the author is careful to note that the field is still young and that established evidence and theoretical hypotheses remain intermingled, drawing a cautious map of the terrain. ■ Photosynthesis: Quantum Coherence That Captures Light The area where the firmest evidence has accumulated in plant quantum biology is photosynthesis. Photosynthetic organisms convert the photons they absorb into chemical energy with almost no loss, achieving a quantum efficiency approaching 100%. The energy of a light-harvesting complex that has absorbed light is delivered to the reaction center within extraordinarily short times—femtoseconds to picoseconds—and this efficiency and speed are difficult to explain by classical physics alone. The phenomenon drawing attention here is quantum coherence. The excitation energy (exciton) generated by photon absorption is not trapped on a single pigment molecule but exists as a wave-like superposition spread across several pigments, so that it can explore multiple routes to the reaction center simultaneously. In the FMO complex of green sulfur bacteria, long-lived coherence persisting even at physiological temperatures has been observed by two-dimensional electronic spectroscopy (2DES), and the protein scaffold is thought to play a role in shielding this coherence from external disturbance. Quantum entanglement between pigments has also been proposed as a way to coordinate exciton movement and aid energy transfer, but direct evidence in photosynthetic systems is not yet as solid as that for coherence. Further, active debate continues over whether this coherence plays a functional role in genuinely improving energy-transfer efficiency or is merely an incidental byproduct of the structure, and over whether it is electronic coherence or vibronic (vibrational–electronic) coherence. On this point, the author presents both supportive and critical views in balance. ■ Magnetosensing: Radical Pairs That Read the Earth's Magnetic Field Plants respond even to fields as weak as the Earth's geomagnetic field, with effects on growth, development, circadian rhythms, and even the direction in which roots grow. The leading framework for explaining this magnetosensitivity is the radical pair mechanism (RPM). The central stage is cryptochrome, a blue-light photoreceptor. When the flavin (FAD) cofactor inside cryptochrome absorbs light and becomes reduced, it forms a radical pair with a neighboring tryptophan (a FAD radical and a tryptophan radical); the rate at which the spins of this radical pair oscillate between singlet and triplet states governs the outcome of the reaction and triggers downstream signaling. How can a magnetic field far weaker than thermal energy influence such a process? The answer lies in the fact that the interconversion between singlet and triplet is governed by electron spin, a purely quantum-mechanical property. Because of this, even a field as weak as the geomagnetic field can, through spin dynamics, alter the ratio of a chemical reaction's products. The author also discusses iron–sulfur (Fe–S) clusters as a potential magnetic-sensor candidate, while noting that direct experimental evidence supporting this in plants is still lacking. ■ Enzyme Catalysis: Quantum Tunneling Through the Barrier The third stage is the enzyme. In classical mechanics, a particle needs sufficient kinetic energy to surmount an energy barrier, but quantum tunneling allows a particle to pass through the barrier to the other side. Especially in reactions involving light particles such as hydrogen atoms, protons, or electrons, tunneling can substantially increase reaction rates. The clearest fingerprint of tunneling is the isotope effect. Because heavier isotopes tunnel less efficiently, reactions involving tunneling exhibit very large isotope effects, and their temperature dependence deviates from classical Arrhenius behavior. Enzymes are thought to raise the probability of tunneling by precisely arranging substrate and catalytic residues at the active site to lower and narrow the reaction's energy barrier. The author introduces attempts to boost, from a quantum standpoint, the efficiency of agriculturally important enzymes such as the carbon-fixation enzyme RuBisCO and nitrogenase, while making clear that such discussions confined to plants remain largely at the computational and theoretical level. ■ Stress Responses: The New Horizon This Review Opens The most original contribution of this paper is the way it connects the quantum phenomena above to plant stress responses. The author examines, in turn, the possibility of quantum effects intervening in four categories: light, oxidative, temperature, and biotic stress. For light stress, the key mechanisms are non-photochemical quenching (NPQ) and the xanthophyll cycle, which dissipate excess light energy as heat to prevent photodamage; here it is proposed that quantum coherence could help rapidly steer excess energy toward quenching sites, reducing the production of reactive oxygen species. For oxidative stress, given that scavenging reactive oxygen species (ROS) is a radical reaction involving unpaired electrons, the possibility is raised that the spin correlations of radical pairs could regulate the pathways and signaling of scavenging reactions. For temperature stress, the author offers the conjecture that quantum effects may be involved in protein folding and in the action of heat shock proteins and chaperones; for biotic stress, the hypothesis that tunneling could speed up the reactions of enzymes synthesizing defensive volatile organic compounds (VOCs) or phytoalexins. The author repeatedly emphasizes, however, that many of these links to stress are not yet established facts but promising hypotheses. Indeed, in the paper's summary schematic, the hypothetical connections to quantum effects are marked separately. ■ The Road to Agriculture, and the Challenges That Remain The author's interest in this field lies in its application potential. Possibilities raised include using magnetic-field treatments to regulate seed germination and growth; designing light-harvesting systems and enzymes on quantum principles to raise crops' photosynthetic efficiency and stress tolerance; and developing biological magnetic sensors that exploit cryptochromes. The author foresees particularly large potential for plant quantum biology as a strategy for creating resilient crops amid climate change. Yet the walls to be scaled are equally clear: the complexity of biological systems, the fleeting and fragile nature of quantum phenomena, and the experimental difficulty of directly observing and verifying these effects inside living cells. The author concludes that the field's next tasks are research that directly observes and manipulates quantum effects within living plants, and the development of robust theoretical models capable of predicting them. In synthesizing the whole of plant quantum biology—beyond isolated experimental cases—from the perspective of stress adaptation and sustainable agriculture, this review reads as a milestone bridging basic science and the agricultural field. #QuantumBiology #PlantScience #Photosynthesis #QuantumCoherence #RadicalPairMechanism #QuantumTunneling #Cryptochrome #Magnetosensing #SustainableAgriculture #StressTolerantCrops https://www.sciencedirect.com/science/article/pii/S2667064X25001988