The energy landscape dictates pathways and outcomes in supramolecular selfassembly, yet harnessing it from the nano to the macro scales remains a major challenge. Here, we demonstrate liquid liquid phase separation (LLPS) as a powerful tool to navigate and engineer the energy landscapes of coassembly systems comprising disordered proteins and peptides. We quantitatively map the energy barriers and transition states governing structural transitions, enabling predictive on off control of assembly and hierarchical order from nano to macro scales. By integrating supramolecular biofabrication, we achieve spatially organized architectures with life like non equilibrium behaviour. Crucially, assembly stability and scalable selfsorting are shown to depend on accessing minimum energy states, regardless of whether the co assembled structures are disordered or ordered. This work establishes energy landscape mediation via LLPS as a general framework for designing lifelike, hierarchically structured materials.
The rapid adoption of generative artificial intelligence (GenAI) in the biosciences is transforming biotechnology, medicine, and synthetic biology. Yet this advancement is intrinsically linked to new vulnerabilities, as GenAI lowers the barrier to misuse and introduces novel biosecurity threats, such as generating synthetic viral proteins or toxins. These dual-use risks are often overlooked, as existing safety guardrails remain fragile and can be circumvented through deceptive prompts or jailbreak techniques. In this Perspective, we first outline the current state of GenAI in the biosciences and emerging threat vectors ranging from jailbreak attacks and privacy risks to the dual-use challenges posed by autonomous AI agents. We then examine urgent gaps in regulation and oversight, drawing on insights from 130 expert interviews across academia, government, industry, and policy. A large majority ($\approx 76$\%) expressed concern over AI misuse in biology, and 74\% called for the development of new governance frameworks. Finally, we explore technical pathways to mitigation, advocating a multi-layered approach to GenAI safety. These defenses include rigorous data filtering, alignment w
Though it goes without saying that linear algebra is fundamental to mathematical biology, polynomial algebra is less visible. In this article, we will give a brief tour of four diverse biological problems where multivariate polynomials play a central role -- a subfield that is sometimes called "algebraic biology." Namely, these topics include biochemical reaction networks, Boolean models of gene regulatory networks, algebraic statistics and genomics, and place fields in neuroscience. After that, we will summarize the history of discrete and algebraic structures in mathematical biology, from their early appearances in the late 1960s to the current day. Finally, we will discuss the role of algebraic biology in the modern classroom and curriculum, including resources in the literature and relevant software. Our goal is to make this article widely accessible, reaching the mathematical biologist who knows no algebra, the algebraist who knows no biology, and especially the interested student who is curious about the synergy between these two seemingly unrelated fields.
Surface acoustic waves (SAWs) convey energy at subwavelength depths along surfaces. Using interdigital transducers (IDTs) and opto-acousto-optic transducers (OAOTs), researchers have harnessed coherent SAWs with nanosecond periods and micrometer localization depth for various applications. However, the utilization of cutting-edge OAOTs produced through surface nanopatterning techniques has set the upper limit for coherent SAW frequencies below 100 GHz, constrained by factors such as the quality and pitch of the surface nanopattern, not to mention the electronic bandwidth limitations of the IDTs. In this context, unconventional optically-controlled nano-transducers based on cleaved superlattices (SLs) are here presented as an alternative solution. To demonstrate their viability, we conducted proof-of-concept experiments using ultrafast lasers in a pump-probe configuration on SLs made of alternating AlxGa1-xAs and AlyGa1-yAs layers with approximately 70 nm periodicity and cleaved along their growth direction to produce a periodic nanostructured surface. The acoustic vibrations, generated and detected by laser beams incident on the cleaved surface, span a range from 40 GHz to 70 GHz,
Systems Biology has emerged in the last years as a new holistic approach based on the global understanding of cells instead of only being focused on their individual parts (genes or proteins), to better understand the complexity of human cells. Since the Systems Biology still does not provide the most accurate answers to our questions due to the complexity of cells and the limited quality of available information to perform a good gene/protein map analysis, we have created simpler models to ensure easier analysis of the map that represents the human cell. Therefore, a virtual organism has been designed according to the main physiological rules for humans in order to replicate the human organism and its vital functions. This toy model was constructed by defining the topology of its genes/proteins and the biological functions associated to it. There are several examples of these toy models that emulate natural processes to perform analysis of the virtual life in order to design the best strategy to understand real life. The strategy applied in this study combines topological and functional analysis integrating the knowledge about the relative position of a node among the others in th
AlphaFold 3 represents a transformative advancement in computational biology, enhancing protein structure prediction through novel multi-scale transformer architectures, biologically informed cross-attention mechanisms, and geometry-aware optimization strategies. These innovations dramatically improve predictive accuracy and generalization across diverse protein families, surpassing previous methods. Crucially, AlphaFold 3 embodies a paradigm shift toward differentiable simulation, bridging traditional static structural modeling with dynamic molecular simulations. By reframing protein folding predictions as a differentiable process, AlphaFold 3 serves as a foundational framework for integrating deep learning with physics-based molecular
Photonic structures in diamond are key to most of its application in quantum technology. Here, we demonstrate tapered nano-waveguides structured directly onto the diamond substrate hosting shallow-implanted nitrogen vacancy (NV) centers. By optimization based on simulations and precise experimental control of the geometry of these pillar-shaped nano-waveguides, we achieve a net photon flux up to ~ $1.7 \cdot 10^6 /s$. This presents the brightest monolithic bulk diamond structure based on single NV centers so far. We observe no impact on excited state lifetime and electronic spin dephasing time ($T_2$) due to the nanofabrication process. Possessing such high brightness with low background in addition to preserved spin quality, this geometry can improve the current nanomagnetometry sensitivity ~ 5 times. In addition, it facilitates a wide range of diamond defects-based magnetometry applications. As a demonstration, we measure the temperature dependency of $T_1$ relaxation time of a single shallow NV center electronic spin. We observe the two-phonon Raman process to be negligible in comparison to the dominant two-phonon Orbach process.
A public preprint server such as arXiv allows authors to publish their manuscripts before submitting them to journals for peer review. It offers the chance to establish priority by making the results available upon completion. This article presents the arXiv section Quantitative Biology and investigates the advantages of preprint publications in terms of reception, which can be measured by means of citations. This paper focuses on the publication and citation delay, citation counts and the authors publishing their e-prints on arXiv. Moreover, the paper discusses the benefit for scientists as well as publishers. The results that are based on 12 selected journals show that submitting preprints to arXiv has become more common in the past few years, but the number of papers submitted to Quantitative Biology is still small and represents only a fraction of the total research output in biology. An immense advantage of arXiv is to overcome the long publication delay resulting from peer review. Although preprints are visible prior to the officially published articles, a significant citation advantage was only found for the Journal of Theoretical Biology.
"Back-of-the-envelope" or "rule-of-thumb" calculations involving rough estimates of quantities play a central scientific role in developing intuition about the structure and behaviour of physical systems, for example in so-called `Fermi problems' in the physical sciences. Such calculations can be used to powerfully and quantitatively reason about biological systems, particularly at the interface between physics and biology. However, substantial uncertainties are often associated with values in cell biology, and performing calculations without taking this uncertainty into account may limit the extent to which results can be interpreted for a given problem. We present a means to facilitate such calculations where uncertainties are explicitly tracked through the line of reasoning, and introduce a `probabilistic calculator' called Caladis, a web tool freely available at www.caladis.org, designed to perform this tracking. This approach allows users to perform more statistically robust calculations in cell biology despite having uncertain values, and to identify which quantities need to be measured more precisely in order to make confident statements, facilitating efficient experimental
Symmetries play a major role in physics, in particular since the work by E. Noether and H. Weyl in the first half of last century. Herein, we briefly review their role by recalling how symmetry changes allow to conceptually move from classical to relativistic and quantum physics. We then introduce our ongoing theoretical analysis in biology and show that symmetries play a radically different role in this discipline, when compared to those in current physics. By this comparison, we stress that symmetries must be understood in relation to conservation and stability properties, as represented in the theories. We posit that the dynamics of biological organisms, in their various levels of organization, are not "just" processes, but permanent (extended, in our terminology) critical transitions and, thus, symmetry changes. Within the limits of a relative structural stability (or interval of viability), variability is at the core of these transitions.
We developed a theory showing that under appropriate normalizations and rescalings, temperature response curves show a remarkably regular behavior and follow a general, universal law. The impressive universality of temperature response curves remained hidden due to various curve-fitting models not well-grounded in first principles. In addition, this framework has the potential to explain the origin of different scaling relationships in thermal performance in biology, from molecules to ecosystems. Here, we summarize the background, principles and assumptions, predictions, implications, and possible extensions of this theory.
This technical monograph provides a comprehensive overview of the field of quantum biology. It approaches quantum biology from a physical perspective with core quantum mechanical concepts presented foremost to provide a theoretical foundation for the field. An extensive body of research is covered to clarify the significance of quantum biology as a scientific field, outlining the field's long-standing importance in the historical development of quantum theory. This lays the essential groundwork to enable further advances in nanomedicine and biotechnology. Written for academics, biological science researchers, physicists, biochemists, medical technologists, and students of quantum mechanics, this text brings clarity to fundamental advances being made in the emerging science of quantum biology.
We have analyzed 44.3M single muons collected by MACRO from 1991 through 2000 in 2,145 live days of operation. We have searched for the solar diurnal, apparent sidereal, and pseudo-sidereal modulation of the underground muon rate by computing hourly deviations of the muon rate from 6 month averages. We find evidence for statistically significant modulations with the solar diurnal and the sidereal periods. The amplitudes of these modulations are <0.1%, and are at the limit of the detector statistics. The pseudo-sidereal modulation is not statistically significant. The solar diurnal modulation is due to the daily atmospheric temperature variations at 20 km, the altitude of primary cosmic ray interactions with the atmosphere; MACRO is the deepest experiment to report this result. The sidereal modulation is in addition to the expected Compton-Getting modulation due to solar system motion relative to the Local Standard of Rest; it represents motion of the solar system with respect to the galactic cosmic rays toward the Perseus spiral arm.
The Virtual Institute for Integrative Biology (VIIB) is a Latin American initiative for achieving global collaborative e-Science in the areas of bioinformatics, genome biology, systems biology, metagenomics, medical applications and nanobiotechnolgy. The scientific agenda of VIIB includes: construction of databases for comparative genomics, the AlterORF database for alternate open reading frames discovery in genomes, bioinformatics services and protein simulations for biotechnological and medical applications. Human resource development has been promoted through co-sponsored students and shared teaching and seminars via video conferencing. E-Science challenges include: interoperability and connectivity concerns, high performance computing limitations, and the development of customized computational frameworks and flexible workflows to efficiently exploit shared resources without causing impediments to the user. Outreach programs include training workshops and classes for high school teachers and students and the new Adopt-a-Gene initiative. The VIIB has proved an effective way for small teams to transcend the critical mass problem, to overcome geographic limitations, to harness the
A measurement of the lateral distribution of Cherenkov light in Extensive Air Showers (EAS) at E0 = 10-100 TeV and a study of the compatibility of the photon number spectra with the expectations from the direct measurements of p and He spectra and the Corsika-QGSJET propagation code in the atmosphere have been performed at the National Gran Sasso Laboratories by the EAS-TOP and MACRO arrays. The telescope array of EAS-TOP has been used as the Cherenkov light detector. The muon tracking system of MACRO in the deep underground Gran Sasso Laboratories (Emuon> 1.3 TeV) served as the EAS detector, including core localization and arrival direction.
Muon energy measurement represents an important issue for any experiment addressing neutrino induced upgoing muon studies. Since the neutrino oscillation probability depends on the neutrino energy, a measurement of the muon energy adds an important piece of information concerning the neutrino system. We show in this paper how the MACRO limited streamer tube system can be operated in drift mode by using the TDC's included in the QTPs, an electronics designed for magnetic monopole search. An improvement of the space resolution is obtained, through an analysis of the multiple scattering of muon tracks as they pass through our detector. This information can be used further to obtain an estimate of the energy of muons crossing the detector. Here we present the results of two dedicated tests, performed at CERN PS-T9 and SPS-X7 beam lines, to provide a full check of the electronics and to exploit the feasibility of such a multiple scattering analysis. We show that by using a neural network approach, we are able to reconstruct the muon energy for $E_μ<$40 GeV. The test beam data provide an absolute energy calibration, which allows us to apply this method to MACRO data.
Cell is the structural and functional unit of life. This Resource Letter serves as a guide to the literature on nano-machines which drive not only intracellular movements, but also motility of the cell. These machines are usually proteins or macromolecular assemblies which require appropriate fuel for their operations. Although, traditionally, these machines were subjects of investigation in biology and biochemistry, increasing use of the concepts and techniques of physics in recent years have contributed to the quantitative understanding of the fundamental principles underlying their operational mechanisms. The possibility of exploiting these principles for the design and control of artificial nano-machines has opened up a new frontier in the bottom-up approach to nano-technology.
This article frames the relation between biology and physics by characterizing the former as a subdiscipline rather than a special case of the latter. To do this, we posit biological physics as the science of living matter in contrast to classic biophysics, the study of organismal properties by physical techniques. At the scale of the individual cell, living matter is nonunitary, i.e., not composed of aggregated subunits, and has features (e.g., intracellular organizational arrangements and biomolecular condensates) that are unlike any materials of the nonliving world. In transiently or constitutively multicellular forms (social microorganisms, animals, plants), living matter sustains physical processes that are generic (shared with nonliving matter, e.g., subunit communication by molecular diffusion in cellular slime molds), biogeneric (analogous to nonliving matter but realized through cellular activities, e.g., subunit demixing in animal embryos) or nongeneric (pertaining to sui generis materials, e.g., budding of active solids in plants). This "forms of matter" perspective is philosophically situated in the dialectical materialism of Engels and Hessen and the multilevel physica
We classify research fields in biology into those on flows of materials, energy, and information. As a representative energy transducing machinery in biology, our research target, V1-ATPase from a bacterium Enterococcus hirae, a typical molecular rotary motor is introduced. Structures of several intermediates of the rotary motor are described and the molecular mechanism of the motor converting chemical energy into mechanical energy is discussed. Comments and considerations on the information flow in biology, especially on the thermodynamic entropy in quantum physical and biological systems, are added in a separate section containing the biologist friendly presentation of this complicated question.
We present the measurement of two event samples induced by atmospheric $ν_μ$ of average energy $ \bar {E}_ν\sim 4 GeV$. In the first sample, the neutrino interacts inside the MACRO detector producing an upward-going muon leaving the apparatus. The ratio of the number of observed to expected events is $ 0.57 \pm0.05_{stat} \pm0.06_{syst} \pm0.14_{theor}$ with an angular distribution similar to that expected from the Bartol atmospheric neutrino flux. The second is a mixed sample of internally produced downward-going muons and externally produced upward-going muons stopping inside the detector. These two subsamples are selected by topological criteria; the lack of timing information makes it impossible to distinguish stopping from downgoing muons. The ratio of the number of observed to expected events is $0.71 \pm 0.05_{stat} \pm0.07_{syst} \pm0.18_{theor}$ . Using the ratio of the two subsamples (for which most theoretical uncertainties cancel) we can test the pathlength dependence of the oscillation hypothesis. The probability of agreement with the no-oscillation hypothesis is 5% . The deviations of our observations from the expectations has a preferred interpretation in terms of $ν