Kerstin Krüger, Yingqi Wang, Lingjun Zhu, Bin Jiang, Hua Guo, Alec M. Wodtke, Oliver Bünermann
Abstract Energy transferred in atom‐surface collisions typically depends strongly on projectile mass, an effect that can be experimentally detected by isotopic substitution. In this work, we present measurements of inelastic H and D atom scattering from a semiconducting Ge(111) c (2×8) surface exhibiting two scattering channels. The first channel shows the expected isotope effect and is quantitatively reproduced by electronically adiabatic molecular dynamics simulations. The second channel involves electronic excitations of the solid and, surprisingly, exhibits almost no isotope effect. We attribute these observations to scattering dynamics, wherein the likelihood of electronic excitation varies with the impact site engaged in the interaction. Key Points Previous work revealed that H atoms with sufficient translational energy can excite electrons over the band gap of a semiconductor in a surface collision. We studied the isotope effect of the energy transfer by H/D substitution and performed band structure calculations to elucidate the underlying excitation mechanism. Our results suggest a site‐specific mechanism that requires the atom to hit a specific surface site to excite an electron‐hole pair.
原子-表面碰撞中的能量转移通常强烈依赖于抛射物的质量，这种效应可以通过同位素取代实验检测到。在这项工作中，我们提出了从半导体Ge(111) c (2×8)表面显示两个散射通道的非弹性H和D原子散射的测量。第一个通道显示了预期的同位素效应，并通过电子绝热分子动力学模拟定量再现。第二个通道涉及固体的电子激发，令人惊讶的是，几乎没有表现出同位素效应。我们将这些观察结果归因于散射动力学，其中电子激发的可能性随参与相互作用的撞击地点而变化。先前的研究表明，具有足够平动能的氢原子可以在表面碰撞中激发半导体带隙上的电子。我们通过H/D取代研究了能量转移的同位素效应，并进行了能带结构计算来阐明潜在的激发机制。我们的研究结果表明了一种位点特异性机制，需要原子撞击特定的表面位点来激发电子空穴对。
{"title":"Isotope effect suggests site‐specific nonadiabaticity on Ge(111)<i>c</i>(2×8)","authors":"Kerstin Krüger, Yingqi Wang, Lingjun Zhu, Bin Jiang, Hua Guo, Alec M. Wodtke, Oliver Bünermann","doi":"10.1002/ntls.20230019","DOIUrl":"https://doi.org/10.1002/ntls.20230019","url":null,"abstract":"Abstract Energy transferred in atom‐surface collisions typically depends strongly on projectile mass, an effect that can be experimentally detected by isotopic substitution. In this work, we present measurements of inelastic H and D atom scattering from a semiconducting Ge(111) c (2×8) surface exhibiting two scattering channels. The first channel shows the expected isotope effect and is quantitatively reproduced by electronically adiabatic molecular dynamics simulations. The second channel involves electronic excitations of the solid and, surprisingly, exhibits almost no isotope effect. We attribute these observations to scattering dynamics, wherein the likelihood of electronic excitation varies with the impact site engaged in the interaction. Key Points Previous work revealed that H atoms with sufficient translational energy can excite electrons over the band gap of a semiconductor in a surface collision. We studied the isotope effect of the energy transfer by H/D substitution and performed band structure calculations to elucidate the underlying excitation mechanism. Our results suggest a site‐specific mechanism that requires the atom to hit a specific surface site to excite an electron‐hole pair.","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"64 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135036617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Evropi Toulkeridou, Carlos Enrique Gutierrez, Daniel Baum, Kenji Doya, Evan P. Economo
Abstract Three‐dimensional (3D) imaging, such as microcomputed tomography (micro‐CT), is increasingly being used by organismal biologists for precise and comprehensive anatomical characterization. However, the segmentation of anatomical structures remains a bottleneck in research, often requiring tedious manual work. Here, we propose a pipeline for the fully automated segmentation of anatomical structures in micro‐CT images utilizing state‐of‐the‐art deep learning methods, selecting the ant brain as a test case. We implemented the U‐Net architecture for two‐dimensional (2D) image segmentation for our convolutional neural network (CNN), combined with pixel‐island detection. For training and validation of the network, we assembled a data set of semimanually segmented brain images of 76 ant species. The trained network predicted the brain area in ant images fast and accurately; its performance tested on validation sets showed good agreement between the prediction and the target, scoring 80% Intersection over Union (IoU) and 90% Dice Coefficient (F1) accuracy. While manual segmentation usually takes many hours for each brain, the trained network takes only a few minutes. Furthermore, our network is generalizable for segmenting the whole neural system in full‐body scans, and works in tests on distantly related and morphologically divergent insects (e.g., fruit flies). The latter suggests that methods like the one presented here generally apply across diverse taxa. Our method makes the construction of segmented maps and the morphological quantification of different species more efficient and scalable to large data sets, a step toward a big data approach to organismal anatomy. Key points Development of a deep learning‐based pipeline for the fully automated segmentation of micro‐CT images of insects, using ant brains as a starting point. Creation of an open access data set of micro‐CT images of ant heads for training and testing. Generalizable computer vision methodology, extendable across diverse taxa and anatomical features.
{"title":"Automated segmentation of insect anatomy from micro‐CT images using deep learning","authors":"Evropi Toulkeridou, Carlos Enrique Gutierrez, Daniel Baum, Kenji Doya, Evan P. Economo","doi":"10.1002/ntls.20230010","DOIUrl":"https://doi.org/10.1002/ntls.20230010","url":null,"abstract":"Abstract Three‐dimensional (3D) imaging, such as microcomputed tomography (micro‐CT), is increasingly being used by organismal biologists for precise and comprehensive anatomical characterization. However, the segmentation of anatomical structures remains a bottleneck in research, often requiring tedious manual work. Here, we propose a pipeline for the fully automated segmentation of anatomical structures in micro‐CT images utilizing state‐of‐the‐art deep learning methods, selecting the ant brain as a test case. We implemented the U‐Net architecture for two‐dimensional (2D) image segmentation for our convolutional neural network (CNN), combined with pixel‐island detection. For training and validation of the network, we assembled a data set of semimanually segmented brain images of 76 ant species. The trained network predicted the brain area in ant images fast and accurately; its performance tested on validation sets showed good agreement between the prediction and the target, scoring 80% Intersection over Union (IoU) and 90% Dice Coefficient (F1) accuracy. While manual segmentation usually takes many hours for each brain, the trained network takes only a few minutes. Furthermore, our network is generalizable for segmenting the whole neural system in full‐body scans, and works in tests on distantly related and morphologically divergent insects (e.g., fruit flies). The latter suggests that methods like the one presented here generally apply across diverse taxa. Our method makes the construction of segmented maps and the morphological quantification of different species more efficient and scalable to large data sets, a step toward a big data approach to organismal anatomy. Key points Development of a deep learning‐based pipeline for the fully automated segmentation of micro‐CT images of insects, using ant brains as a starting point. Creation of an open access data set of micro‐CT images of ant heads for training and testing. Generalizable computer vision methodology, extendable across diverse taxa and anatomical features.","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135064126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The two‐dimensional paraxial equation of optics and the two‐dimensional time‐dependent Schrödinger equation, derived as approximations of the three‐dimensional Helmholtz equation and the three‐dimensional time‐independent Schrödinger equation, respectively, are identical. Here the free propagation in space and time of Hermite–Gauss wave packets (optics) or harmonic oscillator eigenfunctions (quantum mechanics) is examined in detail. The Gouy phase is shown to be a dynamic phase, appearing as the integral of the adiabatic eigenfrequency or eigenenergy. The wave packets propagate adiabatically in that at each space or time point they are solutions of the instantaneous harmonic problem. In both cases, it is shown that the form of the wave function is unchanged along the loci of the normals to wave fronts. This invariance along such trajectories is connected to the propagation of the invariant amplitude of the corresponding free wave number (optics) or momentum (quantum mechanics) wave packets. It is shown that the van Vleck classical density of trajectories function appears in the wave function amplitude over the complete trajectory. A transformation to the co‐moving frame along a trajectory gives a constant wave function multiplied by a simple energy or frequency phase factor. The Gouy phase becomes the proper time in this frame.This paper builds a bridge between quantum mechanics (QM) and classical optics in that the identity of the paraxial equation of optics and the Schrödinger equation of QM is shown, the Bohmian trajectories of QM are defined in optics, the Gouy phase of optics is defined in QM and given a new interpretation and The space and momentum wave functions are equivalent along a trajectory.
{"title":"The propagation of Hermite–Gauss wave packets in optics and quantum mechanics","authors":"J. Briggs","doi":"10.1002/ntls.20230012","DOIUrl":"https://doi.org/10.1002/ntls.20230012","url":null,"abstract":"The two‐dimensional paraxial equation of optics and the two‐dimensional time‐dependent Schrödinger equation, derived as approximations of the three‐dimensional Helmholtz equation and the three‐dimensional time‐independent Schrödinger equation, respectively, are identical. Here the free propagation in space and time of Hermite–Gauss wave packets (optics) or harmonic oscillator eigenfunctions (quantum mechanics) is examined in detail. The Gouy phase is shown to be a dynamic phase, appearing as the integral of the adiabatic eigenfrequency or eigenenergy. The wave packets propagate adiabatically in that at each space or time point they are solutions of the instantaneous harmonic problem. In both cases, it is shown that the form of the wave function is unchanged along the loci of the normals to wave fronts. This invariance along such trajectories is connected to the propagation of the invariant amplitude of the corresponding free wave number (optics) or momentum (quantum mechanics) wave packets. It is shown that the van Vleck classical density of trajectories function appears in the wave function amplitude over the complete trajectory. A transformation to the co‐moving frame along a trajectory gives a constant wave function multiplied by a simple energy or frequency phase factor. The Gouy phase becomes the proper time in this frame.This paper builds a bridge between quantum mechanics (QM) and classical optics in that \u0000\u0000the identity of the paraxial equation of optics and the Schrödinger equation of QM is shown,\u0000the Bohmian trajectories of QM are defined in optics,\u0000the Gouy phase of optics is defined in QM and given a new interpretation and\u0000The space and momentum wave functions are equivalent along a trajectory.\u0000","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86737001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Roth, M. Stiti, D. Frantz, A. Corber, E. Berrocal
SARS-CoV-2 and its ever-emerging variants, are spread from host-to-host via expelled respiratory aerosols and saliva droplets. Knowing the number of virions which are exhaled by a person requires precise measurements of the size, count, velocity and trajectory of the virus-laden particles that are ejected directly from the mouth. These measurements are achieved in 3D, at 15000 images/second, and are applied when speaking, yelling, and coughing. In this study 33 events have been analysed by post-processing ˜500000 images. Using these data, the flow rate of SARS-CoV-2 virions have been evaluated. At high concentrations, 10ˆ7 virions/mL, it is found that 136 to 231 virions are ejected during a single cough, where the virion flow rate peak is capable of reaching 32 virions within a millisecond. This peak can reach tens of virions/ms when yelling, but reduced to only a few virions/ms when speaking. At medium concentrations, ˜10ˆ5 virions/mL, those results are hundreds of times lower. The total number of virions that are ejected when yelling at 110db, instead of speaking at 85db, increases by two to three fold. From the measured data analysed in this article, the flow rate of other diseases such as influenza, tuberculosis or measles, can also be estimated. As these data are openly accessible, they can be used by modellers for the simulation of saliva droplet transport and evaporation, allowing to further advance our understanding of airborne pathogen transmission.
{"title":"Exhaled aerosols and saliva droplets measured in time and 3D space: Quantification of pathogens flow rate applied to SARS‐CoV‐2","authors":"A. Roth, M. Stiti, D. Frantz, A. Corber, E. Berrocal","doi":"10.1002/ntls.20230007","DOIUrl":"https://doi.org/10.1002/ntls.20230007","url":null,"abstract":"SARS-CoV-2 and its ever-emerging variants, are spread from host-to-host via expelled respiratory aerosols and saliva droplets. Knowing the number of virions which are exhaled by a person requires precise measurements of the size, count, velocity and trajectory of the virus-laden particles that are ejected directly from the mouth. These measurements are achieved in 3D, at 15000 images/second, and are applied when speaking, yelling, and coughing. In this study 33 events have been analysed by post-processing ˜500000 images. Using these data, the flow rate of SARS-CoV-2 virions have been evaluated. At high concentrations, 10ˆ7 virions/mL, it is found that 136 to 231 virions are ejected during a single cough, where the virion flow rate peak is capable of reaching 32 virions within a millisecond. This peak can reach tens of virions/ms when yelling, but reduced to only a few virions/ms when speaking. At medium concentrations, ˜10ˆ5 virions/mL, those results are hundreds of times lower. The total number of virions that are ejected when yelling at 110db, instead of speaking at 85db, increases by two to three fold. From the measured data analysed in this article, the flow rate of other diseases such as influenza, tuberculosis or measles, can also be estimated. As these data are openly accessible, they can be used by modellers for the simulation of saliva droplet transport and evaporation, allowing to further advance our understanding of airborne pathogen transmission.","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75398675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arnab Choudhury, Shreya Sinha, David Harlander, Jessalyn DeVine, A. Kandratsenka, P. Saalfrank, D. Schwarzer, A. Wodtke
When a chemical reaction occurs via tunnelling, a simple mass-dependence is expected, where substitution of atoms by heavier isotopes leads to a reduced reaction rate. However, as shown in a recent study of CO orientational isomerization at the NaCl(100) interface [Choudhury et al., Nature 612 , 691 (2022)], the lightest isotopologue need not exhibit the fastest tunnelling; for the CO/NaCl system, the non-monotonic mass-dependence is understood through a new picture of condensed phase tunnelling where the overall rate is dominated by a few pairs of reactant/product states. These state-pairs – termed quantum gateways – gain dynamical importance through accidentally-enhanced tunnelling probabilities, facilitated by a confluence of the energetic landscape underlying the reaction as well as the phonon bath of the surrounding medium. Here, we explore gateway tunnelling through measurements of the kinetic isotope effect (KIE) for CO isomerization in a monolayer buried by many layers of either CO or N 2 . With an N 2 overlayer, tunnelling rates are accelerated for all four isotopologues ( 12 C 16 O, 13 C 16 O, 12 C 18 O, and 13 C 18 O), but the degree of acceleration is isotopologue-specific and non-intuitively mass dependent. A one-dimensional tunnelling model involving an Eckart barrier cannot capture this behaviour. This reflects how a change to the potential energy surface moves states in and out of resonance, changing which tunnelling gateways can be accessed in the isomerization reaction.
{"title":"Manipulating tunnelling gateways in condensed phase isomerization","authors":"Arnab Choudhury, Shreya Sinha, David Harlander, Jessalyn DeVine, A. Kandratsenka, P. Saalfrank, D. Schwarzer, A. Wodtke","doi":"10.1002/ntls.20230006","DOIUrl":"https://doi.org/10.1002/ntls.20230006","url":null,"abstract":"When a chemical reaction occurs via tunnelling, a simple mass-dependence is expected, where substitution of atoms by heavier isotopes leads to a reduced reaction rate. However, as shown in a recent study of CO orientational isomerization at the NaCl(100) interface [Choudhury et al., Nature 612 , 691 (2022)], the lightest isotopologue need not exhibit the fastest tunnelling; for the CO/NaCl system, the non-monotonic mass-dependence is understood through a new picture of condensed phase tunnelling where the overall rate is dominated by a few pairs of reactant/product states. These state-pairs – termed quantum gateways – gain dynamical importance through accidentally-enhanced tunnelling probabilities, facilitated by a confluence of the energetic landscape underlying the reaction as well as the phonon bath of the surrounding medium. Here, we explore gateway tunnelling through measurements of the kinetic isotope effect (KIE) for CO isomerization in a monolayer buried by many layers of either CO or N 2 . With an N 2 overlayer, tunnelling rates are accelerated for all four isotopologues ( 12 C 16 O, 13 C 16 O, 12 C 18 O, and 13 C 18 O), but the degree of acceleration is isotopologue-specific and non-intuitively mass dependent. A one-dimensional tunnelling model involving an Eckart barrier cannot capture this behaviour. This reflects how a change to the potential energy surface moves states in and out of resonance, changing which tunnelling gateways can be accessed in the isomerization reaction.","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84302519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Fagerström, T. Liljefors, M. Sandgren, R. Isaksson, J. Ståhlberg, U. Berg
: Proteins are useful chiral selectors. In order to understand the recognition mechanism and the chiral discrimination, binding of the (R)- and (S)-enantiomers of a series of designed amino alcohol inhibitors based on propranolol to cellobiohydrolase Cel7A (Trichoderma reesei) has been studied more closely. X-ray crystal structures were determined of the protein complex with the (R)- and (S)-enantiomers of the strongest binding propranolol analog. The combination of the structural data, thermodynamic data from capillary electrophoresis and microcalorimetry experiments and computational modeling give a clearer insight into the origin of the enantioselectivity and its opposite thermodynamic signature. The new crystal structures were used in computational molecular flexible dockings of the propranolol analogues using the program Glide. The results indicated that several water molecules in the active site were essential for the docking of the (R)-enantiomers, but not for the (S)-enantiomers. The results are discussed in relation to the enantiomeric discrimination of the enzyme. Both dissociation constants (Kd-values) and thermodynamical data are included to show the effects of the structural modifications in the ligand on enthalpy and entropy in relation to the enantioselectivity.
{"title":"Chiral recognition mechanism of cellobiohydrolase Cel7A for ligands based on the β‐blocker propranolol: The effect of explicit water molecules on binding and selectivities","authors":"A. Fagerström, T. Liljefors, M. Sandgren, R. Isaksson, J. Ståhlberg, U. Berg","doi":"10.1002/ntls.20220050","DOIUrl":"https://doi.org/10.1002/ntls.20220050","url":null,"abstract":": Proteins are useful chiral selectors. In order to understand the recognition mechanism and the chiral discrimination, binding of the (R)- and (S)-enantiomers of a series of designed amino alcohol inhibitors based on propranolol to cellobiohydrolase Cel7A (Trichoderma reesei) has been studied more closely. X-ray crystal structures were determined of the protein complex with the (R)- and (S)-enantiomers of the strongest binding propranolol analog. The combination of the structural data, thermodynamic data from capillary electrophoresis and microcalorimetry experiments and computational modeling give a clearer insight into the origin of the enantioselectivity and its opposite thermodynamic signature. The new crystal structures were used in computational molecular flexible dockings of the propranolol analogues using the program Glide. The results indicated that several water molecules in the active site were essential for the docking of the (R)-enantiomers, but not for the (S)-enantiomers. The results are discussed in relation to the enantiomeric discrimination of the enzyme. Both dissociation constants (Kd-values) and thermodynamical data are included to show the effects of the structural modifications in the ligand on enthalpy and entropy in relation to the enantioselectivity.","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"185 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85785928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Analyzing phase transitions using the inherent geometrical attributes of a system has garnered enormous interest over the past few decades. The usual candidate often used for investigation is graphene—the most celebrated material among the family of tri‐coordinated graphed lattices. We show in this report that other inhabitants of the family demonstrate equally admirable structural and functional properties that at its core are controlled by their topology. Two interesting members of the family are cyclooctatrene (COT) and COT‐based polymer: poly‐bi‐[8]‐annulenylene, both in one and two dimensions that have been investigated by polymer chemists over a period of 50 years for its possible application in batteries exploiting its conducting properties. A single COT unit is demonstrated herein to exhibit topological solitons at sites of a broken bond similar to an open one‐dimensional Su–Schrieffer–Heeger (SSH) chain. We observe that poly‐bi‐[8]‐annulenylene in one dimension mimics two coupled SSH chains in the weak coupling limit, thereby showing the presence of topological edge modes. In the strong coupling limit, we investigate the different parameter values of our system for which we observe zero‐energy modes. Further, the application of an external magnetic field and its effects on the band flattening of the energy bands has also been studied. In two dimensions, poly‐bi‐[8]‐annulenylene forms a square‐octagon lattice which upon breaking time‐reversal symmetry goes into a topological phase forming noise‐resilient edge modes. We hope our analysis would pave the way for synthesizing such topological materials and exploiting their properties for promising applications in optoelectronics, photovoltaics, and renewable energy sources. We show in this paper tri‐coordinated lattice systems: cylooctatrene (COT) and COT‐based polymer: poly‐bi‐[8]‐annulenylene exhibit exotic topological properties. Flat bands are generated upon application of tailored magnetic flux for poly‐bi‐[8]‐annulenylene in one dimension. Insights from this paper open the possibility of using these polymers as an experimental ground to observe many flat‐band and topology‐related phenomena.
{"title":"Foray into the topology of poly‐bi‐[8]‐annulenylene","authors":"V. Muruganandam, M. Sajjan, S. Kais","doi":"10.1002/ntls.20230015","DOIUrl":"https://doi.org/10.1002/ntls.20230015","url":null,"abstract":"Analyzing phase transitions using the inherent geometrical attributes of a system has garnered enormous interest over the past few decades. The usual candidate often used for investigation is graphene—the most celebrated material among the family of tri‐coordinated graphed lattices. We show in this report that other inhabitants of the family demonstrate equally admirable structural and functional properties that at its core are controlled by their topology. Two interesting members of the family are cyclooctatrene (COT) and COT‐based polymer: poly‐bi‐[8]‐annulenylene, both in one and two dimensions that have been investigated by polymer chemists over a period of 50 years for its possible application in batteries exploiting its conducting properties. A single COT unit is demonstrated herein to exhibit topological solitons at sites of a broken bond similar to an open one‐dimensional Su–Schrieffer–Heeger (SSH) chain. We observe that poly‐bi‐[8]‐annulenylene in one dimension mimics two coupled SSH chains in the weak coupling limit, thereby showing the presence of topological edge modes. In the strong coupling limit, we investigate the different parameter values of our system for which we observe zero‐energy modes. Further, the application of an external magnetic field and its effects on the band flattening of the energy bands has also been studied. In two dimensions, poly‐bi‐[8]‐annulenylene forms a square‐octagon lattice which upon breaking time‐reversal symmetry goes into a topological phase forming noise‐resilient edge modes. We hope our analysis would pave the way for synthesizing such topological materials and exploiting their properties for promising applications in optoelectronics, photovoltaics, and renewable energy sources.\u0000We show in this paper tri‐coordinated lattice systems: cylooctatrene (COT) and COT‐based polymer: poly‐bi‐[8]‐annulenylene exhibit exotic topological properties.\u0000Flat bands are generated upon application of tailored magnetic flux for poly‐bi‐[8]‐annulenylene in one dimension.\u0000Insights from this paper open the possibility of using these polymers as an experimental ground to observe many flat‐band and topology‐related phenomena.\u0000","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87865690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohsen Ranjbar, Jeremy J. Yang, Praveen Kumar, Daniel R. Byrd, Elaine L. Bearer, Tudor I. Oprea
Identifying novel autophagy (ATG) associated genes in humans remains an important task for understanding this fundamental physiological process. Machine learning (ML) can highlight potentially “missing pieces” linking core ATG genes with understudied, “dark” genes by mining functional genomic data. Here, a set of 103 (out of 288 genes from the Autophagy Database) was used as training set, based on ATG-associated terms annotated from 3 secondary sources: GO (gene ontology), Kyoto Encyclopedia of Genes and Genomes pathway, and UniProt keywords, as additional confirmation of their importance in ATG. As negative labels, an OMIM list of genes associated with monogenic diseases was used (after excluding the 288 ATG-associated genes). Data related to these genes from 17 different sources were compiled and used to derive a trained MetaPath/XGBoost (MPxgb) ML model for distinguishing ATG and non-ATG genes (10-fold cross-validated, 100-times randomized models, median area under the curve = 0.994 ± 0.008). Sixteen ATG-relevant variables explained 64% of the total model gain. Overall, 23% of the top 251 predicted genes are annotated in the Autophagy Database, whereas 193 genes (77%) are not. In 2019, we suggested that some of these 193 genes may represent “ATG dark genes.” A literature search in 2022 for those top 20 predicted ATG dark genes found that 9 were subsequently reported as ATG genes during the intervening 3.5 years. A post-factum evaluation of data leakage (the presence of ATG-associated terms in the top 40 ML features) confirms that 7 out of these 9 genes and 2 out of 3 other recently validated predictions from the bottom 20 are novel. Those genes with the largest number of ATG features would be most likely to yield valuable experimental insights. Modern high-throughput testing would be capable of spanning the full 193 ATG genes list reported here. Our analysis demonstrates that ML can guide genomics research to gain a more complete functional and pathway annotation of complex processes. Key points – A knowledge-graph based machine learning model was designed for predicting unknown autophagy genes via mining functional genomic data. – Literature search validated predicted genes. – Our machine learning models could be generalized and applied to other genomic libraries to uncover dark genes for various functions.
{"title":"Autophagy dark genes: Can we find them with machine learning?","authors":"Mohsen Ranjbar, Jeremy J. Yang, Praveen Kumar, Daniel R. Byrd, Elaine L. Bearer, Tudor I. Oprea","doi":"10.1002/ntls.20220067","DOIUrl":"https://doi.org/10.1002/ntls.20220067","url":null,"abstract":"Identifying novel autophagy (ATG) associated genes in humans remains an important task for understanding this fundamental physiological process. Machine learning (ML) can highlight potentially “missing pieces” linking core ATG genes with understudied, “dark” genes by mining functional genomic data. Here, a set of 103 (out of 288 genes from the Autophagy Database) was used as training set, based on ATG-associated terms annotated from 3 secondary sources: GO (gene ontology), Kyoto Encyclopedia of Genes and Genomes pathway, and UniProt keywords, as additional confirmation of their importance in ATG. As negative labels, an OMIM list of genes associated with monogenic diseases was used (after excluding the 288 ATG-associated genes). Data related to these genes from 17 different sources were compiled and used to derive a trained MetaPath/XGBoost (MPxgb) ML model for distinguishing ATG and non-ATG genes (10-fold cross-validated, 100-times randomized models, median area under the curve = 0.994 ± 0.008). Sixteen ATG-relevant variables explained 64% of the total model gain. Overall, 23% of the top 251 predicted genes are annotated in the Autophagy Database, whereas 193 genes (77%) are not. In 2019, we suggested that some of these 193 genes may represent “ATG dark genes.” A literature search in 2022 for those top 20 predicted ATG dark genes found that 9 were subsequently reported as ATG genes during the intervening 3.5 years. A post-factum evaluation of data leakage (the presence of ATG-associated terms in the top 40 ML features) confirms that 7 out of these 9 genes and 2 out of 3 other recently validated predictions from the bottom 20 are novel. Those genes with the largest number of ATG features would be most likely to yield valuable experimental insights. Modern high-throughput testing would be capable of spanning the full 193 ATG genes list reported here. Our analysis demonstrates that ML can guide genomics research to gain a more complete functional and pathway annotation of complex processes. Key points – A knowledge-graph based machine learning model was designed for predicting unknown autophagy genes via mining functional genomic data. – Literature search validated predicted genes. – Our machine learning models could be generalized and applied to other genomic libraries to uncover dark genes for various functions.","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136251579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"About Roy Glauber","authors":"B. Friedrich, D. Kleppner, D. Herschbach","doi":"10.1002/ntls.20220064","DOIUrl":"https://doi.org/10.1002/ntls.20220064","url":null,"abstract":"","PeriodicalId":74244,"journal":{"name":"Natural sciences (Weinheim, Germany)","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79862676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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