Pub Date : 2024-07-09DOI: 10.1093/pnasnexus/pgae270
Ana P Millán, Hanlin Sun, Joaquín J Torres, Ginestra Bianconi
Triadic interactions are higher-order interactions which occur when a set of nodes affects the interaction between two other nodes. Examples of triadic interactions are present in the brain when glia modulate the synaptic signals among neuron pairs or when interneuron axo-axonic synapses enable presynaptic inhibition and facilitation, and in ecosystems when one or more species can affect the interaction among two other species. On random graphs, triadic percolation has been recently shown to turn percolation into a fully-fledged dynamical process in which the size of the giant component undergoes a route to chaos. However, in many real cases, triadic interactions are local and occur on spatially embedded networks. Here we show that triadic interactions in spatial networks induce a very complex spatio-temporal modulation of the giant component which gives rise to triadic percolation patterns with significantly different topology. We classify the observed patterns (stripes, octopus and small clusters) with topological data analysis and we assess their information content (entropy and complexity). Moreover we illustrate the multistability of the dynamics of the triadic percolation patterns and we provide a comprehensive phase diagram of the model. These results open new perspectives in percolation as they demonstrate that in presence of spatial triadic interactions, the giant component can acquire a time-varying topology. Hence, this work provides a theoretical framework that can be applied to model realistic scenarios in which the giant component is time-dependent as in neuroscience.
{"title":"Triadic percolation induces dynamical topological patterns in higher-order networks","authors":"Ana P Millán, Hanlin Sun, Joaquín J Torres, Ginestra Bianconi","doi":"10.1093/pnasnexus/pgae270","DOIUrl":"https://doi.org/10.1093/pnasnexus/pgae270","url":null,"abstract":"Triadic interactions are higher-order interactions which occur when a set of nodes affects the interaction between two other nodes. Examples of triadic interactions are present in the brain when glia modulate the synaptic signals among neuron pairs or when interneuron axo-axonic synapses enable presynaptic inhibition and facilitation, and in ecosystems when one or more species can affect the interaction among two other species. On random graphs, triadic percolation has been recently shown to turn percolation into a fully-fledged dynamical process in which the size of the giant component undergoes a route to chaos. However, in many real cases, triadic interactions are local and occur on spatially embedded networks. Here we show that triadic interactions in spatial networks induce a very complex spatio-temporal modulation of the giant component which gives rise to triadic percolation patterns with significantly different topology. We classify the observed patterns (stripes, octopus and small clusters) with topological data analysis and we assess their information content (entropy and complexity). Moreover we illustrate the multistability of the dynamics of the triadic percolation patterns and we provide a comprehensive phase diagram of the model. These results open new perspectives in percolation as they demonstrate that in presence of spatial triadic interactions, the giant component can acquire a time-varying topology. Hence, this work provides a theoretical framework that can be applied to model realistic scenarios in which the giant component is time-dependent as in neuroscience.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572401","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}
Pub Date : 2024-07-08DOI: 10.1093/pnasnexus/pgae263
Federico Zimmerman, Lucía Pedraza, Joaquín Navajas, Pablo Balenzuela
Political polarization has become a growing concern in democratic societies, as it drives tribal alignments and erodes civic deliberation among citizens. Given its prevalence across different countries, previous research has sought to understand under which conditions people tend to endorse extreme opinions. However, in polarized contexts, citizens not only adopt more extreme views but also become correlated across issues that are, a priori, seemingly unrelated. This phenomenon, known as “ideological sorting”, has been receiving greater attention in recent years but the micro-level mechanisms underlying its emergence remain poorly understood. Here, we study the conditions under which a social dynamic system is expected to become ideologically sorted as a function of the mechanisms of interaction between its individuals. To this end, we developed and analyzed a multidimensional agent-based model that incorporates two mechanisms: homophily (where people tend to interact with those holding similar opinions) and pairwise-coherence favoritism (where people tend to interact with ingroups holding politically coherent opinions). We numerically integrated the model’s master equations that perfectly describe the system’s dynamics and found that ideological sorting only emerges in models that include pairwise-coherence favoritism. We then compared the model’s outcomes with empirical data from 24,035 opinions across 67 topics and found that pairwise-coherence favoritism is significantly present in datasets that measure political attitudes but absent across topics not considered related to politics. Overall, this work combines theoretical approaches from system dynamics with model-based analyses of empirical data to uncover a potential mechanism underlying the pervasiveness of ideological sorting.
{"title":"Attraction by pairwise coherence explains the emergence of ideological sorting","authors":"Federico Zimmerman, Lucía Pedraza, Joaquín Navajas, Pablo Balenzuela","doi":"10.1093/pnasnexus/pgae263","DOIUrl":"https://doi.org/10.1093/pnasnexus/pgae263","url":null,"abstract":"Political polarization has become a growing concern in democratic societies, as it drives tribal alignments and erodes civic deliberation among citizens. Given its prevalence across different countries, previous research has sought to understand under which conditions people tend to endorse extreme opinions. However, in polarized contexts, citizens not only adopt more extreme views but also become correlated across issues that are, a priori, seemingly unrelated. This phenomenon, known as “ideological sorting”, has been receiving greater attention in recent years but the micro-level mechanisms underlying its emergence remain poorly understood. Here, we study the conditions under which a social dynamic system is expected to become ideologically sorted as a function of the mechanisms of interaction between its individuals. To this end, we developed and analyzed a multidimensional agent-based model that incorporates two mechanisms: homophily (where people tend to interact with those holding similar opinions) and pairwise-coherence favoritism (where people tend to interact with ingroups holding politically coherent opinions). We numerically integrated the model’s master equations that perfectly describe the system’s dynamics and found that ideological sorting only emerges in models that include pairwise-coherence favoritism. We then compared the model’s outcomes with empirical data from 24,035 opinions across 67 topics and found that pairwise-coherence favoritism is significantly present in datasets that measure political attitudes but absent across topics not considered related to politics. Overall, this work combines theoretical approaches from system dynamics with model-based analyses of empirical data to uncover a potential mechanism underlying the pervasiveness of ideological sorting.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572663","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}
Pub Date : 2024-07-05DOI: 10.1093/pnasnexus/pgae266
Junpei Kuroda, Hiromu Hino, Shigeru Kondo
Collagen fibers provide physical support to animal tissues by orienting in the correct position and at optimal density. Actinotrichia are thick collagen fibers that are present at the tips of fish fins and serve as scaffolds for bone formation. The arrangement and density of actinotrichia must be constantly maintained with a high degree of regularity to form spatial patterns in the fin bones, but the mechanisms of this process are largely unknown. To address this issue, we first identified two fluorescent probes that can stain actinotrichia clearly in vivo. Using these probes and time-lapse observation of actinotrichia synthesized at different growth stages, we revealed the following previously unknown dynamics of actinotrichia. (1) Actinotrichia don’t stay stationary at the place where they are produced; instead, they move towards the dorsal area during the notochord bending and (2) move towards the distal tip during the fin growth. (3) Actinotrichia elongate asymmetrically as new collagen is added at the proximal side. (4) Density is maintained by the insertion of new actinotrichia. (5) Actinotrichia are selectively degraded by osteoclasts. These findings suggest that the regular arrangement of actinotrichia is the outcome of multiple dynamic processes.
{"title":"Dynamics of actinotrichia, fibrous collagen structures in zebrafish fin tissues, unveiled by novel fluorescent probes","authors":"Junpei Kuroda, Hiromu Hino, Shigeru Kondo","doi":"10.1093/pnasnexus/pgae266","DOIUrl":"https://doi.org/10.1093/pnasnexus/pgae266","url":null,"abstract":"Collagen fibers provide physical support to animal tissues by orienting in the correct position and at optimal density. Actinotrichia are thick collagen fibers that are present at the tips of fish fins and serve as scaffolds for bone formation. The arrangement and density of actinotrichia must be constantly maintained with a high degree of regularity to form spatial patterns in the fin bones, but the mechanisms of this process are largely unknown. To address this issue, we first identified two fluorescent probes that can stain actinotrichia clearly in vivo. Using these probes and time-lapse observation of actinotrichia synthesized at different growth stages, we revealed the following previously unknown dynamics of actinotrichia. (1) Actinotrichia don’t stay stationary at the place where they are produced; instead, they move towards the dorsal area during the notochord bending and (2) move towards the distal tip during the fin growth. (3) Actinotrichia elongate asymmetrically as new collagen is added at the proximal side. (4) Density is maintained by the insertion of new actinotrichia. (5) Actinotrichia are selectively degraded by osteoclasts. These findings suggest that the regular arrangement of actinotrichia is the outcome of multiple dynamic processes.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572666","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}
Pub Date : 2024-07-05DOI: 10.1093/pnasnexus/pgae272
Andrei Mironenko, Bert L de Groot, Wojciech Kopec
Potassium (K+) channels combine high conductance with high ion selectivity. To explain this efficiency, two molecular mechanisms have been proposed. The ‘direct knock-on’ mechanism is defined by water-free K+ permeation and formation of direct ion-ion contacts in the highly conserved selectivity filter (SF). The ‘soft knock-on’ mechanism involves co-permeation of water and separation of K+ by water molecules. With the aim to distinguish between these mechanisms, crystal structures of the KcsA channel with mutations in two SF residues - G77 and T75 - were published, where the arrangements of K+ ions and water display canonical soft knock-on configurations. These data were interpreted as evidence of the soft knock-on mechanism in wild-type channels (C. Tilegenova, et al., Structure, function, and ion-binding properties of a K+ channel stabilized in the 2,4-ion–bound configuration. Proceedings of the National Academy of Sciences 116, 16829–16834 (2019)). Here, we test this interpretation using molecular dynamics simulations of KcsA and its mutants. We show that, while a strictly water-free direct knock-on permeation is observed in the wild-type, conformational changes induced by these mutations lead to distinct ion permeation mechanisms, characterized by co-permeation of K+ and water. These mechanisms are characterized by reduced conductance and impaired potassium selectivity, supporting the importance of full dehydration of potassium ions for the hallmark high conductance and selectivity of K+ channels. In general, we present a case where mutations introduced at the critical points of the permeation pathway in an ion channel drastically change its permeation mechanism in a non-intuitive manner.
{"title":"Selectivity filter mutations shift ion permeation mechanism in potassium channels","authors":"Andrei Mironenko, Bert L de Groot, Wojciech Kopec","doi":"10.1093/pnasnexus/pgae272","DOIUrl":"https://doi.org/10.1093/pnasnexus/pgae272","url":null,"abstract":"Potassium (K+) channels combine high conductance with high ion selectivity. To explain this efficiency, two molecular mechanisms have been proposed. The ‘direct knock-on’ mechanism is defined by water-free K+ permeation and formation of direct ion-ion contacts in the highly conserved selectivity filter (SF). The ‘soft knock-on’ mechanism involves co-permeation of water and separation of K+ by water molecules. With the aim to distinguish between these mechanisms, crystal structures of the KcsA channel with mutations in two SF residues - G77 and T75 - were published, where the arrangements of K+ ions and water display canonical soft knock-on configurations. These data were interpreted as evidence of the soft knock-on mechanism in wild-type channels (C. Tilegenova, et al., Structure, function, and ion-binding properties of a K+ channel stabilized in the 2,4-ion–bound configuration. Proceedings of the National Academy of Sciences 116, 16829–16834 (2019)). Here, we test this interpretation using molecular dynamics simulations of KcsA and its mutants. We show that, while a strictly water-free direct knock-on permeation is observed in the wild-type, conformational changes induced by these mutations lead to distinct ion permeation mechanisms, characterized by co-permeation of K+ and water. These mechanisms are characterized by reduced conductance and impaired potassium selectivity, supporting the importance of full dehydration of potassium ions for the hallmark high conductance and selectivity of K+ channels. In general, we present a case where mutations introduced at the critical points of the permeation pathway in an ion channel drastically change its permeation mechanism in a non-intuitive manner.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572665","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}
Tyrosine phenol-lyase (TPL), which is expressed in intestinal bacteria, catalyzes the formation of phenol from the substrate L-Tyr. Bacterial metabolite phenol and the sulfate conjugate (phenyl sulfate) are known as a type of uremic toxins, some of which exert cytotoxicity. Therefore, pathologically elevated phenol and phenyl sulfate levels are strongly implicated in the etiology and outcome of uremia. In this study, we explored the inhibitory effects of dietary polyphenols on TPL-catalyzed phenol production using a TPL activity assay. Quercetin, one of the most popular polyphenols, exhibited the strongest inhibitory activity (Ki =19.9 µM). Quercetin competitively inhibited TPL, and its activity was stronger than that of a known TPL inhibitor (Tyr analog; 2-aza-Tyr, Ki = 42.0 µM). Additionally, quercetin significantly inhibited phenol production in TPL-expressing bacterial cultures (Morganella morganii and Citrobacter koseri) and Tyr-rich (5 %) diet-fed C57BL/6J mouse feces. Our findings suggest that quercetin is the most promising polyphenol for reducing phenol levels. Because quercetin has a low gastrointestinal absorption rate, TPL inhibition in the intestinal tract by quercetin may be an effective strategy for treating uremia.
{"title":"Tyrosine phenol-lyase inhibitor quercetin reduces fecal phenol levels in mice","authors":"Takuma Kobayashi, Shiori Oishi, Misaki Matsui, Kodai Hara, Hiroshi Hashimoto, Kenji Watanabe, Yasukiyo Yoshioka, Noriyuki Miyoshi","doi":"10.1093/pnasnexus/pgae265","DOIUrl":"https://doi.org/10.1093/pnasnexus/pgae265","url":null,"abstract":"Tyrosine phenol-lyase (TPL), which is expressed in intestinal bacteria, catalyzes the formation of phenol from the substrate L-Tyr. Bacterial metabolite phenol and the sulfate conjugate (phenyl sulfate) are known as a type of uremic toxins, some of which exert cytotoxicity. Therefore, pathologically elevated phenol and phenyl sulfate levels are strongly implicated in the etiology and outcome of uremia. In this study, we explored the inhibitory effects of dietary polyphenols on TPL-catalyzed phenol production using a TPL activity assay. Quercetin, one of the most popular polyphenols, exhibited the strongest inhibitory activity (Ki =19.9 µM). Quercetin competitively inhibited TPL, and its activity was stronger than that of a known TPL inhibitor (Tyr analog; 2-aza-Tyr, Ki = 42.0 µM). Additionally, quercetin significantly inhibited phenol production in TPL-expressing bacterial cultures (Morganella morganii and Citrobacter koseri) and Tyr-rich (5 %) diet-fed C57BL/6J mouse feces. Our findings suggest that quercetin is the most promising polyphenol for reducing phenol levels. Because quercetin has a low gastrointestinal absorption rate, TPL inhibition in the intestinal tract by quercetin may be an effective strategy for treating uremia.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141550515","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}
Pub Date : 2024-07-04DOI: 10.1093/pnasnexus/pgae271
Dasol Choi, Ahmad F Alshannaq, Jae-Hyuk Yu
Aflatoxins (AFs) are carcinogenic fungal toxins contaminating up to 25% of the global food supply. Over half of the world’s population is exposed to unmonitored levels of AFs, mostly aflatoxin B1 (AFB1). Despite numerous efforts over the past 60 years, there are no solutions to remove AFs safely from food. Here, we present a safe and effective AF-degrading product called “D-Tox”, a filtered culture broth of Aspergillus oryzae grown in a food-grade liquid medium. When 5 ppm of AFB1 is added to D-Tox, ∼90% is degraded at 48 hr and 24 hr at room temperature and 50°C, respectively. Moreover, when varying amounts (0.1 ppm ∼ 100 ppm) of AFB1 are added to D-Tox at 100°C, over 95% of AFB1 is degraded in 1 hr, suggesting a non-enzymatic process. Examining degradation of 100 ppm AFB1 reveals that aflatoxin D1 (AFD1) is the major transient degradant of AFB1, indicating that degradation occurs irreversibly by lactone ring hydrolysis followed by decarboxylation. D-Tox further degrades AFD1 to unknown fragmented products. Importantly, the practical application of D-Tox is also demonstrated, as more than 70% of AFB1 is degraded when wheat, corn, and peanuts naturally contaminated with high levels of AFB1 (0.3 ∼ 4.5 ppm) are boiled in D-Tox for 1 hr. Additionally, D-Tox can degrade other lactone-ring-containing mycotoxins, including patulin and ochratoxin. D-Tox exhibits no cytotoxicity under the conditions tested in MCF-7 breast cancer cell lines. In summary, D-Tox is a safe and effective AF-detoxifying novel product that can enhance global food safety.
{"title":"Safe and Effective Degradation of Aflatoxins by Food-Grade Culture Broth of Aspergillus oryzae","authors":"Dasol Choi, Ahmad F Alshannaq, Jae-Hyuk Yu","doi":"10.1093/pnasnexus/pgae271","DOIUrl":"https://doi.org/10.1093/pnasnexus/pgae271","url":null,"abstract":"Aflatoxins (AFs) are carcinogenic fungal toxins contaminating up to 25% of the global food supply. Over half of the world’s population is exposed to unmonitored levels of AFs, mostly aflatoxin B1 (AFB1). Despite numerous efforts over the past 60 years, there are no solutions to remove AFs safely from food. Here, we present a safe and effective AF-degrading product called “D-Tox”, a filtered culture broth of Aspergillus oryzae grown in a food-grade liquid medium. When 5 ppm of AFB1 is added to D-Tox, ∼90% is degraded at 48 hr and 24 hr at room temperature and 50°C, respectively. Moreover, when varying amounts (0.1 ppm ∼ 100 ppm) of AFB1 are added to D-Tox at 100°C, over 95% of AFB1 is degraded in 1 hr, suggesting a non-enzymatic process. Examining degradation of 100 ppm AFB1 reveals that aflatoxin D1 (AFD1) is the major transient degradant of AFB1, indicating that degradation occurs irreversibly by lactone ring hydrolysis followed by decarboxylation. D-Tox further degrades AFD1 to unknown fragmented products. Importantly, the practical application of D-Tox is also demonstrated, as more than 70% of AFB1 is degraded when wheat, corn, and peanuts naturally contaminated with high levels of AFB1 (0.3 ∼ 4.5 ppm) are boiled in D-Tox for 1 hr. Additionally, D-Tox can degrade other lactone-ring-containing mycotoxins, including patulin and ochratoxin. D-Tox exhibits no cytotoxicity under the conditions tested in MCF-7 breast cancer cell lines. In summary, D-Tox is a safe and effective AF-detoxifying novel product that can enhance global food safety.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141550516","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}
Pub Date : 2024-07-03DOI: 10.1093/pnasnexus/pgae268
Songlin Lu, Yuanfang Huang, Wan Xiang Shen, Yu Lin Cao, Mengna Cai, Yan Chen, Ying Tan, Yu Yang Jiang, Yu Zong Chen
Feature representation is critical for data learning, particularly in learning spectroscopic data. Machine learning (ML) and deep learning (DL) models learn Raman spectra for rapid, non-destructive, and label-free cell phenotype identification, which facilitate diagnostic, therapeutic, forensic, and microbiological applications. But these are challenged by high-dimensional, unordered and low-sample spectroscopic data. Here we introduced novel 2D image-like dual signal and component aggregated representations by restructuring Raman spectra and principal components, which enables spectroscopic DL for enhanced cell phenotype and signature identification. New ConvNet models DSCARNets significantly outperformed the state-of-the-art (SOTA) ML and DL models on six benchmark datasets, mostly with >2% improvement over the SOTA performance of 85%-97% accuracies. DSCARNets also performed well on four additional datasets against SOTA models of extremely high performances (>98%) and two datasets without a published supervised phenotype classification model. Explainable DSCARNets identified Raman signatures consistent with experimental indications.
特征表示对于数据学习，尤其是光谱数据学习至关重要。机器学习（ML）和深度学习（DL）模型学习拉曼光谱，可用于快速、无损和无标记的细胞表型识别，从而促进诊断、治疗、法医和微生物学应用。但这些技术面临着高维、无序和低样本光谱数据的挑战。在此，我们通过重组拉曼光谱和主成分，引入了新颖的二维图像式双信号和成分聚合表示法，从而利用光谱 DL 增强细胞表型和特征识别。新的 ConvNet 模型 DSCARNets 在六个基准数据集上的表现明显优于最先进的（SOTA）ML 和 DL 模型，与 SOTA 85%-97% 的准确率相比，大多提高了>2%。在另外四个数据集上，DSCARNets 的表现也很出色，与 SOTA 模型的极高表现（>98%）相比，DSCARNets 的表现更胜一筹。可解释的 DSCARNets 识别出的拉曼特征与实验指标一致。
{"title":"Raman spectroscopic deep learning with signal aggregated representations for enhanced cell phenotype and signature identification","authors":"Songlin Lu, Yuanfang Huang, Wan Xiang Shen, Yu Lin Cao, Mengna Cai, Yan Chen, Ying Tan, Yu Yang Jiang, Yu Zong Chen","doi":"10.1093/pnasnexus/pgae268","DOIUrl":"https://doi.org/10.1093/pnasnexus/pgae268","url":null,"abstract":"Feature representation is critical for data learning, particularly in learning spectroscopic data. Machine learning (ML) and deep learning (DL) models learn Raman spectra for rapid, non-destructive, and label-free cell phenotype identification, which facilitate diagnostic, therapeutic, forensic, and microbiological applications. But these are challenged by high-dimensional, unordered and low-sample spectroscopic data. Here we introduced novel 2D image-like dual signal and component aggregated representations by restructuring Raman spectra and principal components, which enables spectroscopic DL for enhanced cell phenotype and signature identification. New ConvNet models DSCARNets significantly outperformed the state-of-the-art (SOTA) ML and DL models on six benchmark datasets, mostly with >2% improvement over the SOTA performance of 85%-97% accuracies. DSCARNets also performed well on four additional datasets against SOTA models of extremely high performances (>98%) and two datasets without a published supervised phenotype classification model. Explainable DSCARNets identified Raman signatures consistent with experimental indications.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141550517","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}
Pub Date : 2024-07-02DOI: 10.1093/pnasnexus/pgae264
Susumu Ito, Nariya Uchida
Collective motion provides a spectacular example of self-organization in Nature. Visual information plays a crucial role among various types of information in determining interactions. Recently, experiments have revealed that organisms such as fish and insects selectively utilize a portion, rather than the entirety, of visual information. Here, focusing on fish, we propose an agent-based model where the direction of attention is guided by visual stimuli received from the images of nearby fish. Our model reproduces a branching phenomenon where a fish selectively follows a specific individual as the distance between two or three nearby fish increases. Furthermore, our model replicates various patterns of collective motion in a group of agents, such as vortex, polarized school, swarm, and turning. We also discuss the topological nature of the visual interaction, as well as the positional distribution of nearby fish and the map of pairwise and three-body interactions induced by them. Through a comprehensive comparison with existing experimental results, we clarify the roles of visual interactions and issues to be resolved by other forms of interactions.
{"title":"Selective decision making and collective behavior of fish by the motion of visual attention","authors":"Susumu Ito, Nariya Uchida","doi":"10.1093/pnasnexus/pgae264","DOIUrl":"https://doi.org/10.1093/pnasnexus/pgae264","url":null,"abstract":"Collective motion provides a spectacular example of self-organization in Nature. Visual information plays a crucial role among various types of information in determining interactions. Recently, experiments have revealed that organisms such as fish and insects selectively utilize a portion, rather than the entirety, of visual information. Here, focusing on fish, we propose an agent-based model where the direction of attention is guided by visual stimuli received from the images of nearby fish. Our model reproduces a branching phenomenon where a fish selectively follows a specific individual as the distance between two or three nearby fish increases. Furthermore, our model replicates various patterns of collective motion in a group of agents, such as vortex, polarized school, swarm, and turning. We also discuss the topological nature of the visual interaction, as well as the positional distribution of nearby fish and the map of pairwise and three-body interactions induced by them. Through a comprehensive comparison with existing experimental results, we clarify the roles of visual interactions and issues to be resolved by other forms of interactions.","PeriodicalId":516525,"journal":{"name":"PNAS Nexus","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141512741","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}
Pub Date : 2024-07-01DOI: 10.1093/pnasnexus/pgae259
Kush Kumar Yadav, Patricia A Boley, Carolyn M Lee, Saroj Khatiwada, Kwonil Jung, Thamonpan Laocharoensuk, Jake Hofstetter, Ronna Wood, Juliette Hanson, Scott P Kenney
Strains of Rocahepevirus ratti, an emerging hepatitis E virus (HEV), have recently been found to be infectious to humans. Rats are a primary reservoir of the virus; thus, it is referred to as “rat HEV”. Rats are often found on swine farms in close contact with pigs. Our goal was to determine whether swine may serve as a transmission host for zoonotic rat HEV by characterizing an infectious cDNA clone of a zoonotic rat HEV, strain LCK-3110, in vitro and in vivo. RNA transcripts of LCK-3110 were constructed and assessed for their replicative capacity in cell culture and in gnotobiotic pigs. Fecal suspension from rat HEV-positive gnotobiotic pigs was inoculated into conventional pigs cohoused with naïve pigs. Our results demonstrated that capped RNA transcripts of LCK-3110 rat HEV replicated in vitro and successfully infected conventional pigs that transmit the virus to cohoused animals. The infectious clone of rat HEV may afford an opportunity to study the genetic mechanisms of rat HEV cross-species infection and tissue tropism.
最近发现，一种新出现的戊型肝炎病毒（HEV）--Rocahepevirus ratti 株系可传染给人类。大鼠是该病毒的主要贮存者，因此被称为 "大鼠戊型肝炎病毒"。猪场中经常发现老鼠与猪密切接触。我们的目标是通过研究人畜共患病大鼠 HEV（LCK-3110 株）感染性 cDNA 克隆的体外和体内特征，确定猪是否可能成为人畜共患病大鼠 HEV 的传播宿主。构建了 LCK-3110 的 RNA 转录本，并评估了其在细胞培养和无饲养动物猪体内的复制能力。将大鼠 HEV 阳性无生物猪的粪悬液接种到与天真猪同群的常规猪体内。我们的研究结果表明，LCK-3110 大鼠 HEV 的封顶 RNA 转录本可在体外复制，并成功感染常规猪，将病毒传播给同群动物。大鼠 HEV 的感染性克隆可能为研究大鼠 HEV 跨物种感染和组织滋养的遗传机制提供了机会。
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Pub Date : 2024-07-01DOI: 10.1093/pnasnexus/pgae261
Yasuhiro Tsubo, Shigeru Shinomoto
Spike raster plots of numerous neurons show vertical stripes, indicating that neurons exhibit synchronous activity in the brain. We seek to determine whether these coherent dynamics are caused by smooth brainwave activity or by something else. By analyzing biological data, we find that their cross-correlograms exhibit not only slow undulation but also a cusp at the origin, in addition to possible signs of monosynaptic connectivity. Here we show that undulation emerges if neurons are subject to smooth brainwave oscillations while a cusp results from non-differentiable fluctuations. While modern analysis methods have achieved good connectivity estimation by adapting the models to slow undulation, they still make false inferences due to the cusp. We devise a new analysis method that may solve both problems. We also demonstrate that oscillations and non-differentiable fluctuations may emerge in simulations of large-scale neural networks.
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