Human Adaptation Research Articles

Exploring the genomic basis of Mpox virus-host transmission and pathogenesis.

Mpox disease, caused by the monkeypox virus (MPXV), was recently classified as a public health emergency of international concern due to its high lethality and pandemic potential. MPXV is a zoonotic disease that emerged and is primarily spread by small rodents. Historically, it was considered mainly zoonotic and not likely to sustain human-to-human transmission. However, the worldwide outbreak of Clade IIb MPXV from 2020 to 2022 and ongoing Clade I MPXV epidemics in the Democratic Republic of the Congo and surrounding areas are a warning that human-adapted MPXVs will continually arise. Understanding the viral genetic determinants of host range, pathogenesis, and immune evasion is imperative for developing control strategies and predicting the future of Mpox. Here, we delve into the MPXV genome to detail genes involved in host immune evasion strategies for this zoonotic rodent-borne and human-circulating virus. We compare MPXV gene content to related Orthopoxviruses, which have narrow host ranges, to identify potential genes involved in species-specific pathogenesis and host tropism. In addition, we cover the key virulence factor differences that distinguish the MPXV clade lineages. Finally, we dissect how genomic reduction of Orthopoxviruses, through various molecular mechanisms, is contributing to the generation of novel MPXV lineages with increased human adaptation. This review aims to highlight gene content that defines the MPXV species, MPXV clades, and novel MPXV lineages that have culminated in this virus being elevated to a public health emergency of national concern.

Archaic introgression contributed to shape the adaptive modulation of angiogenesis and cardiovascular traits in human high-altitude populations from the Himalayas.

It is well established that several Homo sapiens populations experienced admixture with extinct human species during their evolutionary history. Sometimes, such a gene flow could have played a role in modulating their capability to cope with a variety of selective pressures, thus resulting in archaic adaptive introgression events. A paradigmatic example of this evolutionary mechanism is offered by the EPAS1 gene, whose most frequent haplotype in Himalayan highlanders was proved to reduce their susceptibility to chronic mountain sickness and to be introduced in the gene pool of their ancestors by admixture with Denisovans. In this study, we aimed at further expanding the investigation of the impact of archaic introgression on more complex adaptive responses to hypobaric hypoxia evolved by populations of Tibetan/Sherpa ancestry, which have been plausibly mediated by soft selective sweeps and/or polygenic adaptations rather than by hard selective sweeps. For this purpose, we used a combination of composite-likelihood and gene network-based methods to detect adaptive loci in introgressed chromosomal segments from Tibetan WGS data and to shortlist those presenting Denisovan-like derived alleles that participate to the same functional pathways and are absent in populations of African ancestry, which are supposed to do not have experienced Denisovan admixture. According to this approach, we identified multiple genes putatively involved in archaic introgression events and that, especially as regards TBC1D1, RASGRF2, PRKAG2, and KRAS, have plausibly contributed to shape the adaptive modulation of angiogenesis and of certain cardiovascular traits in high-altitude Himalayan peoples. These findings provided unprecedented evidence about the complexity of the adaptive phenotype evolved by these human groups to cope with challenges imposed by hypobaric hypoxia, offering new insights into the tangled interplay of genetic determinants that mediates the physiological adjustments crucial for human adaptation to the high-altitude environment.

Archaic introgression contributed to shape the adaptive modulation of angiogenesis and cardiovascular traits in human high-altitude populations from the Himalayas

It is well established that several Homo sapiens populations experienced admixture with extinct human species during their evolutionary history. Sometimes, such a gene flow could have played a role in modulating their capability to cope with a variety of selective pressures, thus resulting in archaic adaptive introgression events. A paradigmatic example of this evolutionary mechanism is offered by the EPAS1 gene, whose most frequent haplotype in Himalayan highlanders was proved to reduce their susceptibility to chronic mountain sickness and to be introduced in the gene pool of their ancestors by admixture with Denisovans. In this study, we aimed at further expanding the investigation of the impact of archaic introgression on more complex adaptive responses to hypobaric hypoxia evolved by populations of Tibetan/Sherpa ancestry, which have been plausibly mediated by soft selective sweeps and/or polygenic adaptations rather than by hard selective sweeps. For this purpose, we used a combination of composite-likelihood and gene network-based methods to detect adaptive loci in introgressed chromosomal segments from Tibetan WGS data and to shortlist those presenting Denisovan-like derived alleles that participate to the same functional pathways and are absent in populations of African ancestry, which are supposed to do not have experienced Denisovan admixture. According to this approach, we identified multiple genes putatively involved in archaic introgression events and that, especially as regards TBC1D1, RASGRF2, PRKAG2, and KRAS, have plausibly contributed to shape the adaptive modulation of angiogenesis and of certain cardiovascular traits in high-altitude Himalayan peoples. These findings provided unprecedented evidence about the complexity of the adaptive phenotype evolved by these human groups to cope with challenges imposed by hypobaric hypoxia, offering new insights into the tangled interplay of genetic determinants that mediates the physiological adjustments crucial for human adaptation to the high-altitude environment.

Human Adaption to Climate Change: Marine Disaster Risk Reduction in the Era of Intelligence

With the intensification of global warming and sea level rise, extreme weather and climate events occur frequently, increasing the probability and destructive power of marine disasters. The purpose of this paper is to propose the specific application of artificial intelligence (AI) in marine disaster risk reduction. First, this paper uses computer vision to assess the vulnerability of the target and then uses CNN-LSTM to forecast tropical cyclones. Second, this paper proposes a social media communication mechanism based on deep learning and a psychological crisis intervention mechanism based on AIGC. In addition, the rescue response system based on an intelligent unmanned platform is also the focus of this research. Third, this paper also attempts to discuss disaster loss assessment and reconstruction based on machine learning and smart city concepts. After proposing specific application measures, this paper proposes three policy recommendations. The first one is improving legislation to break the technological trap of AI. The second one is promoting scientific and technological innovation to break through key technologies of AI. The third one is strengthening coordination and cooperation to build a disaster reduction system that integrates man and machine. The purpose of this paper is to reduce the risk of marine disasters by applying AI. Furthermore, we hope to provide scientific references for sustainability and human adaptation to climate change.

Resilience in the Population of Cusco in Times of COVID-19

The COVID-19 pandemic has profoundly impacted the world, leading to millions of infections, deaths, and crises. In Cusco, Peru, this complexity has altered social structures and interpersonal relationships. This study aimed to explore human adaptation strategies developed during the pandemic in Cusco. A non-probabilistic sample of 40 adults from the province's eight districts was interviewed using phenomenological and ethnomethodological methods. Data were collected through in-depth interviews and analyzed using Atlas Ti software. Results indicate that the pandemic has changed personal and social characteristics, reflected in altered moods, worries, and priorities. Participants reported increased awareness of their vulnerability, heightened solidarity with others, and shifting family roles that necessitated new forms of coexistence, often with distorted responsibilities. Interpersonal communication became limited, relying heavily on technology, and there was a rise in individual responses, including the use of natural and chemical remedies. Overall, the study concludes that Cusco's inhabitants have developed various adaptation strategies to confront the pandemic, significantly impacting their personal lives and social contexts.

Early Sri Lankan coastal site tracks technological change and estuarine resource exploitation over the last ca. 25,000 years

The island of Sri Lanka was part of the South Asian mainland for the majority of the past 115,000 years, and connected most recently during the Last Glacial Maximum via the now submerged Palk Strait. The degree to which rising sea levels shaped past human adaptations from the Pleistocene and into the mid to late Holocene in Sri Lanka has remained unclear, in part because the earliest reliable records of human occupation come from the island’s interior, where cave sites have revealed occupation of tropical forest ecosystems extending back to 48 thousand years (ka). The island’s earliest known open-air sites are all much younger in date, with ages beginning at 15 ka and extending across the Holocene. Here we report the earliest well-dated open-air coastal site in Sri Lanka, Pathirajawela, which records human occupation back to ca. 25,000 years ago. We show that humans at Pathirajawela consistently adapted to changing ecosystems linked to sea level transgression and coastal evolution from the Last Glacial Maximum into the Holocene. The presence of anthropogenic shell midden deposits at the site from ca. 4.8 ka, focused almost exclusively on a single taxon, indicates intensification of estuarine resource exploitation, as humans responded to opportunities presented by the formation of new coastal ecosystems.

Lower Paleolithic Stone-Animal ontologies: stone scrapers as mediators between early humans and their preferred prey

ABSTRACT Animal meat, fat, and other animal-derived materials have been essential for human adaptation since the Early Palaeolithic, forming a crucial foundation for many hunter-gatherer societies until recently. In these societies, animals were perceived as vital beings with whom a balanced relationship, based on respect, was paramount. Stone tools for multi-stage butchery enabled efficient acquisition and processing of animal remains, aligning with Indigenous ontologies. Ethnographic and ethno-archaeological data globally indicate that stone tools used in hunting, butchery, and hide-working evolved alongside changes in animal availability, driven by practical and ontological factors. Our case study from the Late Lower Palaeolithic Levant illustrates how technological transformations driven by shifting faunal availability may have mirrored cosmological perspectives. We address the viability of employing an ontological approach to interpret Acheulian hominins and suggest that stone tools were practically and perceptually associated with the animals they were designed to procure and process, starting in the Palaeolithic.

Non-optimal temperature-attributable mortality and morbidity burden by cause, age and sex under climate and population change scenarios: a nationwide modelling study in Japan

Future temperature effects on mortality and morbidity may differ. However, studies comparing projected future temperature-attributable mortality and morbidity in the same setting are limited. Moreover, these studies did not consider future population change, human adaptation, and the variations in subpopulation susceptibility. Thus, we simultaneously projected the temperature-related mortality and morbidity by cause, age, and sex under population change, and human adaptation scenarios in Japan, a super-ageing society. We used daily mean temperatures, mortality, and emergency ambulance dispatch (a sensitive indicator for morbidity) in 47 prefectures of Japan from 2015 to 2019 as the reference for future projections. Future mortality and morbidity were generated at prefecture level using four shared socioeconomic pathway (SSP) scenarios considering population changes. We calculated future temperature-related mortality and morbidity by combining baseline values with future temperatures and existing temperature risk functions by cause (all-cause, circulatory, respiratory), age (<65 years, ≥65 years), and sex under various climate change and SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Full human adaptation was simulated based on empirical evidence using a fixed percentile of minimum mortality or morbidity temperature (MMT), while no adaptation was simulated with a fixed absolute MMT. A future temporal decline in mortality burden attributable to non-optimal temperatures was observed, driven by greater cold-related deaths than heat-related deaths. In contrast, temperature-related morbidity increased over time, which was primarily driven by heat. In the 2050s and 2090s, under a moderate scenario, there are 83.69 (95% empirical confidence interval [eCI] 38.32-124.97) and 77.31 (95% eCI 36.84-114.47) all-cause deaths per 100,000 population, while there are 345.07 (95% eCI 258.31-438.66) and 379.62 (95% eCI 271.45-509.05) all-cause morbidity associated with non-optimal temperatures. These trends were largely consistent across causes, age, and sex groups. Future heat-attributable health burden is projected to increase substantially, with spatiotemporal variations and is particularly pronounced among individuals ≥65y and males. Full human adaptation could yield a decreasing temperature-attributable mortality and morbidity in line with a decreasing population. Our findings could support the development of targeted mitigation and adaptation strategies to address future heat-related impacts effectively. This includes improved healthcare allocations for ambulance dispatch and hospital preventive measures during heat periods, particularly custom-tailored to address specific health outcomes and vulnerable subpopulations. Japan Science and Technology Agency and Environmental Restoration and Conservation Agency and Ministry of the Environment of Japan.

Modeling implications of the relationship between active and passive skeletal muscle mechanical properties

It is challenging to obtain in vivo or in situ experimental data from human muscles due to the invasive nature of such measurements. As a result, many investigations of human performance, surgery, or skeletal adaptation are necessarily based on musculoskeletal models. The utility of such models will depend on the question being asked and the extent to which the model is sufficiently accurate to address that question. In this perspective article, we take advantage of unique intraoperative access to the human gracilis muscle and make direct comparisons between commonly modeled parameters and those measured from the human gracilis. We directly compare muscle–tendon unit (MTU) length, optimal fiber length, and tendon slack length. Our results demonstrate that measured and modeled length parameters differ greatly. This is primarily due to the fact that slack muscle length and optimal muscle length differ greatly for the human gracilis and that models assume they are the same length.

Understanding adaptive responses to adversity: Introduction to the special issue on rethinking resilience and posttraumatic growth.

Research on resilience and posttraumatic growth (PTG) has significantly advanced our understanding of human adaptability to adversity, reflecting a widespread belief in the United States that such adaptability is commonplace. However, recent studies have highlighted conceptual and methodological limitations in these fields. These limitations call into question the credibility of existing research and underscore the need for multidisciplinary perspectives in understanding adaptive responses to adversity. This special issue aims to provide a foundation for a new generation of resilience and PTG research. It brings together innovative theoretical and empirical work that focuses on several key areas: the multifaceted nature and impacts of adversity, the importance of clarifying resilience and PTG in marginalized communities, methodological advancements in the field, and challenges to core theoretical and methodological assumptions underlying our scientific practice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Tulum’s underwater caves: insights into the oldest human fossils in the Americas

Evidence of late Pleistocene human and fauna remains has been documented within the extensive cave systems of the Tulum region in northeast Yucatán, Mexico. This unique area is vital for paleontological and paleoanthropological research, providing insights into early human adaptation in the Americas. To date, 10 human fossils have been thoroughly studied, with two additional recent discoveries under investigation. These remains, dating from 13,700 to 8,000 BP, emphasize the paleoanthropological significance of Tulum's submerged caves. A key discovery is the skeleton of Eva de Naharon, dated to 13,721 years cal BP, making her the oldest known human fossil in the Americas. Using 3D facial reconstructions and DNA analysis, researchers have identified craniofacial similarities with South Asian populations, suggesting shared ancestry and migration patterns. These findings enrich our understanding of human migration and adaptation. Ongoing research continues to highlight the role of Tulum’s underwater caves in shaping early human history, survival strategies, and social structures over millennia.

Feasibility of dried blood spot collection for caffeine pharmacokinetic studies in microgravity: Insights from parabolic flight campaigns.

Therapeutic drug monitoring for astronauts faces limitations in conventional blood sampling and sample management onboard the international space station. Here, we explore the feasibility of dried blood spot (DBS) collection during parabolic flights (PF) to overcome these constraints. We assessed the feasibility of blood deposition on blotting paper for preanalytical aspects in a PF using synthetic blood. Subsequently, DBS sampling validation was carried out in another PF campaign. Twenty volunteers participated in a pharmacokinetic study on caffeine and its metabolite, paraxanthine, conducted during parabolic flights. After >18 h caffeine washout, coffee (115 mg), tea (30 mg) or dark chocolate (11 mg) were ingested by the participants. DBS samples were collected at baseline, during weightlessness and post-flight. Caffeine and paraxanthine were analysed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Genotyping for cytochrome P450-1A2 (CYP1A2) was performed and a metabolic ratio by area under the curve for caffeine and paraxanthine (AUCPAX/AUCCAF) for CYP1A2 was determined. A user experience survey was also conducted. Full in-flight pharmacokinetic study was feasible in seventeen volunteers with three unable to perform the sampling due to motion sickness. Nineteen participants (twelve males and seven females) completed pharmacokinetic profiles, with repeated pharmacokinetic studies for six participants. CYP1A2 genotyping resulted in eight ultrarapid, eleven intermediate, and one poor metabolizer. Among the women, four were on oestrogen contraceptives, a known inhibitor of CYP1A2, and were considered as poor metabolizers. Expected differences in kinetic profiles, consistent with consumption habits, the ingested dose and the genotypic/phenotypic information, were observed. The mean caffeine AUC for coffee, tea and chocolate were 9419ng.h.mL-1 (95% confidence interval [CI]: 6222-12 616, n = 10), 6917ng.h.mL-1 (95% CI: 2729-11 105), n = 7) and 3039ng.h.mL-1 (95% CI: 1614-4142, n = 12), respectively. The mean paraxanthine AUC were 10 566ng.h.mL-1 (95% CI: 6242-14 890, n = 10), 4011ng.h.mL-1 (95% CI: 2305-5716, n = 7) and 3638ng.h.mL-1 (95% CI: 1589-40 859, n = 12), respectively. The mean metabolic ratio in oestrogen-treated women was 0.53 (95% CI: 0.35-0.71) compared to 1.19 (95% CI: 0.99-1.33) in others. The mean metabolic ratio was 1.02 (95% CI: 0.81-1.23, n = 15) on the ground and 1.10 (95% CI: 0.70-1.41, n = 13) during the parabolic flights, with no significant difference observed between the two conditions. Overall participants were satisfied with the usability of the method. DBS collection was safe, stable, feasible and well accepted in weightlessness. This method would offer valuable insights into human metabolism adaptation during long-term spaceflight, addressing space pharmacology challenges.

Pengaruh Artificial Intelligence dalam Pembuatan Laporan Keuangan

The presence of Artificial Intelligence (AI) has a significant impact on the preparation of financial reports, especially in terms of efficiency and accuracy. This article aims to examine the influence of AI on the process of preparing financial reports that were previously carried out conventionally and the challenges faced by companies in adopting it. This study uses a literature study method to identify trends and findings related to the use of AI in accounting. The results show that AI is able to improve operational efficiency, data analysis, and security, although there are challenges in its implementation, such as human resource adaptation and data security.

Sztuczna inteligencja. Konteksty i interpretacje

Artificial intelligence (AI) has been developing dynamically, and becomes a core issue in the public debate. The related contemporary achievements, such as generative language models, change the way we work, especially in creative fields. The article analyses the historical development of AI, from the Dartmouth workshops in 1956, through John McCarthy’s and Alan Turing’s symbolic approach to artificial intelligence, to the effect of cybernetics on contemporary technologies. It draws attention to Richard Dreyfuss’ and John Searle’s critique of AI, emphasising their meaning in redefining the differences between human and artificial intelligence. In the context of the AI revolution, the article poses a question about the future of design and technology, considering if the process of human adaptation keeps up with the development of machines. It also refers to ethical aspects of automation, and the growing importance of creative thinking in the face of technological progress. Keywords: artificial intelligence (AI), cybernetics, philosophy, history, design

Clade I mpox virus genomic diversity in the Democratic Republic of the Congo, 2018–2024: Predominance of zoonotic transmission

Recent reports raise concerns on the changing epidemiology of mpox in the Democratic Republic of the Congo (DRC). High-quality genomes were generated for 337 patients from 14/26 provinces to document whether the increase in number of cases is due to zoonotic spillover events or viral evolution, with enrichment of APOBEC3 mutations linked to human adaptation. Our study highlights two patterns of transmission contributing to the source of human cases. All new sequences from the eastern South Kivu province (n= 17; 4.8%) corresponded to the recently described clade Ib, associated with sexual contact and sustainedhuman-to-human transmission. By contrast, all other genomes are clade Ia, which exhibits high genetic diversity with low numbers of APOBEC3 mutations compared with clade Ib, suggesting multiplezoonotic introductions. The presence of multiple clade I variants in urban areas highlights the need for coordinated international response efforts and more studies on the transmission and the reservoir of mpox.

Meta-learning of human motor adaptation via the dorsal premotor cortex

Meta-learning enables us to learn how to learn the same or similar tasks more efficiently. Decision-making literature theorizes that a prefrontal network, including the orbitofrontal and anterior cingulate cortices, underlies meta-learning of decision making by reinforcement learning. Recently, computationally similar meta-learning has been theorized and empirically demonstrated in motor adaptation. However, it remains unclear whether meta-learning of motor adaptation also relies on a prefrontal network. Considering hierarchical information flow from the prefrontal to motor cortices, this study explores whether meta-learning is processed in the dorsolateral prefrontal cortex (DLPFC) or in the dorsal premotor cortex (PMd), which is situated upstream of the primary motor cortex, but downstream of the DLPFC. Transcranial magnetic stimulation (TMS) was delivered to either PMd or DLPFC during a motor meta-learning task, in which human participants were trained to regulate the rate and retention of motor adaptation to maximize rewards. While motor adaptation itself was intact, TMS to PMd, but not DLPFC, attenuated meta-learning, impairing the ability to regulate motor adaptation to maximize rewards. Further analyses revealed that TMS to PMd attenuated meta-learning of memory retention. These results suggest that meta-learning of motor adaptation relies more on the premotor area than on a prefrontal network. Thus, while PMd is traditionally viewed as crucial for planning motor actions, this study suggests that PMd is also crucial for meta-learning of motor adaptation, processing goal-directed planning of how long motor memory should be retained to fit the long-term goal of motor adaptation.

Urine Metabolomics during a Legume Diet Intervention Suggests Altered Metabolic Signatures and Potential New Intake Markers: First Insights.

Given the general increase in legume consumption worldwide, there is a need to characterize the resulting human metabolic adaptations in order to demonstrate potential legume diet/health relationships. A nuclear magnetic resonance (NMR) metabolomics urine study was carried out on a small cohort (n = 18) to characterize the excretory effects of a pilot longitudinal 8-week legume-based dietary intervention. Despite the expected high interindividual variability in the excreted metabolome, the results suggested a nonlinear metabolic response, with higher metabolic activity in the first 4 weeks and a tendency toward baseline at the end of the intervention. The excretion of isoleucine, leucine, and threonine increased, along with metabolite changes suggestive of activation of the tricarboxylic acid cycle (through anaplerosis), ketogenesis, fat catabolism, and glycoprotein biosynthesis. Gut microbiota adaptations were also suggested based on the increased excretion of 2-hydroxyisobutyrate, allantoin, and hippurate. Increased levels of trigonelline were consistent with its role as a legume intake marker, whereas malonate and pseudouridine were suggested as possible additional markers. Correlation of NMR data with nutritional parameters aided putative explanatory hypotheses to be advanced. Our results suggest a dynamic response to legume consumption, mainly through increased amino acid excretion and altered energy metabolism, while advancing potential new markers of legume intake. These results require confirmation in larger cohorts but pave the way for an informed interpretation of the effects of legume-based diets on human health.

Harnessing the power of adaptation: a pre-registered systematic review on executive functions and the adaptation to new technologies

ABSTRACT Given the pervasive integration of technology into everyday life and its importance in mitigating the negative consequences of global crises, an understanding of human adaptation and preceding cognitive abilities remains highly relevant. A systematic review synthesising empirical findings on the association of executive functions (EFs) and the adaptation to new technologies is currently lacking in the literature. The presented pre-registered, systematic review adheres to PRISMA 2020 guidelines and aims to extract the current state of research on this topic [Registration DOI:10.17605/OSF.IO/MKA82]. Empirical studies investigating the influence of EFs on human adaptation were eligible for inclusion, resulting in 11 studies and 3,733 participants among PubMed, Scopus, Web of Science, and PsycINFO. Results suggest an enhancing influence of EFs on the adaptation to new technologies, although findings were partially mixed. Inconsistent findings and the performed risk of bias assessment point toward a need for further high-quality research, e.g. on the influence of technological context. A model of possible covariates was proposed that provides guidance for a structured investigation of the process of human adaptation to technology. This review contributes to a better understanding of the association between EFs and human adaptation to new technologies.

Quantifying human thermal adaptation for indoor environments through field surveys and climate chamber experiments

ABSTRACT Thermal comfort boundaries established through climate chamber experiments are often found to significantly vary in real-world conditions based on the potential for thermal adaptation. In this context, this research aims to quantify the extent of thermal adaptation using a personalized ventilation system. We hypothesize that a personalized ventilation system can enhance thermal adaptation compared to real-world settings with limited opportunity for thermal adaptation. The study is based on thermal comfort surveys in mixed-mode open-plan office spaces of a humid subtropical region (Cwa), and a controlled climate chamber with a provision for personalized ventilation. We obtained 5629 subjective thermal responses through longitudinal field surveys accompanied by environmental measurements. In a climate chamber, 16 acclimatized volunteers were subjected to 140 different set-points with air temperature (Ta), relative humidity (RH), and air velocity (Va) variations yielding 19,200 subjective responses. A thermo-neutral temperature (Tn) of 26.5°C with an acceptability band of ±5.9°C was obtained through the field surveys. The Tn obtained from climate chamber surveys varied from 28.0°C to 29.3°C with an acceptability band of ±3.6°C depending on the ventilation rate. An empirical relationship between thermal sensation vote (TSV) and multiple environmental variables (Calidity) suggests 2°C higher Tn for Caliditychamber, Thermal adaptation correction factor of 2.1°C for warm-dry indoor environment and 1°C for warm-humid indoor environment were deduced through comparative analysis.

Personalized Model-Driven Interventions for Decisions From Experience.

Cognitive models that represent individuals provide many benefits for understanding the full range of human behavior. One way in which individual differences emerge is through differences in knowledge. In dynamic situations, where decisions are made from experience, models built upon a theory of experiential choice (instance-based learning theory; IBLT) can provide accurate predictions of individual human learning and adaptivity to changing environments. Here, we demonstrate how an instance-based learning (IBL) cognitive model, implemented in a cognitive architecture (Adaptive Control of Thought-Rational), can be used to model an individual's decisions in a cybersecurity defense task, accounting for both population average and individual variances. The same IBL model structure with identical architectural parameters generates the full range of human behavior through stochastic memory retrieval processes operating over and contributing to unique experiences. Recurrence quantification analyses allow us to look beyond average behavior between and within individuals to sequential patterns of trial-to-trial behavior. We show how model-tracing and knowledge-tracing techniques can be used to align the model to an individual in real time to drive adaptive and personalized signaling algorithms for a cybersecurity defense system. We also present a method for introspecting into the cognitive model to gain further insight into the cognitive salience of features factored into individual decisions. The combination of techniques provides a blueprint for personalized modeling of individuals. We discuss the results and implications of this adaptive and personalized method for cybersecurity defense and more generally for intelligent artifacts tailored to individual differences in domains such as human-machine teaming.