That blind spot is the post-operative patient. Fernández argues that in patients with poorly controlled gMG who undergo urgent abdominal surgery—say, emergency laparotomy for perforated diverticulitis—myasthenic or cholinergic crisis is too often treated as a diagnosis of exclusion rather than a condition demanding immediate priority intervention once clinically suspected. In practice, respiratory failure in this population is frequently labeled as multifactorial, attributed to sepsis, fluid overload, or post-operative deconditioning, rather than recognized as myasthenic crisis. The problem, she stresses, is not uncertainty about whether crisis belongs in the differential diagnosis; it is diagnostic ambiguity that delays crisis-specific therapy while clinicians sequentially rule out competing explanations.

The immunological logic behind the risk is layered. Immunosuppression can mask both clinical and septic signs, blunting the early warning signals that would normally trigger suspicion. Infection itself can drive autoantibody production, with single-cell immune profiling studies showing that neutrophils promote myasthenia gravis exacerbation through secretion of B-cell activating factor (BAFF). Prolonged fasting around surgery creates nutritional deficits, including hypophosphatemia, which directly impairs diaphragmatic contractility and is further aggravated by refeeding syndrome. Sepsis-related oxidative stress adds yet another hit, damaging the motor endplate where antibodies are already compromising signal transmission. Each mechanism compounds the others, and none announces itself clearly in a sedated, ventilated patient.

The confounders specific to the post-operative setting are formidable. Sedation and pain mask the oculobulbar signs—ptosis, diplopia, bulbar weakness—that typically herald a myasthenic crisis. Post-operative ileus introduces uncertainty about whether orally administered pyridostigmine is even being absorbed, complicating the distinction between myasthenic crisis, in which antibody-mediated weakness predominates, and cholinergic crisis, caused by excess anticholinesterase medication. And the growing number of patients maintained on biologic therapy raises a thorny question: does plasma exchange (PLEX) remain appropriate as first-line rescue in someone already receiving an FcRn antagonist or other biologic agent?

Fernández also challenges a widespread assumption embedded in the literature the review cites: that oculobulbar findings will accompany or precede respiratory failure, prompting early suspicion of crisis. In her clinical experience, myasthenic crisis in the critically ill post-operative patient can present as isolated hypercapnic respiratory failure with no oculobulbar signs at all. In an intubated patient on mechanical ventilation, cooperation-dependent pulmonary function testing is simply not feasible. Her proposed solution is bedside diaphragmatic ultrasonography, a rapid, repeatable tool that can support or exclude the suspicion of crisis without delaying management, and she argues it deserves explicit consideration in future guidance on crisis recognition in post-operative intensive care units.

At the heart of the commentary lies what Fernández calls the central clinical dilemma: the sequencing of exclusion versus treatment. The instinctive pattern—rule out fluid overload, uncontrolled sepsis, cholinergic excess, and mechanical or pulmonary causes before committing to crisis-specific immunotherapy—may be exactly backwards. Pure fluid overload rarely accounts on its own for the need for intubation; one would expect a response to diuretics and non-invasive ventilation, together with a distinct lung ultrasound pattern such as that described in the BLUE protocol. Moreover, the two mechanisms are not mutually exclusive, since respiratory muscle weakness can amplify even mild fluid overload. In a patient with poorly controlled gMG on biologic therapy and acute hypercapnic respiratory failure of neuromuscular pattern in the early post-operative period, the pretest probability of crisis is high enough that treatment should start in parallel with, not subordinate to, the exclusion of alternative diagnoses.

The emerging evidence base for acting quickly is thin but consistent. A systematic review by Tang and colleagues describes improvement with efgartigimod across 20 patients with myasthenic crisis, and a prospective case series by Song and colleagues reports ventilator weaning within a mean of 10.4 days. Adding weight to the argument for early intervention, absence of myasthenia gravis-specific immunosuppressive treatment at intensive care unit admission has been independently associated with prolonged weaning in a WEAN Safe analysis of ventilation outcomes. Together, Fernández contends, these findings support initiating specific treatment without delay, even while acknowledging that efgartigimod’s crisis evidence remains limited to case series rather than randomized trials.

The question of PLEX versus FcRn antagonism in patients already on biologic therapy, Fernández argues, deserves nuance rather than a blanket recommendation. Efgartigimod itself, by inhibiting FcRn, non-specifically reduces circulating IgG, which may also accelerate clearance of IgG-based therapeutic monoclonal antibodies—so it should not be assumed that efgartigimod better preserves concomitant biologic therapy than PLEX does. Biologic agents in gMG are also mechanistically heterogeneous. For B-cell-depleting agents such as rituximab, PLEX matters most shortly after infusion; once B-cell depletion is established, the pharmacodynamic effect may persist even as circulating drug levels fall. Complement inhibitors such as eculizumab and ravulizumab, by contrast, depend on continuous plasma concentrations, so lowering circulating levels—whether by PLEX or by FcRn inhibition—could more directly compromise their efficacy. Her commentary proposes a decision framework weighing hemodynamic and coagulation status, sepsis control, renal and volume status, and the specific biologic agent, since no single dimension alone determines the safest rescue choice.

Looking ahead, Fernández calls on future guidance to address three priorities explicitly: recognition of myasthenic crisis in patients whose post-operative respiratory failure is otherwise labeled multifactorial after urgent abdominal surgery; the role of diaphragmatic ultrasonography in atypical presentations lacking oculobulbar signs; and individualization of rescue therapy by biologic agent, mechanism, and timing, without implying superiority of any single modality in myasthenic crisis. As more patients with difficult-to-control gMG are maintained on biologic therapy, the population of immunosuppressed surgical patients facing this diagnostic minefield is set to grow, making the commentary’s message—that crisis should be treated in parallel with exclusion, not after it—one that intensive care and neurology teams alike cannot afford to ignore.

Subject of Research: Efgartigimod therapy and myasthenic crisis recognition in generalized myasthenia gravis

Article Title: Commentary: Efgartigimod for generalized myasthenia gravis: a comprehensive review of clinical evidence and future perspectives

Article References: Fernández, A. B. (2026). Commentary: Efgartigimod for generalized myasthenia gravis: a comprehensive review of clinical evidence and future perspectives. Frontiers in Neurology, 17, Article 1975630. https://doi.org/10.3389/fneur.2026.1975630

Image Credits: AI Generated

DOI: 10.3389/fneur.2026.1975630

Keywords: efgartigimod, generalized myasthenia gravis, myasthenic crisis, FcRn antagonist, plasma exchange, diaphragmatic ultrasonography, post-operative respiratory failure, neuromuscular disorders, Commentary, generalized, myasthenia, gravis

The central challenge B3GET tackles is one of scale: how do individual behaviors—what an animal eats, whom it mates with, whether it fights or flees—add up to the population and ecosystem patterns we observe in nature? Individual-based models, also called agent-based models, are theoretically ideal for bridging this gap because they explicitly represent every individual rather than averaging across a population. In practice, however, the field has struggled to realize that promise. Classical demographic models operate at the population level and ignore individual variation, while mechanistic individual-level models become too complex to scale. The result has been a proliferation of narrowly scoped, single-species models built ad hoc for specific systems—so many, and so redundant, that critics coined the YAAWN syndrome: “Yet Another Agent-Based Model… Whatever… Nevermind.”

B3GET was designed at the University of Minnesota, initially as a virtual laboratory for a course on primate ecology and social behavior, and refined through multiple semesters of classroom use beginning in fall 2014. Implemented in NetLogo 6.2.2, a freely available agent-based modeling program, it balances generality with mechanistic depth by drawing on behavioral ecology, evolutionary game theory, optimal foraging theory, life-history theory, resource competition, and artificial life. The environment is a toroidal grid of 10,000 PLANTS—simulated entities are written in ALL CAPS to distinguish them from real organisms—on which a population of ANIMAL agents lives, forages, breeds, and dies. User-defined controls set PLANT resource quality, spatial distribution, and seasonal cycles, driving the ecological pressures that shape everything downstream.

Each ANIMAL carries a genotype composed of heritable stimulus–response rules called genes. These rules determine which actions an individual performs—moving, eating, mating, fighting, helping, carrying offspring—and how much energy it allocates to each, based on the observable traits of nearby individuals and plants relative to its own internal state. Every action incurs a nonzero energetic cost, enforcing realistic tradeoffs: energy spent on growth cannot be spent on survival maintenance, movement, or reproduction. Survival itself is a probability that continuously declines with age and must be maintained through energetic investment, so individuals that fail to acquire sufficient food can die at any life stage. During sexual reproduction, genes mutate and recombine, allowing adaptive strategies and counterstrategies to emerge over generations without any explicit global fitness function.

The virtual plants themselves are dynamic, inspired by Conway’s Game of Life. PLANTS grow best within a preferred neighborhood size, controlled by user-set minimum and maximum neighbor parameters, and at specific times of the year. Higher neighbor settings generate discrete energy patches, while lower settings produce homogeneous distributions—and unexpectedly maze-like patterns emerged when the maximum-neighbor parameter was set low. The research team ran a full factorial experiment crossing four virtual primate species with 36 combinations of PLANT settings, each simulated twice, for 288 baseline runs executed at the Minnesota Supercomputing Institute over roughly six days in July 2021. Every run lasted 100,000 timesteps—approximately five adult lifespans—and all reached the end without crashing.

Persistence was tightly linked to resource stability. Across the 288 simulations, 204 populations—83.6 percent—survived the full duration, with olive baboon populations showing the highest extinction rate at 29.2 percent, followed by chimpanzees at 12.5 percent, geladas at 8.3 percent, and hamadryas baboons at just 5.6 percent. Populations declined or collapsed when mean PLANT abundance fell below roughly 1.5 energy units per cell and patchiness exceeded about 20, while abundance above 2.0 with patchiness under 10 supported populations of 150 to 250 individuals or more. Consistent increases in mean generation number over time confirmed that persistence reflected genuine generational turnover rather than survival of unusually long-lived individuals.

Evolutionary change was commonly observed. In one CHIMPANZEE simulation, the gene controlling bite.capacity—the energy-intake capacity of adults—rose gradually from an initial value of 0.001 to 0.014 by the end of the run, and adult bite.capacity increased significantly between ancestral and descendant generations, from 0.2384 to 0.3752 on average. Most conceptions were achieved by individuals with moderate to high bite capacity, demonstrating directional selection for greater energy-intake capacity. In contrast, a GELADA simulation showed evolutionary stasis in gestation duration: while the maternal gene evolved toward zero investment in triggering birth—consistent with the expectation that mothers conserve energy for future offspring—the overall distribution of gestation durations did not differ significantly between ancestral and descendant populations, suggesting stabilizing selection.

The behavioral results are the most striking. CHIMPANZEE males were strictly philopatric while nearly all females dispersed from their natal communities, and only about half of dispersing females successfully joined a new group—mirroring patterns documented at Gombe and Ngogo. Dispersal was costly: 56.7 percent of juvenile females that died did so after leaving their natal group but before joining another. CHIMPANZEE communities were the largest among the four virtual species, averaging 43.2 individuals, and exhibited high range fidelity at 91.3 percent, with home-range boundaries that closely followed the spatial distribution of PLANT energy. GELADA females were largely philopatric while 84.3 percent of males dispersed and transferred a mean of roughly 25 times over their lifetimes, forming the loose, shifting clusters characteristic of gelada multilevel societies. HAMADRYAS females dispersed to join recruiting males, residing in a median of 12 groups over their lifetimes, and in 67 of 72 simulations a gene enabling males to recruit follower males—initially set to zero—mutated to positive values, causing follower males to emerge on their own. OLIVE females never dispersed while all males did, though 69.2 percent of dispersing males died before successfully joining a new group, contributing to their species’ relatively low persistence.

What makes B3GET notable is its bottom-up architecture: species-typical societies emerged from genotype-encoded rules without any top-down enforcement. Small genotype edits produced large societal differences—the four PRIMATE genotypes shared 112 core genes governing general mammalian functions, with only about 10 species-specific genes each, and the genotype development process accelerated as genes were reused across species, taking several months for geladas but just one week for olive baboons. Because B3GET can emulate a broad range of animal species, it provides a promising approach for investigating questions in animal behavior and primate socioecology, both for research and education. Users with no coding background have successfully edited, saved, and reloaded population and genotype files to conduct new experiments in classroom laboratories, student projects, and conference workshops.

The framework is not without limitations. PLANT growth is governed by internal rule-based dynamics and does not use phenology, climate inputs, or externally derived resource maps, and timesteps and energy units are non-dimensional, reducing realism for system-specific forecasting. B3GET can identify combinations of mechanisms capable of reproducing empirical patterns, but successful reproduction does not demonstrate that the underlying mechanisms are uniquely correct—multiple processes may generate similar outcomes given the vast parameter space, on the order of more than 300 trillion possible ANIMAL behaviors when all potential genotype mutations are considered. The team plans longer simulations to examine oscillatory resource–consumer dynamics reminiscent of classical predator–prey interactions, multiple PLANT species within the same landscape, neural-network architectures that permit learning and plasticity, and calibration procedures that use empirical data to construct genotype rules more efficiently. For now, B3GET stands as a reusable foundation for multiscale ecological modeling—a digital sandbox where virtual primates live, evolve, and organize themselves into societies that look remarkably like our own living world.

Subject of Research: Simulating the socioecology of virtual primates using B3GET: a generalized behavioral modeling tool

Article Title: Simulating the socioecology of virtual primates using B3GET: a generalized behavioral modeling tool

Article References: Crouse, K. N., Lehman, C. L., & Wilson, M. L. (2026). Simulating the socioecology of virtual primates using B3GET: a generalized behavioral modeling tool. Individual-based Ecology, 2, Article e174844. https://doi.org/10.3897/ibe.2.174844

Image Credits: AI Generated

DOI: 10.3897/ibe.2.174844

Keywords: Simulating, socioecology, virtual, primates, B3GET, generalized, behavioral, modeling, tool, scientific research