Search Results (263)

Background/Objectives: LINAC-based, single-isocenter, non-coplanar, stereotactic radiotherapy (SRT) is an effective treatment for patients with multiple brain metastases (BMs). Within such a treatment plan, individual beams can be assigned to treat a subset of the metastases, this is referred to as multi-target beam setup (MTBS). This work evaluates and compares several strategies for MTBS. Methods: A planning study was performed, comparing plan quality parameters for plans resulting from several MTBS strategies, including two automated approaches. Each BM was individually prescribed a dose depending on its volume, resulting in treatment plans with multiple prescription doses. Paddick conformity index and Paddick gradient index were adapted to work with multiple prescription doses. Results: Given the same number of treatment beams, distributing BMs over treatment beams gave statistically significant improvements over targeting the BMs with all beams by 2% CI, 9% GI, 15% V15Gy, and 10% V5Gy. No statistically significant difference was found between different methods to distribute BMs over treatment beams. Increasing the number of treatment beams gave a further statistically significant improvement in plan quality at the cost of increased treatment time. Conclusions: MTBS is an important tool to increase the quality of non-coplanar LINAC-based stereotactic treatment plans for multiple brain metastases with individual dose prescriptions. MTBS can be automated to save planners a significant amount of time. The MTBS algorithm should be restricted in terms of the number of beams it can generate, to limit treatment times. Full article

Different strategies have been proposed to optimize injection mold cooling to reduce cycle time and improve efficiency. While recent research has focused on the design of additively manufactured conformal cooling inserts, the impact of mold maintenance conditions on cooling performance has received limited attention, particularly regarding the formation of limescale. This work presents a numerical modeling approach to quantify the combined effects of thermal resistance and hydraulic restriction caused by limescale accumulation in high-aspect-ratio cooling channels used in slender mold cores. An integrated thermal-fluid analysis is employed to evaluate coolant flow behavior and heat-transfer performance and to assess their coupled influence on cooling efficiency and part dimensional stability. The results show that, in slender cooling channels, even thin limescale deposits can significantly reduce cooling performance, with hydraulic restriction emerging as the dominant mechanism under the investigated conditions due to the reduced effective flow area. Design strategies that reduce effective frictional length and mitigate limescale deposition reduced part temperature by approximately 10 °C and shortened cooling time by about 17%. Further optimization of coolant flow conditions yielded an additional 65% reduction in cooling time. These findings highlight the importance of integrating cooling design with preventive maintenance to achieve robust injection molding performance. Full article

Nuclear lamins are the core molecular bridge linking the extracellular mechanical microenvironment to intranuclear gene regulation, and play a central regulatory role in cellular mechanosensation and mechanotransduction. Here, we systematically integrate the latest global research progress on nuclear lamins, delineating the cascade regulatory mechanism by which lamins mediate the transmission of mechanical signals across the nuclear envelope and the subsequent regulation of chromatin remodeling and epigenetic modification, with a focus on the molecular characteristics and functional specificity of distinct nuclear lamin subtypes and their interaction modes with the Linker of Nucleoskeleton and Cytoskeleton complex (LINC complex) and chromatin. Existing studies have established that nuclear lamins are mainly divided into three categories: A-type lamins (Lamin A/C), B-type lamins (Lamin B1, B2), and germ cell-specific subtypes. Among these, A-type lamins directly determine the mechanical stiffness of the nucleus and serve as the core mediators of intranuclear mechanical signal transduction. Each subtype of B-type nuclear lamins has a well-defined, non-redundant functional division: Lamin B1 and Lamin B2 indirectly maintain nuclear structural stability and regulate epigenetic status by anchoring facultative heterochromatin and constitutive heterochromatin, respectively. Notably, Lamin A/C distributed in the nucleoplasm also bears significant mechanical tension, which challenges the long-standing view that the mechanical functions of nuclear lamins are restricted to the nuclear envelope region. After mechanical force is transmitted across the nuclear envelope to nuclear lamins via the LINC complex, it can regulate the spatial conformation of chromatin and epigenetic modifications, thereby determining core cellular life activities including proliferation, differentiation, and migration. Dysregulation of this pathway is closely associated with a wide spectrum of human diseases, including cardiovascular diseases, progeria, muscular dystrophy, and neurodevelopmental disorders. Taken together, this review systematically delineates the hierarchical regulatory network of the “LINC complex–nuclear lamina–chromatin” axis, advances our understanding of the fundamental principles of cellular mechanobiology, and provides a theoretical framework for deciphering the pathological mechanisms and developing targeted therapeutic drugs for related diseases. Full article

Converting carbon dioxide (CO₂) into value-added chemicals and/or capturing it before emission are complementary strategies to mitigate rising atmospheric CO₂ levels. Copper-based materials are widely investigated for CO₂ conversion because Cu can bind and electronically activate CO₂ and related intermediates. In this computational research, an evaluation of CO₂ activation in Cu_xSc_γ nanoclusters (Cu₃Sc, Cu₂Sc₂, and CuSc₃) anchored on a graphene bilayer doped with three nitrogen atoms (graphene-3N) was performed using conformational screening and thermochemical adsorption analysis at 298.15, 300, and 400 K. Initially, the Cu₃Sc, Cu₂Sc₂, and CuSc₃ nanoclusters were optimized and characterized (relative energy, multiplicity, and electronic characteristics), and the support model (graphene-3N bilayer) was validated by comparing free geometry with partially restricted geometry, corroborating minima through vibrational analysis. Subsequently, CO₂ adsorption/activation on Cu_xSc_γ @graphene-3N was evaluated, and ΔH and ΔG values were calculated. Ultimately, based on the ΔG(T) values, the Sabatier regimes were established, where it was observed that Cu₃Sc exhibits moderate exergonic adsorption (ΔG = −76.07, −67.31, and −58.92 kJ·mol⁻¹ at 298.15, 350, and 400 K). In contrast, Cu₂Sc₂ exhibits intense adsorption (−165.02, −156.36, and −148.04 kJ·mol⁻¹), and CuSc₃ results in practically irreversible fixation (−293.98, −287.32, and −279.09 kJ·mol⁻¹), giving priority to Cu₃Sc as the most optimal cluster in terms of activation-regeneration. Full article

Both frequentist and Bayesian approaches are presented in this paper for a multiple step-stress accelerated life test. It is assumed that the lifetime distributions of experimental units under each stress level conform to a two-parameter exponentiated Rayleigh distribution. Additionally, the distributions corresponding to each stress level are related via the cumulative exposure model. In a step-stress experiment, with the applied stress level on the rise, the failure process of experimental units is accelerated, which gives rise to a reduction in their expected lifetime. This order restriction is explicitly incorporated into the statistical inference. Under the classical framework, via reparameterization, the order-restricted maximum likelihood estimates (MLEs) of unknown parameters are provided, and asymptotic confidence intervals are constructed based on the observed Fisher information matrix. In the Bayesian framework, we conduct the Bayesian analyses and obtain credible intervals using the importance sampling techniques. Extensive simulation studies are conducted, and a real dataset is analyzed for illustrative purposes. Full article

Background/Objectives: Natural killer (NK) cells are key innate lymphoid cells that restrict tumour progression by secreting proinflammatory cytokines and directly lysing malignant cells, with their activity tightly regulated by a balance of activating and inhibitory surface receptors. The natural cytotoxicity receptor NKp44 is induced on NK cells following stimulation with IL-2 or IL-15 and recognizes platelet-derived growth factor D (PDGF-DD) as a ligand. Mechanistic interpretation of NKp44 signalling upon PDGF-DD engagement is confounded by the existence of three distinct NKp44 isoforms (NKp44-1, -2, and -3), each capable of initiating divergent intracellular signalling cascades. Unlike NKp44-2 and -3, NKp44-1 encodes a cytoplasmic tyrosine residue (Y238) that conforms to a putative immunoreceptor tyrosine-based inhibition motif (ITIM) and has been reported to suppress NK cell effector functions in some contexts. However, it remains unclear whether the NKp44 isoforms are translated and expressed in NK cells, and formal evidence defining NKp44-1 signalling in response to engagement by PDGF-DD is lacking. Methods: In this study, we used C-terminal targeting monoclonal antibodies (mAbs) and a NFAT-GFP reporter system to define the expression and signalling properties of NKp44 isoforms in response to PDGF-DD. Results: We demonstrate protein expression of NKp44-1 and NKp44-2-/3 receptors in IL-2 expanded NK cells. We further show that NKp44-1 transduces activating rather than inhibitory signals when engaged by PDGF-DD ligand, albeit weaker than NKp44-3. Intriguingly, we find that Y238 is dispensable for NKp44-1 activating signalling and instead functions as a YXXΦ internalisation motif. Conclusions: Collectively, these findings provide the first evidence that the NKp44-1 and NKp44-2/3 isoforms are expressed in NK cells and establish that PDGF-DD activates signalling through NKp44-1 independently of Y238. This work lays the foundations for future studies investigating how PDGF-DD sensing by the different NKp44 isoforms shapes immune functions in different physiological and pathological contexts. Full article

Background: Propofol is used worldwide as a short-acting intravenous anesthetic in clinical practice; however, side effects such as injection pain and respiratory depression remain clinically relevant. Therefore, identification of safer propofol analogs is required. Method: In response to the urgent need for optimized potency and reduced side effects, a series of dihydrobenzofuran derivatives were designed as expectedly better propofol analogs through conformational restriction. A loss of righting reflex assay was conducted to evaluate the sedative/anesthetic properties of the synthesized compounds, and a respiratory depression test was performed for safety assessment. Results: Most of the designed compounds were shown to possess promising anesthetic properties as propofol analogs. The represented 53A had higher potency and a wider safety margin (ED₅₀:3.898 vs. 8.040 mg/kg in mice; 2.985 vs. 5.894 mg/kg in rats; TI (therapeutic index): 6.172 vs. 5.061 in mice; 4.362 vs. 2.580 in rats) than propofol, and fast onset and recovery times were maintained. The phosphate prodrug 56A also exhibited better efficiency and safety than fospropofol, along with a longer duration and faster recovery time in sedative profiles. Furthermore, alleviation of the adverse effects of respiratory depression has been demonstrated. Conclusions: 53A has the potential to be selected as a preclinical candidate for clinical development. Full article

If our observable Universe is only a tiny region of a vastly larger and conformally older spacetime, then the usual formulations of the classical flatness and horizon problems of the Hot Big Bang can be reinterpreted as artifacts manifesting an observational selection effect; we occupy a small causal domain of a much larger causally-connected and possibly non-flat spacetime. A sufficiently large positive cosmological constant, $\Lambda$, sets the future asymptotic horizon scale of the observable Universe, ∼${\Lambda }^{-1/2}$, thereby implying that the observable Universe may simply be a minute patch of a far larger pre-existing one, hereafter a Small Patch Hypothesis. Importantly, this observational bound is purely geometric; regardless of when the Universe is observed, the maximum accessible scale is finite and fixed by $\Lambda$, independent of inflationary dynamics, anthropic arguments, or assumptions about the global hosting spacetime. The externally possibly frozen past-eternal state implied by a pre-existing, causally connected spacetime motivates, but does not strictly require, viewing the perturbation field as being in (or arbitrarily close to) a coarse-grained maximum-entropy—equilibrium—configuration. Conditionalizing only on fixed mean and variance, a Gaussian distribution uniquely emerges, while the absence of entropy gradients corresponds to adiabaticity. In this work these features are therefore treated as plausible maximum-ignorance priors for super-horizon perturbations, rather than as rigorously derived consequences of a fully developed microscopic notion of gravitational entropy. In this sense, inflation becomes one viable realization of the proposed Small Patch Hypothesis. Here, one particular non-inflationary alternative is considered for illustrative purposes in which a primordial spectrum $P_{\zeta }\left(k\right)$ of the gauge-invariant perturbation $\zeta$ that pre-dates the Big Bang grows logarithmically toward large scales, $k\to 0$, and in fact diverges at some finite $k_c$. If $k_c\ll {\Lambda }^{-1/2}$, then our local cosmic patch probes only the regime where $\zeta \ll 1$ and appears exceptionally smooth. Over the comparatively narrow observable window, this $P_{\zeta }\left(k\right)$ mimics a slightly red-tilted, inflation-like spectrum. Rather than introducing high-energy new fields, this perspective frames large-scale homogeneity, isotropy, Gaussianity, adiabaticity, and the observed thermodynamic Arrow of Time as possible consequences of restricted observational access to a much larger Universe in equilibrium, rather than signatures of a unique early-Universe mechanism. Current observations cannot distinguish this logarithmically running spectrum from the standard power-law one, but future probes—for example high-resolution 21-cm measurements of the Dark Ages—may be able to falsify it. Full article

The blood–brain barrier (BBB) is a major obstacle to the development of brain-targeted drug delivery systems, restricting greater than 98% of small molecules (<500 Da) and virtually all large-molecule drugs from entering the brain tissues from the bloodstream, resulting in suboptimal drug doses and therapeutic failure in the treatment of Alzheimer’s disease (AD). However, the advent of nanotechnology has provided significant solutions to the BBB challenges, enabling particle size reduction, enhanced drug solubility, reduced premature drug degradation, extended and sustained drug release, enhanced drug transport across the BBB, increased drug target specificity and enhanced therapeutic efficacy. In corollary, a library of brain-targeted surface-functionalized nanotherapeutics has been widely reported in the current literature. These promising in vitro, in vivo and pre-clinical results from the existing literature provide quantitative evidence for the relative clinical utility of each of the techniques, indicating remarkable capacity for brain-targeted carrier systems; many of them are still being tested in human clinical trials. However, despite the recorded research successes in drug transport across the BBB, there are currently no clinically proven medications that can slow or reverse the progression of AD because most of the novel therapeutics have not been successful during the clinical trials. Therefore, the main option for the treatment of AD is symptomatic treatment using cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists. Although these therapies help to alleviate symptoms of AD and improve patients’ quality of life, they neither slow the progression of disease nor cure it. Thus, an effective disease-modifying therapy for the treatment of AD is an unmet clinical need. It is apparent that a deeper understanding of the structural complexity and controlling dynamic functions of the BBB in tandem with a comprehensive elucidation of AD pathogenesis are crucial to the development of novel nanocarriers for the effective treatment of AD. Therefore, this narrative review describes the contextual analysis of several promising strategies that enhance brain-targeted drug delivery across the BBB in AD treatment and recent research efforts on two major AD biomarkers that have revolutionized AD diagnosis, amyloid-beta plaques and phosphorylated tau protein tangle, as potential targets in AD drug development. This has led to the Food and Drug Administration (FDA)’s approval of two intravenous (IV) anti-amyloid monoclonal antibodies, Lecanemab (Leqembi^®) and Donanemab (Kisunla^®), which were developed based on the Aβ cascade hypothesis for the treatment of early AD. This review also discusses the recent shift in the Aβ cascade hypothesis to Aβ oligomer (conformer), a soluble intermediate of Aβ, which is the most toxic mediator of AD and could be the most potent drug target in the future for a more accurate and effective drug development model for the treatment of AD. Furthermore, various promising nanoparticle-based drug carriers (therapeutic nanoparticles) that were developed from intensive research are discussed, including their clinical utility, challenges and prospects in the treatment of AD. Overall, it suffices to state that the advent of nanotechnology provided several innovative techniques for overcoming the BBB and improving drug delivery to the brain; however, their long-term biosafety is a relevant concern. Full article

Synucleinopathies, including Parkinson’s disease (PD), are neurodegenerative disorders characterized by aberrant aggregation of α-synuclein (α-syn), a presynaptic protein with an intrinsic disorder nature. The transition of soluble monomers into oligomeric and fibrillar species represents a key molecular event driving neuronal dysfunction and neurodegeneration. Emerging evidence suggests that nutraceuticals, bioactive compounds derived from dietary sources, can modulate α-syn aggregation at multiple conformational stages. Polyphenols, alkaloids, ginsenosides, and food-derived peptides interfere with α-syn structure and assembly, suppressing the formation of toxic oligomer species and promoting the clearance of misfolded assemblies. Despite this potential, clinical translational of nutraceuticals is currently limited by poor systemic bioavailability and restricted central nervous system penetration due to blood–brain barrier constraints, which have largely confined research to preclinical studies. In this context, this review summarizes current knowledge of nutraceutical interventions targeting the conformational landscape of α-syn and highlighting both direct and indirect molecular mechanisms with involved in aggregation-prone species. Furthermore, we critically examine key challenges related to bioavailability and clinical translation, focusing on advanced delivery systems and precision-based approaches to enhance neuroprotective efficacy and support the potential of nutraceuticals as novel or adjunctive therapeutic strategies for PD. Full article

Wee1-like protein kinase 2 (WEE2) is an oocyte-specific kinase that regulates meiotic arrest and fertilization. Its largely restricted expression in female germ cells and absence in somatic tissues make it a highly selective target for reproductive health interventions. Despite its central role in human fertility, no clinically approved WEE2 modulator is available. In this study, we employed an integrated in silico approach that combines structure-based virtual screening, molecular dynamics (MD) simulations, and MM-PBSA free-energy calculations to identify repurposed drug candidates with potential WEE2 inhibitory activity. Screening of ~3800 DrugBank compounds against the WEE2 catalytic domain yielded ten high-affinity hits, from which Midostaurin and Nilotinib emerged as the most mechanistically relevant based on kinase-targeting properties and pharmacological profiles. Docking analyses revealed strong binding affinities (−11.5 and −11.3 kcal/mol) and interaction fingerprints highly similar to the reference inhibitor MK1775, including key contacts with hinge-region residues Val220, Tyr291, and Cys292. All-atom MD simulations for 300 ns demonstrated that both compounds induce stable protein–ligand complexes with minimal conformational drift, decreased residual flexibility, preserved compactness, and stable intramolecular hydrogen-bond networks. Principal component and free-energy landscape analyses further indicate restricted conformational sampling of WEE2 upon ligand binding, supporting ligand-induced stabilization of the catalytic domain. MM-PBSA calculations confirmed favorable binding free energies for Midostaurin (−18.78 ± 2.23 kJ/mol) and Nilotinib (−17.47 ± 2.95 kJ/mol), exceeding that of MK1775. To increase the translational prioritization of candidate hits, we place our structure-based pipeline in the context of modern machine learning (ML) and deep learning (DL)-enabled virtual screening workflows. ML/DL rescoring and graph-based molecular property predictors can rapidly re-rank docking hits and estimate absorption, distribution, metabolism, excretion, and toxicity (ADMET) liabilities before in vitro evaluation. Full article

Promoting the development of aerospace vehicles toward structural–functional integration and intelligent sensing is a key strategy for achieving lightweight, high-reliability, and autonomous operation and maintenance of next-generation aircraft. However, traditional external sensors face significant limitations because of their bulky size, installation challenges, and incompatibility with aerodynamic surfaces. These issues are particularly pronounced on complex, high-curvature substrates, where achieving conformal bonding is difficult, thus restricting their application in critical components. In this study, aerosol jet printing (AJP) was employed to directly fabricate silver nanoparticle-based temperature sensors with real-time monitoring capabilities on the surface of high-curvature stainless steel sleeves, which serve as typical engineering components. This approach enables the in situ manufacturing of high-precision conformal sensors. Through optimized structural design and thermal treatment, the sensors exhibit reliable temperature sensitivity. Microscopic characterization reveals that the printed sensors possess uniform linewidths and well-defined outlines. After gradient sintering at 250 °C, a dense and continuous conductive path is formed, ensuring strong adhesion to the substrate. Temperature-monitoring results indicate that the sensor exhibits a nearly linear resistance response (R² > 0.999) across a broad detection range of 20–200 °C. It also demonstrates high sensitivity, characterized by a temperature coefficient of resistance (TCR) of 2.15 × 10^−3/°C at 20 °C. In repeated thermal cycling tests, the sensor demonstrates excellent repeatability and stability over 100 cycles, with resistance fluctuations kept within 0.5% and negligible hysteresis observed. These findings confirm the feasibility of using AJP technology to fabricate high-performance conformal sensors on complex surfaces, offering a promising strategy for the development of intelligent structural components in next-generation aerospace engineering. Full article

P-glycoprotein (P-gp) is an ATP-driven transporter that effluxes a wide range of xenobiotics from cells, and its overexpression is a primary cause of multidrug resistance (MDR) in cancer. It is well-established that P-gp functions through conformational changes, yet its large-scale structural dynamics at work have been unexplored. Here, we directly visualized single P-gp molecules reconstituted in nanodiscs using high-speed atomic force microscopy (HS-AFM). The HS-AFM movies revealed that P-gp is intrinsically dynamic in its apo state, with its nucleotide-binding domains (NBDs) undergoing large, spontaneous opening and closing motions. However, addition of ATP stabilized a conformation characterized by NBD proximity with a strong tendency toward closure. We then leveraged this dynamic viewpoint to elucidate the relationship between Elacridar’s function and the resulting structural dynamics of P-gp. Elacridar is designed to overcome multidrug resistance (MDR) in cancer and acts as a potent dual inhibitor of both P-gp and the Breast Cancer Resistance Protein (BCRP), effectively blocking the drug efflux function of these transporters. This inhibitor has suggested concentration-dependent function: it is effluxed as a substrate at low concentrations and acts as an inhibitor at high concentrations. Our direct observations revealed that low concentrations induced active dynamics in P-gp, whereas high concentrations severely restricted its motion, leading to a rigid, non-productive state. Our study provides critical insights into how observing molecular motion itself can unravel complex biological mechanisms. Full article

Carbapenem-resistant Enterobacterales (CREs) pose a critical threat to global public health, largely driven by the enzymatic activity of Klebsiella pneumoniae carbapenemase-2 (KPC-2), a class A serine β-lactamase that hydrolyzes most β-lactam antibiotics. While β-lactamase inhibitors like avibactam offer temporary relief, emerging KPC variants demand novel, sustainable inhibitory scaffolds. This study aimed to identify and characterize potential natural inhibitors of KPC-2 from Pongamia pinnata, leveraging a comprehensive in silico workflow. A curated library of 86 phytochemicals was docked against the active site of KPC-2 (PDB ID: 3DW0). The top-performing ligands were subjected to ADMET profiling (pkCSM), and 100 ns molecular dynamics simulations (GROMACS) to evaluate structural stability and interaction persistence, using avibactam as control. Ponganone V exhibited the most favorable binding energy (−9.0 kcal/mol), engaging Ser70 via a hydrogen bond and forming π–π interactions with Trp105. Glabrachromene II demonstrated a broader interaction network but reduced long-term stability. ADMET analysis confirmed high intestinal absorption, non-mutagenicity, and absence of hERG inhibition for both ligands. Molecular dynamics simulations revealed that Ponganone V maintained compact structure and stable hydrogen bonding throughout the 100 ns trajectory, closely mirroring the behavior of avibactam, whereas Glabrachromene II displayed increased fluctuation and loss of compactness beyond 80 ns. Principal Component Analysis (PCA) further supported these findings, with Ponganone V showing restricted conformational motion and a single deep free energy basin, while avibactam and Glabrachromene II exhibited broader conformational sampling and multiple energy minima. The integrated computational findings highlight Ponganone V as a potent and pharmacologically viable natural KPC-2 inhibitor, with strong binding affinity, sustained structural stability, and minimal toxicity. This study underscores the untapped potential of Pongamia pinnata phytochemicals as future anti-resistance therapeutics and provides a rational basis for their experimental validation. Full article

Sestrin2 (SESN2) is a highly conserved stress-inducible protein that serves as a central hub for integrating cellular responses to nutrient availability, oxidative stress, and endoplasmic reticulum (ER) stress. A key function of SESN2 is its role as a direct sensor for the branched-chain amino acid (BCAA) leucine, which modulates the activity of the mechanistic target of rapamycin complex 1 (mTORC1), a master regulator of cell growth and metabolism. While the functional link between leucine and SESN2 is well-established, the precise molecular determinants that confer its high specificity for leucine over other BCAAs, such as isoleucine and valine, remain poorly understood. This study employs an integrated computational approach, spanning atomic interactions to global protein dynamics, combining molecular docking, extensive all-atom molecular dynamics (MD) simulations, and binding free energy calculations, to elucidate the structural and dynamic basis of BCAA-SESN2 recognition. Our thermodynamic analysis reveals a distinct binding affinity hierarchy (Leucine > Isoleucine > Valine), which is primarily driven by superior van der Waals interactions and the shape complementarity of leucine’s isobutyl side chain within the protein’s hydrophobic pocket. Critically, a quantitative analysis of the conformational ensemble reveals that leucine induces a dramatic collapse of the protein’s structural heterogeneity. This “conformational locking” mechanism funnels the flexible, high-entropy unbound protein—which samples 35 distinct conformations—into a sharply restricted ensemble of just 9 stable states. This four-fold reduction in conformational freedom is accompanied by a kinetic trapping effect, which significantly lowers the rate of transitions between states. This process of conformational selection stabilizes a well-defined, signaling-competent structure, providing a comprehensive, atom-to-global-scale model of SESN2’s function. In the context of these findings, this work provides a critical framework for understanding SESN2’s complex role in disease and offers a clear rationale for the design of next-generation allosteric therapeutics. Full article