We present a highly interpretable and efficient machine learning framework for predictive and generative modeling of adsorption energies on surfaces using subgraph isomorphic decision trees (SIDTs). Extracting graph representations of 344 756 relaxed geometries and their associated adsorption energies from the OC20 database, we used them to train a 24 777-node SIDT that achieves 0.36 eV MDAE, 0.54 eV MAE, and 0.82 eV RMSE. We then developed and implemented novel techniques to use SIDTs as generative models enabling efficient catalyst optimization for arbitrary objective functions and constraints as a function of the adsorption energies and prediction uncertainties of multiple adsorbates and the catalyst structure itself. In particular, our SIDT provides substructure representations of the subdistributions of adsorption energy, rather than mere samples from the subdistributions, as is commonly done in traditional generative modeling. We show how this can be exploited for efficient and interpretable catalyst active site design in two examples. For the ammonia decomposition reaction sequence, we show that we are able to use our generative techniques to minimize the overall barrier height of the sequence generating catalyst substructures predicted to decrease the overall barrier from 2.7 eV on Pt(111) to 0.4 eV. We also discuss how we can exploit the accurate SIDT uncertainties and the interpretability of the SIDT to identify regions of chemical space that are in need of improved coverage and might be improved using active-learning schemes.
Vocal communication behavior in anurans is energetically expensive and can reveal caller locations, making them vulnerable to predation. Thus, it is likely that calls have been selected to minimize energy and make signals difficult to locate. In earlier work, Jones and Ratnam (2023) suggested that differences in the acoustic receivers of anurans and mammals may be exploited to make anuran calls difficult for mammals to locate, thereby reducing some if not all predation pressure. To test some of these ideas, this study examined sound localization performance in human listeners in response to a synthetic narrowband frog call (pulsed calls of the gray treefrog Dryophytes versicolor, 28% duty-cycle) and its variations, in a dichotic listening task using interaural time differences (ITD) alone. Sounds which were easy to locate (positive control) and difficult to locate (negative control) were also tested. Localization performance in response to synthetic calls (64%) lay between those of positive control (86%) and negative control (32%, chance level). We argue that differences in performance were largely a function of call bandwidth. Among all the variations of calls that were tested (excluding controls), the synthetic call most closely resembling the gray treefrog call had the lowest call energy, the narrowest spectral bandwidth, and was the most difficult to localize. We suggest that calls may have been selected to keep their energy as low as possible by reducing their duty cycle and reducing spectral leakage to maintain narrowband characteristics.
Mantle plumes are a fundamental component of the Earth's convective regime, but their long-term behaviour remains poorly understood. The Iceland plume, which is bisected by the Mid-Atlantic Ridge, presents an opportunity to constrain plume evolution. Here, we reconstruct its influence upon seafloor spreading by exploiting the geochemistry of basalts drilled south of Iceland during International Ocean Discovery Program (IODP) Expedition 395. Trace element and isotopic measurements, combined with contextual geophysical observations, demonstrate that plume influence waned after continental break-up at  ~ 55 Ma, collapsed rapidly at  ~ 38 Ma, and then was progressively re-established to the present day. Recovered  ~ 32 Ma basalt samples have rare earth element compositions equivalent to mid-Atlantic Ridge dredge samples located south of the present-day plume influence. These compositions can be modelled by passive upwelling and melting of depleted MORB mantle with a potential temperature of  ~ 1300 ∘C. In contrast, basalts recovered from younger (i.e. 0-14 Ma) sites show unequivocal evidence for plume influence. Together, these results imply dramatic changes in the extent of plume-ridge interaction across the North Atlantic region, providing key chemical constraints for geodynamic models of plume evolution and its imprint upon the geological record.
Programmable photonic networks carry out universal unitary functions by independently operating on the amplitude and phase of guided light. Exploiting the reconfigurability and spatiospectral degrees of freedom of these systems, the majority of state-of-the-art photonics applications, ranging from microwave photonics to photonic computing and optical communication links, can be demonstrated in one unified system. Existing techniques require a large footprint due to weak modulation efficiency, and continuous power dissipation to maintain the configured state. Here, we demonstrate a programmable recirculating mesh unit cell based on the nonvolatile low-loss phase-change material Sb2Se3. The demonstrated devices achieve an ultrashort active length (<10 μm, more than 15 times smaller than the current state of the art of competing technologies) and zero static power, in combination with high-extinction switching (>20 dB), broadband operation (>15 nm), and low insertion loss (<2 dB). This work forms the basis for nonvolatile field-programmable coupler arrays (nv-FPCAs) and zero-static power reconfigurable optical interconnects.
Ubiquitination, a central post-translational mechanism, shapes the amplitude and duration of cellular signalling. Josephin domain-containing 2 (JOSD2), a Machado-Joseph disease (MJD) family deubiquitinase, eliminates ubiquitin moieties from ubiquitin-conjugated substrates and tunes proteostasis and signalling outputs. Emerging evidence links aberrant JOSD2 activity to diverse pathological states. This review, aims to summarize the current data regarding of JOSD2 as a regulatory node in ubiquitin-dependent signalling and discuss the role of its dysregulation in malignancies through interconnected mechanisms, including metabolic rewiring, rewiring of oncogenic signalling circuits, and altered therapeutic responses that promote resistance. Furthermore, the context-dependent roles of JOSD2 beyond cancer emphasized, with reported pathogenic or protective functions in cardiovascular disorders and inflammatory bowel disease. The literature highlights JOSD2 as a signalling-relevant deubiquitinase with pleiotropic, context-dependent functions. This review discusses key knowledge gaps-such as incomplete substrate mapping and determinants of tissue specificity-and outlines translational opportunities and challenges for exploiting JOSD2 as a biomarker and therapeutic target.
Protein lysine crotonylation (KCro), a metabolically linked epigenetic modification, lacks comprehensive profiling methods due to expensive, cross-reactive antibodies. Herein, we developed an antibody-free strategy, MPA-KCro, exploiting 2-mercaptophosphonic acid (2-MPA) as a bifunctional probe. The thiol group undergoes selective Michael addition with the α,β-unsaturated crotonyl moiety, while the phosphonate handle enables efficient Ti4+-IMAC enrichment. Critically, the bio-orthogonal C-P bond resists enzymatic hydrolysis, preventing interference from endogenous phosphoproteins, and a characteristic immonium ion (m/z 294.09) enables unambiguous site-specific determination of Kcro. Applied to HeLa cell histones, the MPA-KCro method identified 22 crotonylation sites, including well-characterized residues (H3.1 K23, H2B K5) and 12 novel sites, enabling proteome-wide crotonylation mapping and functional investigation of the emerging epigenetic mark.
Two-dimensional (2D) inorganic materials provide a powerful platform for electronic-structure engineering through precise control of the composition and crystal structure. While cation substitution has been widely exploited in oxide nanosheets, anion engineering remains far less developed, particularly in molecularly thin oxynitride systems with controlled nitrogen doping. Here, we report a generalizable route to nitrogen-doped perovskite oxide nanosheets that overcomes long-standing challenges associated with nitridation and structural instability. Using Dion-Jacobson (DJ)-type perovskite oxynitrides, RbSr2(Nb1-xTax)3O10-yNy, as a model platform, we demonstrate that the combination of cation substitution and nitrogen doping enables systematic modulation of both composition and electronic band structure in 2D perovskites. DJ-type perovskite oxynitrides with substantial nitrogen incorporation can be obtained via an unexpected transformation from pseudo-Ruddlesden-Popper-type phases, induced by alkali metal salt-assisted nitridation followed by simple aqueous treatment, without altering the anion composition. These oxynitrides are subsequently exfoliated into single-layer nanosheets that preserve the perovskite framework and the designed cation stoichiometry. Direct determination of both valence and conduction band edges by combined ultraviolet and inverse photoelectron spectroscopy reveals composition-dependent, nonmonotonic band alignment behavior that cannot be resolved by indirect optical or electrochemical approaches. This work establishes an integrated materials and characterization framework for the rational electronic-structure design in 2D oxynitride nanosheets.
Lentil (Lens culinaris Medik.), a nutrient-rich legume cultivated worldwide, plays a vital role in combating malnutrition and hidden hunger. Understanding the genetic architecture underlying key phenological and agronomic traits in lentil is crucial for accelerating molecular breeding. In this study, genome-wide association mapping was conducted using 142 genetically diverse lentil accessions, evaluated across two field environments over two years. High-throughput sequencing generated 34,995 high-quality single-nucleotide polymorphisms, which were used for genetic characterization and for the identification of marker-trait associations for phenological and yield-associated traits. Population structure analysis identified three subpopulations (K = 3), with UPGMA clustering showing a similar pattern. Association mapping was performed using multi-locus models and further confirmed through a single-locus generalized linear model. A total of 64 significant associations were identified, of which Chr5_342836807 and Chr6_200603138 were consistently detected across all environments for days to 50% flowering. Putative candidate genes located near these phenology-associated loci such as abscisate β-glucosyltransferase, pentatricopeptide repeat proteins, and transcription factors from the MYB, MADS-box, and GRAS families are likely involved in flowering-time regulation in lentil. These findings reveal novel associations between genetic variants and complex traits and identify putative genes that may be exploited in marker-assisted selection and genomic prediction strategies. The online version contains supplementary material available at 10.1007/s12298-026-01739-x.
Quadrupolar nuclei with half-integer spin, which represent 66 % of the NMR-active isotopes, are present in a wide range of materials with applications in various fields, including heterogeneous catalysis, optoelectronics and energy. The solid-state NMR spectra of these isotopes are affected by quadrupolar interactions, which provide unique information on the local environment of these nuclei, in addition to their chemical shifts. These anisotropic interactions, which are generally larger than other internal spin interactions, split and broaden the NMR transitions, which reduce the sensitivity for the detection of these isotopes. In addition, the large dimensions of their density matrices and the numerous NMR transitions complicate the spin dynamics and can reduce the efficiency of coherence transfers, such as cross-polarization under magic-angle spinning (CPMAS), which is widely employed to boost the sensitivity for the detection of spin-1/2 isotopes. In the last decade, sensitivity gains provided by dynamic nuclear polarization (DNP) have been exploited to detect half-integer quadrupolar nuclei in solids. This review discusses the advantages and limitations of the different DNP-NMR techniques that have been proposed for the detection of these isotopes, including direct excitation and CPMAS, and two more recently introduced methods called PRESTO (Phase-shifted Recoupling Effects by Smooth Transfer of Order) and D-RINEPT (Dipolar-mediated Refocusing Insensitive Nuclei Enhanced by Polarization Transfer). We also show how these techniques can be applied to obtain new insights on the structure of materials, notably of their surfaces, and hence, contribute to extend the range of applications of the surface-enhanced NMR spectroscopy (DNP-SENS).
Controlling the quantum coherence of excitons in bulk semiconductors is crucial for developing scalable quantum photonic platforms. Here, we demonstrate active control of excitonic quantum beats in the 1S orthoexciton in cuprous oxide (Cu2O) via strain engineering. By applying uniaxial bending stress, we induce and precisely tune the fine structure splitting of the 1S orthoexciton. The split states display orthogonal linear polarizations, enabling selective preparation of coherent superpositions. The presence of a quantum beating signal confirms coherent coupling. Our results demonstrate that the beat frequency can be continuously tuned by changing the applied stress, and the beat amplitude can be switched on and off by rotating the detection polarization. These strain-controlled quantum interference effects not only shed light on the fundamental excitonic dynamics but also open avenues for exploiting Cu2O's unique properties in quantum optics and information processing.
Oral squamous cell carcinoma (OSCC) is one of the most common cancers globally, accounting for a significant portion of head and neck malignancies. Most cases are preceded by oral potentially malignant disorders (OPMD), which may progress through histological changes such as hyperplasia, hyperkeratosis, and oral epithelial dysplasia (OED). A key factor in this progression is immune evasion, particularly through the PD-1/PD-L1 pathway, which tumour cells exploit to escape immune surveillance. Although therapeutic strategies targeting PD-1/PD-L1 are promising, their expression patterns and prognostic significance in OED and OSCC remain underexplored. This study aimed to evaluate and compare the immunohistochemical expression of PD-1 and PD-L1 in OED and OSCC, including their different grades. An analytical cross-sectional study was conducted with 66 samples (33 each of OED and OSCC). Diagnoses were confirmed histopathologically. Samples were stained using immunohistochemistry for PD-1 and PD-L1, and expression was assessed using the immunoreactivity score (IRS). Statistical analysis was performed using SPSS version 20. PD-1 and PD-L1 expression were significantly higher in OSCC compared with OED (P < 0.001). Expression levels increased progressively with higher grades of dysplasia and poorer tumour differentiation. A positive correlation between PD-1 and PD-L1 expression was observed within both groups, aligning with previous studies. These findings highlight the potential role of the PD-1/PD-L1 axis in early tumour development and immune evasion. Further research with larger sample sizes and clinical correlation could establish PD-1/PD-L1 as targets for immunotherapy, potentially improving outcomes in advanced OSCC and severe dysplasia.
We describe DQ-9, a dual-pharmacophore artezomib analogue that combines selective inhibition of immunoproteasome β5i with iron-dependent activation of artemisinin. DQ-9 exploits the elevated labile iron pool characteristic of hematologic malignancies, yielding selective cytotoxicity toward leukemia and multiple myeloma cells. DQ-9 affords sustained proteasome inhibition and induces oxidative stress and apoptosis through its iron-mediated activation and subsequent intracellular conversion to additional inhibitory species. In contrast, the deoxy analogue DQ-10, which lacks this activatable component, displays activity attributable solely to β5i inhibition, with correspondingly reduced cytotoxic potency. These findings establish iron-activable, β5i-targeting hybrids as a promising strategy to achieve enhanced selectivity and therapeutic efficacy against hematological malignancies.
Mutations in splicing factors are recurrent across human cancers and drive widespread RNA splicing dysregulation. Among these, SF3B1 is the most frequently mutated, yet its hotspot mutations exhibit lineage specificity, with SF3B1R625 mutations predominantly found in melanoma and SF3B1K700E in hematologic malignancies. However, the mechanistic basis for this cancer-type specificity remains unclear. Here, we demonstrate that SF3B1R625H induces greater activation of alternative 3' splice site than SF3B1K700E. Mechanistically, the polyadenine-enriched sequence surrounding cryptic branch point sites confers SF3B1R625H selective advantage in aberrant splicing. This splicing bias leads to preferential missplicing of NF1, a RAS inhibitor, resulting in RAS hyperactivation and accelerated melanoma progression in mouse models. This study redefines the oncogenic paradigm of SF3B1 mutations by demonstrating that distinct hotspot mutations exploit lineage-specific splicing vulnerabilities to drive tumorigenesis and establishes RAS activation as key mechanism underlying SF3B1R625H-driven melanoma, positioning RAS pathway as tractable therapeutic target in SF3B1-mutant melanoma.
Adaptive behavior requires organisms to make decisions under uncertainty, balancing the exploitation of known options with exploration as environmental structure changes. Across ecology and neuroscience, this problem has been studied using distinct experimental and theoretical frameworks, including probabilistic choice, reversal learning, foraging tasks, reinforcement learning, and Bayesian inference. Here, we synthesize some of these ideas within a predictive processing perspective, arguing that they address a shared computational challenge: inferring latent environmental structure and adjusting behavior in response to different sources of variability. We distinguish key forms of uncertainty and review evidence that animals can regulate learning rates, persistence, and exploration according to the inferred origin of outcome variability. Laboratory paradigms such as probabilistic reversal learning provide controlled settings to dissociate sensitivity to noise from sensitivity to change, while foraging tasks reveal how local fluctuations are integrated with global estimates of environmental quality. Across species, apparent decision variability often reflects adaptive sampling rather than suboptimal noise. We further review evidence suggesting that cortical and subcortical circuits can encode predictions and environmental statistics, and that neuromodulator systems, including noradrenaline, acetylcholine, dopamine, and serotonin, modulate the influence of new evidence relative to prior beliefs. Together, these findings support a view of adaptive decision-making as hierarchical uncertainty resolution that operates across behavioral timescales and experimental contexts, and provide a framework for linking ecological decision rules, laboratory models, and neural mechanisms.
This review explores the role of in vitro electrical and mechanical stimulation in modulating wound-healing behavior, with a primary focus on the predominant skin cell types: fibroblasts and keratinocytes. By analyzing the existing literature, we delineate the complex relationships between stimulation parameters-such as voltage, current, frequency, and mechanical strain-and cellular responses, including proliferation and migration. Our data-driven approach compiled more than 390 experimental data points for electrical stimulation and over 170 for mechanical stimulation in vitro, constructing a comprehensive library of cell responses that were previously fragmented and difficult to compare across studies. We critically evaluate various stimulation platforms and configurations, emphasizing their influence on cellular mechanobiology and their translational potential in regenerative medicine. Ultimately, this review underscores the necessity of a multi-parameter optimization strategy to effectively exploit electromechanical cues for targeted skin tissue regeneration.
Photothermal therapy (PTT) holds transformative potential for precision cancer treatment, yet clinical translation remains constrained by the scarcity of molecularly defined, biocompatible, and efficiently NIR-absorbing photothermal agents (PTAs). Here we report a rational donor-acceptor-donor (D-A-D) framework that delivers ultrasmall organic PTAs with record photothermal conversion efficiencies (49.8%) and intrinsic immunogenic cell death (ICD) activity. The design exploits 6,7-diphenyl-[1,2,5]thiadiazolo[3,4-g]quinoxaline as a π-extended, multi-nitrogenated acceptor core flanked by trifluoromethyl groups to deepen the LUMO, while methoxylated triphenylamine donors intensify intramolecular charge-transfer and suppress radiative decay. Nanoprecipitation furnishes monodisperse nanoparticles that exhibit intense NIR-II absorption, exceptional photostability across five hyperthermic cycles, and lysosome-directed uptake. In vitro, single-dose FTPA NPs plus 808-nm laser irradiation trigger mitochondrial depolarization, G0/G1 arrest, and apoptosis in > 70% of 4T1 cells while releasing abundant ATP and surface calreticulin-canonical ICD signals. A prophylactic vaccination model corroborates these molecular cues: mice primed with FTPA-NP-treated tumor cells reject contralateral challenge, achieving > 90% long-term survival, expansion of cytotoxic CD8+ T cells (≈ 70% activation), and suppression of Tregs (≈ 3%). No systemic toxicity or off-target pathology is observed. This study establishes a chemically tunable, metal-free PTA platform that synergizes thermal ablation with systemic anti-tumor immunity, providing a versatile scaffold for next-generation precision immuno-photothermal medicine.
Assessment of the health status of individual animals is a key step in the timely and targeted treatment of infections, which is critical in the fight to slow the development of anthelmintic and antimicrobial resistance. The FAMACHA scoring system has been used successfully to detect anaemia caused by infection with the parasitic nematode Haemonchus contortus in small ruminants and is an effective way to identify individuals in need of treatment. However, assessing FAMACHA is labour-intensive and costly, as individuals must be manually examined at frequent intervals. Here, accelerometers were used to measure the individual activity of extensively grazing small ruminants (sheep and goats) exposed to natural Haemonchus contortus worm infection in southern Africa, over long time scales (13+ months). When combined with machine learning, this activity data can predict poorer health (increases in FAMACHA score) in sheep with an area under the receiver operating characteristic curve (AUC) of 82.7%, as well as to identify animals that fail to respond to treatment with AUC of 66.4%. We demonstrate that these classifiers remain robust over time, and that interpretation of their trained results reveals that poorer health, such as that resulting from haemonchosis, significantly affects the night-time activity levels, more so than that of the daytime. Our study thus reveals that low-cost biologgers can exploit behavioural patterns to detect subtle changes in animal health and enable timely and targeted intervention. This has real potential to improve economic outcomes and animal welfare, as well as to limit the use of anthelmintic drugs and diminish selective pressures on anthelmintic resistance in both commercial and resource-poor communal farming.
Digadoglucitol is an extracellular macrocyclic dinuclear gadolinium-based contrast agent (GBCA) based on the association of two [Gd-(HP-DO3A)] units conjugated through a spacer containing the glucamine moiety. It displays a relaxivity per Gd that is 2 to 3 times higher than the most currently used GBCAs, allowing the use of reduced doses while ensuring a noninferior image contrast. Its high relaxivity is the result of a rational design aimed at exploiting the intramolecular catalysis of the prototropic exchange of the coordinated -OH groups as well as the second sphere contribution brought about by the presence of the hydroxyl functionalities on glucamine. Digadoglucitol maintains the excellent kinetic and thermodynamic properties of the parent [Gd-(HP-DO3A)] with an SAP/TSAP ratio of 2/3. A HPLC workup yielded three fractions of diastereoisomers based on the chirality of the 2-hydroxypropyl pendants with similar relaxometric and stability properties. From pH 5 to 9, the deprotonated glucamine nitrogen acts as base to catalyze the prototropic exchange of the coordinating -OH group bringing an enhancement of 1.5-2.0 mM-1 s-1 of the observed relaxivity with respect to the expected value for a q = 1 complex of a similar formula weight. Biodistribution and the Magnetic Resonance Imaging pharmacokinetics of digadoglucitol resulted very similarly to those found for [Gd-(BT-DO3A)].
Androgen receptor (AR) signaling is central to prostate cancer progression, yet resistance to AR-targeted therapies remains a major clinical challenge. Understanding the molecular consequences of AR pathway inhibition is therefore essential for improving therapeutic outcomes. Here, we identify a previously unrecognized link between AR antagonism and cuproptosis, a copper-dependent form of regulated cell death. Using integrated genomic profiling, we find that AR-targeted agents transcriptionally activate the key cuproptosis regulator Ferredoxin-1 (FDX1), thereby rendering prostate cancer cells markedly more susceptible to copper-induced lethality. Mechanistically, ligand-bound AR directly engages FDX1 cis-regulatory elements, which are rendered accessible by the pioneer factor GATA2, and drives FDX1 upregulation upon AR antagonist exposure. Consistent with this mechanism, FDX1 expression is elevated in clinical prostate cancer samples following androgen deprivation therapy or AR antagonist treatment. Increased FDX1 enhances intracellular Cu+ accumulation, destabilizes Fe-S cluster proteins, and disrupts mitochondrial metabolism, establishing a procuproptotic state. Functionally, combining AR antagonists with copper ionophores synergistically induces cuproptosis and potently suppresses tumor growth in AR-positive prostate cancer cells, three-dimensional (3D) spheroids, patient-derived organoids, and xenograft models, with minimal systemic toxicity. This synergy is abolished by FDX1 loss or copper chelation, confirming dependence on AR-FDX1 axis activation. Together, these findings uncover FDX1 as a mechanistic effector of AR pathway inhibition and propose a well-tolerated combination strategy that exploits cuproptosis to improve therapeutic responses in prostate cancer.
Autophagy plays a dual role in cancer progression, and strategies to drive excessive autophagic flux remain a promising yet challenging therapeutic avenue. Herein, we develop an endoplasmic reticulum (ER)-targeted self-assembling peptide system (P-1-ERT@Rap) that enables localized photodynamic damage and robust ER stress, which synergizes with rapamycin (Rap) for inducing dual autophagy activation in cancer cells. The peptide P-1-ERT co-assembles with Rap into well-dispersed micelles, which exhibit pH-responsive morphological transformation from nanoparticles to nanofibers under acidic conditions, thereby facilitating lysosomal escape and cellular release of therapeutics. Importantly, P-1-ERT selectively accumulates in the ER and generates reactive oxygen species under laser exposure, triggering significant ER stress with upregulation of CHOP proteins. Concurrently, cellular delivery of Rap, an autophagy inducer, further amplifies autophagic flux with increasing LC3B-II/I ratios, ultimately promoting programmed cell death in A375 cells. Notably, the P-1-ERT@Rap system achieves higher tumor accumulation compared to free photosensitizer in vivo. Moreover, intravenous administration of P-1-ERT@Rap alongside laser irradiation significantly inhibits tumor growth in an A375-xenografted mouse model, with minimal systemic toxicity observed. This dual modulation strategy for autophagy regulation effectively enhances photodynamic therapy efficacy, and it offers a promising approach for exploiting organelle specific stress pathways in cancer treatment. STATEMENT OF SIGNIFICANCE: This study presents a endoplasmic reticulum (ER)-targeted self-assembling peptide nanoplatform (P‑1‑ERT@Rap) that integrates organelle-specific photodynamic therapy (PDT) with autophagy modulation for synergistic cancer treatment. The system uniquely exploits pH-responsive morphological transformation from micelles to nanofibers in acidic tumor environments, facilitating lysosomal escape and efficient intracellular delivery. By selectively accumulating in the ER and generating localized reactive oxygen species upon irradiation, it induces severe ER stress and upregulates CHOP, while co-delivered rapamycin further amplifies autophagic flux. This dual activation of autophagy leads to enhanced programmed cell death in melanoma cells, as demonstrated both in vitro and in vivo. Our work provides a pioneering strategy for organelle-precise therapy that leverages dual stress pathways to overcome the limitations of conventional monotherapies. We believe that this new approach has the potential to revolutionize the field of precision oncology, setting a new paradigm for significantly enhancing treatment outcomes across a broad spectrum of tumor types.