The Effects of Mechanical Loading on Resonant Response of a Conformal Load-Bearing Antenna System.

Glass fibre-reinforced polymer (GFRP) is a suitable substrate material for constructing a Conformal Load-Bearing Antenna Structure (CLAS). The relative permittivity of the CLAS substrate, which determines its resonant frequency, is affected by damage sustained by GFRP. This paper investigates the effects of damage (induced by mechanically loading the substrate) on the resonant response of the CLAS. Decoupling the antenna from the substrate was essential to evaluate the CLAS's true response to the induced damage. This paper details a systematic investigation examining how the frequency response of a "pristine" antenna and a surface-mounted antenna respond to a substrate subjected to quasi-statically induced mechanical damage and cyclic fatigue loading. The results demonstrate that the resonant frequency of the CLAS varies as a function of the substrate's mechanical damage. The prepared CLAS is tolerant to a certain degree of mechanical loading and related damage with its resonant frequency remaining within an acceptable bandwidth.

Large language model uncertainty proxies: discrimination and calibration for medical diagnosis and treatment.

INTRODUCTION: The inability of large language models (LLMs) to communicate uncertainty is a significant barrier to their use in medicine. Before LLMs can be integrated into patient care, the field must assess methods to estimate uncertainty in ways that are useful to physician-users. OBJECTIVE: Evaluate the ability for uncertainty proxies to quantify LLM confidence when performing diagnosis and treatment selection tasks by assessing the properties of discrimination and calibration. METHODS: We examined confidence elicitation (CE), token-level probability (TLP), and sample consistency (SC) proxies across GPT3.5, GPT4, Llama2, and Llama3. Uncertainty proxies were evaluated against 3 datasets of open-ended patient scenarios. RESULTS: SC discrimination outperformed TLP and CE methods. SC by sentence embedding achieved the highest discriminative performance (ROC AUC 0.68-0.79), yet with poor calibration. SC by GPT annotation achieved the second-best discrimination (ROC AUC 0.66-0.74) with accurate calibration. Verbalized confidence (CE) was found to consistently overestimate model confidence. DISCUSSION AND CONCLUSIONS: SC is the most effective method for estimating LLM uncertainty of the proxies evaluated. SC by sentence embedding can effectively estimate uncertainty if the user has a set of reference cases with which to re-calibrate their results, while SC by GPT annotation is the more effective method if the user does not have reference cases and requires accurate raw calibration. Our results confirm LLMs are consistently over-confident when verbalizing their confidence (CE).

Impact of immune-related adverse events on survival among patients with head-and-neck squamous cell carcinoma.

Aim: Immune-checkpoint inhibitors (ICIs) have revolutionized treatment of metastatic head and neck squamous cell carcinomas (HNSCCs). Our goal was to assess for an association between immune-related adverse events (irAEs) and clinical outcomes for patients on ICIs.Methods: We analyzed a cohort of 110 HNSCC patients who received ICI therapy at the University of Virginia.Results: On review, 48% of our patients experienced an irAE with the most common events being hypothyroidism (30%), dermatitis (14%) and hepatitis (11%). Women were more likely to experience irAEs. Treatment interruption/discontinuation occurred in 43% patients with irAEs. Development of irAEs was associated with superior objective response rate (68 vs. 39%, p = 0.009), with a greater rate of CR (17 vs. 5%) and PR (32 vs. 16%). Twelve patients underwent ICI re-treatment following irAE, with 17% attaining a complete disease response, 25% attaining a partial response, 33% achieving stable disease and 25% experiencing disease progression with ICI resumption.Conclusion: Development of irAE was associated with superior objective response rate, with a greater rate of CR and PR. ICI re-treatment following irAE was feasible in a significant proportion of patients and can be attempted in carefully selected patients, given the dearth of second-line therapies for these patients.

While outcomes for patients who receive immunotherapy for advanced head and neck cancer are greatly improved compared with traditional chemotherapy, a feared complication of this treatment is immune-related side effects. The exact incidence of these side effects is not known in head and neck cancer but are well described in other cancers. In this study, about half of head and neck cancer patients who received immunotherapy developed side effects due to immune over-activation. Women and patients who did not receive radiation were more likely to develop these side effects. Patient who developed immune side effects were more likely to see shrinkage in their tumors, and may have a higher likelihood of longer survival, although the findings were not statistically significant.

Surface Charge Regulation of Graphene by Fluorine and Chlorine Co-Doping for Constructing Ultra-Stable and Large Energy Density Micro-Supercapacitors.

Settling the structure stacking of graphene (G) nanosheets to maintain the high dispersity has been an intense issue to facilitate their practical application in the microelectronics-related devices. Herein, the co-doping of the highest electronegative fluorine (F) and large atomic radius chlorine (Cl) into G via a one-step electrochemical exfoliation protocol is engineered to actualize the ultralong cycling stability for flexible micro-supercapacitors (MSCs). Density functional theoretical calculations unveiled that the F into G can form the "ionic" C─F bond to increase the repulsive force between nanosheets, and the introduction of Cl can enlarge the layer spacing of G as well as increase active sites by accumulating the charge on pore defects. The co-doping of F and Cl generates the strong synergy to achieve high reversible capacitance and sturdy structure stability for G. The as-constructed aqueous gel-based MSC exhibited the superb cycling stability for 500,000 cycles with no capacitance loss and structure stacking. Furthermore, the ionic liquid gel-based MSC demonstrated a high energy density of 113.9 mW h cm-3 under high voltage of up to 3.5 V. The current work enlightens deep insights into the design and scalable preparation of high-performance co-doped G electrode candidate in the field of flexible microelectronics.

Reinforcement learning processes as forecasters of depression remission.

BACKGROUND: Aspects of reinforcement learning have been associated with specific depression symptoms and may inform the course of depressive illness. METHODS: We applied support vector machines to investigate whether blood­oxygen-level dependent (BOLD) responses linked with neural prediction error (nPE) and neural expected value (nEV) from a probabilistic learning task could forecast depression remission. We investigated whether predictions were moderated by treatment use or symptoms. Participants included 55 individuals (n = 39 female) with a depression diagnosis at baseline; 36 of these individuals completed standard cognitive behavioral therapy and 19 were followed during naturalistic course of illness. All participants were assessed for depression diagnosis at a follow-up visit. RESULTS: Both nPE and nEV classifiers forecasted remission significantly better than null classifiers. The nEV classifier performed significantly better than the nPE classifier. We found no main or interaction effects of treatment status on nPE or nEV accuracy. We found a significant interaction between nPE-forecasted remission status and anhedonia, but not for negative affect or anxious arousal, when controlling for nEV-forecasted remission status. LIMITATIONS: Our sample size, while comparable to that of other studies, limits options for maximizing and evaluating model performance. We addressed this with two standard methods for optimizing model performance (90:10 train and test scheme and bootstrapped sampling). CONCLUSIONS: Results support nEV and nPE as relevant biobehavioral signals for understanding depression outcome independent of treatment status, with nEV being stronger than nPE as a predictor of remission. Reinforcement learning variables may be useful components of an individualized medicine framework for depression healthcare.

Stiffness and Interface Engineered Soft Electronics with Large-Scale Robust Deformability.

Skin-like stretchable electronics emerge as promising human-machine interfaces but are challenged by the paradox between superior electronic property and reliable mechanical deformability. Here, a general strategy is reported for establishing robust large-scale deformable electronics by effectively isolating strains and strengthening interfaces. A copolymer substrate is designed to consist of mosaic stiff and elastic areas with nearly four orders of magnitudes modulus contrast and cross-linked interfaces. Electronic functional devices and stretchable liquid metal (LM) interconnects are conformally attached at the stiff and elastic areas, respectively, through hydrogen bonds. As a result, functional devices are completely isolated from strains, and resistances of LM conductors change by less than one time when the substrate is deformed by up to 550%. By this strategy, solar cells, wireless charging antenna, supercapacitors, and light-emitting diodes are integrated into a self-powered electronic skin that can laminate on the human body and exhibit stable performances during repeated multimode deformations, demonstrating an efficient path for realizing highly deformable energy autonomous soft electronics.

In-Situ Polymerized High-Voltage Solid-State Lithium Metal Batteries with Dual-Reinforced Stable Interfaces.

Solid polymer electrolytes (SPEs) represent a pivotal advance toward high-energy solid-state lithium metal batteries. However, inadequate interfacial contact remains a significant bottleneck, impeding scalability and application. Inadequate interfacial contact remains a significant bottleneck, impeding scalability and application. Recent efforts have focused on transforming liquid/solid interfaces into solid/solid ones through in situ polymerization, which shows potential especially in reducing interface impedance. Here, we designed high-voltage SSLMBs with dual-reinforced stable interfaces by combining interface modification with an in situ polymerization technology inspired by targeted effects in medicine. Theoretical calculations and time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis demonstrate that tetramethylene sulfone (TMS) and bis(2,2,2-trifluoromethyl) carbonate (TFEC) exhibit selective adsorption at the interface of the LiNi0.8Co0.1Mn0.1O2 (NCM) cathode and Li anode, respectively. These compounds further decompose to form a stable cathode-electrolyte interface (CEI) film and a solid electrolyte interface (SEI) film, thereby simultaneously achieving a superior interface between the SPE and both the Li anode and NCM cathode. The developed Li||SPE||Li cell sustained cycling for more than 1000 h at 0.3 mA cm-2, and the NCM||SPE||Li cell also demonstrated an excellent capacity retention of 86.8% after 1000 cycles at 1 °C. This work will provide valuable insights for the rational design of high-voltage SSLMBs with stable interfaces, leveraging in situ polymerization as a cornerstone technology.

Dual-gradient Concentration Distribution in Sb-Cu Alloy Nanoarrays for Robust Sodium-ionStorage.

Alloy-type materials are attractive for anodes in sodium-ion batteries (SIBs) owing to their high theoretical capacities and overall performance. However, the accumulation of stress/strain during repeated cycling results in electrode pulverization, leading to rapid capacity decay and eventual disintegration, thus hindering their practical applications. Herein, we report a 3D coral-like Sb-Cu alloy nanoarray with gradient distribution of both elements. The array features a Sb-rich bottom and a Cu-rich top with increasing Sb and decreasing Cu concentrations from top to bottom. The former is the active component that provides the high capacity, whereas the latter serves as an inert additive that acts against volume variation. The gradual transition in composition within the electrode introduces a ladder-type volume expansion effect, facilitating a smooth distribution and effective release of stress, thereby ensuring the wanted mechanical stability and structural integrity. The as-developed nanoarray affords a high reversible capacity (460 mAh g-1 at 0.5 C), stable cycling (89% retention over 120 cycles at 1.0 C), and superior rate capability (354 mAh g-1 at 10 C). The concentration dual-gradient strategy paves a new pathway of designing alloy-type materials for SIBs.

"Very" Very Late Stent Thrombosis: A Detailed Look at Two Cases.

Although percutaneous coronary intervention (PCI) has radically transformed the scope of treating coronary artery disease with stenting, stent thrombosis (STh) remains a feared complication. Very late STh, a rare complication after PCI, refers to STh occurring greater than one year after post-stent implantation. An even rarer phenomenon, "very" very late stent thrombosis (VVLST), is described in the literature as STh occurring more than five years post-stent implantation. To our knowledge, there are only 10 case reports and one case series describing VVLST. We discuss two additional complex clinical cases of VVLST presenting as ST-elevation myocardial infarction. We highlight epidemiology, pathophysiology, presentation, diagnostic methods, treatment approach, associated complications, and the need for more extensive future work to minimize the risk of VVLST.

Reversibly Reactive Affinity Selection-Mass Spectrometry Enables Identification of Covalent Peptide Binders.

Covalent peptide binders have found applications as activity-based probes and as irreversible therapeutic inhibitors. Currently, there is no rapid, label-free, and tunable affinity selection platform to enrich covalent reactive peptide binders from synthetic libraries. We address this challenge by developing a reversibly reactive affinity selection platform termed ReAct-ASMS enabled by tandem high-resolution mass spectrometry (MS/MS) to identify covalent peptide binders to native protein targets. It uses mixed disulfide-containing peptides to build reversible peptide-protein conjugates that can enrich for covalent variants, which can be sequenced by MS/MS after reduction. Using this platform, we identified covalent peptide binders against two oncoproteins, human papillomavirus 16 early protein 6 (HPV16 E6) and peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 protein (Pin1). The resulting peptide binders efficiently and selectively cross-link Cys58 of E6 at 37 °C and Cys113 of Pin1 at room temperature, respectively. ReAct-ASMS enables the identification of highly selective covalent peptide binders for diverse molecular targets, introducing an applicable platform to assist preclinical therapeutic development pipelines.

Ultrathin Boundary-Less SnO2 Films with Surface-Activated Two-Dimensional Nanograins Enable Fast and Sensitive Hydrogen Gas Sensing.

Fast and reliable semiconductor hydrogen sensors are crucially important for the large-scale utilization of hydrogen energy. One major challenge that hinders their practical application is the elevated temperature required, arising from undesirable surface passivation and grain-boundary-dominated electron transportation in the conventional nanocrystalline sensing layers. To address this long-standing issue, in the present work, we report a class of highly reactive and boundary-less ultrathin SnO2 films, which are fabricated by the topochemical transformation of 2D SnO transferred from liquid Sn-Bi droplets. The ultrathin SnO2 films are purposely made to consist of well-crystallized quasi-2D nanograins with in-plane grain sizes going beyond 30 nm, whereby the hydroxyl adsorption and grain boundary side-effects are effectively suppressed, giving rise to an activated (101)-dominating dangling-bond surface and a surface-controlled electrical transportation with an exceptional electron mobility of 209 cm2 V-1 s-1. Our work provides a new cost-effective strategy to disruptively improve the gas reception and transduction of SnO2. The proposed chemiresistive sensors exhibit fast, sensitive, and selective hydrogen sensing performance at a much-reduced working temperature of 60 °C. The remarkable sensing performance as well as the simple and scalable fabrication process of the ultrathin SnO2 films render the thus-developed sensors attractive for long awaited practical applications in hydrogen-related industries.

Environmental DNA-based biodiversity profiling along the Houdong River in north-eastern Taiwan.

Background: This paper describes two datasets: species occurrences, which were determined by environmental DNA (eDNA) metabarcoding and their associated DNA sequences, originating from a research project which was carried out along the Houdong River (), Jiaoxi Township, Yilan, Taiwan. The Houdong River begins at an elevation of 860 m and flows for approximately 9 km before it empties into the Pacific Ocean. Meandering through mountains, hills, plains and alluvial valleys, this short river system is representative of the fluvial systems in Taiwan. The primary objective of this study was to determine eukaryotic species occurrences in the riverine ecosystem through the use of the eDNA analysis. The second goal was, based on the current dataset, to establish a metabarcoding eDNA data template that will be useful and replicable for all users, particularly the Taiwan community. The species occurrence data are accessible at the Global Biodiversity Information Facility (GBIF) portal and its associated DNA sequences have been deposited in the European Nucleotide Archive (ENA) at EMBL-EBI, respectively. A total of 12 water samples from the study yielded an average of 1.5 million reads. The subsequent species identification from the collected samples resulted in the classification of 432 Operational Taxonomic Units (OTUs) out of a total of 2,734. Furthermore, a total of 1,356 occurrences with taxon matches in GBIF were documented (excluding 4,941 incertae sedis, accessed 05-12-2023). These data will be of substantial importance for future species and habitat monitoring within the short river, such as assessment of biodiversity patterns across different elevations, zonations and time periods and its correlation to water quality, land uses and anthropogenic activities. Further, these datasets will be of importance for regional ecological studies, in particular the freshwater ecosystem and its status in the current global change scenarios. New information: The datasets are the first species diversity description of the Houdong River system using either eDNA or traditional monitoring processes.

Bi-directional charge transfer channels in highly crystalline carbon nitride enabling superior photocatalytic hydrogen evolution.

Introducing a donor-acceptor (D-A) unit is an effective approach to facilitate charge transfer in polymeric carbon nitride (PCN) and enhance photocatalytic performance. However, the introduction of hetero-molecules can lead to a decrease in crystallinity, limiting interlayer charge transfer and inhibiting further improvement. In this study, we constructed a novel D-A type carbon nitride with significantly higher crystallinity and a bi-directional charge transfer channel, which was achieved through 2,5-thiophenedicarboxylic acid (2,5-TDCA)-assisted self-assembly followed by KCl-templated calcination. The thiophene and cyano groups introduced serve as the electron donor and acceptor, respectively, enhancing in-plane electron delocalization. Additionally, introduced potassium ions are intercalated among the adjacent layers of carbon nitride, creating an interlayer charge transfer channel. Moreover, the highly ordered structure and improved crystallinity further facilitate charge transfer. As a result, the as-prepared photocatalyst exhibits superior photocatalytic hydrogen evolution (PHE) activity of 7.449 mmol h-1 g-1, which is 6.03 times higher than that of pure carbon nitride. The strategy of developing crystalline D-A-structured carbon nitride with controlled in-plane and interlayer charge transfer opens new avenues for the design of carbon nitride with enhanced properties for PHE.

Development of an α-Klotho Recognizing High-Affinity Peptide Probe from In-Solution Enrichment.

The kidney, parathyroid gland, and choroid plexus express the aging-related transmembrane protein α-Klotho, a coreceptor of the fibroblast growth factor 23 (FGF23) receptor complex. Reduced α-Klotho levels are correlated with chronic kidney disease and other age-related diseases, wherein they are released from membranes into circulation. Klotho's potential physiological action as a hormone is of current scientific interest. Part of the challenges associated with advancing these studies, however, has been the long-standing difficulty in detecting soluble α-Klotho in biofluids. Here, we describe the discovery of peptides that recognize α-Klotho with high affinity and selectivity by applying in-solution size-exclusion-based affinity selection-mass spectrometry (AS-MS). After two rounds of AS-MS and subsequent N-terminal modifications, the peptides improved their binding affinity to α-Klotho by approximately 2300-fold compared to the reported starting peptide Pep-10, previously designed based on the C-terminal region of FGF23. The lead peptide binders were shown to enrich α-Klotho from cell lysates and to label α-Klotho in kidney cells. Our results further support the utility of in-solution, label-free AS-MS protocols to discover peptide-based binders to target proteins of interest with high affinity and selectivity, resulting in functional probes for biological studies.

Electrochemical Knocking-Down of Zn Metal Clusters into Single Atoms.

Single Atoms Catalysts (SACs) have emerged as a class of highly promising heterogeneous catalysts, where the traditional bottom-up synthesis approaches often encounter considerable challenges in relation to aggregation issues and poor stability. Consequently, achieving densely dispersed atomic species in a reliable and efficient manner remains a key focus in the field. Herein, we report a new facile electrochemical knock-down strategy for the formation of SACs, whereby the metal Zn clusters are transformed into single atoms. While a defect-rich substrate plays a pivotal role in capturing and stabilizing isolated Zn atoms, the feasibility of this novel strategy is demonstrated through a comprehensive investigation, combining experimental and theoretical studies. Furthermore, when studied in exploring for potential applications, the material prepared shows a remarkable improvement of 58.21% for the Li+ storage and delivers a capacity over 300 Wh kg-1 after 500 cycles upon the transformation of Zn clusters into single atoms.

Challenges and Opportunities in Preserving Key Structural Features of 3D-Printed Metal/Covalent Organic Framework.

Metal-organic framework (MOF) and covalent organic framework (COF) are a huge group of advanced porous materials exhibiting attractive and tunable microstructural features, such as large surface area, tunable pore size, and functional surfaces, which have significant values in various application areas. The emerging 3D printing technology further provides MOF and COFs (M/COFs) with higher designability of their macrostructure and demonstrates large achievements in their performance by shaping them into advanced 3D monoliths. However, the currently available 3D printing M/COFs strategy faces a major challenge of severe destruction of M/COFs' microstructural features, both during and after 3D printing. It is envisioned that preserving the microstructure of M/COFs in the 3D-printed monolith will bring a great improvement to the related applications. In this overview, the 3D-printed M/COFs are categorized into M/COF-mixed monoliths and M/COF-covered monoliths. Their differences in the properties, applications, and current research states are discussed. The up-to-date advancements in paste/scaffold composition and printing/covering methods to preserve the superior M/COF microstructure during 3D printing are further discussed for the two types of 3D-printed M/COF. Throughout the analysis of the current states of 3D-printed M/COFs, the expected future research direction to achieve a highly preserved microstructure in the 3D monolith is proposed.

AbDPP: Target-oriented antibody design with pretraining and prior biological structure knowledge.

Antibodies represent a crucial class of complex protein therapeutics and are essential in the treatment of a wide range of human diseases. Traditional antibody discovery methods, such as hybridoma and phage display technologies, suffer from limitations including inefficiency and a restricted exploration of the immense space of potential antibodies. To overcome these limitations, we propose a novel method for generating antibody sequences using deep learning algorithms called AbDPP (target-oriented antibody design with pretraining and prior biological knowledge). AbDPP integrates a pretrained model for antibodies with biological region information, enabling the effective use of vast antibody sequence data and intricate biological system understanding to generate sequences. To target specific antigens, AbDPP incorporates an antibody property evaluation model, which is further optimized based on evaluation results to generate more focused sequences. The efficacy of AbDPP was assessed through multiple experiments, evaluating its ability to generate amino acids, improve neutralization and binding, maintain sequence consistency, and improve sequence diversity. Results demonstrated that AbDPP outperformed other methods in terms of the performance and quality of generated sequences, showcasing its potential to enhance antibody design and screening efficiency. In summary, this study contributes to the field by offering an innovative deep learning-based method for antibody generation, addressing some limitations of traditional approaches, and underscoring the importance of integrating a specific antibody pretrained model and the biological properties of antibodies in generating novel sequences. The code and documentation underlying this article are freely available at https://github.com/zlfyj/AbDPP.

Diffuse Pneumonitis after Lutetium-177-PSMA-617 Treatment in a Patient with Metastatic Castration-Resistant Prostate Cancer.

We present the case of a patient with heavily pretreated metastatic castration-resistant prostate cancer (mCRPC) who received lutetium Lu-177 vipivotide tetraxetan (also known as 177Lu-PSMA-617) due to progressive disease despite chemotherapy, hormonal therapy and radiation, including palliative mediastinal and central nervous system radiation. He was subsequently hospitalised for worsening acute onset dyspnoea despite clinically responding to therapy. Interval imaging revealed progressive multifocal ground-glass opacities superimposed on a background of underlying peribronchovascular fibrosis. Further workup, including an extensive workup to identify a possible infectious aetiology, ruled out most aetiologies leaving radiation pneumonitis (RP), radiation recall pneumonitis (RRP) and drug-induced pneumonitis as possible diagnoses secondary to 177Lu -PSMA-617. The associated imaging findings of ground-glass opacities and consolidation can be like other aetiologies such as acute infection and subsequently may be treated incorrectly. In the use of theragnostics like 177Lu -PSMA-617, it is fundamental to apply the practices of radioprotection learnt from radiotherapy, as well as to consider prior radiotherapy treatments and their possible side effects when used in conjunction.

Nanofiltration Ceramic Membranes as a Feasible Two-Pronged Approach toward Desalination and Lithium Recovery.

Ceramic membranes are taking center stage for separation technologies in water treatment. Among them, ceramic nanofiltration membranes are at the forefront of membrane technologies. The desalination of seawater using ceramic nanofiltration membranes is a potential application toward increasing the global water supply and tackling water scarcity. However, while the high fabrication cost poses a challenge to their large-scale applications, high-value separation applications can help to offset the overall cost. In this regard, ceramic nanofiltration membranes can also be explored as a viable option for high-value lithium extraction from the waste seawater brine. In order to determine the potential of nanofiltration ceramic membranes for desalination and lithium recovery from seawater, the current efficiency of salt rejection across various operation parameters must be thoroughly evaluated. Specifically, the interactions between the Donnan exclusion, steric exclusion, zeta potential, and salt concentration play an important role in determining the salt rejection efficiency. Several strategies are then proposed to guide ceramic nanofiltration membranes toward potentially practical applications regarding desalination and lithium recovery.

Structure of the p53 degradation complex from HPV16.

Human papillomavirus (HPV) is a significant contributor to the global cancer burden, and its carcinogenic activity is facilitated in part by the HPV early protein 6 (E6), which interacts with the E3-ligase E6AP, also known as UBE3A, to promote degradation of the tumor suppressor, p53. In this study, we present a single-particle cryoEM structure of the full-length E6AP protein in complex with HPV16 E6 (16E6) and p53, determined at a resolution of ~3.3 Å. Our structure reveals extensive protein-protein interactions between 16E6 and E6AP, explaining their picomolar binding affinity. These findings shed light on the molecular basis of the ternary complex, which has been pursued as a potential therapeutic target for HPV-driven cervical, anal, and oropharyngeal cancers over the last two decades. Understanding the structural and mechanistic underpinnings of this complex is crucial for developing effective therapies to combat HPV-induced cancers. Our findings may help to explain why previous attempts to disrupt this complex have failed to generate therapeutic modalities and suggest that current strategies should be reevaluated.