The ability of cells to sense and respond to metabolic signals is fundamental to life, yet the molecular mechanisms underlying metabolite surveillance remain incompletely understood. Here, we elucidate the structural basis of metabolite recognition by OXGR1, a G Protein-Coupled Receptor (GPCR) that senses key intermediates in the tricarboxylic acid (TCA) cycle. Using cryo-electron microscopy, we determined cryo-EM structures of OXGR1 bound to α-ketoglutarate (AKG), itaconate (ITA), and structurally related metabolites succinate (SUC) and maleate (MA). These structures reveal a positively charged binding pocket and an extensive hydrogen-bond network that mediate selective recognition of dicarboxylic acids. In addition, we identify a distinct arrangement of hydrophobic residues that modulates ligand potency and selectivity. Mutational analysis and molecular dynamics simulations further demonstrate that noncanonical micro-switch motifs, including FRY and NLxxY, are essential for ligand recognition and receptor activation. Comparative structural and evolutionary analyses indicate that these mechanisms are conserved across species, underscoring the critical role of OXGR1 in maintaining metabolic homeostasis. Together, our findings define a mechanistic framework for metabolite sensing by OXGR1 and provide a framework for therapeutic modulation of metabolic and inflammatory diseases. OXGR1, a GPCR that senses TCA intermediates, regulates energy balance, acid-base homeostasis, and inflammation. Cryo-EM structures of OXGR1 bound to four dicarboxylic metabolites reveal selective recognition of TCA intermediates through a conserved binding mode and a non-canonical GPCR activation mechanism. Structural analyses of OXGR1 bound to TCA-cycle metabolites identify a conserved binding mode and a non-canonical GPCR activation mechanism.

Magnetic nanoparticles (MNPs) have emerged as a powerful tool in cancer theranostics due to their unique size-dependent magnetic properties, surface functionalization capabilities, and responsiveness to external magnetic fields. This review outlines different types of MNPs, including those composed of pure metals, metal oxides, and metallic alloys, and highlights their size-dependent magnetic behavior, such as superparamagnetism and dynamic magnetizations. We also explore the critical role of surface modification strategies in enhancing MNPs’ biocompatibility, colloidal stability, and functional versatility for targeted biomedical applications. The applications of MNPs in cancer therapy are discussed, with a focus on magnetic hyperthermia, drug and gene delivery, and a combination of various therapies. Additionally, we examine their cancer diagnostic roles in imaging techniques such as magnetic resonance imaging (MRI) and magnetic particle imaging (MPI), and emerging magnetic biosensing technologies such as giant magnetoresistance (GMR), magnetic tunnel junction (MTJ), magnetic particle spectroscopy (MPS), and nuclear magnetic resonance (NMR)-based platforms. These advances collectively establish MNPs as key components in the future of personalized cancer diagnosis and treatment.

Over the past decade, thin-film-based magnetoresistive (MR) sensors have undergone significant advancements. These conventional rigid thin-film MR sensors provided high sensitivity and reliability but were limited by their mechanical rigidity and incompatibility with curved or wearable surfaces. To address this flexibility issue, later flexible MR sensors were achieved by thinning or transferring the active layers of rigid sensors onto compliant substrates, which enabled strain-tolerant operation and integration with soft electronic platforms. However, these devices still relied on conventional film-based geometries that were restricted by the high fabrication costs, complexity, and poor scalability. Non-traditional granular MR sensors have emerged as a promising direction in spintronics research owing to their cost-effective fabrication, structural simplicity, and compatibility with flexible and wearable electronics. Despite these advantages, several challenges remain, particularly the need to enhance their sensitivity for low magnetic field detection, such as biomagnetic fields. This review aims to provide a comprehensive overview of to-date reported non-traditional granular MR devices, their physical mechanisms, material configurations, fabrication strategies, and MR device performance evolution over the past two decades. We highlighted how advances in nanoparticle engineering, insulating matrices, and polymeric binders have expanded the potential of granular MR systems for next-generation flexible and printable magnetoelectronic applications.

Magnetic particle spectroscopy (MPS) has emerged as a powerful biosensing modality due to its high sensitivity, matrix-free detection, and compatibility with point-of-care diagnostics. However, the lack of robust multiplexing capability remains a major bottleneck that limits its broader application in complex bioassays. To address this challenge, spatial and spectral separation strategies have been explored in recent years. While spatial separation approaches enable multiplexing without sacrificing sensitivity, they require physically distinct assay regions and substantially increase assay complexity, cost, and reagent consumption. In contrast, spectral separation offers a more resource-efficient solution by decoding multiple analyte signals from a single MPS measurement, but its performance critically depends on the choice of harmonic components used for decoding. In practical multiplexed MPS bioassays, numerical instability in solving harmonic equations directly translates into analyte misquantification and degrades assay performance. Despite significant progress, there is currently no systematic framework to guide the selection of harmonic sets that maximize spectral separation accuracy across different mixture complexities. Herein, we systematically investigate truncated spectral separation across binary, ternary, and quaternary mixtures of distinct magnetic nanoparticle labels by evaluating a wide range of harmonic component combinations under identical experimental conditions. We demonstrate that the absolute determinant of the truncated reference matrix serves as a robust and effective criterion for identifying harmonic sets that yield the lowest decoding error under the evaluated experimental conditions. The proposed harmonic selection framework is demonstrated to be effective across multiple decoding strategies and provides practical design guidance for robust and scalable multiplexed MPS bioassays.

Precise classification of breast cancer in histopathological images has the potential to greatly improve diagnostic accuracy and patient outcomes. However, inherent class imbalance within medical imaging datasets leads to biased model predictions, particularly underrepresenting rare tumor subtypes. This constitutes a considerable limitation in biased model predictions that can overlook critical and rare classes. We employed EfficientNet, a state-of-the-art convolutional neural network (CNN) that balances high accuracy with computational efficiency. To address data imbalance, we implemented an intensive data augmentation pipeline and cost-sensitive learning, enabling the model to better represent minority classes. This approach provides the ability to learn effectively from rare tumor types, improving its robustness. Additionally, we applied transfer learning by fine-tuning weights initially trained on binary classification tasks to support multi-class classification, thereby improving pattern recognition on the BreakHis dataset. Our framework achieved substantial improvements in both binary and multi-class classification tasks. In binary classification, recall for benign cases increased from 0.92 to 0.95, while accuracy improved from 97.35% to 98.23%. For multi-class classification, accuracy rose from 91.27% with standard augmentation to 94.3% with intensive augmentation, and further to 94.82% with transfer learning. The approach also enhanced precision in minority subtypes such as Mucinous carcinoma and Papillary carcinoma, while maintaining consistently high recall across classes.

Accurate and efficient segmentation of brain tumors is critical for diagnosis, treatment planning, and monitoring in clinical practice. In this study, we present an enhanced ResU-Net architecture for automatic brain tumor segmentation, integrating an EfficientNetB0 encoder, a channel attention mechanism, and an atrous spatial pyramid pooling (ASPP) module. The EfficientNetB0 encoder leverages pre-trained features to improve feature extraction efficiency, while the channel attention mechanism enhances the model's focus on tumor-relevant features. ASPP enables multi-scale contextual learning, which is crucial for handling tumors of varying sizes and shapes. The proposed model was evaluated on two benchmark datasets: The Cancer Genome Atlas Low Grade Glioma and brain tumor segmentation (BraTS-2020). Experimental results demonstrate that our method consistently outperforms the baseline ResU-Net and its EfficientNet variant, achieving dice similarity coefficient of 0.903 and 0.851, and HD95 scores of 9.43 and 3.54 for whole tumor and tumor core (TC) regions on the BraTS 2020 dataset, respectively. Compared to state-of-the-art methods, our approach shows competitive performance, particularly in whole tumor and TC segmentation. These results indicate that combining a powerful encoder with attention mechanisms and ASPP can significantly enhance BraTS performance. The proposed approach holds promise for further optimization and application in other medical image segmentation tasks.

The dynamic magnetization of magnetic nanoparticles (MNPs) arises from coupled Néel and Brownian relaxations, which are influenced by intrinsic particle properties such as size, saturation magnetization, magnetic anisotropy, and damping. While experimental AC magnetization measurements can reveal the collective dynamic behavior of MNP ensembles, extracting accurate nanoparticle-specific parameters from such data remains a challenge due to experimental limitations and model oversimplifications. To address this, we apply a stochastic Langevin model that explicitly captures the time-dependent magnetization response of MNPs under alternating magnetic fields by incorporating both thermal fluctuations and stochastic relaxation processes. This model provides a physically grounded framework for simulating magnetization hysteresis under experimental conditions, enabling parameter estimation through direct data fitting. In this work, we fit the stochastic Langevin model to experimentally measured hysteresis loops of different MNPs collected under a 20 mT, 5 kHz AC field. By coupling the model with Bayesian optimization and Gaussian process regression, we identify optimal values of key magnetic parameters: saturation magnetization (Ms), effective anisotropy (Ka), and Gilbert damping parameter (α). Furthermore, theMsis experimentally measured and employed as a validation parameter. Accordingly, the determination of theαand theKais based on two complementary criteria: (1) the best agreement between the simulated and experimental AC response magnetization hysteresis loops, quantified by the coefficient of determination (R2), and (2) the closest correspondence between the estimated and experimentally measuredMsvalues, evaluated using the mean absolute percentage error. Our approach is validated on four commercial MNP products (SHS30, IPG30, SHP25, and SHP15, from Ocean Nanotech, LLC), yielding high-fidelity fits to experimental data and robust estimation of their magnetic properties.

Inappropriate disposal of electronic waste (e-waste) can pollute ecosystems and deplete mineral resources, highlighting the urgency to develop sustainable and recyclable electronics. While various metal nanoparticles have been tested in literature regarding built-in recyclability for electronics, it remains unclear on how recycling processes affect their properties, since oxidation and contamination of recycled nanomaterials may compromise the functional and reliable performance of remanufactured devices. This study aims to fill this knowledge gap by systematically investigating the behaviors of metal particles at different remanufacturing stages and by developing an effective, printing-enabled, remanufacturing route using fully recyclable, noble-metal-free, conductive inks. Recyclability of the printed conductors is investigated in terms of electrical properties across multiple reuse cycles, achieving ∼90% recovery of electrical conductivity after 3 reuse cycles (at least 1 order of magnitude higher than the regular "mill-to-print" approach). As proof of concept, a wireless strain-sensing platform is designed for real-time monitoring of small strains generated by the human body, highlighting potential for wearable human-machine interface applications.

Magnetic particle imaging (MPI) and magnetic hyperthermia therapy (MHT) both rely strongly on the dynamic magnetic response of magnetic nanoparticles (MNPs), yet the particle design requirements for achieving strong imaging contrast and efficient heating are not always aligned. Here, we systematically investigate the effects of core size and PEG surface coating on the dual MPI-MHT performance of iron oxide MNPs. Six formulations with core sizes of 10, 20, and 30 nm, either uncoated Fe3O4 or PEG-coated Fe3O4 (Fe3O4@PEG), were systematically evaluated. MPI performance was assessed using magnetic particle spectroscopy (MPS) under an excitation field of 10 mT at 7.7 and 11.4 kHz. Harmonic analysis revealed that 20 nm Fe3O4@PEG nanoparticles generated the strongest MPI response, characterized by enhanced higher-order harmonic magnitudes and slower harmonic decay. MHT performance was then evaluated under various alternating magnetic field (AMF) conditions: 30 mT at 101.5 kHz, 15 mT at 434.4 kHz, 25 mT at 252.5 kHz, and 10 mT at 951.8 kHz. Results demonstrate that 20 nm Fe3O4@PEG nanoparticles also showed superior heating efficiency, especially under low-field, high-frequency excitation. These findings suggest that a 20 nm core size, combined with a PEG coating, provides an optimal balance between rapid magnetic response, colloidal stability, and energy dissipation. Furthermore, colloidal stability over seven days and cell viability assays confirm that the MNPs are colloidally stable and that 20 and 30 nm MNPs are biocompatible under the tested conditions for up to 48 h. This study provides a rational design framework for developing dual-functional iron oxide nanoparticles for image-guided magnetic hyperthermia and other integrated diagnostic-therapeutic biomedical applications.

Magnetic particle imaging (MPI) is an emerging imaging modality that exploits the magnetization response of magnetic nanoparticle tracers. While MPI offers substantially higher resolution compared to magnetic resonance imaging, its translation to human-scale applications remains limited. These challenges stem from the requirement of high-intensity electric currents to generate strong magnetic fields, as well as reduced field uniformity with increasing coil spacing. To overcome these barriers, comprehensive simulation studies are essential for guiding MPI prototype design and performance optimization. In this work, we present a finite element method (FEM)-based design of a three-dimensional (3D) MPI prototype. The system integrates electromagnetic coils for the selection, drive, and focus fields, along with a gradiometer configuration for signal reception. Each coil’s geometry and magnetic field were first simulated independently to validate its ability to generate the desired magnetic field and subsequently combined into a full-system design with time-domain input excitation signals. This framework achieved 3D field-free point (FFP) scanning within a 20 mm3 field of view. The selection field provided a gradient of 4, 2, and 2 T/m in z axis, y axis, and x axis, respectively, the drive field produced 20 mT, and the focus fields generated 40 mT (z-axis) and 20 mT (y-axis), enabling controlled spatial movement of the FFP. Overall, this study establishes a complete 3D FEM simulation framework for MPI system design and lays the foundation for future optimization toward clinical-scale applications.

Gallium oxide (Ga2O3) (GO) and aluminum gallium oxide (AlxGa1-x)2O3 (AGO) are promising semiconductor oxides for deep-UV optoelectronics and high-power electronics applications. Despite recent efforts to realize ultra-wide bandgap AGO films grown by different deposition techniques, high aluminum content beta-type AGO films remain a challenge. In this work, a multilayer sputtering deposition strategy is introduced, in which Al-only layers are periodically incorporated between GO or AGO layers. This controlled Al stacking method effectively increases the Al incorporation in AGO and leads to an optical bandgap increase when compared to uniform AGO. The multilayer approach allows for tunable Al composition and sputtering target-oxidation resistant alternative to the conventional co-sputtering method for obtaining ultra-wide-bandgap Al-rich AGO thin films.

Magnetic resonance imaging (MRI) is a non-invasive and non-ionizing imaging modality that provides high-resolution images of internal organs such as the breast, brain, and cardiovascular system, enabling three-dimensional visualization of soft tissues. While MRI offers excellent soft tissue contrast, its sensitivity can be further enhanced using contrast agents, and many clinical applications rely on exogenous agents to improve detection and diagnostic accuracy. Two primary classes are used clinically: paramagnetic substances, exemplified by gadolinium (Gd), which predominantly shorten longitudinal (T1) relaxation, and superparamagnetic iron oxide nanoparticles (SPIONs), which exert strong effects on transverse (T2) relaxation. The performance and safety of these agents are strongly influenced by their pharmacokinetics and biodistribution, including rapid recognition and clearance by the reticuloendothelial system, which can both enable liver-spleen imaging and limit target-specific contrast in other organs. In this review, we first summarize the fundamental principles of MRI contrast generation, with an emphasis on relaxation mechanisms relevant to magnetic nanoparticles (MNPs). We then discuss the use of MNPs as contrast agents in representative biomedical applications, focusing on cardiac, breast, and brain MRI and illustrating how organ-specific physiology constrains nanoparticle design and performance. Finally, we examine biocompatibility and safety considerations for both Gd-based agents and SPIONs, highlighting current regulatory concerns, open questions regarding long-term toxicity, and key challenges that must be addressed to translate next-generation nanoparticle-based MRI contrast agents into routine clinical practice.

Prolactin-releasing peptide (PrRP) is an endogenous ligand for the PrRPR, whose activation has been linked to anti-obesity effects. However, PrRP and its analogs also activate the neuropeptide FF receptor 2 (NPFF2R), which is associated with adverse cardiovascular effects. Understanding how PrRP-related peptides differentially engage these two distinct receptors is critical for developing safer, more selective therapeutics. In this study, we present cryo-EM structures of the PrRP analog GUB08248 bound to PrRPR-Gαq and NPFF2R-Gαi at resolutions of 2.45 Å and 2.85 Å, respectively. These structures reveal a conserved ligand recognition mode across both receptors, while highlighting distinct receptor-specific interactions. The NPFF2R-Gαi complex further uncovers key features of receptor activation and G protein coupling. Together, our results offer structural insights that could guide structure-based drug design strategies favoring PrRPR selectivity, thereby advancing the therapeutic potential of the PrRP-PrRPR axis for obesity treatment.

The alarming rates of deaths due to opioid overdose present an urgent need for safer opioid analgesics. Positive allosteric modulators (PAMs) of opioid receptors (ORs) offer a promising approach to enhance opioid efficacy while reducing risks of overdose. In this study, we unveil the selective mechanism of PAM modulation of the OR family through structure elucidation of the δ-opioid receptor and μ-opioid receptor (μOR) bound to orthosteric agonists and PAMs BMS986187 (BMS187) and BMS986122 (BMS122). In addition, we uncovered an unexpected but conserved allosteric site across the transmembrane helices TM2 to TM4 of ORs, occupied by BMS187 but not BMS122. Leveraging these structural insights, we designed 9-(5-(4-chlorophenyl)furan-2-yl)-3,3,6,6-tetramethyl-3,4,5,6,7,9-hexahydro-1H-xanthene-1,8(2H)-dione (MPAM-15), whose αβ cooperativity factor is 33-fold higher than BMS122 and threefold higher than BMS187, indicating markedly stronger positive allosterism. Animal studies demonstrate that MPAM-15 shows excellent brain penetration and enhances morphine-induced antinociception without exacerbating respiratory depression or constipation. Molecular dynamics simulations revealed that MPAM-15 promotes and stabilizes the conformational equilibrium of μOR toward the canonical active state, providing a mechanistic basis for its enhanced allosteric potency. These discoveries substantially advance our understanding of OR allosteric mechanism and pave the way for the structure-based development of allosteric opioid analgesics.

Abstract Introduction mRNA-1647 is an investigational vaccine composed of six mRNAs encoding human cytomegalovirus (hCMV) gB and pentamer antigens. To evaluate vaccine immunogenicity, we developed two hCMV microneutralization (MN) assays to measure neutralizing antibodies that can block viral entry and serve as potential correlates of protection. Methods Cell-based MN assays were validated for fibroblast-tropic AD169 and epithelial-tropic VR1814 strains. Infection was measured as foci-forming units via immunofluorescent detection of immediate early-1 protein. Neutralization titers were expressed as ID50, the serum dilution yielding 50% inhibition relative to virus-only controls. Validation followed a prespecified plan assessing limits of quantitation (LOQs), relative accuracy, dilution linearity, precision, specificity, and stability. Results Dynamic LOQs were 22—7,842 (fibroblast) and 13—206,687 (epithelial), with broader linearity for the epithelial assay. Relative accuracy met the ±2-fold criterion for both assays; the overall geometric mean fold bias (GMFB) was 1.00, and all dynamic-LOQ samples fell within ±2-fold criterion, confirming accuracy. Intra-assay precision CVs were 23.7% and 20.4%, and intermediate precision CVs were 53.7% and 28.7% for fibroblast and epithelial assays, respectively demonstrating acceptable precision. Specificity was confirmed in both assays by observing a ≥ 4-fold titer reduction when competed with homologous antigens, while heterologous antigen competition produced ≤2-fold reductions in ≥ 80% and ≥60% samples in fibroblast and epithelial assay respectively. Serum samples were demonstrated to be stable through 15 freeze—thaw cycles and up to 72 hours at ambient temperature. Conclusion These validated hCMV MN assays demonstrated acceptable accuracy, precision, linearity, stability, and specificity across the dynamic range, enabling reliable, strain- and cell type—specific quantification of nAb responses for clinical evaluation of mRNA-1647. Funding Source Moderna, Inc funded this project. Topic Categories Vaccines and Immunotherapy (VAC)

Abstract Difelikefalin is an FDA-approved κ-opioid receptor (KOR) peptide agonist used to treat chronic pruritus. However, as a balanced agonist that activates both G protein and β-arrestin pathways, difelikefalin remains associated with undesirable side effects linked to β-arrestin signaling. Here, we report the cryo-EM structure of the difelikefalin-KOR-Gi complex, identifying Y3207.43 as a key residue that is critical for signaling bias. Guided by this structural insight, we engineer beta01, a β-amino acid-substituted analog with potent G protein activation but minimal β-arrestin recruitment. In mouse models, beta01 retains robust antinociceptive and antipruritic efficacy while significantly reducing sedation and anxiety-like behaviors. Structural, molecular dynamics simulations and 2D 13C-Met NMR analyses further reveal beta01 stabilizes a unique KOR conformation with an expanded intracellular cavity that disfavors β-arrestin binding. This work establishes a rational structure-based framework for designing safer and more effective GPCR-targeted therapeutics.

Magnetic nanoparticles (MNPs) are attracting increasing attention for applications in energy, environment, and biomedicine. Among all MNP synthesis methods, ball milling is a cost-effective route for producing large quantities of MNPs at low cost. This work aims to investigate the magnetic hyperthermia performance of MNPs synthesized through a mechanochemical ball milling approach. Herein, we first varied the milling conditions and thoroughly characterized the physical properties of the produced MNPs; later, their hyperthermia performance was studied under different alternating magnetic fields (AMF). We report that the MNPs, after ball milling for up to 55 h at 200 rpm, show a higher magnetite phase with an average hydrodynamic size of ~270 nm and irregular morphology. These MNPs were subjected to clinically safe AMF (30 mT, 101.5 kHz), yielding a maximum temperature rise of ~50 °C, including in the SKOV3 cancer cell medium. Additionally, to enable controlled heating and avoid unintended damage to healthy tissues, we applied pulsed AMFs, achieving a temperature of ~30 °C. Lastly, the cellular uptake, colloidal stability, and biocompatibility tests were conducted on suspensions. This study reports a straightforward, cost-effective, large-scale synthesis route for MNPs and highlights their effective hyperthermia performance, showcasing their potential for future safer tumor treatment.

The Mas1 receptor, an orphan class A G-protein-coupled receptor (GPCR), plays pivotal roles in cardiovascular and anti-inflammatory regulation. Despite its therapeutic relevance, the structural mechanisms underlying Mas1 ligand binding and activation remain poorly understood. Here, we report cryo-EM structures of Mas1 bound to two chemically distinct agonists-neuropeptide FF (NPFF) and synthetic small-molecule AR234958-captured in complex with inhibitory G proteins. These structures reveal a conserved orthosteric binding pocket accommodating both ligands through shared hydrophobic interactions. Unlike many other class A GPCRs that rely on direct W6.48 toggle switch engagement, Mas1 adopts a non-canonical activation strategy driven by a ligand-induced hydrophobic compression plane involving residues Y2486.55, L872.60, I842.57, and L2667.39 at the bottom of the ligand binding pocket. This mechanism transmits mechanical tension to promote TM6 displacement and G protein coupling. Functional mutagenesis validates this model, identifying two transmembrane helix 6 (TM6) residues, M2446.51 and F2376.44, as critical molecular switches. Comparative analyses of Mas1-related receptors, MRGPRX1-X4, reveal conserved features and mechanistic divergence within this subfamily. These findings provide a structural framework for understanding Mas1 pharmacology and rational design of selective therapeutics.

Background/Objectives: No licensed vaccine against cytomegalovirus (CMV) is currently available, despite the significant risk of mother-to-infant transmission leading to serious neurodevelopmental impairment and the substantial morbidity caused by CMV infection in immunocompromised persons. We report results from a phase 2 trial of the investigational CMV mRNA vaccine mRNA-1647 and a long-term extension study (NCT04232280; NCT04975893). Methods: This randomized, observer-blind, placebo-controlled phase 2 study, conducted at 9 US sites, enrolled participants in two parts. In the first part, healthy adults aged 18–40 years were stratified by baseline CMV status into CMV-seronegative and CMV-seropositive parallel cohorts and randomized 3:1 to receive mRNA-1647 (50, 100, or 150 μg) or placebo. In the second part, healthy female participants aged 18–40 years were randomized 3:1 to receive 100 μg mRNA-1647 or placebo. In both parts, vaccine or placebo was administered at Months 0, 2, and 6. Participants completing the Primary Trial through Month 18 were eligible to enroll in the extension study, wherein safety and immunogenicity were assessed every 6 months until all participants reached Month 48 (interim analysis) and a subset had Month 54 immunogenicity samples available. Primary objectives were to assess safety and neutralizing antibody responses. Results: Solicited adverse reactions were mostly grade 1 or 2 in severity, and no notable dose-related safety trends were identified. Neutralizing antibody and antigen-specific binding IgG responses were induced in CMV-seronegative participants and boosted in CMV-seropositive participants, with durability of responses through Month 48 and up to Month 54. Conclusions: The investigational vaccine mRNA-1647 was generally well tolerated and induced durable humoral immune responses across baseline CMV serostatus, with persistence supported through Month 48 and by available Month 54 data.