Faculty Bibliography

Boiogito (BOT), a traditional Kampo herbal medicine, has been reported to exhibit anti-inflammatory and anti-obesity properties. However, its potential role in protecting adipocyte function under inflammatory conditions at different stages of adipocyte development remains unclear. This study investigated the effects of BOT on adipogenesis and tumor necrosis factor-α (TNF-α)-induced inflammatory responses in differentiating and mature 3T3-L1 adipocytes. In this study, 3T3-L1 preadipocytes were induced to differentiate and exposed to TNF-α in the presence or absence of BOT during differentiation or after full adipocyte maturation. Lipid accumulation was assessed by Oil Red O staining, while adipokine secretion and inflammatory cytokine production were evaluated by ELISA. The expression of adipogenic markers and inflammatory signaling molecules was analyzed using quantitative PCR and Western blotting. TNF-α significantly inhibited the expression of adipogenesis-related factors at the transcriptional level in adipocytes, reduced lipid accumulation and adiponectin expression, and enhanced inflammatory cytokine production. BOT treatment dose-dependently attenuated these effects, restoring adipogenic capacity and suppressing inflammatory responses in both differentiating and mature adipocytes. Mechanistically, BOT reduced TNF-α-induced activation of the NF-κB pathway, as evidenced by decreased phosphorylation of NF-κB p65 and IκB. These findings demonstrate that BOT preserves adipocyte function and mitigates inflammation-associated adipocyte dysfunction throughout adipocyte development. The protective effects of BOT may contribute to the regulation of obesity-associated metabolic inflammation, partly through modulation of NF-κB signaling.

Hepatitis-hydropericardium syndrome (HHS) caused by fowl adenovirus serotype 4 (FAdV-4) has led to substantial economic losses in the poultry industry. Subunit vaccines based on the knob domains of Fiber1 and Fiber2 (F1F2K) are safe but exhibit limited immunogenicity. To address this, we sought to enhance the immune response by presenting F1F2K on self-assembling Mi3 nanoparticles (F1F2K:Mi3) and to compare its efficacy with the F1F2K monomer. F1F2K was conjugated to Mi3 via the SpyTag/SpyCatcher system. Chickens were immunized twice with F1F2K:Mi3 nanoparticles, F1F2K monomer, Mi3, or PBS, and then challenged with a lethal dose of FAdV-4. Humoral and cellular immune responses were evaluated by enzyme-linked immunosorbent assay (ELISA), virus neutralization tests, and cytokine assays. Compared with the F1F2K monomer, F1F2K:Mi3 nanoparticles induced significantly higher antigen-specific IgG titers at 28 days post-vaccination (dpv) and a 2.5-log₂ increase in neutralizing antibody titers. Nanoparticle immunization also elicited stronger T helper 1/T helper 2 (Th1/Th2) cytokine responses (IFN-γ, IL-4, and IL-2). Following challenge, all chickens in both the nanoparticle and monomer groups survived. However, compared with the F1F2K monomer group, the F1F2K:Mi3 group exhibited less weight loss, lower tissue viral loads, reduced viral shedding, and markedly less liver damage, thereby more effectively blocking FAdV-4 pathogenicity in target organs. Our study demonstrates that displaying the F1F2K antigen on Mi3 nanoparticles synergistically enhances both humoral and cellular immune responses against FAdV-4, providing a promising next-generation nanoparticle vaccine strategy for HHS control.

Stroke remains a major cause of disability worldwide, and population-level indicators that integrate multidimensional vulnerability with physiological reserve may provide useful perspectives for characterizing cerebrovascular health in aging populations. This cross-sectional study examined the association between the Frailty-to-estimated Cardiorespiratory Fitness Ratio (FCR) and self-reported prevalent stroke among middle-aged and older adults using NHANES 2011-2014 data. FCR was calculated as a 23-item modified Frailty Index divided by estimated cardiorespiratory fitness, providing an interpretable load-to-reserve measure that linked accumulated health deficits with estimated cardiorespiratory reserve. The final analytical sample included 3511 participants aged 45 years or older. Survey-weighted logistic regression models, sensitivity analyses, exploratory subgroup analyses, and spline models were used to evaluate the association. The weighted prevalence of self-reported prevalent stroke increased across FCR quartiles, from 2.2% in Q1 to 12.9% in Q4. In the conventional clinical adjustment model, participants in the highest FCR quartile had greater odds of self-reported prevalent stroke than those in the lowest quartile (OR = 6.13, 95% CI: 2.97-12.66; p<0.001), with similar findings in the overlap-aware model (OR = 6.31, 95% CI: 3.07-12.97; p<0.001). Log-transformed FCR was also consistently associated with greater odds of self-reported prevalent stroke across adjustment models, and spline analysis suggested a generally increasing association. These findings support FCR, particularly when modeled using quartiles or log-transformed values, as an interpretable integrative load-to-reserve construct associated with self-reported prevalent stroke, and suggest its potential relevance for population-based characterization of cerebrovascular health in aging adults.

In nonequilibrium quantum systems, the quantum Mpemba effect (QME) emerges as a counterintuitive phenomenon: Systems exhibiting greater initial symmetry breaking restore symmetry faster. It has been attracting broad interest in studying QME dynamics and potential applications in quantum information science. While theoretical exploration of QME has surged, experimental studies, specifically on its flexible modulation, remain limited. Here, we report the observation and modulation of QME using a superconducting processor featuring an all-to-all connected, tunable-coupling architecture that enables precise control from short- to long-range interactions. This platform allows independent manipulation of coupling regimes, on-site potentials, and initial states, enabling us to elucidate their roles in QME. To quantify symmetry restoration, we employ entanglement asymmetry (EA), derived from the reconstructed density matrix via quantum state tomography, as a sensitive probe. In strong short-range coupling regimes, EA crossovers during quenches from tilted Néel states confirm the presence of QME. In contrast, in intermediate-coupling regimes, synchronized EA and entanglement entropy dynamics reveal the suppression of QME. Remarkably, QME reemerges with the introduction of on-site linear potentials or quenches from tilted ferromagnetic states, the latter proving robust against on-site disorder. Our study demonstrates flexible QME modulation on a superconducting platform with multiple controllable parameters, shedding light on quantum many-body nonequilibrium dynamics and opening avenues for quantum information applications.

INTRODUCTION/BACKGROUND:Durvalumab consolidation after concurrent chemoradiotherapy (cCRT) is standard for unresectable stage III NSCLC; however, radiation pneumonitis (RP) remains a major treatment-limiting toxicity. Lung dosimetry incompletely explains the risk of toxicity. Recent studies have established radiographic thymic health as clinically relevant in cancer, but its relationship to treatment-related toxicity remains unclear. We evaluated whether percent thymic tissue (pTT), an interpretable CT-derived measure of residual thymic tissue, is associated with severe pneumonitis after cCRT in NSCLC. METHODS:We analyzed patients with locally advanced NSCLC treated with cCRT with or without durvalumab in RTOG 0617 (n = 453) and at the Memorial Sloan Kettering Cancer Center (MSKCC, n = 230). pTT was derived from pretreatment CT using autosegmentation and Gaussian mixture modeling. Logistic regression with restricted cubic splines assessed the associations of pTT, mean radiation dose to the thymic region, and volume of lungs receiving more than or equal to 20 Gy (lung V20) with high-grade (≥3) pneumonitis. RESULTS:Higher pTT was associated with lower severe pneumonitis rates, independent of lung V20. Grade 3+ pneumonitis occurred in 8.0% versus 3.1% of low- versus high-pTT patients in RTOG 0617 (p = 0.03) and in 13.9% versus 5.2% at the MSKCC (p = 0.04). Patients with both low pTT and high lung V20 had the highest severe pneumonitis rates. Mean radiation dose to the thymic region revealed a weaker, nonlinear relationship with pneumonitis risk. CONCLUSIONS:pTT is an interpretable, host-specific radiographic biomarker associated with severe pneumonitis after cCRT in NSCLC. Incorporating pTT into risk stratification may improve individualized treatment planning and support the safer delivery of curative-intent therapy in locally advanced NSCLC.

Neurodevelopmental disorders are genetically heterogeneous and often remain unresolved despite extensive clinical evaluation and genomic testing. Here, we report a proband with a progressive neurodevelopmental disorder evaluated through the Undiagnosed Diseases Network who harbored heterozygous de novo missense variants in two genes, DCLK1 (p.(S228L)) and SFPQ (p.(P623R)). To determine the clinical significance of these candidate variants, we employed an integrative pipeline combining structural modeling, cross-species functional genomics, and patient-derived neuronal analyses. While the SFPQ variant yielded no detectable phenotype in Drosophila melanogaster, modeling the DCLK1 p.S228L variant in Caenorhabditis elegans induced severe locomotor deficits and aberrant neuronal morphology, including neurite blebbing. Parallel analyses of directly reprogrammed patient-derived neurons recapitulated these neurite defects, characterized by neurite beading, swelling and fragmentation, and elevated apoptosis. Transcriptomic profiling revealed dysregulation of neurodevelopmental and axon-guidance pathways alongside molecular signatures of neurodegeneration. Crucially, exogenous expression of wild-type DCLK1 or pharmacological targeting of a downstream dysregulated pathway partially rescued the neurite defects. Collectively, our findings implicate DCLK1 in a previously unrecognized progressive neurodevelopmental disorder and demonstrate the power of integrative cross-species functional genomics in resolving ultra-rare disease variants.

Full-arch implant rehabilitation-necessitating a holistic, transdisciplinary approach-has been one of the most rapidly advancing disciplines in implant dentistry, driven by rising standards and modern technologic advancements. Despite indicated cases and genuine efforts to improve efficiency, the current trend of an immediacy (or 'teeth-in-a-day') protocol may have unintentionally veiled a more conservative, predictable, and practical potential in wound healing process, esthetics, and occlusion. Through an approach that is more phased and utilizes terminal dentitions as strategic abutments, this case report with 3 years of follow-up emphasizes the leverage of natural biologic phenomena in tissue maturation, remodeling, and condensation, along with prosthetic sophistications focusing on its meticulousness in execution and long-range trajectory success. This workflow actualizes a high-quality level of craftsmanship with surgical and prosthetic innovations, introduced as a 'retightening bilateral sling periosteal mattress suture' concept for intermittent tensocompressive mechanotransduction-induced guided bone regeneration and 'LegOvate' protocol for seamless loading of prosthetic conversions, emphasizing the intricate reciprocity between physiology and biomechanics for a primary goal of a nondestructive equilibrium.

BACKGROUND:Effective screening and cohort enrichment remain major challenges in clinical trials for Alzheimer's disease (AD), where traditional diagnostic pathways rely on costly, invasive, and time-consuming procedures. Speech and language analysis has emerged as a scalable, low-burden approach for detecting subtle cognitive-linguistic and motor-speech changes that may appear early in the disease course. SUMMARY/CONCLUSIONS:This review synthesizes current evidence on acoustic, prosodic, lexical, semantic, and syntactic speech features associated with AD and mild cognitive impairment (MCI) and evaluates their reported utility across a range of elicitation tasks including picture description, verbal fluency, narrative recall, spontaneous speech, and reading. Across studies, machine-learning models trained on speech and language features have reported consistent performance, although results vary substantially depending on task design, feature sets, and cohort characteristics. Task-dependent variability is evident, with picture description and verbal fluency tasks capturing lexical-semantic and timing markers, while narrative and spontaneous speech tasks capture impairments in coherence, information content, and prosody. Hybrid approaches integrating hand-crafted and machine-extracted features have also been explored to improve interpretability and model performance. Speech and language analytics may support digital prescreening, cohort enrichment, and quality-assurance monitoring within clinical trials; however, their application depends on methodological considerations and validation across diverse settings. KEY MESSAGES/CONCLUSIONS:Despite encouraging findings, several methodological challenges persist, including interindividual variability, limited dataset sizes, differences in recording conditions, and limitations in automatic speech recognition performance in cognitively impaired populations. Continued development of standardized protocols, disorder-adapted speech models, and multimodal analytic pipelines is needed to support clinical translation. Collectively, current evidence suggests that speech and language features represent candidate digital markers that may improve screening efficiency and support clinical trial enrichment in AD, although further validation is required to establish their reliability and generalizability.

We present a topology-optimization methodology for designing single-sided, tri-state electrode patterns (+V, 0, electrode-free) that maximize shear-mode purity in lithium niobate (LiNbO₃) wafers. The framework combines a complex-Hermitian adjoint sensitivity formulation based on Wirtinger calculus with a coarse-fine design-mesh decomposition and Heaviside projection, and treats the bottom-face electrical boundary condition as an explicit design variable. Applying the method to five crystal cuts (X, Y, Z, 41°Y, 128°Y) over 3.30-4.10 MHz under grounded and single-sided configurations, we find that the optimal boundary condition is jointly determined by crystal cut and frequency through the rotated piezoelectric tensor and that topology optimization improves purity by up to 28.8 percentage points when the baseline is poorly matched but can be counterproductive when it is already optimal (Z-cut). We distil these behaviors into a three-regime taxonomy that predicts, a priori, when optimization is worthwhile. The result is a reusable design methodology, together with per-cut design rules, for shear-mode LiNbO₃ transducers.