General anesthesia induces reversible changes in consciousness through cortical activity and connectivity alterations, yet the functional connectome dynamics underlying propofol-induced unconsciousness remains unclear. We analyze high-density 128-channel electroencephalogram (EEG) from 31 surgical patients using source localization to identify neurobiological connectome signatures of propofol anesthesia. Propofol anesthesia increases delta and theta functional connectivity and decreases alpha, beta, and gamma connectivity. A classification model and dynamic analysis of consciousness loss reveals that alpha-band connectivity between parietal, occipital, and subcortical regions is critical for sustaining consciousness, with its disruption marking a key transition to unconsciousness. EEG from 46 additional patients under mild sedation with low-dose propofol confirms that decreased parietal-related alpha connectivity serves as a stable marker of reduced consciousness, insensitive to subtle fluctuations but sensitive to the transition from consciousness to unconsciousness. These findings suggest that parietal, occipital, and subcortical alpha connectivity serves as a reliable neural correlate of propofol-induced unconsciousness.
Publications by Year: 2026
2026
In Alzheimer's disease (AD), pathological tau protein shows a progressive accumulation of post-translational modifications (PTMs), reflecting disease severity, progression, and prion-like activity. Although many neurodegenerative diseases with dementia display tau aggregates, the pathological proteoforms of tau protein from each disease type remain unknown. Here, using a quantitative mass spectrometry-based proteomics platform, FLEXITau, deep characterization of pathological tau protein isolated from the brains of 203 human subjects with AD, familial AD (fAD), chronic traumatic encephalopathy (CTE), corticobasal degeneration (CBD), Pick's disease (PiD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB)-a non-tauopathy symptomatic control-and healthy controls (CTR) is performed. Unsupervised data analyses and supervised machine learning identify distinct molecular features of pathological tau for each disease, enabling molecular disease stratification. This study identifies potential disease-specific biomarkers and therapeutic targets for tauopathies and provides critical quantitative information for pharmacokinetic modeling required for therapeutic and disease mechanism studies.
Alterations in KRAS, NRAS, and HRAS occur in roughly 20% of patients with cancer, making RAS one of the most intensively studied oncogenic targets. The discovery of mutant-selective KRASG12C inhibitors has provided a proof-of-concept for RAS-directed therapies, heralding a new era in the treatment of RAS-driven cancers. Yet, the efficacy of first-generation KRASG12C inhibitors is limited by the rapid emergence of resistance. Novel classes of (K)RAS inhibitors with distinct mechanisms of action and broader target coverage hold promise to overcome resistance and extend the benefits of RAS-targeted therapies to a wider patient population. In this review, we summarize clinical evidence for KRASG12C inhibitors across tumor types and delineate key mechanisms of resistance. We further discuss the rapidly evolving landscape of next-generation (K)RAS inhibitors, with particular emphasis on their target selectivity, mechanisms of action, preliminary clinical efficacy, and the therapeutic opportunities and challenges inherent to each class.
BACKGROUND: Vascular calcification is a major contributor to cardiovascular morbidity and mortality in diabetes and is driven in part by osteogenic reprogramming of vascular smooth muscle cells (SMCs). Diabetes is also associated with circadian rhythm disruption; however, how circadian regulators contribute to vascular calcification remains poorly understood. We investigated the role of the core circadian protein Bmal1 (basic helix-loop-helix ARNT-like protein 1) in diabetes-associated vascular calcification.
METHODS: Bmal1 expression was examined in diabetic mouse aortas, human diabetic arterial tissues, and vascular SMCs exposed to high glucose. SMC-specific Bmal1 knockout mice were generated and subjected to low-dose streptozotocin-induced diabetes. Vascular calcification and stiffness were assessed by calcium staining and quantification, and pulse wave velocity. RNA sequencing, chromatin immunoprecipitation, luciferase reporter assay, and clustered regularly interspaced short palindromic repeats-clustered regularly interspaced short palindromic repeat-associated 9-mediated genome editing were used to define Bmal1-regulated molecular mechanisms.
RESULTS: Bmal1, but not other circadian regulators, was selectively upregulated in diabetic arteries and vascular SMCs under hyperglycemic conditions. SMC-specific deletion of Bmal1 markedly attenuated diabetes-induced vascular calcification, reduced aortic stiffness, and suppressed osteogenic gene expression in vivo and in vitro. RNA-sequencing analysis revealed enrichment of Bmal1-dependent genes involved in osteogenic differentiation and extracellular matrix organization. Mechanistically, Bmal1 directly binds to an E-box motif in the Runx2 (Runt-related transcription factor 2) promoter, enhancing Runx2 transcription independently of canonical circadian pathways. Disruption of Bmal1 binding to the Runx2 promoter abolished Bmal1-induced Runx2 expression.
CONCLUSIONS: Our findings identify Bmal1 as a key mediator of diabetes-induced vascular calcification through direct transcriptional regulation of Runx2 via a noncanonical circadian mechanism. These results reveal a previously unrecognized pathogenic role for Bmal1 in vascular disease and suggest that targeting dysregulated circadian factors may represent a novel therapeutic strategy for preventing vascular calcification in diabetes.
The growing societal demand for convenient and personalized healthcare solutions has driven significant progress in human-interactive technologies. Soft electronics, with their extrinsic deformability, have sparked innovations in the design of stretchable and highly adaptable biomedical devices that enhance wearability. Despite these advancements, portable power sources remain a key limitation, constrained by short operating times and the inconvenience of frequent recharging or battery replacement. To overcome this hurdle, triboelectric nanogenerators (TENGs), which convert mechanical energy into electricity, have emerged as promising sustainable power sources, offering high efficiency, lightweight design, and self-sustaining operation. Recent developments in integrating TENGs with ionic materials have enabled their use on or beneath the skin, allowing the harvesting of biomechanical energy that would otherwise be wasted to power healthcare devices. This review provides a comprehensive overview of attachable and implantable TENGs, classified by electronic and ionic materials, and examines their material choices, device structures, and operational mechanisms. This review further explores various sustainable biomedical applications, assessing the performance of these devices in both sustainable power sources and self-powered physiological signal sensing. Finally, key future research directions are outlined, including sweat tolerance, skin compliance, AI-enabled TENG biointerfaces, acoustic transparency, minimally invasive implantation strategies, and regulatory considerations for clinical translation.
INTRODUCTION: Because Americans spend approximately 87% of their time indoors, indoor air quality is a critical determinant of childhood asthma outcomes. Indoor environmental pollutants are heterogenous and dynamic, reflecting variations in household behaviors, building characteristics, and outdoor air quality and environmental exposures that penetrate the home envelope. The purpose of this state-of-the-art review is to provide an overview of current knowledge on common indoorpollutants.
METHODS: PubMed was queried for studies published on indoor air pollutants between 2020 and 2025. Key pollutants identified are mold, particulate matter ≤ 2.5 µm (PM2.5), nitrogen dioxide (NO₂), volatile organic compounds (VOCs), and radon.
RESULTS: These studies highlight significant associations between pollutants and asthma prevalence, increased asthma symptoms, and reduced lung function. Some associations exist despite exposures levels below thresholds set by the U.S. Environmental Protection Agency (EPA) and the World Health Organization (WHO).
CONCLUSION: Further research is needed to expand our understanding of mixture effects and develop evidence-based practices for decreasing exposure to improve asthma outcomes.
BACKGROUND: Medical professional liability claims are a marker of conflict between a patient and a health care provider.
OBJECTIVES: The purpose of this study was to evaluate the contributing factors (CFs) associated with medical professional liability claims.
METHODS: A total of 764 cardiovascular-related closed claims with 1,945 CFs were identified from a large insurer (The Doctor's Company) from 2010 to 2023.
RESULTS: Three clinical CFs: technical performance (329; 43% of claims), patient assessment (242; 32%), and management/selection of therapy (216; 28%) were the most frequently cited CFs. Patient factors, mainly due to nonadherence to medications or instructions, were identified in 171 claims (22%). Nonclinical CFs (987) were more frequent than clinical CFs (787) and patient factors (patient: 171). Nonclinical CFs were very diverse but the most frequent were communication between providers and patient (20%), communication among providers (16%), insufficient documentation (11%), and off-shift/weekend hours (10%). Payment was less common in claims with technical performance or patient factor CFs and more common in claims with patient assessment, selection/management of therapy, and in the 4 most frequent nonclinical CFs. Nonclinical CFs were more commonly observed in claims with payment (1.1/claim) when compared to claims without (0.64/claim). No differences among the different cardiovascular subspecialties were identified. Closed claims were identified in 3% of covered cardiovascular providers over the last reliable portion of the study period.
CONCLUSIONS: Clinical and nonclinical CFs are equally important for malpractice claims. While focusing on clinical quality is important, implementing strategies that also account for nonclinical issues, with a particular focus on communication, documentation, and off-shift/weekend coverage could have significant benefits.
STUDY DESIGN: Retrospective cohort study.
OBJECTIVE: To understand the strengths of titanium cages for ACDF using a propensity score matched analysis while characterizing radiologic and clinical outcomes associated with graft material.
SUMMARY OF BACKGROUND EVIDENCE: Structural allografts and synthetic grafts such as titanium cages have been frequently utilized for anterior cervical discectomy and fusion (ACDF). Although the biomechanical properties have been compared between these 2 graft types, there remains limited data on their comparative performance for cervical procedures.
METHODS: We assembled a cohort of patients who underwent an ACDF with a structural allograft or titanium cage at a tertiary care medical center and community hospital by a single surgeon. To compare outcomes, 1:1 propensity score matching was performed using optimal pair matching and a generalized linear model.
RESULTS: Of 376 patients, 269 received a structural allograft and 107 a titanium cage [median age: 56 y, 51.6% (n=194) female, 22.9% (n=86) current smokers]. Almost half of ACDFs (161 patients, 42.8%) were multilevel fusions. Across both graft materials, ACDFs had a relatively safe complication profile with a low intraoperative blood loss. There was durable symptom relief, with 94.5% (n=345 of 365) of patients reporting improved to resolved symptoms at last follow-up. Patients with titanium cages had significantly greater cervical Cobb angle change compared with patients with structural allografts (P<0.001). After propensity score matching, patients with titanium cages had a lower estimated blood loss (P=0.03) and shorter hospital length of stay (P<0.001). However, there were no significant differences in rates of fusion, cage subsidence, pseudoarthrosis, or revision surgery.
CONCLUSIONS: Titanium cages demonstrate a similar safety and efficacy profile to structural allografts and may enable greater cervical Cobb angle changes. Longer neurosurgical follow-up may be required to assess need for revision procedures and quantitative patient-reported outcomes across cage materials.
Innovation in biomaterials has brought both breakthroughs and challenges in medicine, as implant materials have become increasingly multifunctional and complex. One of the greatest issues is the difficulty in assessing the temporal and multidimensional dynamics of tissue-implant interactions. Implant biology remains difficult to decipher without a noninvasive and multiplexed technique that can accurately monitor real-time biological processes. To address this, we developed a multifunctional, self-sensing implant material composed of gold nanocolumns patterned on a titanium surface (AuNC-Ti). This material acts as a nanoengineered surface-enhanced Raman spectroscopy (SERS) substrate that amplifies biological Raman signals at the tissue-implant interface, providing the ability to sense tissue-material interactions in a multiplexed and nondestructive manner. AuNC-Ti SERS substrates were fabricated using oblique angle deposition (OAD) and characterized using scanning electron microscopy (SEM) to show uniform formation of AuNCs (360 ± 40 nm in length and 50 ± 16 nm in width). X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and contact angle measurements demonstrated a biocompatible surface chemistry with ideal wettability. Biocompatibility was further demonstrated via in vitro cytotoxicity assays on human aortic endothelial cells (HAECs) cultured on AuNC-Ti surfaces. The median SERS enhancement factor (EF) was calculated to be 1.8 × 105, and spatial identification of reporter molecules and porcine tissue components on AuNC-Ti surfaces was demonstrated by using confocal Raman imaging and multivariate analysis. Our approach utilizes unlabeled SERS and machine learning techniques, promising multiplexed characterization of tissue-material interactions and subsequently enabling tissue state determination and noninvasive monitoring of implant-tissue interaction.