Viscoelastic Adhesive, Super-Conformable, and Semi-Flowable Liquid Metal Eutectogels for High-Fidelity Electrophysiological Monitoring.

Integrating gels with human skin through wearables provides unprecedented opportunities for health monitoring technology and artificial intelligence. However, most conductive hydrogels, organogels, and ionogels lack essential environmental stability, biocompatibility, and adhesion for reliable epidermal sensing. In this study, we have developed a liquid metal eutectogel simultaneously possessing superior viscoelasticity, semiflowability, and mechanical rigidity for low interfacial skin impedance, high skin adhesion, and durability. Liquid metal particles (LMPs) are employed to generate free radicals and gallium ions to accelerate the polymerization of acrylic acid monomers in a deep eutectic solvent (DES), obtaining highly viscoelastic polymer networks via physical cross-linking. In particular, graphene oxide (GO) is utilized to encapsulate the LMPs through a sonication-assisted electrostatic assembly to stabilize the LMPs in DES, which also enhances the mechanical toughness and regulates the rheological properties of the eutectogels. Our optimized semi-flowable eutectogel exhibits viscous fluid behavior at low shear rates, facilitating a highly conformable interface with hairy skin. Simultaneously, it demonstrates viscoelastic behavior at high shear rates, allowing for easy peel-off. These distinctive attributes enable the successful applications of on-skin adhesive strain sensing and high-fidelity human electrophysiological (EP) monitoring, showcasing the versatility of these ionically conductive liquid metal eutectogels in advanced personal health monitoring.

Prediction Value of Initial Serum Levels of SERPINA3 in Intracranial Pressure and Long-Term Neurological Outcomes in Traumatic Brain Injury.

Traumatic brain injury (TBI) is a severe neurological condition characterized by inflammation in the central nervous system. SERPINA3 has garnered attention as a potential biomarker for assessing this inflammation. Our study aimed to explore the predictive value of postoperative serum SERPINA3 levels in identifying the risk of cerebral edema and its prognostic implications in TBI. This study is a prospective observational study, including 37 patients with TBI who finally met our criteria. The Glasgow Outcome Scale (GOS), Levels of Cognitive Functioning (LCF), Disability Rating Scale (DRS), and Early Rehabilitation Barthel Index (ERBI) scores at six months after trauma were defined as the main study endpoint. We further calculated the ventricle-to-intracranial-volume ratio (VBR) at 6 months from CT scans. The study included patients with Glasgow Coma Scale (GCS) scores ranging from 3 to 8, who were subsequently categorized into two groups: the critical TBI group (GCS 3-5 points) and the severe TBI group (GCS 6-8 points). Within the critical TBI group, SERPINA3 levels were notably lower. However, among patients with elevated SERPINA3 levels, both the peak intracranial pressure (ICP) and average mannitol consumption were significantly reduced compared with those of patients with lower SERPINA3 levels. In terms of the 6-month outcomes measured via the GOS, LCF, DRS, and ERBI, lower levels of SERPINA3 were indicative of poorer prognosis. Furthermore, we found a negative correlation between serum SERPINA3 levels and the VBR. The receiver operating characteristic (ROC) curve and decision curve analysis (DCA) demonstrated the predictive performance of SERPINA3. In conclusion, incorporating the novel biomarker SERPINA3 alongside traditional assessment tools offers neurosurgeons an effective and easily accessible means, which is readily accessible early on, to predict the risk of intracranial pressure elevation and long-term prognosis in TBI patients.

Brain Delivery of Protein Therapeutics by Cell Matrix-Inspired Biomimetic Nanocarrier.

Protein therapeutics are anticipated to offer significant treatment options for central nervous system (CNS) diseases. However, the majority of proteins are unable to traverse the blood-brain barrier (BBB) and reach their CNS target sites. Inspired by the natural environment of active proteins, the cell matrix components hyaluronic acid (HA) and protamine (PRTM) are used to self-assemble with proteins to form a protein-loaded biomimetic core and then incorporated into ApoE3-reconstituted high-density lipoprotein (rHDL) to form a protein-loaded biomimetic nanocarrier (Protein-HA-PRTM-rHDL). This cell matrix-inspired biomimetic nanocarrier facilitates the penetration of protein therapeutics across the BBB and enables their access to intracellular target sites. Specifically, CAT-HA-PRTM-rHDL facilitates rapid intracellular delivery and release of catalase (CAT) via macropinocytosis-activated membrane fusion, resulting in improved spatial learning and memory in traumatic brain injury (TBI) model mice (significantly reduces the latency of TBI mice and doubles the number of crossing platforms), and enhances motor function and prolongs survival in amyotrophic lateral sclerosis (ALS) model mice (extended the median survival of ALS mice by more than 10 days). Collectively, this cell matrix-inspired nanoplatform enables the efficient CNS delivery of protein therapeutics and provides a novel approach for the treatment of CNS diseases.

Thermally Conductive and UV-EMI Shielding Electronic Textiles for Unrestricted and Multifaceted Health Monitoring.

Skin-attachable electronics have garnered considerable research attention in health monitoring and artificial intelligence domains, whereas susceptibility to electromagnetic interference (EMI), heat accumulation issues, and ultraviolet (UV)-induced aging problems pose significant constraints on their potential applications. Here, an ultra-elastic, highly breathable, and thermal-comfortable epidermal sensor with exceptional UV-EMI shielding performance and remarkable thermal conductivity is developed for high-fidelity monitoring of multiple human electrophysiological signals. Via filling the elastomeric microfibers with thermally conductive boron nitride nanoparticles and bridging the insulating fiber interfaces by plating Ag nanoparticles (NPs), an interwoven thermal conducting fiber network (0.72 W m-1 K-1) is constructed benefiting from the seamless thermal interfaces, facilitating unimpeded heat dissipation for comfort skin wearing. More excitingly, the elastomeric fiber substrates simultaneously achieve outstanding UV protection (UPF = 143.1) and EMI shielding (SET > 65, X-band) capabilities owing to the high electrical conductivity and surface plasmon resonance of Ag NPs. Furthermore, an electronic textile prepared by printing liquid metal on the UV-EMI shielding and thermally conductive nonwoven textile is finally utilized as an advanced epidermal sensor, which succeeds in monitoring different electrophysiological signals under vigorous electromagnetic interference. This research paves the way for developing protective and environmentally adaptive epidermal electronics for next-generation health regulation.

Superelastic Radiative Cooling Metafabric for Comfortable Epidermal Electrophysiological Monitoring.

Epidermal electronics with superb passive-cooling capabilities are of great value for both daytime outdoor dressing comfort and low-carbon economy. Herein, a multifunctional and skin-attachable electronic is rationally developed on a porous all-elastomer metafabric for efficient passive daytime radiative cooling (PDRC) and human electrophysiological monitoring. The cooling characteristics are realized through the homogeneous impregnation of polytetrafluoroethylene microparticles in the styrene-ethylene-butylene-styrene fibers, and the rational regulation of microporosity in SEBS/PTFE metafabrics, thus synergistically backscatter ultraviolet-visible-near-infrared light (maximum reflectance over 98.0%) to minimize heat absorption while efficiently emit human-body midinfrared radiation to the sky. As a result, the developed PDRC metafabric achieves approximately 17 °C cooling effects in an outdoor daytime environment and completely retains its passive cooling performance even under 50% stretching. Further, high-fidelity electrophysiological monitoring capability is also implemented in the breathable and skin-conformal metafabric through liquid metal printing, enabling the accurate acquisition of human electrocardiograph, surface electromyogram, and electroencephalograph signals for comfortable and lengthy health regulation. Hence, the fabricated superelastic PDRC metafabric opens a new avenue for the development of body-comfortable electronics and low-carbon wearing technologies.

Quasi-Homogeneous and Hierarchical Electronic Textiles with Porosity-Hydrophilicity Dual-Gradient for Unidirectional Sweat Transport, Electrophysiological Monitoring, and Body-Temperature Visualization.

On-skin electronics based on impermeable elastomers and stacking structures often suffer from inferior sweat-repelling capabilities and severe mechanical mismatch between sub-layers employed, which significantly impedes their lengthy wearing comfort and functionality. Herein, inspired by the transpiration system of vascular plants and the water diode phenomenon, a hierarchical nonwoven electronic textile (E-textile) with multi-branching microfibers and robust interlayer adhesion is rationally developed. The layer-by-layer electro-airflow spinning method and selective oxygen plasma treatment are utilized to yield a porosity-hydrophilicity dual-gradient. The resulting E-textile shows unidirectional, nonreversible, and anti-gravity water transporting performance even upon large-scale stretching (250%), excellent mechanical matching between sub-layers, as well as a reversible color-switching ability to visualize body temperature. More importantly, the conducting and skin-conformal E-textile demonstrates accurate and stable detecting capability for biomechanical and bioelectrical signals when applied as an on-skin bioelectrode, including different human activities, electrocardiography, electromyogram, and electrodermal activity signals. Further, the E-textile can be efficiently implemented in human-machine interfaces to build a gesture-controlled dustbin and a smart acousto-optic alarm. Hence, this hierarchically-designed E-textile with integrated functionalities offers a practical and innovative method for designing comfortable and daily applicable on-skin electronics.

Perspiration-Wicking and Luminescent On-Skin Electronics Based on Ultrastretchable Janus E-Textiles.

Stretchable electronics have attracted surging attention for next-generation smart wearables, yet traditional flexible devices fabricated on hermetical elastic substrates cannot satisfy lengthy wearing comfort and signal stability due to their poor moisture and air permeability. Herein, perspiration-wicking and luminescent on-skin electrodes are fabricated on superelastic nonwoven textiles with a Janus configuration. Through the electrospin-assisted face-to-face assembly of all-SEBS microfibers with differentiated diameters and composition, porosity and wettability asymmetry are constructed across the textile, endowing it with antigravity water transport capability for continuous sweat release. Also, the phosphor particles evenly encapsulated in the elastic fibers empower the Janus textile with stable light-emitting capability under extreme stretching in a dark environment. Additionally, the precise printing of highly conductive liquid metal (LM) circuits onto the matrix not only equips the electronic textile with broad detectability for various biophysical and electrophysiological signals but also enables successful implementation of human-machine interface (HMIs) to control a mechanical claw.

Large-scale assessment of missed opportunity risks in a complex hospital setting.

In this research, we apply a large-scale logistic regression analysis to assess the patient missed opportunity risks at a complex VA (US Department of Veterans Affairs) hospital in three categories, namely, no-show alone, no-show combined with late patient cancellation and no-show combined with late patient and clinic cancellations. The analysis includes unique explanatory variables related to VA patients for predicting missed opportunity risks. Furthermore, we develop two aggregated weather indices by combining many weather measures and include them as explanatory variables. The results indicate that most of the explanatory variables considered are significant factors for predicting the missed opportunity risks. Patients with afternoon appointment, higher percentage service connected, and insurance, married patients, shorter lead time and appointments with longer appointment length are consistently related to lower risks of missed opportunity. Furthermore, the VA patient-related factors and the two proposed weather indices are useful predictors for the risks of no-show and patient cancellation. More importantly, this research presents an effective procedure for VA hospitals and clinics to analyze the missed opportunity risks within the complex VA information technology system, and help them to develop proper interventions to mitigate the adverse effects caused by the missed opportunities.

Communication enhancement and best practices for co-managing dual care rural Veteran patients by VA and non-VA providers: a survey study.

Many rural Veteran patients receive healthcare services from both Veterans Affairs (VA) and non-VA providers. Effective management of dual care Veteran patients to ensure the best clinical outcomes is a VA mission. The previous VA studies indicate that coordination between VA and non-VA providers has been lacking for dual care management of Veteran patients. In this study, we propose that VA proactively shares information with non-VA providers to enhance the communication process and identify the best practices to be carried out by both VA and non-VA providers for better coordination. Structured questionnaires are designed and distributed to VA and non-VA providers to obtain their evaluations on the proposed VA proactive information sharing approaches and the best practice items for dual care management. The non-VA provider respondents largely support the proposed proactive sharing items by VA, with the lowest average score being 3.96 out of a 5.0 scale on one item. In terms of the best practice items on co-managing dual care patients, three out of five items are overall rated higher than 4.0 from both sides. A pair-wise comparison between VA and non-VA perspectives further shows that the difference in average ratings of a proposed item could be significant. For such best practice items, the implementations from both sides may not be most effective.

A two-phase approach to scheduling multi-category outpatient appointments--a case study of a women's clinic.

In this paper, we propose a two-phase approach for designing a weekly scheduling template for outpatient clinics providing multiple types of services. In many outpatient clinics, various service types are categorized to address the operational challenge of substantial changeover time between certain pairs of services. In the first phase of our approach, a mixed-integer program is formulated to assign service categories to clinic sessions during a week and determine the optimal number of appointments reserved for each service type in each clinic session. The objective in the first phase is to balance the workload of the providers among clinic sessions. In the second phase, a stochastic mixed-integer program is formulated for each clinic session to assign each contained appointment with a starting time based on several time-based performance measures. To solve the formulated stochastic program, we develop a Monte Carlo sampling based genetic algorithm. The two-phase approach is tested numerically with cases derived from a real women's clinic. Our results demonstrate that the two-phase approach can efficiently find promising weekly appointment scheduling templates for outpatient clinics. In addition, our results suggest that the best suboptimal scheduling templates found become more sensitive to the weighting coefficients of the time-based measures as the provider workload increases.