Alkali Metals Activated High Entropy Double Perovskites for Boosted Hydrogen Evolution Reaction.

An efficient and facile water dissociation process plays a crucial role in enhancing the activity of alkaline hydrogen evolution reaction (HER). Considering the intricate influence between interfacial water and intermediates in typical catalytic systems, meticulously engineered catalysts should be developed by modulating electron configurations and optimizing surface chemical bonds. Here, a high-entropy double perovskite (HEDP) electrocatalyst La2(Co1/6Ni1/6Mg1/6Zn1/6Na1/6Li1/6)RuO6, achieving a reduced overpotential of 40.7 mV at 10 mA cm-2 and maintaining exemplary stability over 82 h in a 1 m KOH electrolyte is reported. Advanced spectral characterization and first-principles calculations elucidate the electron transfer from Ru to Co and Ni positions, facilitated by alkali metal-induced super-exchange interaction in high-entropy crystals. This significantly optimizes hydrogen adsorption energy and lowers the water decomposition barrier. Concurrently, the super-exchange interaction enhances orbital hybridization and narrows the bandgap, thus improving catalytic efficiency and adsorption capacity while mitigating hysteresis-driven proton transfer. The high-entropy framework also ensures structural stability and longevity in alkaline environments. The work provides further insights into the formation mechanisms of HEDP and offers guidelines for discovering advanced, efficient hydrogen evolution catalysts through super-exchange interaction.

Research on denoising method based on temperature and humidity profile lidar.

Due to the fact that the vibration and pure rotational Raman signals collected by the temperature and humidity profile lidar were 3-4 orders of magnitude weaker than the Mie scattering signal, they were susceptible to electronic and white noise interference, which seriously affected the system signal-to-noise ratio. In this paper, an improved VMD-WT filtering method was adopted to extract effective signals and denoise. The processing outcome of several filtering algorithms was evaluated, and noisy signals were simulated to confirm the algorithm's efficacy. Based on the quantitative computation of evaluation indicators, such as signal-to-noise ratio, root mean square error, and correlation, the improved VMD-WT algorithm had more significant advantages in indicators such as signal-to-noise ratio. In order to further verify the robustness and adaptability of the proposed algorithm, experimental analysis of the filtering algorithm was conducted on the continuously collected temperature and humidity measured signals. The results demonstrated that the algorithm not only improved the detection range of lidar and suppressed high-altitude noise effectively, but also performed well in processing strong interference signals, like clouds, which led to a significant improvement in the atmospheric optical parameter inversion results. Furthermore, pseudo-color images of aerosols, temperature, and humidity changes over time and space have been used to further illustrate the algorithm's dependability and wide range of potential uses.

Noninvasive Assessing Low Back Pain by a Novel Near-Infrared Spectroscopy Flexible Probe With the Aid of Cupping Protocol.

Low back pain (LBP) is the leading cause of disability worldwide, yet its quantitative and noninvasive assessment remains challenging. Considering that near-infrared spectroscopy (NIRS) became a promising noninvasive tool for monitoring muscle and cupping therapy could regulate muscle blood flow to relieve LBP, we attempted to incorporate cupping and hemodynamics monitoring in muscle tissue by NIRS to assess LBP. We collected 3-min NIRS recordings on 12 LBP patients and 12 healthy subjects before and after 20-min cupping. Initially, no significant hemodynamic differences were observed between the groups. After cupping, the concentration changes of oxy-hemoglobin (Δ[HbO2]) in the emitter-detector channel parallel to spine unexpectedly exhibited that LBP was remarkably lower by approximately 67% compared with the controls. This study highlighted the potential of combining NIRS and cupping protocol as a quantitative assessment technique for LBP, also providing a new idea for clinical integration of novel optical assessment technologies.

Image encryption hiding algorithm based on digital time-varying delay chaos model and compression sensing technique.

Most of the existing image encryption algorithms encrypt images as meaningless cryptographic images, which can easily attract the attention of attackers during transmission. To address this problem, scholars have proposed to hide the cipher image in a meaningless carrier image. However, larger carrier images are often required, which occupy more bandwidth. In order to solve this problem, this paper realizes embedding the color secret image into the carrier image whose size is equal to or even smaller than the original image by combining the chaotic compressed sensing model. First of all, the original image is sparsely processed using discrete wavelet transform. Then the time varying delay chaotic model is used to generate pseudo random sequence and then the measurement matrix is constructed to compress and encrypt the image. In the end, using singular value decomposition to achieve image embedding, the carrier image carrying information is obtained.

Combination of silicene and boronene as a potential anode material for high-performance lithium-ion batteries: Insights from first principles.

Material design is essential for the development and preparation of new materials. In this paper, a new two-dimensional heterostructure material (B@Si) consisting of boronene and silicene is designed and used as an anode material for lithium-ion batteries in order to improve the performance of lithium-ion batteries, and the structural properties, stability, electronic properties, and performance as an anode material for lithium-ion batteries are systematically investigated by first-principle calculations of the B@Si heterostructure. The results show that the B@Si heterostructure is energetically, thermodynamically and dynamically stable, and although the Dirac cone in the energy band structure of silicene disappears after the formation of the heterojunction, the overall electrical conductivity of the material improves considerably and the electron transport rate is faster. Due to the synergistic effect, Li has more stable adsorption sites and lower diffusion barriers than boronene and silicene in the B@Si heterostructure, higher theoretical specific capacity (1208 mAhg-1), and stronger mechanical properties (C11 = 296.6 N/m, C22 = 142.8 N/m). The volume expansion in the fully lithiated state is also only 8 %. These advantages indicate that B@Si heterostructures are good potential anode materials for high-performance Li-ion batteries.

Fracture Behavior of a 2D Imine-Based Polymer.

2D polymers have emerged as a highly promising category of nanomaterials, owing to their exceptional properties. However, the understanding of their fracture behavior and failure mechanisms remains still limited, posing challenges to their durability in practical applications. This work presents an in-depth study of the fracture kinetics of a 2D polyimine film, utilizing in situ tensile testing within a transmission electron microscope (TEM). Employing meticulously optimized transferring and patterning techniques, an elastic strain of ≈6.5% is achieved, corresponding to an elastic modulus of (8.6 ± 2.5) GPa of polycrystalline 2D polyimine thin films. In step-by-step fractures, multiple cracking events uncover the initiation and development of side crack near the main crack tip which toughens the 2D film. Simultaneously captured strain evolution through digital image correlation (DIC) analysis and observation on the crack edge confirm the occurrence of transgranular fracture patterns apart from intergranular fracture. A preferred cleavage orientation in transgranular fracture is attributed to the difference in directional flexibility along distinct orientations, which is substantiated by density functional-based tight binding (DFTB) calculations. These findings construct a comprehensive understanding of intrinsic mechanical properties and fracture behavior of an imine-linked polymer and provide insights and implications for the rational design of 2D polymers.

Biocatalytic Desymmetrization for the Atroposelective Synthesis of Axially Chiral Biaryls Using an Engineered Imine Reductase.

The enzymatic atroposelective synthesis of biaryl compounds is relatively rare, despite considerable attention received by biocatalysis in academic and industrial sectors. Imine reductases (IREDs) are an important class of enzymes that have been applied in the asymmetric synthesis of chiral amine building blocks. In this work, two IREDs (IR140 and IR189) were identified to catalyze the efficient desymmetrization of biaryls utilizing various amine donors. Further protein engineering enabled the identification of variants (IR189 M8-M9 and IR189 M13-M14) that are able to catalyze the formation of both (R) and (S) atropisomers in excellent yields and atroposelectivities for up to 24 examples (up to 99% ee and yield). The absolute configuration and rotational barriers were confirmed, and the reactions were readily enlarged to allow isolation of the atropisomeric products in 99% ee and 82% isolated yields. The optically pure biaryl amines were further derivatized into various synthetically useful atropisomers. To shed light on the molecular recognition mechanisms, molecular dynamics (MD) simulations were performed, offering plausible explanations for the improved atroposelectivities and enzymatic activities. The current strategy expands the scope of IRED-catalyzed synthesis of axially chiral biaryl amines, contributing significantly to the field of atroposelective biocatalysis.

Fast and sensitive detection of viable Escherichia coli O157:H7 using a microwell-confined and propidium monoazide-assisted digital CRISPR microfluidic platform.

Escherichia coli O157:H7 is a major foodborne pathogen that poses a significant threat to food safety and human health. Rapid and sensitive detection of viable Escherichia coli O157:H7 can effectively prevent food poisoning. Here, we developed a microwell-confined and propidium monoazide-assisted digital CRISPR microfluidic platform for rapid and sensitive detection of viable Escherichia coli O157:H7 in food samples. The reaction time is significantly reduced by minimizing the microwell volume, yielding qualitative results in 5 min and absolute quantitative results in 15 min. With the assistance of propidium monoazide, this platform can eliminate the interference from 99% of dead Escherichia coli O157:H7. The direct lysis method obviates the need for a complex nucleic acid extraction process, offering a limit of detection of 3.6 × 101 CFU mL-1 within 30 min. Our results demonstrated that the platform provides a powerful tool for rapid detection of Escherichia coli O157:H7 and provides reliable guidance for food safety testing.

Assessing the Structural Diversity of Form II Red Phosphorus via Stepwise Crystal Structure Search.

Recently, the long less-known Form II red phosphorus (RP) (viz. Type II RP) was ascertained by the state-of-the-art 3-dimensional electron diffraction technique with a triclinic lattice, completely distinct from other known elemental phosphorus and leaving atomic coordinates not determined. The cell composed of ∼250 atoms might exceed the capacity of current readily available crystal structure search packages, which have been widely applied to systems with several tens of atoms. Besides, mistaking Form II RP for violet phosphorus is still surprisingly common in the studies on allotropic phosphorus due to misinterpretations on JCPDS card #00-044-0906. Herein, by reproducing annealing synthesis and cell relaxation of structures obtained in the literature, we verified two former crystal structures for Form II RP to be wrong and explained how the misinterpretations have occurred. Then, on the basis of experimental lattice data, we provided possible Form II RP models containing atomic positions by a nearly exhaustive high-throughput stepwise crystal structure search approach optimized by molecular mechanics, machine-learned force field, and density functional theory in succession. The energetic stability of Form II RP was found to rank between white phosphorus and black phosphorus, similar to the nanorod modifications.

The effect of physical exercise on depression among college students: a systematic review and meta-analysis.

Objective: The goal of the present research was to evaluate the effectiveness of physical exercise intervention in enhancing psychological well-being and decreasing symptoms of depression among college students, adopting a systematic review and meta-analysis. Methodology: The study was performed by searching four databases (PubMed, Embase, Web of Science, and the Cochrane Library) to determine randomized controlled trials (RCTs) exploring the impacts of physical exercise therapies among college students with symptoms of depression. The sequential execution of a meta-analyses, subgroup analyses, and publication bias analyses was accomplished utilizing the software package RevMan version 5.3. Results: There were eight articles included. This research demonstrated a significant impact (d = -0.75, P < 0.05), indicating that physical exercise has a substantial impact on decreasing or mitigating depression. The subgroup analyses revealed that interventions involving physical exercise workouts lasting 12 weeks or longer (d = -0.93, P < 0.05), with physical exercise sessions lasting between 30 and 60 min (d = -0.77, P < 0.05), and with physical exercise performed minimum of three times a week (d = -0.90, P < 0.05) were the most effective in reducing symptoms of depression. Conclusion: Physical exercise interventions have a beneficial impact on reducing depression among college students. The optimal mode was discovered to be college students participating in each session for a duration of 30 to 60 min, at least three times per week, and for more than 12 weeks. College students are encouraged to cultivate a consistent and long-term physical exercise routine to sustain their physical and mental health.

Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence.

Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative analgesia method during abdominal and pelvic surgeries. Due to the anatomical complexity and individual variability of the quadratus lumborum muscle (QLM) on ultrasound images, nerve blocks heavily rely on anesthesiologist experience. Therefore, using artificial intelligence (AI) to identify different tissue regions in ultrasound images is crucial. In our study, we retrospectively collected 112 patients (3162 images) and developed a deep learning model named Q-VUM, which is a U-shaped network based on the Visual Geometry Group 16 (VGG16) network. Q-VUM precisely segments various tissues, including the QLM, the external oblique muscle, the internal oblique muscle, the transversus abdominis muscle (collectively referred to as the EIT), and the bones. Furthermore, we evaluated Q-VUM. Our model demonstrated robust performance, achieving mean intersection over union (mIoU), mean pixel accuracy, dice coefficient, and accuracy values of 0.734, 0.829, 0.841, and 0.944, respectively. The IoU, recall, precision, and dice coefficient achieved for the QLM were 0.711, 0.813, 0.850, and 0.831, respectively. Additionally, the Q-VUM predictions showed that 85% of the pixels in the blocked area fell within the actual blocked area. Finally, our model exhibited stronger segmentation performance than did the common deep learning segmentation networks (0.734 vs. 0.720 and 0.720, respectively). In summary, we proposed a model named Q-VUM that can accurately identify the anatomical structure of the quadratus lumborum in real time. This model aids anesthesiologists in precisely locating the nerve block site, thereby reducing potential complications and enhancing the effectiveness of nerve block procedures.

Sex-specific in the association between depressive symptoms and risk of cognitive impairment in Chinese older adults.

BACKGROUND: Many studies have focused on the relationship between depressive symptoms and cognitive impairment, but gender differences in this relationship are unclear, especially among Chinese older adults. Therefore, this study explores whether there are gender differences between depressive symptoms and risk of cognitive impairment based on a survey of a Chinese older adult population. STUDY DESIGN: This is a cross-sectional study. METHOD: We screened 9678 older adults aged 65 to 105 from the 2018 CLHLS database. The 10-item Center for Epidemiological Studies Depression Scale (CESD-10) and Mini-Mental State Examination (MMSE) were utilized for measuring depressive symptoms and cognitive performance, respectively. Logistic regressions and restricted cubic spline were applied to investigate the relationship between depressive symptoms and cognitive impairment. RESULTS: Of the 9678 participants, 4719 (48.8 %) were men. The association between severe depressive symptoms and cognitive impairment was more pronounced in older men (male × severe depressive symptoms: OR = 2.71, 95%CI = 1.07-6.92, p = 0.037). Compared with no depressive symptoms, severe depressive symptoms were associated with an almost five times greater risk of cognitive impairment in men (OR = 4.84, 95 % CI = 2.26-10.40, p < 0.001, compared to OR = 2.25, 95 % CI = 1.27-3.96, p = 0.005 in women). Gender differences were demonstrated in the association of individual ten depressive symptoms with cognitive impairment: men who felt lonely were more likely to have cognitive impairment (OR = 1.24, 95 % CI = 1.06-1.47, p = 0.010), while women who slept poorly were more likely to have cognitive impairment (OR = 1.42, 95 % CI = 1.16-1.74, p = 0.001). CONCLUSION: Results indicate a stronger association between severe depressive symptoms and cognitive impairment among older Chinese males. Our study suggests that reducing loneliness can help prevent cognitive impairment in older men, and improving sleep quality can help improve cognitive function in older women.

Upregulated SKP2 Empowers Epidermal Proliferation Through Downregulation of P27 Kip1.

BACKGROUND: Excessive growth of keratinocytes is the critical event in the etiology of psoriasis. However, the underlying molecular mechanism of psoriatic keratinocyte hyperproliferation is still unclear. OBJECTIVE: This study aimed to figure out the potential contributory role of S-phase kinase-associated protein 2 (SKP2) in promoting the hyperproliferation of keratinocytes in psoriasis. METHODS: We analyzed microarray data (GSE41662) to investigate the gene expression of SKP2 in psoriatic lesion skins compared with their adjacent non-lesional skin. Then, we further confirmed the mRNA and protein expression of SKP2 in human psoriatic skin tissues, imiquimod (IMQ)-induced psoriatic mice back skins and tumor necrosis factor α (TNF-α), interleukin (IL)-17A and IL-6-stimulated keratinocytes by using real-time quantitative polymerase chain reaction and western blot (WB). Furthermore, we explored the potential pathogenic role and its underlying cellular mechanism of SKP2 in promoting keratinocytes hyperproliferation through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, cell cycle detection, 5-ethynyl-2'-deoxyuridine staining and WB. Finally, we determined whether inhibition of SKP2 can effectively alleviate the keratinocytes hyperproliferation in vivo. RESULTS: We identified that SKP2 is aberrantly upregulated in the psoriatic lesion skin and cytokines-stimulated keratinocytes. Moreover, upregulated SKP2 augments cytokines-induced keratinocytes hyperproliferation. Mechanistically, enhanced SKP2 increased the S phase ratio through inhibiting Cyclin-Dependent Kinase Inhibitor p27 (P27 Kip1) expression. Correspondingly, suppression of SKP2 with SMIP004 can significantly ease the epidermis hyperplasia in vivo. CONCLUSION: Our results suggest that elevated SKP2 can empower keratinocytes proliferation and psoriasis-like epidermis hyperplasia via downregulation of P27 Kip1. Therefore, targeting SKP2-P27 Kip1 axis might be a promising therapeutic strategy for the treatment of psoriasis in future.

In Situ Alloying Enabled by Active Liquid Metal Filler for Self-Healing Composite Polymer Electrolytes.

Solid inorganics, known for kinetically inhibiting polymer crystallization and enhancing ionic conductivity, have attracted significant attention in solid polymer electrolytes. However, current composite polymer electrolytes (CPEs) are still facing challenges in Li metal batteries, falling short of inhibiting severe dendritic growth and resulting in very limited cycling life. This study introduces Ga62.5In21.5Sn16 (Galinstan) liquid metal (LM) as an active liquid alternative to conventional passive solid fillers, aiming at realizing self-healing protection against dendrite problems. Compared to solid inorganics, for example silica, LM droplets could more significantly reduce polymer crystallinity and enhance Li-ion conductivity due to their liquid nature, especially at temperatures below the polymer melting point. More importantly, LMs are unraveled as dynamic chemical traps, which are capable of blocking and consuming lithium dendrites upon contact via in situ alloying during battery operation and further inhibiting dendritic growth due to the lower deposition energy barrier of the formed Li-LM alloy. As a proof of concept, by strategically designing an asymmetric CPE with the active LM filling, a solid-state Li/LiFePO4 battery achieves promising full-cell functionality with notable rate performance and stable cycle life. This active filler-mediated self-healing approach could bring new insights into the battery design in versatile solid-state systems.

Influence of Water and Fertilizer Reduction on Respiratory Metabolism in Sugar Beet Taproot (Beta vulgaris L.).

Inner Mongolia, a major region in China for growing sugar beet, faces challenges caused by unscientific water and fertilizer management. This mismanagement restricts the improvement of sugar beet yield and quality and exacerbates water waste and environmental pollution. This study aims to evaluate the effects of reduced water and fertilizer on the growth and physiological metabolism of sugar beet taproot. Field experiments were conducted in Ulanqab, Inner Mongolia, in 2022 and 2023, using a split-plot design with three levels each of fertilization and irrigation. The study analyzed the effects of reduced water and fertilizer treatments on fresh taproot weight, respiration rate, energy metabolism, respiratory enzyme activity, and gene expression in sugar beet taproot. It was found that a 10% reduction in fertilizer significantly increased the beet taproot fresh weight. Further research revealed that during the rapid leaf growth phase and the taproot and sugar growth period, a 10% reduction in fertilizer upregulated HK and IDH gene expression and downregulated G6PDH gene expression in the beet taproot. This increased HK and IDH activities, decreased G6PDH activity, enhanced the activity of the EMP-TCA pathway, and inhibited the PPP. Taproot weight was positively correlated with the respiration rate, ATP content, EC, and ATPase, HK, and IDH activities, thereby increasing the taproot growth rate and taproot fresh weight, with an average increase of 4.0% over two years. These findings introduce a novel method for optimizing fertilizer use, particularly beneficial in water-scarce regions. Implementing this strategy could help farmers in western Inner Mongolia and similar areas improve crop yield and sustainability. This study offers new insights into resource-efficient agricultural practices, highlighting the importance of customized fertilization strategies tailored to local environmental conditions.

An electrochemical point-of-care testing device for specific diagnosis of the albinism biomarker based on paradigm shift designs.

L-tyrosine is a recognized biomarker of albinism, whose endogenous level in human bodies is directly linked to melanin synthesis while no attention has been paid to its specific diagnosis. To this end, we have developed an electrochemical point-of-care testing device based on a molecularly imprinted gel prepared by a universal paradigm shift design to achieve the enhanced specific recognition of the L-tyrosine. Interestingly, this theoretically optimized molecularly imprinted gel validates the recognition pattern of L-tyrosine and optimizes the structure of the polymer itself with the aid of computational chemistry. Besides, modified extended-layer MXene and Au nanoclusters have significantly improved the sensing activity. As a result, the linear diagnostic range of this electrochemical point-of-care testing device for L-tyrosine is 0.1-100 µM in actual human fluids, which fully covers the L-tyrosine levels of healthy individuals and people with albinism. The diagnosis is completed in 90 s and then the results are transmitted by Bluetooth low energy to the smart mobile terminal. Therefore, we are convinced that this electrochemical point-of-care testing device is a promising tool in the future smart medical system.

Bile acids attenuate hepatic inflammation during ischemia/reperfusion injury.

Background & Aims: Persistent cholestasis has been associated with poor prognosis after orthotopic liver transplantation. In this study, we aimed to investigate how the accumulation of tauro-beta-muricholic acid (TßMCA), resulting from the reprogramming of bile acid (BA) metabolism during liver ischemia/reperfusion (IR) stress, attenuates liver inflammation. Methods: Ingenuity Pathway Analysis was performed using transcriptome data from a murine hepatic IR model. Three different models of hepatic IR (liver warm IR, bile duct separation-IR, common bile duct ligation-IR) were employed. We generated adeno-associated virus-transfected mice and CD11b-DTR mice to assess the role of BAs in regulating the myeloid S1PR2-GSDMD axis. Hepatic BA levels were analyzed using targeted metabolomics. Finally, the correlation between the reprogramming of BA metabolism and hepatic S1PR2 levels was validated through RNA-seq of human liver transplant biopsies. Results: We found that BA metabolism underwent reprogramming in murine hepatocytes under IR stress, leading to increased synthesis of TßMCA, catalyzed by the enzyme CYP2C70. The levels of hepatic TßMCA were negatively correlated with the severity of hepatic inflammation, as indicated by the serum IL-1ß levels. Inhibition of hepatic CYP2C70 resulted in reduced TßMCA production, which subsequently increased serum IL-1ß levels and exacerbated IR injury. Moreover, our findings suggested that TßMCA could inhibit canonical inflammasome activation in macrophages and attenuate inflammatory responses in a myeloid-specific S1PR2-GSDMD-dependent manner. Additionally, Gly-ßMCA, a derivative of TßMCA, could effectively attenuate inflammatory injury in vivo and inhibit human macrophage pyroptosis in vitro. Conclusions: IR stress orchestrates hepatic BA metabolism to generate TßMCA, which attenuates hepatic inflammatory injury by inhibiting the myeloid S1PR2-GSDMD axis. Bile acids have immunomodulatory functions in liver reperfusion injury that may guide therapeutic strategies. Impact and implications: Our research reveals that liver ischemia-reperfusion stress triggers reprogramming of bile acid metabolism. This functions as an adaptive mechanism to mitigate inflammatory injury by regulating the S1PR2-GSDMD axis, thereby controlling the release of IL-1ß from macrophages. Our results highlight the crucial role of bile acids in regulating hepatocyte-immune cell crosstalk, which demonstrates an immunomodulatory function in liver reperfusion injury that may guide therapeutic strategies targeting bile acids and their receptors.

General synthesis of high-entropy single-atom nanocages for electrosynthesis of ammonia from nitrate.

Given the growing emphasis on energy efficiency, environmental sustainability, and agricultural demand, there's a pressing need for decentralized and scalable ammonia production. Converting nitrate ions electrochemically, which are commonly found in industrial wastewater and polluted groundwater, into ammonia offers a viable approach for both wastewater treatment and ammonia production yet limited by low producibility and scalability. Here we report a versatile and scalable solution-phase synthesis of high-entropy single-atom nanocages (HESA NCs) in which Fe and other five metals-Co, Cu, Zn, Cd, and In-are isolated via cyano-bridges and coordinated with C and N, respectively. Incorporating and isolating the five metals into the matrix of Fe resulted in Fe-C5 active sites with a minimized symmetry of lattice as well as facilitated water dissociation and thus hydrogenation process. As a result, the Fe-HESA NCs exhibited a high selectivity toward NH3 from the electrocatalytic reduction of nitrate with a Faradaic efficiency of 93.4% while maintaining a high yield rate of 81.4 mg h-1 mg-1.

Enhancing cerebral arteriovenous malformation analysis: Development and application of patient-specific lumped parameter models based on 3D imaging data.

OBJECTIVES: Cerebral arteriovenous malformations (AVMs) present complex neurovascular challenges, characterized by direct arteriovenous connections that disrupt normal brain blood flow dynamics. Traditional lumped parameter models (LPMs) offer a simplified angioarchitectural representation of AVMs, yet often fail to capture the intricate structure within the AVM nidus. This research aims at refining our understanding of AVM hemodynamics through the development of patient-specific LPMs utilizing three-dimensional (3D) medical imaging data for enhanced structural fidelity. METHODS: This study commenced with the meticulous delineation of AVM vascular architecture using threshold segmentation and skeletonization techniques. The AVM nidus's core structure was outlined, facilitating the extraction of vessel connections and the formation of a detailed fistulous vascular tree model. Sampling points, spatially distributed and derived from the pixel intensity in imaging data, guided the construction of a complex plexiform tree within the nidus by generating smaller Y-shaped vascular formations. This model was then integrated with an electrical analog model to enable precise numerical simulations of cerebral hemodynamics with AVMs. RESULTS: The study successfully generated two distinct patient-specific AVM networks, mirroring the unique structural and morphological characteristics of the AVMs as captured in medical imaging. The models effectively represented the intricate fistulous and plexiform vessel structures within the nidus. Numerical analysis of these models revealed that AVMs induce a blood shunt effect, thereby diminishing blood perfusion to adjacent brain tissues. CONCLUSION: This investigation enhances the theoretical framework for AVM research by constructing patient-specific LPMs that accurately reflect the true vascular structures of AVMs. These models offer profound insights into the hemodynamic behaviors of AVMs, including their impact on cerebral circulation and the blood steal phenomenon. Further incorporation of clinical data into these models holds the promise of deepening the theoretical comprehension of AVMs and fostering advancements in the diagnosis and treatment of AVMs.

Biomedical Utility of Non-Enzymatic DNA Amplification Reaction: From Material Design to Diagnosis and Treatment.

Nucleic acid nanotechnology has become a promising strategy for disease diagnosis and treatment, owing to remarkable programmability, precision, and biocompatibility. However, current biosensing and biotherapy approaches by nucleic acids exhibit limitations in sensitivity, specificity, versatility, and real-time monitoring. DNA amplification reactions present an advantageous strategy to enhance the performance of biosensing and biotherapy platforms. Non-enzymatic DNA amplification reaction (NEDAR), such as hybridization chain reaction and catalytic hairpin assembly, operate via strand displacement. NEDAR presents distinct advantages over traditional enzymatic DNA amplification reactions, including simplified procedures, milder reaction conditions, higher specificity, enhanced controllability, and excellent versatility. Consequently, research focusing on NEDAR-based biosensing and biotherapy has garnered significant attention. NEDAR demonstrates high efficacy in detecting multiple types of biomarkers, including nucleic acids, small molecules, and proteins, with high sensitivity and specificity, enabling the parallel detection of multiple targets. Besides, NEDAR can strengthen drug therapy, cellular behavior control, and cell encapsulation. Moreover, NEDAR holds promise for constructing assembled diagnosis-treatment nanoplatforms in the forms of pure DNA nanostructures and hybrid nanomaterials, which offer utility in disease monitoring and precise treatment. Thus, this paper aims to comprehensively elucidate the reaction mechanism of NEDAR and review the substantial advancements in NEDAR-based diagnosis and treatment over the past five years, encompassing NEDAR-based design strategies, applications, and prospects.