Target response controlled enzyme activity switch for multimodal biosensing detection.

How to achieve delicate regulation of enzyme activity and empower it with more roles is the peak in the field of enzyme catalysis research. Traditional proteases or novel nano-enzymes are unable to achieve stimulus-responsive activity modulation due to their own structural limitations. Here, we propose a novel Controllable Enzyme Activity Switch, CEAS, based on hemin aggregation regulation, to deeply explore its regulatory mechanism and develop multimodal biosensing applications. The core of CEAS relies on the dimerizable inactivation of catalytically active center hemin and utilizes a DNA template to orderly guide the G4-Hemin DNAzyme to tightly bind to DNA-Hemin, thereby shutting down the catalytic ability. By customizing the design of the guide template, different target stimulus responses lead to hemin dimerization dissociation and restore the synergistic catalysis of G4-Hemin and DNA-Hemin, thus achieving a target-regulated enzymatic activity switch. Moreover, the programmability of CEAS allowed it easy to couple with a variety of DNA recognition and amplification techniques, thus developing a series of visual protein detection systems and highly sensitive fluorescent detection systems with excellent bioanalytical performance. Therefore, the construction of CEAS is expected to break the limitation of conventional enzymes that cannot be targetable regulated, thus enabling customizable enzymatic reaction systems and providing a new paradigm for controllable enzyme activities.

Analysis of the Chaotic Component of Photoplethysmography and Its Association with Hemodynamic Parameters.

Wearable technologies face challenges due to signal instability, hindering their usage. Thus, it is crucial to comprehend the connection between dynamic patterns in photoplethysmography (PPG) signals and cardiovascular health. In our study, we collected 401 multimodal recordings from two public databases, evaluating hemodynamic conditions like blood pressure (BP), cardiac output (CO), vascular compliance (C), and peripheral resistance (R). Using irregular-resampling auto-spectral analysis (IRASA), we quantified chaotic components in PPG signals and employed different methods to measure the fractal dimension (FD) and entropy. Our findings revealed that in surgery patients, the power of chaotic components increased with vascular stiffness. As the intensity of CO fluctuations increased, there was a notable strengthening in the correlation between most complexity measures of PPG and these parameters. Interestingly, some conventional morphological features displayed a significant decrease in correlation, indicating a shift from a static to dynamic scenario. Healthy subjects exhibited a higher percentage of chaotic components, and the correlation between complexity measures and hemodynamics in this group tended to be more pronounced. Causal analysis showed that hemodynamic fluctuations are main influencers for FD changes, with observed feedback in most cases. In conclusion, understanding chaotic patterns in PPG signals is vital for assessing cardiovascular health, especially in individuals with unstable hemodynamics or during ambulatory testing. These insights can help overcome the challenges faced by wearable technologies and enhance their usage in real-world scenarios.

Dancing in local space: rolling hoop orbital amplification combined with local cascade nanozyme catalytic system to achieve ultra-sensitive detection of exosomal miRNA.

The exosomal miRNA (exo-miRNA) derived from tumor cells contains rich biological information that can effectively aid in the early diagnosis of disease. However, the extremely low abundance imposes stringent requirements for accurate detection techniques. In this study, a novel, protease-free DNA amplification strategy, known as "Rolling Hoop Orbital Amplification" (RHOA), was initially developed based on the design concept of local reaction and inspired by the childhood game of rolling iron ring. Benefiting from the local space constructed by the DNA orbital, the circular DNA enzyme rolls directionally and interacts efficiently with the amplification element, making it nearly 3-fold more productive than conventional free-diffusion amplification. Similarly, the localized cascade nanozyme catalytic system formed by bridging DNA probes also exhibits outperformed than free ones. Therefore, a localized energized high-performance electrochemiluminescence (ECL) biosensor was constructed by bridging cascading nanozymes on the electrode surface through DNA probes generated by RHOA, with an impressive limit of detection (LOD) of 1.5 aM for the detection of exosomal miRNA15a-5p and a stable linearity over a wide concentration range from 10- 2 to 108 fM. Thus, this work is a focused attempt at the localized reaction, which is expected to provide a reliable method for accurately detecting of exo-miRNAs.

Domain Knowledge-Based Evolutionary Reinforcement Learning for Sensor Placement.

Reducing pollutant detection time based on a reasonable sensor combination is desirable. Clean drinking water is essential to life. However, the water supply network (WSN) is a vulnerable target for accidental or intentional contamination due to its extensive geographic coverage, multiple points of access, backflow, infrastructure aging, and designed sabotage. Contaminants entering WSN are one of the most dangerous events that may cause sickness or even death among people. Using sensors to monitor the water quality in real time is one of the most effective ways to minimize negative consequences on public health. However, it is a challenge to deploy a limited number of sensors in a large-scale WSN. In this study, the sensor placement problem (SPP) is modeled as a sequential decision optimization problem, then an evolutionary reinforcement learning (ERL) algorithm based on domain knowledge is proposed to solve SPP. Extensive experiments have been conducted and the results show that our proposed algorithm outperforms meta-heuristic algorithms and deep reinforcement learning (DRL).

Vitamin E Reversed Apoptosis of Cardiomyocytes Induced by Exposure to High Dose Formaldehyde During Mice Pregnancy.

In this study, we investigated the protection effect of Vitamin E (Vit E) on formaldehyde (FA) exposure during pregnancy induced apoptosis of cardiomyocytes, and used an HL-1 cell line to confirmed the findings in vivo.Pregnant mice received different doses of FA (0.5 mg/kg, 1.0 mg/kg, 1.5 mg/kg, 0.1 µg Vit E, or 1.5 mg/kg + 0.1 µg Vit E). TUNEL staining was used to reveal the apoptosis in cardiomyocytes, and SOD, MDA, GSH, Livin, and Caspase-3 in cardiomyocytes were detected by ELISA, RT-PCR, and Western blot. For in vitro study, HL-1 cells were treated with vehicle, 5 µmol/L FA, 25 µmol/L FA, 50 µmol/L FA, 10 mg/L Vit. E, and 50 µmol/L FA+ 10 mg/L Vit E, respectively. CCK-8 assay and flow cytometry were used to evaluate cell vitality and apoptosis. A high dose of FA exposure led to cytotoxicity in both pregnant mice and offspring, as TUNEL staining revealed a significant apoptosis of cardiomyocytes, and the alternation in SOD, GSH, MDA, Livin, and Caspase-3 was found in cardiomyocytes. 0.1 µg Vit. E could reverse high doses of FA exposure induced apoptosis of cardiomyocytes in both pregnant mice and offspring. The in vitro study revealed that FA exposure induced a decrease of cell viability and increased cell apoptosis, as well as oxidative stress in HL-1 cells with alternation in SOD, GSH, MDA, Livin, and Caspase-3.This study revealed a high dose of FA induced oxidative stress and apoptosis of cardiomyocytes in both pregnant mice and offspring, and Vit E supplement during pregnancy reversed the systemic and myocardial toxicity of FA.

Pomegranate-Bionic Encapsulating Horseradish Peroxidase Using Dopamine Flexible Scaffold-Coated Multishell Porous ZIF-8 To Enhance Immunochromatographic Diagnosis.

Nanoparticle-natural enzyme complexes are receiving increasing attention as the promising signal reporters for colorimetric lateral flow immunoassay (LFIA). Nonetheless, it remains a challenge to develop the nanocomplexes with high loading efficiency, catalytic efficiency, and colorimetric signal brightness. Herein, inspired by pomegranate structure, we reported the synthesis of a colorimetric catalytic nanocomplex ((HRP@ZIF-8)3@PDA@HRP), using dopamine flexible scaffold-coated multishell porous zeolitic imidazolate framework-8 (ZIF-8) as a hierarchical scaffold to encapsulate horseradish peroxidase (HRP), and described its potential to promote an ultrasensitive colorimetric LFIA of cardiac troponin I (cTnI). (HRP@ZIF-8)3@PDA@HRP exhibited ultrahigh HRP loading efficiency and catalytic activity due to the epitaxial shell-by-shell overgrowth of porous ZIF-8 scaffold, which provided more cavities for enzyme immobilization and a diffusion path for the catalytic substrate. Furthermore, the polydopamine (PDA) layer on the (HRP@ZIF-8)3 surface both enhanced the colorimetric signal brightness and acted as a flexible scaffold to immobilize HRP, further increasing the amount of enzyme. Following integration with LFIA, the developed platform achieved an ultrasensitive colorimetric test strip assay for cTnI with pre- and postcatalytic naked-eye detection sensitivities of 0.5 ng mL-1 and 0.01 ng mL-1, respectively, which were 4/2- and 200/100-fold higher than gold nanoparticles (AuNPs)/PDA-based LFIA and comparable to chemiluminescence immunoassay. Further, the quantitative testing results of the developed colorimetric LFIA on 57 clinical serum samples agreed well with the clinical data. This work provides ideas for the design of natural enzymes-based colorimetric catalytic nanocomplex to encourage applications for the development of ultrasensitive LFIA for early diseases diagnosis.

Blood pressure assessment with in-ear photoplethysmography.

Objective. In this study, we aimed to estimate blood pressure (BP) from in-ear photoplethysmography (PPG). This novel implementation provided an unobtrusive and steady way of recording PPG, whereas previous PPG measurements were mostly performed at the wrist, finger, or earlobe.Methods. The time between forward and reflected PPG waves was very short at the ear site. To minimize errors introduced by feature extraction, a multi-Gaussian decomposition of in-ear PPG was performed. Both hand-crafted and whole-based features were extracted and the best combination of features was selected using a backward-search wrapper method and evaluated by the Akaike information criteria. Hemodynamic parameters such as compliance and inertance were estimated from a four-element Windkessel (WK4) model, which was used to pre-classify PPG signals and generate different BP estimation algorithms. Calibration was done by using previous measurements from the same class. To validate this novel approach, 53 subjects were recruited for a one-month follow-up study, and 17 subjects were recruited for a two-month follow-up study. Calibrated systolic BP estimation accuracy was significantly improved with inertance-based pre-classification, while diastolic BP showed less improvement.Results. With proper feature selection, pre-classification and calibration, we have achieved a mean absolute error of 5.35 mmHg for SBP estimation, compared to 6.16 mmHg if no pre-classification was carried out. The performance did not deteriorate in two months, showing a decent BP trend-tracking ability.Conclusion. The study demonstrated the feasibility of in-ear PPG to reliably measure BP, which represents an important technological advancement in terms of unobtrusiveness and steadiness.

Robust blood pressure estimation from finger photoplethysmography using age-dependent linear models.

OBJECTIVE: This work aims to develop an efficient and robust age-dependent multiple linear regression (MLR) model to estimate blood pressure (BP) from a single-source photoplethysmography (PPG) and biometrics, which could be embedded in the microcontroller of pulse oximeters. APPROACH: Hemodynamic features were extracted from the PPG signal using its waveform, derivatives, and biometrics. Whole-based, feature-based, and fusion models were evaluated and compared for different age groups. Their performance was tested using 1086 subjects with a leave-one-subject-out cross-validation. The improvement by adding biometrics and the long-term calibration effect were investigated in detail. The relative importance of each feature was compared between different age groups and the implication was discussed. MAIN RESULTS: The fusion model achieved the best performance in subjects with well-defined PPG features, whereas the feature-based method was better suited for subjects with damped signals. Adding age significantly improved both systolic BP (SBP) and diastolic BP (DBP) estimation accuracy for older subjects (> 50 years old) with well-defined features, while it only improved diastolic BP accuracy for older subjects with damped signals. For younger subjects (≤ 50 years old), the contribution of age was very small. A simple subtraction of subject-specific calibration factors significantly reduced biometric-related errors, which also improved the linearity of BP estimation. The relative importance analysis of input features suggests that separate models are indeed necessary for different age groups with different signal qualities, especially for DBP estimation in older subjects. SIGNIFICANCE: This study shows a reasonable BP estimation accuracy with age-dependent MLR models, which may help to equip current pulse oximeters with additional functionalities.

Rapid lateral flow immunoassay for the fluorescence detection of SARS-CoV-2 RNA.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for rapid and accurate nucleic acid detection at the point of care. Here, we report an amplification-free nucleic acid immunoassay, implemented on a lateral flow strip, for the fluorescence detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in less than one hour. The assay uses DNA probes that are designed to bind to the conserved open reading frame 1ab (ORF1ab), envelope protein (E) and the nucleocapsid (N) regions of the SARS-CoV-2 genome, and a fluorescent-nanoparticle-labelled monoclonal antibody that binds to double-stranded DNA-RNA hybrids. In a multi-hospital randomized double-blind trial involving 734 samples (593 throat swabs and 141 sputum) provided by 670 individuals, the assay achieved sensitivities of 100% and specificities of 99% for both types of sample (ground truth was determined using quantitative PCR with reverse transcription). The inexpensive amplification-free detection of SARS-CoV-2 RNA should facilitate the rapid diagnosis of COVID-19 at the point of care.

An Unobtrusive and Calibration-free Blood Pressure Estimation Method using Photoplethysmography and Biometrics.

We introduce a novel paradigm to unobtrusively and optically measure blood pressure (BP) without calibration. The algorithm combines photoplethysmography (PPG) waveform analysis and biometrics to estimate BP, and was evaluated in subjects with various age, height, weight and BP levels (n = 1249). In the young population (<50 years old) with low, medium and high systolic blood pressures (SBP, <120 mmHg; 120-139 mmHg; ≥140 mmHg), the fitting errors are 6.3 ± 7.2, -3.9 ± 7.2 and -20.2 ± 14.2 mmHg for SBP respectively; In the older population (>50 years old) with the same categories, the fitting errors are 12.8 ± 9.0, 0.5 ± 8.2 and -14.6 ± 11.5 mmHg for SBP respectively. A simple personalized calibration reduces fitting errors significantly (n = 147), and good peripheral perfusion helps to improve the fitting accuracy. In conclusion, PPG may be used to calculate BP without calibration in certain populations. When calibrated, it shows great potential to serially monitor BP fluctuation, which can bring tremendous economic and health benefits.