Infertility and Subclinical Antecedents of Heart Failure With Preserved Ejection Fraction in the Framingham Heart Study.

BACKGROUND: Infertility has been shown to be associated with a greater risk of incident heart failure with preserved ejection fraction. We studied the association of infertility with subclinical markers of heart failure with preserved ejection fraction, including echocardiographic signs of cardiac remodeling and cardiac biomarkers. METHODS AND RESULTS: A history of infertility was ascertained in 2002 women enrolled in the Framingham Heart Study. We examined the association of infertility with echocardiographic measures and cardiac biomarkers with multivariable-adjusted linear regression models. Among 2002 women (mean age 40.84 ± 9.71 years), 285 (14%) reported a history of infertility. Infertility was associated with a greater E/e' ratio (ß = 0.120, standard error 0.057, P = .04), even after adjustment for common confounders. Infertility was not associated with other echocardiographic measures or cardiac biomarkers. CONCLUSIONS: Infertility was associated with a greater E/e' ratio, a marker of diastolic dysfunction that may signal earlier subclinical cardiac remodeling in women with infertility.

Bioinspired Dual-Mode Stretchable Strain Sensor Based on Magnetic Nanocomposites for Strain/Magnetic Discrimination.

Recently, flexible stretchable sensors have been gaining attention for their excellent adaptability for electronic skin applications. However, the preparation of stretchable strain sensors that achieve dual-mode sensing while still retaining ultra-low detection limit of strain, high sensitivity, and low cost is a pressing task. Herein, a high-performance dual-mode stretchable strain sensor (DMSSS) based on biomimetic scorpion foot slit microstructures and multi-walled carbon nanotubes (MWCNTs)/graphene (GR)/silicone rubber (SR)/Fe3 O4 nanocomposites is proposed, which can accurately sense strain and magnetic stimuli. The DMSSS exhibits a large strain detection range (≈160%), sensitivity up to 100.56 (130-160%), an ultra-low detection limit of strain (0.16% strain), and superior durability (9000 cycles of stretch/release). The sensor can accurately recognize sign language movement, as well as realize object proximity information perception and whole process information monitoring. Furthermore, human joint movements and micro-expressions can be monitored in real-time. Therefore, the DMSSS of this work opens up promising prospects for applications in sign language pose recognition, non-contact sensing, human-computer interaction, and electronic skin.

Bioinspired Engineering of Fillable Gradient Structure into Flexible Capacitive Pressure Sensor Toward Ultra-High Sensitivity and Wide Working Range.

Tactile sensing is required for electronic skin and intelligent robots to function properly. However, the dielectric layer's poor structural compressibility in conventional pressure sensors results in a limited pressure sensing range and low sensitivity. To solve this issue, a flexible pressure sensor with a crocodile-inspired fillable gradient structure is provided. The fillable gradient structure and grooves in the pressure sensor accommodate the deformed microstructure that permits the enhancement of the media layer compressibility via COMSOL finite element simulation and optimization. The pressure sensor exhibits a high sensitivity of up to 0.97 k Pa-1 (0-4 kPa), a wide pressure detection range (7 Pa-380 kPa), and outstanding repeatability. The sensor can detect Morse code, robotic grabbing, and human motion monitoring. As a result, flexible sensors with a bionic fillable gradient structure pave the way for wearable devices and offer a novel method for achieving highly precise tactile perception.

Biologically Emulated Flexible Sensors With High Sensitivity and Low Hysteresis: Toward Electronic Skin to a Sense of Touch.

Recently, flexible pressure sensors (FPSs) have attracted intensive attention owing to their ability to mimic and function as electronic skin. Some sensors are exploited with a biological structure dielectric layer for high sensitivity and detection. However, traditional sensors with bionic structures usually suffer from a limited range for high-pressure scenes due to their high sensitivity and high hysteresis in the medium pressure range. Here, a reconfigurable flea bionic structure FPS based on 3D printing technology, which can meet the needs of different scenes via tailoring of the dedicated structural parameters, is proposed. FPS exhibits high sensitivity (1.005 kPa-1 in 0-1 kPa), wide detection range (200 kPa), high repeatability (6000 cycles in 10 kPa), low hysteresis (1.3%), fast response time (40 ms), and very low detection limit (0.5 Pa). Aiming at practical application implementation, FPS has been correspondingly placed on a finger, elbow, arm, neck, cheek, and manipulators to detect the actions of various body parts, suggestive of excellent applicability. It is also integrated to make a flexible 3 × 3 sensor array for detecting spatial pressure distribution. The results indicate that FPS exhibits a significant application potential in advanced biological wearable technologies, such as human motion monitoring.

Crystalline Hydrate Dehydration Sensing Based on Integrated Terahertz Whispering Gallery Mode Resonators.

Water molecules play a very important role in the hydration and dehydration process of hydrates, which may lead to distinct physical and chemical properties, affecting their availability in practical applications. However, miniaturized, integrated sensors capable of the rapid, sensitive sensing of water molecules in the hydrate are still lacking, limiting their proliferation. Here, we realize the high-sensitivity sensing of water molecules in copper sulfate pentahydrate (CuSO4·5H2O), based on an on-chip terahertz whispering gallery mode resonator (THz-WGMR) fabricated on silicon material via CMOS-compatible technologies. An integrated THz-WGMR with a high-Q factor of 3305 and a resonance frequency of 410.497 GHz was proposed and fabricated. Then, the sensor was employed to distinguish the CuSO4·xH2O (x = 5, 3, 1). The static characterization from the CuSO4·5H2O to the copper sulfate trihydrate (CuSO4·3H2O) experienced blueshifts of 0.55 GHz/µmol, whereas the dehydration process of CuSO4·3H2O to copper sulfate monohydrate (CuSO4·H2O) exhibited blueshifts of 0.21 GHz/µmol. Finally, the dynamic dehydration processes of CuSO4·5H2O to CuSO4·3H2O at different temperatures were monitored. We believe that our proposed THz-WGMR sensors with highly sensitive substance identification capabilities can provide a versatile and integrated platform for studying the transformation between substances, contributing to hydrated/crystal water-assisted biochemical applications.

Electrochemical protein biosensors for disease marker detection: progress and opportunities.

The development of artificial intelligence-enabled medical health care has created both opportunities and challenges for next-generation biosensor technology. Proteins are extensively used as biological macromolecular markers in disease diagnosis and the analysis of therapeutic effects. Electrochemical protein biosensors have achieved desirable specificity by using the specific antibody-antigen binding principle in immunology. However, the active centers of protein biomarkers are surrounded by a peptide matrix, which hinders charge transfer and results in insufficient sensor sensitivity. Therefore, electrode-modified materials and transducer devices have been designed to increase the sensitivity and improve the practical application prospects of electrochemical protein sensors. In this review, we summarize recent reports of electrochemical biosensors for protein biomarker detection. We highlight the latest research on electrochemical protein biosensors for the detection of cancer, viral infectious diseases, inflammation, and other diseases. The corresponding sensitive materials, transducer structures, and detection principles associated with such biosensors are also addressed generally. Finally, we present an outlook on the use of electrochemical protein biosensors for disease marker detection for the next few years.

A miniprotein receptor electrochemical biosensor chip based on quantum dots.

Recently protein binders have emerged as a promising substitute for antibodies due to their high specificity and low cost. Herein, we demonstrate an electrochemical biosensor chip through the electronic labelling strategy using lead sulfide (PbS) colloidal quantum dots (CQDs) and the unnatural SARS-CoV-2 spike miniprotein receptor LCB. The unnatural receptor can be utilized as a molecular probe for the construction of CQD-based electrochemical biosensor chips, through which the specific binding of LCB and the spike protein is transduced to sensor electrical signals. The biosensor exhibits a good linear response in the concentration range of 10 pg mL-1 to 1 µg mL-1 (13.94 fM to 1.394 nM) with the limit of detection (LOD) being 3.31 pg mL-1 (4.607 fM for the three-electrode system) and 9.58 fg mL-1 (0.013 fM for the HEMT device). Due to the high sensitivity of the electrochemical biosensor, it was also used to study the binding kinetics between the unnatural receptor LCB and spike protein, which has achieved comparable results as those obtained with commercial equipment. To the best of our knowledge, this is the first example of using a computationally designed miniprotein receptor based on electrochemical methods, and it is the first kinetic assay performed with an electrochemical assay alone. The miniprotein receptor electrochemical biosensor based on QDs is desirable for fabricating high-throughput, large-area, wafer-scale biochips.

Flexible Strain Sensor Based on Nickel Microparticles/Carbon Black Microspheres/Polydimethylsiloxane Conductive Composites for Human Motion Detection.

Herein, we report a dual-functional flexible sensor (DFFS) using a magnetic conductive polymer composed of nickel (Ni), carbon black (CB), and polydimethylsiloxane (PDMS). The material selection for the DFFS utilizes the excellent elasticity of the PDMS matrix and the synergistic interaction between Ni and CB. The DFFS has a wide strain range of 0-170%, a high sensitivity of 74.13 (140-170%), and a low detection limit of 0.3% strain. The DFFS based on superior performance can accurately detect microstrain/microvibration, oncoming/contacting objects, and bicycle riding speed. Additionally, the DFFS can be used for comprehensive monitoring of human movements. Therefore, the DFFS of this work shows significant value for implementation in intelligent wearable devices and noncontact intelligent control.

Electrochemical biosensor using SnO2 colloidal quantum wire for monitoring the interaction of microcystin antigen-antibody.

Electrochemical sensors that incorporate immunoassay principles have the ability to monitor dynamic processes of antigen-antibody interactions in real time. In this study, a gold electrode was modified with tin dioxide colloidal quantum wire (SnO2 QWs) and then coated with the leucine/arginine subtype microcystin (MC-LR) antibody. The active site of SnO2 QWs that was not bound by MC-LR antibody was then passivated with bovine serum protein (BSA). When the MC-LR antigen binds specifically to the antibodies on the electrode's surface, it triggers electrochemical reactions and generates electrical signals at specific voltage conditions. The SnO2 QW exhibits excellent electron transport ability, and its ability to form a loose and porous microstructure on the gold electrode surface, which is conducive to the receptor function of the biosensor. The results show a high affinity between the MC-LR antigen and antibody, ranging from 1 pg/mL to 10 ng/mL of MC-LR antigen concentration. The kinetic characteristics of the immune reaction between MC-LR antigen and antibody were elucidated, obtaining a binding constant of 1.399 × 1011 M-1 and a dissociation constant of 7.147 pM, demonstrating the potential of electrochemical biosensing technology in biomolecular interactions.

Flexible Amperometric Immunosensor Based on Colloidal Quantum Dots for Detecting the Myeloperoxidase (MPO) Systemic Inflammation Biomarker.

Myeloperoxidase (MPO) has been demonstrated to be a biomarker of neutrophilic inflammation in various diseases. Rapid detection and quantitative analysis of MPO are of great significance for human health. Herein, an MPO protein flexible amperometric immunosensor based on a colloidal quantum dot (CQD)-modified electrode was demonstrated. The remarkable surface activity of CQDs allows them to bind directly and stably to the surface of proteins and to convert antigen-antibody specific binding reactions into significant currents. The flexible amperometric immunosensor provides quantitative analysis of MPO protein with an ultra-low limit of detection (LOD) (31.6 fg mL-1), as well as good reproducibility and stability. The detection method is expected to be applied in clinical examination, POCT (bedside test), community physical examination, home self-examination and other practical scenarios.

Association between implanted cardioverter-defibrillators and mortality for patients with left ventricular ejection fraction between 30% and 35.

BACKGROUND: Consensus guidelines support the use of implanted cardioverter-defibrillators (ICD) for primary prevention of sudden cardiac death in patients with either non-ischaemic or ischaemic cardiomyopathy with left ventricular ejection fraction (LVEF) ≤35%. However, evidence from trials for efficacy specifically for patients with LVEF near 35% is weak. Past trials are underpowered for this population and future trials are unlikely to be performed. METHODS: Patients with lowest LVEF between 30% and 35% without an ICD prior to the lowest-LVEF echo (defined as 'time zero') were identified by querying echocardiography data from 28 November 2001 to 9 July 2020 at the Massachusetts General Hospital linked to ICD treatment status. To assess the association between ICD and mortality, propensity score matching followed by Cox proportional hazards models considering treatment status as a time-dependent covariate was used. A secondary analysis was performed for LVEF 36%-40%. RESULTS: Initially, 526 440 echocardiograms representing 266 601 unique patients were identified. After inclusion and exclusion criteria were applied, 6109 patients remained for the analytical cohort. In bivariate unadjusted comparisons, patients who received ICDs were substantially more often male (79.8% vs 65.4%, p<0.0001), more often white (87.5% vs 83.7%, p<0.046) and more often had a history of ventricular tachycardia (74.5% vs 19.1%, p<0.0001) and myocardial infarction (56.1% vs 38.2%, p<0.0001). In the propensity matched sample, after accounting for time-dependence, there was no association between ICD and mortality (HR 0.93, 95% CI 0.75 to 1.15, p=0.482). CONCLUSIONS: ICD therapy was not associated with reduced mortality near the conventional LVEF threshold of 35%. Although this treatment design cannot definitively demonstrate lack of efficacy, our results are concordant with available prior trial data. A definitive, well-powered trial is needed to answer the important clinical question of primary prevention ICD efficacy between LVEF 30% and 35%.

Natural Language Processing for the Ascertainment and Phenotyping of Left Ventricular Hypertrophy and Hypertrophic Cardiomyopathy on Echocardiogram Reports.

Extracting and accurately phenotyping electronic health documentation is critical for medical research and clinical care. We sought to develop a highly accurate and open-source natural language processing (NLP) module to ascertain and phenotype left ventricular hypertrophy (LVH) and hypertrophic cardiomyopathy (HCM) diagnoses from echocardiogram reports within a diverse hospital network. After the initial development on 17,250 echocardiogram reports, 700 unique reports from 6 hospitals were randomly selected from data repositories within the Mass General Brigham healthcare system and manually adjudicated by physicians for 10 subtypes of LVH and diagnoses of HCM. Using an open-source NLP system, the module was formally tested on 300 training set reports and validated on 400 reports. The sensitivity, specificity, positive predictive value, and negative predictive value were calculated to assess the discriminative accuracy of the NLP module. The NLP demonstrated robust performance across the 10 LVH subtypes, with the overall sensitivity and specificity exceeding 96%. In addition, the NLP module demonstrated excellent performance in detecting HCM diagnoses, with sensitivity and specificity exceeding 93%. In conclusion, we designed a highly accurate NLP module to determine the presence of LVH and HCM on echocardiogram reports. Our work demonstrates the feasibility and accuracy of NLP to detect diagnoses on imaging reports, even when described in free text. This module has been placed in the public domain to advance research, trial recruitment, and population health management for patients with LVH-associated conditions.

Flexible Capacitive Pressure Sensor with High Sensitivity and Wide Range Based on a Cheetah Leg Structure via 3D Printing.

Flexible pressure sensors can be used in human-computer interaction and wearable electronic devices, but one main challenge is to fabricate capacitive sensors with a wide pressure range and high sensitivity. Here, we designed a capacitive pressure sensor based on a bionic cheetah leg microstructure, validated the benefits of the bionic microstructure design, and optimized the structural feature parameters using 3D printing technology. The pressure sensor inspired by the cheetah leg shape has a high sensitivity (0.75 kPa-1), a wide linear sensing range (0-280 kPa), a fast response time of roughly 80 ms, and outstanding durability (24,000 cycles). Furthermore, the sensor can recognize a finger-operated mouse, monitor human motion, and transmit Morse code information. This work demonstrates that bionic capacitive pressure sensors hold considerable promise for use in wearable devices.

Room-Temperature Semiconductor Gas Sensors: Challenges and Opportunities.

Our demand for ubiquitous and reliable gas detection is spurring the design of intelligent and enabling gas sensors for the next-generation Internet of Things and Artificial Intelligence. The desire to introduce gas sensors everywhere is fueled by opportunities to create room-temperature semiconductor gas sensors with ultralow power consumption. In this Perspective, we provide an overview of the recent achievement of room-temperature gas sensors that have been translated from the advances in the design of the chemical and physical properties of low-dimensional semiconductor nanomaterials. The emergence of solution-processable nanomaterials opens up remarkable opportunities to integrate into high-performance and flexible room-temperature gas sensors by using low-temperature, large-area, solution-based methods instead of costly, high-vacuum, high-temperature device manufacturing processes. We review the fundamental factors which affect the receptor and transducer functions of semiconductor gas sensors. We also discuss challenges that must be addressed in the move to the continuous miniaturization and evolution of semiconductor gas sensors.

All-solid-state SARS-CoV-2 protein biosensor employing colloidal quantum dots-modified electrode.

Rapid and reliable detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody can provide immunological evidence in addition to nucleic acid test for the early diagnosis and on-site screening of coronavirus disease 2019 (COVID-19). All-solid-state biosensor capable of rapid, quantitative SARS-CoV-2 antibody testing is still lacking. Herein, we propose an electronic labelling strategy of protein molecules and demonstrate SARS-CoV-2 protein biosensor employing colloidal quantum dots (CQDs)-modified electrode. The feature current peak corresponding to the specific binding reaction of SARS-CoV-2 antigen and antibody proteins was observed for the first time. The unique charging and discharging effect depending on the alternating voltage applied was ascribed to the quantum confinement, Coulomb blockade and quantum tunneling effects of quantum dots. CQDs-modified electrode could recognize the specific binding reaction between antigen and antibody and then transduce it into significant electrical current. In the case of serum specimens from COVID-19 patient samples, the all-solid-state protein biosensor provides quantitative analysis of SARS-CoV-2 antibody with correlation coefficient of 93.8% compared to enzyme-linked immunosorbent assay (ELISA) results. It discriminates patient and normal samples with accuracy of about 90%. The results could be read within 1 min by handheld testing system prototype. The sensitive and specific protein biosensor combines the advantages of rapidity, accuracy, and convenience, facilitating the implement of low-cost, high-throughput immunological diagnostic technique for clinical lab, point-of-care testing (POCT) as well as home-use test.

B-Cell-Epitope-Based Fluorescent Quantum Dot Biosensors for SARS-CoV-2 Enable Highly Sensitive COVID-19 Antibody Detection.

A new antibody diagnostic assay with more rapid and robust properties is demanded to quantitatively evaluate anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunity in a large population. Here, we developed a nanometer-scale fluorescent biosensor system consisting of CdSe-ZnS quantum dots (QDs) coupled with the highly sensitive B-cell epitopes of SARS-CoV-2 that could remarkably identify the corresponding antibody with a detection limit of 100 pM. Intriguingly, we found that fluorescence quenching of QDs was stimulated more obviously when coupled with peptides than the corresponding proteins, indicating that the energy transfer between QDs and peptides was more effective. Compared to the traditional enzyme-linked immunosorbent assay (ELISA), the B-cell-epitope-based QD-biosensor could robustly distinguish coronavirus disease 2019 (COVID-19) antibody-positive patients from uninfected individuals with a higher sensitivity (92.3-98.1% positive rates by QD-biosensor vs. 78.3-83.1% positive rates by ELISAs in 207 COVID-19 patients' sera) in a more rapid (5 min) and labor-saving manner. Taken together, the 'QD-peptides' biosensor provided a novel real-time, quantitative, and high-throughput method for clinical diagnosis and home-use tests.

Rapid-Response, Low Detection Limit, and High-Sensitivity Capacitive Flexible Tactile Sensor Based on Three-Dimensional Porous Dielectric Layer for Wearable Electronic Skin.

Three-dimensional (3D) porous conductive composites explored in highly sensitive tactile sensors have attracted extensive close attention in recent years owing to their peculiar porous structure and unique physical properties in terms of excellent mechanical flexibility, high relative dielectric permittivity, and good elastic property. Herein, we report an practical, efficient, and macroscopic dip-coating process to manufacture rapid-response, low detection limit, high-sensitivity, and highly sensitive capacitive flexible tactile sensors. The fabrication process, tactile perception mechanism, and sensing performance of the developed devices are comparatively investigated. The homogeneous 3D hybrid network constructed by graphene nanoplatelets/carboxyl-functionalized multiwalled carbon nanotubes/silicone rubber composites anchored on polyurethane sponge skeletons exhibits a significantly improved dielectric property, resulting in a high-performance capacitive flexible tactile sensor with a fast response time (∼45 ms), an extremely low-pressure detection limit of ∼3 Pa, excellent sensitivity (∼0.062 kPa-1), and excellent durability and stability over 2000 cycles. Importantly, the flexible devices can be used as the wearable electronic skin and successfully mounted on human skin or a soft-bodied robot to achieve the capability of physiological stimuli monitoring, micropressure monitoring, soft grabbing, etc. Our rapid-response, low detection limit, and high-sensitivity capacitive flexible tactile sensor with a novel 3D porous dielectric layer could be a prospective candidate for the wearable applications in real-time and high-accuracy portable healthcare monitoring devices, advanced human-machine interfaces, and intelligent robot perception systems.