The value of ultrasensitive C-reactive protein and homocysteine levels in predicting the diagnosis and functional prognostic assessment of cerebral infarction in the elderly.

OBJECTIVE: To evaluate the diagnostic value of ultrasensitive C-reactive protein (hs-CRP) and homocysteine (Hcy) for cerebral infarction. METHODS: 260 elderly patients with cerebral infarction were recruited and assigned to the stroke group, and 60 healthy elderly were identified as controls and included in the normal group. Serum samples of all subjects were collected at the time of admission for the determination of hs-CRP and Hcy levels. RESULTS: Patients with cerebral infarction exhibited significantly higher hs-CRP and Hcy levels than healthy controls. the patients were then categorized into mild-moderate and moderate-severe groups according to the National Institutes of Health Stroke Scale (NIHSS) score. No significant association was identified between Hcy levels and infarction severity, while more severe infarction was potentially related to higher hs-CRP levels, as evidenced by the higher hs-CRP levels observed in patients with moderate-severe infarction versus a milder severity. Patients with disease recurrence within 2 years were also included in a recurrence group, while those without recurrence were in a non-recurrence group. Results showed that patients with or without disease recurrence had similar hs-CRP and Hcy levels. CONCLUSION: In elderly patients with cerebral infarction, serum hs-CRP, and Hcy levels are potentially promising markers for the diagnosis of stroke, assessment of stroke severity, and prediction of functional recovery. hs-CRP provides more benefits in diagnosing cerebral infarction, and Hcy is more conducive to the assessment of stroke severity and prediction of functional recovery. Combined detection of the two indices did not offer additional benefits in diagnostic and predictive efficacy.

Carbon/Silicone Nanocomposite-Enabled Soft Pressure Sensors with a Liquid-Filled Cell Structure Design for Low Pressure Measurement.

In the fields of humanoid robots, soft robotics, and wearable electronics, the development of artificial skins entails pressure sensors that are low in modulus, high in sensitivity, and minimal in hysteresis. However, few sensors in the literature can meet all the three requirements, especially in the low pressure range (<10 kPa). This article presents a design for such pressure sensors. The bioinspired liquid-filled cell-type structural design endows the sensor with appropriate softness (Young's modulus < 230 kPa) and high sensitivity (highest at 0.7 kPa-1) to compression forces below 0.65 N (6.8 kPa). The low-end detection limit is ~0.0012 N (13 Pa), only triple the mass of a bee. Minimal resistance hysteresis of the pressure sensor is 7.7%. The low hysteresis is attributed to the study on the carbon/silicone nanocomposite, which reveals the effect of heat treatment on its mechanical and electromechanical hysteresis. Pressure measurement range and sensitivity of the sensor can be tuned by changing the structure and strain gauge parameters. This concept of sensor design, when combined with microfluidics technology, is expected to enable soft, stretchable, and highly precise touch-sensitive artificial skins.

Study of Fiber-Based Wearable Energy Systems.

Fiber-based electronic and photonic devices have the most desired human-friendly features, such as being soft, ubiquitous, flexible, stretchable, light, and permeable, and thus are ideal to be employed as the interface platform between humans, the environment, and machines. Today, these smart wearable devices are normally powered by rechargeable batteries. It is extremely desirable to have an undisrupted power supply for us to go anywhere at any time. Harvesting energy from the ambient environment or our body can potentially fulfill such a goal. Explorations of high performance, flexible functional materials and energy conversion devices have led many exiting discoveries. In order to realize their applications, equally important are fundamental studies of the physical phenomena and mechanisms that will provide scientific guidance for the direction of exploration and development of devices and systems. Hence, this Account provides a brief review of our recent progress in this topic area. Based upon materials science, mechanics and device physics, we have succeeded in establishment of several new theoretical models for fiber-based piezoelectric, triboelectric, and hybrid generators. These models have been verified experimentally. Excellent results were obtained for fiber-based triboelectric generators without any adjustable parameters. Reasonable agreement was demonstrated for the piezoelectric generators because of some uncertainty in the material properties and deformation modes. From both simulated and experimental results, we did not detect any synergic effect in the hybrid generator consisting of cascaded piezoelectric and triboelectric units. The verified models can be used to predict the output voltage, current, and power of the devices in terms of material properties, parameters of device structure, harvesting circuits, and operating conditions. Furthermore, by considering the electric breakdown due to field-induced-emission and gas-ionization, we have identified the theoretical upper limits of charge density and output power from contact-mode fiber-based triboelectric nanogenerators. The analysis sheds new light on the scope and focus for further exploration and provides guidance on engineering design of such devices. In addition, we have setup an experimental platform for reliable triboelectric charge measurement of highly deformable and porous materials like fabrics. An extended triboelectric series has been reported by us including 21 types of commercial and new fibers. Based upon the findings, we have made significant improvements of the performance of these energy harvesting devices. Finally, we have explored a class of new flexible thermoelectric materials exhibiting high performance for fiber-based thermoelectric generators, which can be fabricated by low-temperature and cost-effective processes, such as in situ reduction coating and three-dimensional printing. The resultant large-area, flexible, and wearable fiber-base thermoelectric generators are key devices for great potential applications such as powering wearable microelectronic systems, active microclimate regulating systems, and waste thermal energy harvesting.

Highly Sensitive and Durable Structured Fibre Sensors for Low-Pressure Measurement in Smart Skin.

Precise measurements of low pressure are highly necessary for many applications. This study developed novel structured fibre sensors embedded in silicone, forming smart skin with high sensitivity, high durability, and good immunity to crosstalk for precise measurement of pressure below 10 kPa. The transduction principle is that an applied pressure leads to bending and stretching of silicone and optical fibre over a purposely made groove and induces the axial strain in the gratings. The fabricated sensor showed high pressure sensitivity up to 26.8 pm/kPa and experienced over 1,000,000 cycles compression without obvious variation. A theoretical model of the sensor was presented and verified to have excellent agreement with experimental results. The prototype of smart leg mannequin and wrist pulse measurements indicated that such optical sensors can precisely measure low-pressure and can easily be integrated for smart skins for mapping low pressure on three-dimensional surfaces.

Graphene-Draped Semiconductors for Enhanced Photocorrosion Resistance and Photocatalytic Properties.

Semiconductor photocatalysts have been widely used for photochemical water splitting, purification of organic contaminants, and bacterial detoxification. However, most photocatalysts suffer greatly from photocorrosion under visible-light irradiation. Here we report a viable strategy to markedly improve photocorrosion resistance of photocatalysts by draping ultrathin yet highly impermeable graphene layers over a semiconductor CdS electrode. Remarkably, the average lifetime of three-layer-graphene-draped CdS photocatalyst is prolonged by 8 times compared to the as-prepared CdS counterpart without graphene draping. The introduction of graphene layers largely suppresses the charge carrier recombination of the CdS film and decreases the carrier transfer resistance at the graphene-draped CdS electrode/electrolyte interface, as revealed by the photoluminescence (PL) and electrochemical impedance spectroscopy studies, respectively, thereby leading to increased photocurrent and enhanced photocatalytic performance (i.e., a 2.5-fold increase in comparison to that in as-prepared CdS case). Our density functional theory calculations also show that electrons are readily transferred from CdS to graphene, correlating well with the PL measurement. The photocorrosion is mainly caused by oxidation reaction between CdS and O2 and H2O assisted with photogenerated holes, evidenced by X-ray photoelectron spectroscopy characterization. The draped graphene effectively prevents the direct contact between the CdS film and O2 and H2O, thus considerably retarding the photocorrosion of CdS upon visible-light exposure. This simple yet robust graphene-draping strategy for antiphotocorrosion of semiconductor photocatalysts is environmentally friendly as it prevents them from entering into the surrounding environment, thus eliminating the possible secondary pollution.

Self-Powered Piezoionic Strain Sensor toward the Monitoring of Human Activities.

Wearable sensors for the detection of human activities including subtle physiological signals and large-scale body motion as well as distinguishing the motion direction are highly desirable, but still a challenge. A flexible wearable piezoionic strain sensor based on the ionic polymer membrane sandwiched between two conductive electrodes is developed. This ionic polymer sensor can generate electrical signal output (≈mV) with rapid response (≈50 ms) under the applied bending deformation due to the internal mobile ion redistribution. Compared with the currently studied resistive and capacitive sensors, this sensor can generate sensing signals without the requirement of additional power supply, and is able to distinguish the direction of the bending strain by observing the direction of generated electrical signals. For the sensor with metallic electrode, an output voltage of 1.3 mV is generated under a bending-induced strain of 1.8%, and this voltage can be largely increased when replacing the metallic electrodes by graphene composites. After simple encapsulation of the piezoionic sensor, a wearable sensor is constructed and succeeded in monitoring the diverse human activities ranging from complex large scale multidimensional motions to subtle signals, including wrist bending with different directions, sitting posture sensing, pulse wave, and finger touch.

Association between socioeconomic status and metabolic control and diabetes complications: a cross-sectional nationwide study in Chinese adults with type 2 diabetes mellitus.

BACKGROUND: Low socioeconomic status (SES) is associated with adverse cardiovascular risk factor patterns and poor outcomes in patients with diabetes. The aim of this study was to determine whether SES is associated with the control of blood glucose, blood pressure, blood cholesterol (3Bs), and diabetic complications in Chinese adults with type 2 diabetes. METHODS: Data regarding patients' demographics, social economics, diabetes complications, and cardiovascular risk profiles were analyzed for 25,454 patients. The outcomes of interest were the proportions of patients with HbA1c <7.0 %, blood pressure <140/80 mmHg, total serum cholesterol <4.5 mmol/L, and diabetes complications. Multivariable logistic regression was used for analysis. RESULTS: Of the 25,454 patients, the least educated patients (1695, 6.7 %) had the highest chances of developing cardiovascular diseases (p = 0.048), cerebrovascular diseases (p < 0.001), and retinopathy (p < 0.001). The patients with lowest household income (10,039, 40.8 %) had the highest prevalence of retinopathy (p < 0.001) and neuropathy (p < 0.001). The most educated patients were more likely than the least educated patients to achieve HbA1c <7.0 % [adjusted odds ratio (OR) 1.38; 95 % confidence interval (95 % CI) 1.22-1.56] and 3B goals (adjusted OR 1.30; 95 % CI 1.11-1.53). The patients with highest household income were more likely to achieve BP < 140/80 mmHg (adjusted OR 1.16; 95 % CI 1.07-1.27), but less likely to reach HbA1c < 7.0 % (adjusted OR 0.90; 95 % CI 0.83-0.98) than those lowest income patients. CONCLUSIONS: Low SES was associated with poor metabolic control and more diabetes complications in adult patients in China. Individual diabetes management based on the SES of patients is encouraged.

Binary breath figures for straightforward and controllable self-assembly of microspherical caps.

The intense interest surrounding asymmetrical microparticles originates from their unique anisotropic properties and promising applications. In this work, direct self-assembly of polymeric microspherical caps without the assistance of any additives has been achieved by using low-surface-tension methanol (MeOH) and high-surface-tension water as binary breath figures (BFs). With the evaporation of polystyrene (PS) solution containing low-boiling-point solvent in the binary vapors, the formed MeOH BFs could quickly diffuse into solution, while water BFs tended to remain at the solution surface. This led to the formation of a gradient nonsolvent layer at the vapor/solution interface, which induced the formation of nuclei and guided further asymmetrical growth of polymer particles. After the spontaneous removal of MeOH, water and residual solvent by evaporation, polymeric microspherical caps were left on the substrate. Through controlling the proportion of water introduced by adjusting the ratios of MeOH and water, polymeric microspherical caps with a range of controllable shapes (divided at different positions of a sphere) were successfully obtained. The formation mechanism was explained based on the difference of vapor pressure, surface tension and miscibility between the employed solvents and nonsolvents. A solvent possessing a high vapor pressure, low surface tension and good miscibility with MeOH contributed to the formation of microspherical caps. This flexible, green and straightforward technique is a nondestructive strategy, and avoids complicated work on design, preparation and removal of hard templates and additives.

Enantioselective ruthenium(II)/Xyl-SunPhos/Daipen-catalyzed hydrogenation of γ-ketoamides.

A series of γ-hydroxy amides were synthesized with high enantioselectivities (up to 99%) using asymmetric hydrogenation of the corresponding γ-ketoamides in the presence of Ru-Xyl-SunPhos-Daipen catalyst providing key building blocks for a variety of naturally occurring and biologically active compounds.

TBEEG: A Two-Branch Manifold Domain Enhanced Transformer Algorithm for Learning EEG Decoding.

The electroencephalogram-based (EEG) brain-computer interface (BCI) has garnered significant attention in recent research. However, the practicality of EEG remains constrained by the lack of efficient EEG decoding technology. The challenge lies in effectively translating intricate EEG into meaningful, generalizable information. EEG signal decoding primarily relies on either time domain or frequency domain information. There lacks a method capable of simultaneously and effectively extracting both time and frequency domain features, as well as efficiently fuse these features. Addressing these limitations, a two-branch Manifold Domain enhanced transformer algorithm is designed to holistically capture EEG's spatio-temporal information. Our method projects the time-domain information of EEG signals into the Riemannian spaces to fully decode the time dependence of EEG signals. Using wavelet transform, the time domain information is converted into frequency domain information, and the spatial information contained in the frequency domain information of EEG signal is mined through the spectrogram. The effectiveness of the proposed TBEEG algorithm is validated on BCIC-IV-2a dataset and MAMEM-SSVEP-II datasets.

A multimodal physiological dataset for driving behaviour analysis.

Physiological signal monitoring and driver behavior analysis have gained increasing attention in both fundamental research and applied research. This study involved the analysis of driving behavior using multimodal physiological data collected from 35 participants. The data included 59-channel EEG, single-channel ECG, 4-channel EMG, single-channel GSR, and eye movement data obtained via a six-degree-of-freedom driving simulator. We categorized driving behavior into five groups: smooth driving, acceleration, deceleration, lane changing, and turning. Through extensive experiments, we confirmed that both physiological and vehicle data met the requirements. Subsequently, we developed classification models, including linear discriminant analysis (LDA), MMPNet, and EEGNet, to demonstrate the correlation between physiological data and driving behaviors. Notably, we propose a multimodal physiological dataset for analyzing driving behavior(MPDB). The MPDB dataset's scale, accuracy, and multimodality provide unprecedented opportunities for researchers in the autonomous driving field and beyond. With this dataset, we will contribute to the field of traffic psychology and behavior.

Green moisture-electric generator based on supramolecular hydrogel with tens of milliamp electricity toward practical applications.

Moisture-electric generators (MEGs) has emerged as promising green technology to achieve carbon neutrality in next-generation energy suppliers, especially combined with ecofriendly materials. Hitherto, challenges remain for MEGs as direct power source in practical applications due to low and intermittent electric output. Here we design a green MEG with high direct-current electricity by introducing polyvinyl alcohol-sodium alginate-based supramolecular hydrogel as active material. A single unit can generate an improved power density of ca. 0.11 mW cm-2, a milliamp-scale short-circuit current density of ca. 1.31 mA cm-2 and an open-circuit voltage of ca. 1.30 V. Such excellent electricity is mainly attributed to enhanced moisture absorption and remained water gradient to initiate ample ions transport within hydrogel by theoretical calculation and experiments. Notably, an enlarged current of ca. 65 mA is achieved by a parallel-integrated MEG bank. The scalable MEGs can directly power many commercial electronics in real-life scenarios, such as charging smart watch, illuminating a household bulb, driving a digital clock for one month. This work provides new insight into constructing green, high-performance and scalable energy source for Internet-of-Things and wearable applications.

Brain-Inspired Image Perceptual Quality Assessment based on EEG: A QoE Perspective.

Human-oriented image communication should take the quality of experience (QoE) as an optimization goal, which requires effective image perceptual quality metrics. However, traditional user-based assessment metrics are limited by the deviation caused by human high-level cognitive activities. To tackle this issue, in this paper, we construct a brain response-based image perceptual quality metric and develop a brain-inspired network to assess the image perceptual quality based on it. Our method aims to establish the relationship between image quality changes and underlying brain responses in image compression scenarios using the electroencephalography (EEG) approach. We first establish EEG datasets by collecting the corresponding EEG signals when subjects watch distorted images. Then, we design a measurement model to extract EEG features that reflect human perception to establish a new image perceptual quality metric: EEG perceptual score (EPS). To use this metric in practical scenarios, we embed the brain perception process into a prediction model to generate the EPS directly from the input images. Experimental results show that our proposed measurement model and prediction model can achieve better performance. The proposed brain response-based image perceptual quality metric can measure the human brain's perceptual state more accurately, thus performing a better assessment of image perceptual quality.

A randomized controlled trial of standard vs customized graduated elastic compression stockings in patients with chronic venous disease.

OBJECTIVE: This study aimed to compare the efficacy of customized graduated elastic compression stockings (c-GECSs) based on lower leg parameter models with standard GECSs (s-GECSs) in patients with chronic venous disease (CVD). METHODS: In this randomized, single-blind, controlled trial, 79 patients with stage C2 or C3 CVD were assigned to one of two groups: c-GECSs or s-GECSs. The primary outcome was change to Venous Insufficiency Epidemiological and Economic Study Quality of Life (VEINES-QOL) scores at months 1, 3, and 6 as compared with baseline. Secondary outcomes included compliance with wearing ECSs, interface pressure at the smallest circumference of the ankle (point B) and the largest circumference of the calf (point C), and calf volume (CV). RESULTS: There were 13 pairs of s-GECS and 2 pairs of c-GECS that showed pressure values higher than the standard at either point B or C. The c-GECSs were significantly superior to s-GECSs in terms of score improvement at all three time points (month 1, 8.47 [95% confidence interval (CI), 7.47-9.45] vs 5.89 [95% CI, 5.00-6.78]; month 3, 9.60 [95% CI, 8.47-10.72] vs 6.72 [95% CI, 5.62-7.83]; month 6, 7.09 [95% CI, 5.93-8.24] vs 3.92 [95% CI, 2.67-5.18]; P < .0001). Besides, at month 1, the mean daily use time of the c-GECS and s-GECS groups was 10.7 and 9.5 hours, respectively (P < .05). Correlation analysis indicated a negative relationship between local high pressure and daily duration in the s-GECS group (rpb = -0.388; n = 38; P < .05). Variances in pressure were greater in the s-GECSs group. The c-GECSs showed advantage in maintaining pressure. Both c-GECSs and s-GECSs effectively reduced CV (mL), with no significant differences between groups (month 1, 90.0 [95% CI, 71.4-108.5] vs 85.0 [95% CI, 65.6-104.2]; month 3, 93.8 [95% CI, 69.7-117.8] vs 85.9 [95% CI, 65.5-106.2]; month 6, 70.8 [95% CI, 46.5-95.2]) vs 60.8 [95% CI, 44.1-77.5]). CONCLUSIONS: The c-GECSs based on individual leg parameter models significantly improved VEINES-QOL scores and provided stable and enduring pressure as compared with s-GECSs for patients with stage C2 or C3 CVD. Although both c-GECSs and s-GECSs effectively reduced CV, the superior fit and comfort of c-GECSs improved patient compliance. Hence, c-GECSs are a viable alternative for patients who have difficulty tolerating s-GECSs.

Novel oxymagnesite/green rust nanohybrids for selective removal and slow release of phosphate in water.

The new paradigm in wastewater treatment demands to change traditional pollutants removal into resource recovery, especially for non-renewable P resources, effectively recovering phosphate from wastewater and reutilizing it as a nutrient is crucial to P sustainable utilization and P-related pollution control. The nanomaterial-based adsorption technology for P recovery from wastewater is becoming a research hotspot due to its high efficiency and selectivity. Herein, to recover aqueous phosphate, we developed novel oxymagnesite/green rust (OMGR) nanohybrids by a one-pot hydrothermal method. Green rust nanoparticles dispersed on the highly reactive oxymagnesite (MgO2MgCO3) nanosheets could achieve efficient recovery and reuse of P. The volume ratio of water to ethylene glycol played an important role in the preparation of OMGR. The OMGR possessed an excellent selectivity of phosphate removal in the presence of multi-anions and wide pH adaptability in 4.0-10.0. The formation of MgP nanocrystals and the inner-sphere FeOP complexes via ligand exchange contributed to the selective removal of P by OMGR, and the removal capacity reached 141 mg P.g-1. The process of phosphate removal by OMGR was spontaneously endothermic and controlled by the intraparticle and boundary layer diffusion. Most importantly, the high bioavailable P (127 mg.g-1) of P-loaded OMGR had a persistent release behavior regulated by dissolution and diffusion, indicating that the P-loaded OMGR can act as a slow-release P-fertilizer. The findings provide a green and eco-friendly approach to realizing P resource recovery and reuse for phosphate-containing wastewaters.

Asymmetric strategy for enhanced performance of flexible electroadhesive clutch.

Flexible electroadhesive clutches with high shear stress and fast response working at low voltage are much desired in wearable electronics and robotic systems. Dielectric materials with opposite charge characteristics could maximize the clutch performance by taking advantages of the boosted electroadhesion between the two contact pads in an asymmetrically structured clutch. In this paper, asymmetrically structured electroadhesive clutches are proposed and reported for the first time. The asymmetric structured clutch exhibits a two-fold increment in the shear force but similar response time by simply reversing the electrode polarity. This work provides a new dimension to realize high-performance electroadhesive clutches based on an asymmetric strategy.

Fast NURBS-based parametric modeling of human calves with high-accuracy for personalized design of graduated compression stockings.

BACKGROUND AND OBJECTIVES: Accurate human body models are increasingly demanded by high-quality human-centered ergonomic applications, especially the design and manufacturing of compressive functional apparels. However, existing parametric models in related works are not capable to accurately describe detailed local shape features of human. METHODS: In this work, a high-accuracy parametric modeling approach for human limb was proposed. 3D Scans of human calves were studied. Key data points of the scanned human calves were identified according to human anatomy, forming a quasi-triangular mesh of feature points. Then, non-uniform rational B-splines (NURBS) method was implemented. Control points were calculated from the key data points, with which the human calf shapes can be reconstructed by the smooth NURBS surface, giving rise to a new parametric model of human calves. Error between the scanned and reconstructed calf shapes were analyzed to verify the effectiveness of this model. RESULTS: Error analysis showed that, this proposed method delivers a high-efficiency and high-accuracy parametric shape modeling approach with averaged error observed as only 0.37% for all the 260 subjects, much less compared to previous relative works (around 5%). For tentative application, customized medical compression stockings were designed based on this model and proved as valid to exert desired gradient compression on the according calf mannequin. CONCLUSIONS: By introducing the non-uniform rational B-splines method, a parametric model capable of characterizing human limbs with high-accuracy was proposed. Using very small amount of data, this model is expected to highly facilitate remote customized design and provide 3D shape references for design of compressive garments. Moreover, the proposed methods can inspire developments of other mixed modeling methods for high-accuracy applications.

Silencing FOXP2 reverses vemurafenib resistance in BRAFV600E mutant papillary thyroid cancer and melanoma cells.

BACKGROUND: Vemurafenib (VEM) is a commonly used inhibitor of papillary thyroid cancer (PTC) and melanoma with the BRAFV600E mutation; however, acquired resistance is unavoidable. The present study aimed to identify a potential target to reverse resistance. MATERIALS AND METHODS: A VEM-resistant PTC cell line (B-CPAP/VR) was established by gradually increasing the drug concentration, and a VEM-resistant BRAFV600E melanoma cell line (A375/VR) was also established. RNA sequencing and bioinformatics analyses were conducted to identify dysregulated genes and construct a transcription factor (TF) network. The role of a potential TF, forkhead box P2 (FOXP2), verified by qRT-PCR, was selected for further confirmation. RESULTS: The two resistant cell lines were tolerant of VEM and displayed higher migration and colony formation abilities (p < 0.05). RNA sequencing identified 9177 dysregulated genes in the resistant cell lines, and a TF network consisting of 13 TFs and 44 target genes was constructed. Alterations in FOXP2 expression were determined to be consistent between the two VEM-resistant cell lines. Finally, silencing FOXP2 resulted in an increase in drug sensitivity and significant suppression of the migration and colony formation abilities of the two resistant cell lines (p < 0.05). CONCLUSIONS: The present study successfully established two VEM-resistant cell lines and identified a potential target for VEM-resistant PTC or melanoma.

Gigantic and Continuous Output Power in Ionic Thermo-Electrochemical Cells by Using Electrodes with Redox Couples.

The main obstacle of ionic thermo-electrochemical cells (TECs) in continuous power supply lies in a low heat-to-electricity energy conversion efficiency because most TECs work in thermodiffusion mode in which the ions are confined in a liquid/electrolyte media. The introduction of the redox couple onto the electrode surface may overcome the obstacle by resolving the low mass transport rate of ions caused by the redox process occurring near but not on the electrode surface. Herein, the authors demonstrate enhancement of TECs by integrating the redox couple directly onto the electrode surface to maximize the mass transport efficiency. A discontinuous interfacial modification strategy is developed by using a carbon cloth/iron (II/III) phytate as the symmetric electrodes. The gelled electrolyte consisting of a polyacrylamide matrix and phytic acid is shown to promote selective ion diffusion. A synergistic combination consisting of the thermodiffusion effect and redox reactions on the electrode is established in a pre-treated layout. Such TEC affords a high output voltage of 0.4 V, an excellent instantaneous output power density (20.26 mW m-2 K-2 ) and a record-high 2 h output energy density (2451 J m-2 ) under TH = 30 °C with TC = 15 °C, with an ultrahigh Carnot-relative efficiency of 1.12%.