With the high sensitivity and anti-interference provided by a dual Z-scheme structure photoanode and a two-electrode system, a high-performance self-powered photoelectrochemical (PEC) aptasensor for oxytetracycline (OTC) detection was established in this work. Graphitic carbon nitride (g-C3N4) with excellent photoelectric properties was used to be combined with WO3 and MnO2 to form a kind of dual Z-scheme heterojunction. The designed unique structure and the complementary performances of the three materials collectively guaranteed the highly stable photocurrent output of the photoanode due to the wide range of light absorption and the high separation rate of electron–hole pairs. The aptamer-based cathode modified with reduced graphene oxide (rGO) and Au nanoparticles (Au NPs) provided high conductivity and aptamer-binding sites, which brought excellent selective recognition of OTC as well as the self-powered capacity by receiving electrons from the photoanode. In the PEC sensing of OTC, the device presented a wide detection range from 1 pM to 150 nM and a low detection limit of 0.1 pM. Besides, the developed PEC aptasenor showed good selectivity, reproducibility, and stability, so as to be applied to real samples. The proposed PEC sensing method can be considered an effective and promising direction for the detection of antibiotics in the future.

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BackgroundFrailty caused by deterioration in multiple physiological systems has led to a significant increase in adverse events such as falls, disability, and death in frail older people. Similar to frailty, sarcopenia, defined as loss of skeletal muscle mass and strength, is tightly related to mobility disorders, falls, and fractures. With population aging, co-occurrences of frailty and sarcopenia are increasingly common in the elderly, which are more deleterious for the health and independence of older adults. But the high similarity and overlap between the frailty and sarcopenia increase the difficulty of early recognition of frailty with sarcopenia. The purpose of this study is to use detailed gait assessment to determine the more convenient and sensitive digital biomarker of sarcopenia in the frail population.MethodsNinety-five frail elderly people (age = 86 ± 7 years old, BMI, and body mass index = 23.21 ± 3.40 kg/m2) were screened out by the evaluation of Fried criteria. Then, 41 participants (46%) were identified with sarcopenia, and 51 participants (54%) were identified without sarcopenia. Using a validated wearable platform, participants’ gait performance was evaluated under single-task and dual-task (DT). Participants walked back and forth on the 7-m-long trail for 2 min at a habitual speed. Gait parameters of interest include cadence, gait cycle duration, step duration, gait speed, variability of gait speed, stride length, turn duration, and steps in turn.ResultsOur results showed that compared with the frail elderly without sarcopenia, the gait performance of the sarcopenic group in single-task and dual-task walking was worse. Overall, the parameters with high performance were the gait speed (DT) (OR 0.914; 95% CI 0.868–0.962) and turn duration (DT) (OR 7.907; 95% CI 2.401–26.039) under dual-task conditions, and the AUC in distinguishing between frail older adults with and without sarcopenia was 0.688 and 0.736, respectively. Turn duration in dual-task testing had larger observed effect than gait speed to identify sarcopenia in the frail population, this result remained significant even after controlling for potential confounds. When gait speed (DT) and turn duration (DT) were combined in the model, AUC increased from 0.688 to 0.763.ConclusionThis study shows that gait speed and turn duration under dual-task are good predictors of sarcopenia in frail elderly, and turn duration (DT) has a better predictive ability. The gait speed (DT) combined with turn duration (DT) is a potential gait digital Biomarker of sarcopenia in the frail elderly. Dual-task gait assessment and detailed gait indexes provide important value for identification of sarcopenia in frail elderly people.

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