Bioresorbable electronics that can be absorbed and become part of the organism after their service life are a new trend to avoid secondary invasive surgery. However, the material limitation is a significant challenge. There are fewer biodegradable materials with pressure‐sensitive properties. Here, a pressure sensor based on the triboelectric effect between bioabsorbable materials is reported. This effect is available in almost all materials. The bioresorbable triboelectric sensor (BTS) can directly convert ambient pressure changes into electrical signals. This device successfully identifies abnormal vascular occlusion events in large animals (dogs). The service life of the BTS reaches 5 days with a high service efficiency (5.95%). The BTS offers excellent sensitivity (11 mV mmHg−1), linearity (R2 = 0.993), and good durability (450 000 cycles). The antibacterial bioresorbable materials (poly(lactic acid)–(chitosan 4%)) for the BTS can achieve 99% sterilization. Triboelectric devices are expected to be applied in postoperative care as bioresorbable electronics.

The purpose this paper is the development a novel polymeric fiber-optic magnetostrictive metal detector, using a fiber–optic Mach-Zehnder interferometer and polymeric magnetostrictive material. Metal detection is based on the strain-induced optical path length change steming from the ferromagnetic material introduced in the magnetic field. Varied optical phase shifts resulted largely from different metal objects. In this paper, the preliminary results on the different metal material detection will be discussed.

Background Gliomas, especially the high-grade glioblastomas (GBM), are highly aggressive tumors in the central nervous system (CNS) with dismal clinical outcomes. Effective biomarkers, which are not currently available, may improve clinical outcomes through early detection. We sought to develop a non-invasive diagnostic approach for gliomas based on 5-hydroxymethylcytosines (5hmC) in circulating cell-free DNA (cfDNA). Methods We obtained genome-wide 5hmC profiles using the 5hmC-Seal technique in cfDNA samples from 111 prospectively enrolled patients with gliomas and 111 age-, gender-matched healthy individuals, which were split into a training set and a validation set. Integrated models comprised of 5hmC levels summarized for gene bodies, long non-coding RNAs (lncRNAs), cis-regulatory elements, and repetitive elements were developed using the elastic net regularization under a case-control design. Results The integrated 5hmC-based models differentiated healthy individuals from gliomas (AUC [area under the curve] = 84%; 95% confidence interval [CI], 74-93%), GBM patients (AUC = 84%; 95% CI, 74-94%), WHO II-III glioma patients (AUC = 86%; 95% CI, 76-96%), regardless of IDH1 (encoding isocitrate dehydrogenase) mutation status or other glioma-related pathological features such as TERT, TP53 in the validation set. Furthermore, the 5hmC biomarkers in cfDNA showed the potential as an independent indicator from IDH1 mutation status and worked in synergy with IDH1 mutation to distinguish GBM from WHO II-III gliomas. Exploration of the 5hmC biomarkers for gliomas revealed relevance to glioma biology. Conclusions The 5hmC-Seal in cfDNA offers the promise as a non-invasive approach for effective detection of gliomas in a screening program.

This paper presents a new metal detector using a fiberoptic magnetostriction sensor. The metal sensor uses a fiber-optic Mach-Zehnder interferometer with a newly developed ferromagnetic polymer as the magnetostrictive sensing material. This polymeric magnetostrictive fiberoptic metal sensor is simple to fabricate, small in size, and resistant to RF interference (which is common in typical electromagnetic type metal detectors). Metal detection is based on disruption of the magnetic flux density across the magnetostriction sensor. In this paper, characteristics of the material being sensed and magnetic properties of the ferromagnetic polymers will be discussed.

BackgroundAlthough both high-power (HP) ablation and lesion size index (LSI) are novel approaches to make effective lesions during pulmonary vein isolation (PVI) for atrial fibrillation (AF), the optimal LSI in HP ablation for PVI is still unclear. Our study sought to explore the association between LSI and acute conduction gap formation and investigate the optimal LSI in HP ablation for PVI.MethodsA total of 105 consecutive patients with AF who underwent HP ablation guided by LSI (LSI-guided HP) for PVI in our institute between June 2019 and July 2020 were retrospectively enrolled. Each ipsilateral PV circle was subdivided into four segments, and ablation power was set to 50 W with target LSI values at 5.0 and 4.0 for anterior and posterior walls, respectively. We compared the LSI values with and without acute conduction gaps after the initial first-pass PVI.ResultsPVI was achieved in all patients, and the incidence of first-pass PVI was 78.1% (82/105). A total of 6,842 lesion sites were analyzed, and the acute conduction gaps were observed in 23 patients (21.9%) with 45 (0.7%) lesion points. The gap formation was significantly associated with lower LSI (3.9 ± 0.4 vs. 4.6 ± 0.4, p < 0.001), lower force-time integral (82.6 ± 24.6 vs. 120.9 ± 40.4 gs, p < 0.001), lower mean contact force (5.7 ± 2.4 vs. 8.5 ± 2.8 g, p < 0.001), shorter ablation duration (10.5 ± 3.6 vs. 15.4 ± 6.4 s, p < 0.001), lower mean temperature (34.4 ± 1.4 vs. 35.6 ± 2.6°C, p < 0.001), and longer interlesion distance (4.4 ± 0.3 vs. 4.3 ± 0.4 mm, p = 0.031). As per the receiver operating characteristic analysis, the LSI had the highest predictive value for gap formation in all PVs segments, with a cutoff of 4.35 for effective ablation (sensitivity 80.0%; specificity 75.4%, areas under the curve: 0.87). The LSI of 4.55 and 3.95 had the highest predictive value for gap formation for the anterior and posterior segments of PVs, respectively.ConclusionUsing LSI-guided HP ablation for PVI, more than 4.35 of LSI for all PVs segments showed the best predictive value to avoid gap formation for achieving effective first-pass PVI. The LSI of 4.55 for the anterior wall and 3.95 for the posterior wall were the best cutoff values for predicting gap formation, respectively.