Soft mechanical sensors for wearable and implantable applications

Wearable and implantable sensing of biomechanical signals such as pressure, strain, shear, and vibration can enable a multitude of human-integrated applications, including on-skin monitoring of vital signs, motion tracking, monitoring of internal organ condition, restoration of lost/impaired mechanoreception, among many others. The mechanical conformability of such sensors to the human skin and tissue is critical to enhancing their biocompatibility and sensing accuracy. As such, in the recent decade, significant efforts have been made in the development of soft mechanical sensors. To satisfy the requirements of different wearable and implantable applications, such sensors have been imparted with various additional properties to make them better suited for the varied contexts of human-integrated applications. In this review, focusing on the four major types of soft mechanical sensors for pressure, strain, shear, and vibration, we discussed the recent material and device design innovations for achieving several important properties, including flexibility and stretchability, bioresorbability and biodegradability, self-healing properties, breathability, transparency, wireless communication capabilities, and high-density integration. We then went on to discuss the current research state of the use of such novel soft mechanical sensors in wearable and implantable applications, based on which future research needs were further discussed. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices Implantable Materials and Surgical Technologies > Nanomaterials and Implants</p

Mining Weighted Frequent Closed Episodes over Multiple Sequences

Frequent episode discovery is introduced to mine useful and interesting temporal patterns from sequential data. The existing episode mining methods mainly focused on mining from a single long sequence consisting of events with time constraints. However, there can be multiple sequences of different importance as the persons or entities associated with each sequence can be of different importance. Aiming to mine episodes in multiple sequences of different importance, we first define a new kind of episodes, i.e., the weighted frequent closed episodes, to take sequence importance, episode distribution and occurrence frequency into account together. Secondly, to facilitate the mining of such new episodes, we present a new concept called maximal duration serial episodes to cut a whole sequence into multiple maximum episodes using duration constraints, and discuss its properties for episode shrinking processing. Finally, based on the theoretical properties, we propose a two-phase approach to efficiently mine these new episodes. In Phase I, we adopt a level-wise episode shrinking framework to discover the candidate frequent closed episodes with the same prefixes, and in Phase II, we match the candidates with different prefixes to find the frequent close episodes. Experiments on simulated and real datasets demonstrate that the proposed episode mining strategy has good mining effectiveness and efficiency

What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?

Various types of Multi-Agent Reinforcement Learning (MARL) methods have been developed, assuming that agents' policies are based on true states. Recent works have improved the robustness of MARL under uncertainties from the reward, transition probability, or other partners' policies. However, in real-world multi-agent systems, state estimations may be perturbed by sensor measurement noise or even adversaries. Agents' policies trained with only true state information will deviate from optimal solutions when facing adversarial state perturbations during execution. MARL under adversarial state perturbations has limited study. Hence, in this work, we propose a State-Adversarial Markov Game (SAMG) and make the first attempt to study the fundamental properties of MARL under state uncertainties. We prove that the optimal agent policy and the robust Nash equilibrium do not always exist for an SAMG. Instead, we define the solution concept, robust agent policy, of the proposed SAMG under adversarial state perturbations, where agents want to maximize the worst-case expected state value. We then design a gradient descent ascent-based robust MARL algorithm to learn the robust policies for the MARL agents. Our experiments show that adversarial state perturbations decrease agents' rewards for several baselines from the existing literature, while our algorithm outperforms baselines with state perturbations and significantly improves the robustness of the MARL policies under state uncertainties

Trends in acupuncture for infertility: a scoping review with bibliometric and visual analysis

BackgroundUnexplained recurrent implantation failure and the high cost of assisted reproductive techniques for those experiencing infertility have increasingly resulted in the use of acupuncture. However, the trends and research status of acupuncture on infertility resulting in natural conception have not been systematically summarized. This scoping review and knowledge graph analysis aimed to summarize existing clinical studies on acupuncture for infertility that resulted in natural conception.MethodsSeven databases, namely, PubMed, Embase, the Cochrane Library, CNKI, VIP, Wanfang Data, and SinoMed, were searched up to August 2023 (updated on 1 April). Two authors independently identified related clinical studies and systematic reviews, and extracted data from included studies on acupuncture for infertility; any discrepancies were resolved by discussion or judged by a third author. A meta-analysis was conducted based on randomized controlled trials (RCTs), and data were synthesized using risk ratios with 95% confidence intervals.ResultsOf the 310 articles meeting the inclusion criteria, 274 were primary studies, 7 were systematic reviews, and 29 were case reports. Reported adverse events included mild ovarian irritation and early signs of miscarriage. Out of the 274 primary studies, there were 40 (14.60%) cases of male infertility and 234 (85.40%) cases of female infertility. Current research highlights on acupuncture for infertility focused on female infertility caused by polycystic ovary syndrome, ovulation disorder, and luteinized unruptured follicle syndrome (LUFS), while acupuncture for male infertility was a hotspot in the early research stage. The meta-analysis also suggested that acupuncture was more effective than human chorionic gonadotropin (HCG) [RR = 1.89, 95% CI (1.47, 2.42), 11 RCTs, 662 participants]. Acupuncture combined with HCG was comparable to HCG [RR = 2.33, 95% CI (1.53, 3.55), four RCTs, 259 participants]. Compared with no treatment, acupuncture resulted in a higher pregnancy rate [RR = 22.12, 95% CI (1.39, 353.09), one RCT, 47 participants]. There was no statistical difference between acupuncture combined with HCG plus letrozole and HCG plus letrozole [RR = 1.56, 95% CI (0.84, 2.89), one RCT, 84 participants].ConclusionCurrent research highlights on acupuncture for infertility resulting in natural conception focused on female infertility caused by polycystic ovary syndrome, ovulation disorder, and LUFS, while studies on male infertility and female infertility caused by blockage in the fallopian tube, thin endometrium, and other factors were insufficient. Well-designed confirmatory clinical studies are still needed as the research hypotheses of most studies were unclear

Transient Inhibition of mTORC1 Signaling Ameliorates Irradiation-Induced Liver Damage

Recurrent liver cancer after surgery is often treated with radiotherapy, which induces liver damage. It has been documented that activation of the TGF-β and NF-κB signaling pathways plays important roles in irradiation-induced liver pathologies. However, the significance of mTOR signaling remains undefined after irradiation exposure. In the present study, we investigated the effects of inhibiting mTORC1 signaling on irradiated livers. Male C57BL/6J mice were acutely exposed to 8.0 Gy of X-ray total body irradiation and subsequently treated with rapamycin. The effects of rapamycin treatment on irradiated livers were examined at days 1, 3, and 7 after exposure. The results showed that 8.0 Gy of irradiation resulted in hepatocyte edema, hemorrhage, and sinusoidal congestion along with a decrease of ALB expression. Exposure of mice to irradiation significantly activated the mTORC1 signaling pathway determined by pS6 and p-mTOR expression via western blot and immunostaining. Transient inhibition of mTORC1 signaling by rapamycin treatment consistently accelerated liver recovery from irradiation, which was evidenced by decreasing sinusoidal congestion and increasing ALB expression after irradiation. The protective role of rapamycin on irradiated livers might be mediated by decreasing cellular apoptosis and increasing autophagy. These data suggest that transient inhibition of mTORC1 signaling by rapamycin protects livers against irradiation-induced damage

Nurse educators perceptions of simulation teaching in Chinese context: benefits and barriers

Background Although simulated teaching was introduced to China in the 1990s, it remains underused in nursing education. Determining how Chinese nurse educators feel about using simulation in their institutions is very important for faculty training and has the potential to influence simulation implementation. Method This cross-sectional descriptive study was undertaken to identify the nurse educators’ experiences in the use of simulation from various regions of China. One hundred and thirty-six nurse educators provided demographic data and information about simulation implementation within their institutions and explored the perceived barriers and benefits of simulation usage. Results The survey data shows that 108 participants have used simulation in their work, but less than 92 (67.6%) of the respondents had used this teaching strategy more than ten times in last year. The study identified four factors hindering nurse faculty from simulation adoption: (1) concerns with student readiness; (2) the need for faculty team-building for simulation teaching; (3) lack of adequate simulation resources; and (4) thoughtful integration of simulation into nursing curricula. Conclusions Study data suggest that faculty training programs for simulation should be based on the nurse educators’ training needs, including systematically designed training topics, and the provision of hands-on learning simulation activities with expert feedback to help nurse educators achieve the competencies required for effective simulation-based education

E-Polymers: Applications in Biological Interfaces and Organisms

Future electronics will play a more critical role in people’s lives, as reflected in the realization of advanced human–machine interfaces, disease detection, medical treatment, and health monitoring. The current electronic products are rigid, non-degradable, and cannot repair themselves. Meanwhile, the human body is soft, dynamic, stretchable, degradable, and self-healing. Consequently, it is valuable to develop new electronic materials with skin-like properties that include stretchability, inhibition of invasive reactions, self-healing, long-term durability, and biodegradability. These demands have driven the development of a new generation of electronic materials with high-electrical performance and skin-like properties, among which e-polymers are increasingly being more extensively investigated. This review focuses on recent advances in synthesizing e-polymers and their applications in biointerfaces and organisms. Discussions include the synthesis and properties of e-polymers, the interrelationships between engineered material structures and human interfaces, and the application of implantable and wearable systems for sensors and energy harvesters. The final section summarizes the challenges and future opportunities in the evolving materials and biomedical research field