To read the full-text of this research, you can request a copy directly from the authors.
... The burgeoning evolution of high-speed telecommunications from 5G to the anticipated 6G has inadvertently intensified the prevalence of electromagnetic pollution [1][2][3]. To guarantee the reliable operation of electronic devices as well as to prevent harmful of electromagnetic pollution on human body, there is an imperative need in developing electromagnetic interference shielding materials (EMISM) that are not only lightweight and facile to process but also exhibit excellent electromagnetic interference shielding effectiveness (EMISE) [4][5][6]. ...
With the burgeoning application of diverse electronic equipment in daily life and national defense, the requirements for electromagnetic interference shielding effectiveness (EMISE) are constantly increasing. The precise adjustment of pore structure and the controllable distribution of conductive fillers in pores have become key challenges in optimizing EMISE of porous materials. Herein, we fabricated fluorinated carbon nanotube (FCNT) and polyarylene ether nitrile (PEN) FCNT/PEN composites with advanced EMISE by precisely controlling the pore structure of PEN porous films via delayed phase conversion (DPC) method and distributing FCNT on the obtained pore walls. Dispersion and electronegativity of carbon nanotube are firstly modified by fluorination treatment, offering FCNT. The pore structures of PEN porous films with enriched FCNT on their pore walls are adjusted by changing constitution of coagulation bath and amount of porogen PVP K30. Benefiting from the separated pore structure and continuous conducting network of FCNT inside the pore, these porous films exhibit up to 27.3 dB absorption dominated EMISE with a low conductivity of 0.06 S/m. Further continuous hot pressing on these porous films results in thinner and denser films whose specific EMISE reaches an astonishing value of 6794.9 dB/cm. This in situ self-assembly of FCNT during the DPC process achieving the directional distribution of fillers in the prepared porous films initiates a novel approach for fabricating materials with advanced EMISE.
... With the improvement in life quality and health awareness [1][2][3][4][5][6], there is increasing attention to healthcare and natural medications, as people seek more holistic and preventive approaches to maintaining health [7][8][9]. Tissue engineering Huoli Hu, Wenjia Zhang, and Yundong Zhou contributed equally to this work. [10][11][12] has played a role in the biomedical applications [13][14][15][16]. ...
Acute respiratory distress syndrome (ARDS) continues to be a life-threatening challenge, especially for patients in intensive care units (ICUs). Despite extensive research, cost-effective treatments remains elusive, primarily due to the difficulties in delivering adequate medications to damaged tissues and managing lung inflammation. This study presents a novel approach in which mitochondrial and lung-targeting liposomes loaded with ROS scavengers (LMR) were constructed through fusion. Briefly, mitochondria were extracted from human AC16 cardiac muscle cells using a specific commercial kit. Characterization involved techniques such as TEM imaging, zeta potential analysis, and SDS-PAGE. PCR and qRT-PCR were used to measure gene expression, while ROS levels were detected using a microplate reader. The lung-targeted liposomes ensured prolonged retention, thereby facilitating their immunoregulatory functions. By targeting mitochondrial damage and oxidative stress, LMR showed improved ATP production and reduced LPS-induced ROS stress in macrophages. Treatment with LMR not only enhanced mitochondrial integrity but also shifted macrophages towards an anti-inflammatory state, evidenced by reduced expression of TNF-α, IL-1β, CD86, and IL-6 and increased production of the anti-inflammatory cytokine CD206. This reduction in inflammation and oxidative stress led to improved therapeutic outcomes in a mouse model of ARDS. Overall, this hybrid nanoplatform offers a versatile strategy for drug delivery by integrating biomaterials and therapeutic agents through the fusion of mitochondria with liposomes, thereby enhancing lung biodistribution and amplifying the anti-inflammatory response in ARDS treatment.
... It also helps to rehabilitate the illnesses and diseases safely and effectively. The rapid development in material technology and detection techniques led to the fabrication of different biomedical devices, including disposable devices, wearables, monitoring devices, implantable devices, imaging, and computer-aided techniques [4][5][6][7][8]. Computer-aided or assisted therapy is a new technology using computation in therapeutics for assistance, evaluation, and support. ...
Computer-assisted smart neurotherapy (CASNuT) is an emerging technology used for psychiatric rehabilitation, neurological rehabilitation, and schizophrenia to improve treatment and clinical decision-making. Combined mental practice (cognitive control) and physical practice (bending fingers) were incorporated into the prepared CASNuT. It is constructed using the network of multifunctional piezo-tribo hybrid (PDMS/BCST) composite film-based intrinsic hybrid nanogenerators (which acts as a mechano-electric sensor for the smart gloves) and computation with the interfacing circuit/display devices. Successful integration of piezoelectric and triboelectric charges enhanced the intrinsic hybrid nanogenerator output (426 V, 1.72 mA/m², and 368.66 µW/m² at 100 MΩ) and sensing properties. Next, it demonstrated rehabilitation treatment (via CASNuT) and smart medical assistance using a mechano-electric smart medical glove. Computer-aided or assisted therapy computes for better assistance and treatment.
Graphical abstract
... With increasing awareness of healthcare [24][25][26] and required high-standard living conditions [27][28][29], more advanced materials [30] and devices [31][32][33][34] have been designed and built [35]. Natural products such as bamboo [36][37][38] and lignin [39][40][41] have attracted more attentions due to their increasing usage in our daily lives [42][43][44][45][46]. ...
Non-alcoholic fatty liver disease is a prevalent chronic metabolic condition, for which no approved medications are available. As a condiment and traditional Chinese medicine, ginger can be useful in reducing the symptoms of non-alcoholic fatty liver disease. Although its active ingredients and mechanisms of action are unknown, there is a lack of research on them. The purpose of this study is to prepare magnetite (Fe3O4)@Stearoyl-CoA desaturase 1 (SCD1) materials and analyze them using ultra-high performance liquid-chromatography-mass spectrometry (UPLC-MS) for rapid screening of potential inhibitors of SCD1 in ginger. Based on this analysis, it has been shown that the primary components in ginger that bind SCD1 directly are gingerols, with 10-gingerol having a greater affinity for binding to SCD1 than 8-gingerol and 6-gingerol. Moreover, further studies indicated that free fatty acids (FFA)-induced lipid accumulation is improved by this class of compounds in normal human hepatocytes (THLE-3), with 10-gingerol being the most effective compound. This study provides a new insight into the mechanism, by which ginger contributes to the improvement of non-alcoholic fatty liver disease (NAFLD) and provide support for the effective use of 10-gingerol for the treatment of NAFLD.
Coronavirus pandemic (COVID-19) has infected more than ten million persons worldwide. Therefore, researchers are trying to address various aspects that may help in diagnosis this pneumonia. Image segmentation is a necessary pr-processing step that implemented in image analysis and classification applications. Therefore, in this study, our goal is to present an efficient image segmentation method for COVID-19 Computed Tomography (CT) images. The proposed image segmentation method depends on improving the density peaks clustering (DPC) using generalized extreme value (GEV) distribution. The DPC is faster than other clustering methods, and it provides more stable results. However, it is difficult to determine the optimal number of clustering centers automatically without visualization. So, GEV is used to determine the suitable threshold value to find the optimal number of clustering centers that lead to improving the segmentation process. The proposed model is applied for a set of twelve COVID-19 CT images. Also, it was compared with traditional k-means and DPC algorithms, and it has better performance using several measures, such as PSNR, SSIM, and Entropy.
Background:
With the outbreak of COVID-19, large-scale telemedicine applications can play an important role in the epidemic areas or less developed areas. However, the transmission of hundreds of megabytes of Sectional Medical Images (SMIs) from hospital's Intranet to the Internet has the problems of efficiency, cost, and security. This article proposes a novel lightweight sharing scheme for permitting Internet users to quickly and safely access the SMIs from a hospital using an Internet computer anywhere but without relying on a virtual private network or another complex deployment.
Methods:
A four-level endpoint network penetration scheme based on the existing hospital network facilities and information security rules was proposed to realize the secure and lightweight sharing of SMIs over the Internet. A "Master-Slave" interaction to the interactive characteristics of multiplanar reconstruction and maximum/minimum/average intensity projection was designed to enhance the user experience. Finally, a prototype system was established.
Results:
When accessing SMIs with a data size ranging from 251.6 to 307.04 MB with 200 kBps client bandwidth (extreme test), the network response time to each interactive request remained at approximately 1 s, the original SMIs were kept in the hospital, and the deployment did not require a complex process; the imaging quality and interactive experience were recognized by radiologists.
Conclusions:
This solution could serve Internet medicine at a low cost and may promote the diversified development of mobile medical technology. Under the current COVID-19 epidemic situation, we expect that it could play a low-cost and high-efficiency role in remote emergency support.
Background:
A cardiotocogram (CTG) is a device used to perceive the status of a fetus in utero in real time. There are a few reports of its use at home or during emergency transport.
Objective:
The aim of this study was to test whether CTG and other perinatal information can be transmitted accurately using an experimental station with a 5G transmission system.
Methods:
In the research institute, real-time fetal heart rate waveform data from the CTG device, high-definition video ultrasound images of the fetus, and high-definition video taken with a video camera on a single line were transmitted by 5G radio waves from the transmitting station to the receiving station.
Results:
All data were proven to be transmitted with a minimum delay of less than 1 second. The CTG waveform image quality was not inferior, and there was no interruption in transmission. Images of the transmitted ultrasound examination and video movie were fine and smooth.
Conclusions:
CTG and other information about the fetuses and pregnant women were successfully transmitted by a 5G system. This finding will lead to prompt and accurate medical treatment and improve the prognosis of newborns.
Unstructured:
Disasters and pandemics pose unique challenges to health care delivery. As healthcare systems are set to be further stretched with the increasing burden of COVID-19, telemedicine, including tele-education may be effective way to rationally allocate medical resources. During the COVID-19 pandemic, practice showed that telemedicine was a feasible, effective way with good acceptability in western China, translating in significant improvement in professional coverage in this underserviced area. The successes of telemedicine in western China may provide a useful reference for other parts of the world.
Objective:
The purpose of this study was to determine the efficacy and feasibility of 5th generation wireless systems (5G) telerobotic spinal surgery in our first 12 cases.
Methods:
A total of 12 patients (5 males, 7 females; age, 23-71 years) with spinal disorders (4 thoracolumbar fractures, 6 lumbar spondylolisthesis, 2 lumbar stenosis) were treated with 5G telerobotic spinal surgery. Sixty-two pedicle screws were implanted.
Results:
All patients had substantial relief from their symptoms. Screw placements were classified using Gertzbein-Robbins criteria. There were 59 grade A, 3 grade B. Mean operation time was 142.5 ± 46.7 minutes. Mean guiding wire insertion time was 41.3 ± 9.8 minutes. The deviation between the planned and actual positions was 0.76 ± 0.49 mm. No intraoperative adverse event was found.
Conclusion:
5G remote robot-assisted spinal surgery is accurate and reliable. We conclude that 5G telerobotic spinal surgery is both efficacious and feasible for the management of spinal diseases with safety.
Purpose
The aim of the current narrative review was to summarize the available evidence in the literature on artificial intelligence (AI) methods that have been applied during robotic surgery.
Methods
A narrative review of the literature was performed on MEDLINE/Pubmed and Scopus database on the topics of artificial intelligence, autonomous surgery, machine learning, robotic surgery, and surgical navigation, focusing on articles published between January 2015 and June 2019. All available evidences were analyzed and summarized herein after an interactive peer-review process of the panel.
Literature review
The preliminary results of the implementation of AI in clinical setting are encouraging. By providing a readout of the full telemetry and a sophisticated viewing console, robot-assisted surgery can be used to study and refine the application of AI in surgical practice. Machine learning approaches strengthen the feedback regarding surgical skills acquisition, efficiency of the surgical process, surgical guidance and prediction of postoperative outcomes. Tension-sensors on the robotic arms and the integration of augmented reality methods can help enhance the surgical experience and monitor organ movements.
Conclusions
The use of AI in robotic surgery is expected to have a significant impact on future surgical training as well as enhance the surgical experience during a procedure. Both aim to realize precision surgery and thus to increase the quality of the surgical care. Implementation of AI in master–slave robotic surgery may allow for the careful, step-by-step consideration of autonomous robotic surgery.
The rapidly increasing interest from various verticals for the upcoming 5th generation (5G) networks expect the network to support higher data rates and have an improved quality of service. This demand has been met so far by employing sophisticated transmission techniques including massive Multiple Input Multiple Output (MIMO), millimeter wave (mmWave) bands as well as bringing the computational power closer to the users via advanced baseband processing units at the base stations. Future evolution of the networks has also been assumed to open many new business horizons for the operators and the need of not only a resource efficient but also an energy efficient ecosystem has greatly been felt. The deployment of small cells has been envisioned as a promising answer for handling the massive heterogeneous traffic, but the adverse economic and environmental impacts cannot be neglected. Given that 10% of the world’s energy consumption is due to the Information and Communications Technology (ICT) industry, energy-efficiency has thus become one of the key performance indicators (KPI). Various avenues of optimization, game theory and machine learning have been investigated for enhancing power allocation for downlink and uplink channels, as well as other energy consumption/saving approaches. This paper surveys the recent works that address energy efficiency of the radio access as well as the core of wireless networks, and outlines related challenges and open issues.
In dense indoor areas, high numbers of people use their smartphones and tablets to share or download pictures, videos, or data. The heterogeneous network (HetNet) solves the problems caused by the explosion of data generated by smartphones and tablets. Heterogeneous networks use a mix of Relay, Femtocell, Pico, and Macro base stations to improve spectral efficiency per unit area. Operators wish to know how to upgrade existing networks and how to design new ones. This subject has become hot in the industry. In this paper, we presented the architecture of heterogeneous networks. The parameters affecting the heterogeneous networks topology plan are discussed. Moreover, a comparison of existing solutions that consider the problems of base station layout planning is presented. Finally, a road map is given to point out to the main future directions of researches on the topological design of dense area heterogeneous mobile networks.
The fast and accurate segmentation of lung nodule image sequences is the basis of subsequent processing and diagnostic analyses. However, previous research investigating nodule segmentation algorithms cannot entirely segment cavitary nodules, and the segmentation of juxta-vascular nodules is inaccurate and inefficient. To solve these problems, we propose a new method for the segmentation of lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise (DBSCAN). First, our method uses three-dimensional computed tomography image features of the average intensity projection combined with multi-scale dot enhancement for preprocessing. Hexagonal clustering and morphological optimized sequential linear iterative clustering (HMSLIC) for sequence image oversegmentation is then proposed to obtain superpixel blocks. The adaptive weight coefficient is then constructed to calculate the distance required between superpixels to achieve precise lung nodules positioning and to obtain the subsequent clustering starting block. Moreover, by fitting the distance and detecting the change in slope, an accurate clustering threshold is obtained. Thereafter, a fast DBSCAN superpixel sequence clustering algorithm, which is optimized by the strategy of only clustering the lung nodules and adaptive threshold, is then used to obtain lung nodule mask sequences. Finally, the lung nodule image sequences are obtained. The experimental results show that our method rapidly, completely and accurately segments various types of lung nodule image sequences.
The rapidly increasing number of mobile devices, voluminous data, and higher data rate are pushing to rethink the current generation of the cellular mobile communication. The next or fifth generation (5G) cellular networks are expected to meet high-end requirements. The 5G networks are broadly characterized by three unique features: ubiquitous connectivity, extremely low latency, and very high-speed data transfer. The 5G networks would provide novel architectures and technologies beyond state-of-the-art architectures and technologies. In this paper, our intent is to find an answer to the question: " what will be done by 5G and how? " We investigate and discuss serious limitations of the fourth generation (4G) cellular networks and corresponding new features of 5G networks. We identify challenges in 5G networks, new technologies for 5G networks, and present a comparative study of the proposed architectures that can be categorized on the basis of energy-efficiency, network hierarchy, and network types. Interestingly, the implementation issues, e.g., interference, QoS, handoff, security-privacy, channel access, and load balancing, hugely effect the realization of 5G networks. Furthermore, our illustrations highlight the feasibility of these models through an evaluation of existing real-experiments and testbeds.
Robotic surgical systems have greatly contributed to the advancement of minimally invasive endoscopic surgery. However, current robotic systems do not provide tactile or haptic feedback to the operating surgeon. Under certain circumstances, particularly with the manipulation of delicate tissues and suture materials, this may prove to be a significant irritation. We hypothesize that haptic feedback, in the form of sensory substitution, facilitates the performance of surgical knot tying. This preliminary study describes evidence that visual sensory substitution permits the surgeon to apply more consistent, precise, and greater tensions to fine suture materials without breakage during robot-assisted knot tying.
The demand for telesurgery is rising rapidly, but robust evidence regarding the feasibility of its application in urology is still rare. From March to October 2021, a surgeon-controlled surgical robot in a tertiary hospital in Qingdao was used to remotely conduct robot-assisted laparoscopic radical nephrectomy (RN) in 29 patients located in eight primary hospitals. The median round-trip delay was 26 ms (interquartile range [IQR] 5) and the median distance between the primary hospital and the surgeon was 187 km (IQR 57). Both the master unit and the slave unit were guaranteed by network and mechanical engineers, and surgical assistants were well prepared on the patient side to prevent complications. The primary evaluation metric was the success rate, defined as the percentage of patients who underwent successful remote RN without conversion to other surgical procedures and no major intraoperative or postoperative complications. The results demonstrate that the combination of 5G technology and surgical robots is a novel potential telemedicine-based therapy choice for renal tumors.
Patient summary
Our study shows that telesurgery using 5G technology is a safe and feasible treatment option for patients with kidney tumors. The total delay between the remote location and the operating rooms where surgery was being performed was just 200 ms. This approach could reduce health care costs and improve the quality of medical services accessed by patients.
The converged transmission-assisted network communication architecture used in this study could meet the requirements of telesurgery, and effectively guarantee the security and immediacy of communication. With the security, flexibility, and universality of the network converged transmission, the clinical practical application of telesurgery and telemedicine would step up to a higher level.
Objectives
Telemedicine allows for the remote delivery of patient care and has been found to have a wide range of uses in otolaryngology. In order to achieve best practices in telemedicine, a platform must be effective and both patients and providers must be satisfied with the use of technology. As telemedicine becomes more widely used in otolaryngology clinics, particularly in the face of the current COVID-19 pandemic, it is important to assess its applicability in this field. The goal of this study was to evaluate existing literature on telemedicine and assess overall image quality, diagnostic concordance, and patient and provider satisfaction with telemedicine technologies.
Methods
A systematic review was conducted on PubMed and MEDLINE according to the PRISMA 2009 guidelines for articles from 1982 to 2019 relating to telemedicine in otolaryngology. English language studies with primary or secondary endpoints pertaining to image quality, diagnostic concordance, or patient or provider satisfaction were included. Descriptive studies, editorials, and literature reviews were excluded.
Results
A total of 32 studies were included in our review. Studies assessing imaging quality and diagnostic concordance reported adequate results but with some heterogeneity. Patient and provider satisfaction were consistently high.
Conclusions
The literature supports telemedicine delivery of otorhinolaryngologic care as having achieved high rates of patient and provider satisfaction with adequate image quality and heterogeneity in diagnostic concordance. Variability in diagnostic accuracy was reported, but appears improved given proper clinical context. More standardized studies are needed specific to telemedicine in the field of otolaryngology.
Study design:
A meta-analysis OBJECTIVE.: To investigate whether robot-assisted techniques are superior to conventional techniques in terms of the accuracy of pedicle screw placement and clinical indexes.
Summary of background data:
Robot-assisted techniques are increasingly applied to spine surgery to reduce the rate of screw misplacement. However, controversy about the superiority of robot-assisted techniques over conventional freehand techniques remains.
Methods:
We conducted a comprehensive search of PubMed, EMBASE, and Cochrane Library for potentially eligible articles. The outcomes were evaluated in terms of risk ratio (RR) or standardized mean difference (SMD) and the associated 95% confidence intervals (CIs). Meta-analysis was performed using the RevMan 5.3 software and subgroup analyses were performed based on the robot type for the accuracy of pedicle screw placement.
Results:
Nine randomized controlled trials with 696 patients were included in this meta-analysis. The results demonstrated that the robot-assisted technique was more accurate in pedicle screw placement than the freehand technique. Subgroup analyses showed that the TINAVI robot-assisted technique was more accurate in screw positions Grade A (RR, 1.10; 95% CI, 1.06-1.14), Grade B (RR, 0.46; 95% CI, 0.28-0.75), and Grades C + D + E (RR, 0.21; 95% CI, 0.09-0.45) than the freehand technique, whereas the Renaissance robot-assisted technique showed the same accuracy as the freehand technique in screw positions Grade A, Grade B, and Grades C + D + E. Furthermore, the robot-assisted techniques showed equivalent postoperative stay, visual analogue scale scores, and Oswestry disability index scores to those of the freehand technique and shorter intraoperative radiation exposure time, fewer radiation dose and proximal facet violations but longer surgical time than the freehand technique.
Conclusion:
The robot-assisted technique is more accurate in pedicle screw placement than the freehand technique. And TINAVI robot-assisted pedicle screw placement is a more accurate alternative to conventional techniques and the Renaissance robot-assisted procedure.
Level of evidence:
1.
A physician-staffed helicopter emergency medical service called a doctor helicopter (DH) in Eastern Shizuoka was equipped with a smartphone video transmission system in April 2018. We herein report on the introduction of this system for the verification of transfusion in the DH. A 51-year-old man visited a local hospital after cutting his left neck himself. He was diagnosed with jugular vein injury and underwent compressive hemostasis. As he entered profound hemorrhagic shock, he underwent tracheal intubation, massive fluid resuscitation, and administration of 3 vasopressor agents to maintain circulation. The Eastern Shizuoka DH was requested to transport this patient. After making contact with the patient, the staff of the DH started prehospital transfusion. Because this was the first case of transfusion in a prehospital setting for our hospital, we held a meeting in which we used a smartphone video transmission system to verify the condition surrounding the transfusion in the DH. By reviewing the video record, we confirmed that the transfusion was performed safely and correctly in the prehospital setting. This smartphone video transmission system was useful for verifying the activity of the staff in the DH.
The existing 4G networks have been widely used in the Internet of Things (IoT) and is continuously evolving to match the needs of the future Internet of Things (IoT) applications. The 5G networks are expected to massive expand today’s IoT that can boost cellular operationgs, IoT security, and network challenges and driving the Internet future to the edge. The existing IoT solutions are facing a number of challenges such as large number of conneciton of nodes, security, and new standards. This paper reviews the current research state-of-the-art of 5G IoT, key enabling technologies, and main research trends and challenges in 5G IoT.
The deluge of huge data demanding applications has imposed a challenge for next generation cellular system to support high data rate with reduced energy consumption besides ensuring good quality of service. Massive MIMO and small cells are the foremost technologies to address such challenges. Massive MIMO technique refers to deploying a very large number of antennas at the base station, and thus, improving energy efficiency and spectral efficiency of wireless networks. Small cell provides high data rate and good coverage with reduced transmit power by decreasing the distance between base station and user. This paper surveys state of the art of massive MIMO technique with small cell network. First, we discuss fundamental background for massive MIMO. Then, performance metrics and modeling tools for system analysis are studied. Next, details of enabling technologies to massive MIMO small cell network are stated in the paper. Finally, the paper highlights future challenges and research problems.
Fundamentals of Surgical Simulation explains in detail, from a behavioural science/human factors perspective, why modern image guided medicine such as surgery, interventional cardiology and interventional radiology are difficult to learn and practice. Medicine is currently at a tipping point in terms of how physicians in procedural based medicine are trained. Fundamentals of Surgical Simulation helps drive this change and is a valuable resource for medical trainers and trainees alike. For trainers, this book gives explicit theoretical and applied information on how this new training paradigm works thus allowing them to tailor the application of simulation training to their program, no matter where in the world they work. For the trainee, it allows them to see and understand the rules of this new training paradigm thus allowing them to optimize their approach to training and reaching proficiency in as efficient a manner as possible. For the simulation researcher, engineer and medical profession Fundamentals of Surgical Simulation poses some difficult questions that require urgent unambiguous and agreed answers.
5G bytes: Small cells explained
IEEE SPECTRUM
379-380
A Nordrum
K Clark
Nordrum, A. and K. Clark, 5G bytes: Small cells explained. IEEE Spectrum:
413(6854): p. 379-380.