Monitoring Devices Research Articles

Improving Accessibility and Delivery of Healthcare Services to Underserved Children through Technology: A Comprehensive Approach of Literature Review

This study investigates the use of technology to improve healthcare accessibility and delivery for children in underprivileged communities through article review comprehensively. A literature review with qualitative method that involved four distinct steps. In the initial stage, the search was conducted using Google Scholar (GS) and Scopus website. The second stage was filtering, which entails selecting the journals that will be examined. The last stage was analysis the articles, this analysis uses a 4-step PRISMA process to identify 123 articles published from 2019 to 2024 in Scopus journal. The review was evaluated the efficacy of telemedicine, mobile health applications, and wearable devices in monitoring and addressing children's health, while considering genetic predispositions and underlying medical issues that influence growth patterns. The research emphasizes the importance of a comprehensive strategy in evaluating child growth and development, utilizing health data to tailor interventions. Online systems, such as mobile phones and PDAs, can support healthcare workers in underserved rural areas. The integration of technology is essential for addressing unique challenges in underserved areas and ensuring access to high-quality healthcare services for all children. Current monitoring methods include regular check-ups, growth charts, and developmental screenings, with advancements in technology providing new tools like mobile health apps and wearable devices. Involving various stakeholders in the evaluation process is crucial, with participatory research focusing on community empowerment, ownership, and capacity building. Online systems offer efficient and accessible ways to track health data but may come with privacy concerns and data breach risks. The study focuses on the effectiveness of online systems for monitoring child health indicators, discussing data collection methods, sampling strategies, and ethical considerations. Findings reveal the need to address areas such as limited social interaction and incorporate interactive activities and group projects into online curriculum. Understanding the impact of online learning on students' health and well-being is crucial for tailoring approaches to ensure comprehensive support. The research findings have significant implications for child health policy and practice, emphasizing the importance of social connection and mental well-being in online learning environments.

In-Motion, Non-Contact Detection of Ties and Ballasts on Railroad Tracks

This study aims to develop a robust and efficient system to identify ties and ballasts in motion using a variety of non-contact sensors mounted on a robotic rail cart. The sensors include distance LiDAR sensors and inductive proximity sensors for ferrous materials to collect data while traversing railroad tracks. Many existing tie/ballast health monitoring devices cannot be mounted on Hyrail vehicles for in-motion inspection due to their inability to filter out unwanted targets (i.e., ties or ballasts). The system studied here addresses that limitation by exploring several approaches based on distance LiDAR sensors. The first approach is based on calculating the running standard deviation of the measured distance from LiDAR sensors to tie or ballast surfaces. The second approach uses machine learning (ML) methods that combine two primary algorithms (Logistic Regression and Decision Tree) and three preprocessing methods (six models in total). The results indicate that the optimal configuration for non-contact, in-motion differentiation of ties and ballasts is integrating two distance LiDAR sensors with a Decision Tree model. This configuration provides rapid, accurate, and robust tie/ballast differentiation. The study also facilitates further sensor and inspection research and development in railroad track maintenance.

Modified extended Rauch–Tung–Striebel smoother method for the dynamic external excitation identification of piezoelectric vibration energy harvesting systems

A vibration energy harvester can collect vibration energy from the environment to supply low-power devices, such as wireless sensor nodes. Reducing the size and power consumption of these devices is a challenging problem. A dual-function device, which includes energy harvesting and vibration measurement, may solve this problem. Therefore, studying inversion methods for identifying the external excitation of a harvester is meaningful. In this study, a modified inversion method that combines an extended Rauch–Tung–Striebel smoother (ERTSS) with the particle swarm optimization (PSO) algorithm, i.e., the ERTSS-PSO method, is proposed to identify the time domain signal of external excitation through the voltage response of a piezoelectric vibration energy harvester. A modified ERTSS approach with sliding windows is developed. The sliding windows are partially overlapped to eliminate identification errors between the two contiguous windows. Near real-time identification is achieved for the small sliding window. PSO is utilized to estimate state noise covariance and measurement noise covariance, improving identification accuracy compared with the L-curve approach. Under this proposed framework, prior knowledge regarding the statistical data of unknown external excitations is unnecessary, enabling a more comprehensive range of applications. To assess the performance of the proposed ERTSS-PSO method, numerical simulations, including two piezoelectric vibration energy harvesting systems with third-order and fifth-order nonlinear stiffness, are conducted to verify the effectiveness of the proposed method under harmonic, multifrequency, and random excitations. The method proposed in this study is also validated by a circular laminated piezoelectric plate harvester under harmonic and random excitations in an experiment. Results from the experimental studies demonstrate that the proposed method improves identification accuracy by at least 9% compared with the extended Kalman filter, at least 7% compared with the augmented Kalman filter (AKF) with Rauch–Tung–Striebel smoother (ARTSS), and at least 40% compared with AKF under random excitation. In addition, the proposed method is unaffected by initial conditions, and it is more stable and accurate than AKF and ARTSS. The proposed method lays the theoretical foundation for identifying the external excitation of a harvester. It is also a possible solution for the miniaturization and compactness of wireless monitoring devices.

Perceptions of Behaviour Change Interventions for Physical Activity in People with Chronic Obstructive Pulmonary Disease: A Survey

Abstract Background Physical inactivity in chronic obstructive pulmonary disease (COPD) is common and behaviour change interventions could help improve physical activity (PA). This survey aimed to explore perceptions of behaviour change interventions for physical activity in people with COPD. Methods An anonymous cross-sectional electronic and paper survey was distributed among people with COPD in the Republic of Ireland (n=150) via relevant gatekeepers. Descriptive statistics, means, medians, percentages and frequencies, were used to summarise and describe the findings. Chi- squared t-tests (where P was set at 0.05) were used to investigate relationships between variables. Results Responses were received from n=113 people with COPD (75.33% response rate, 113/150) and most respondents (83.03%, n= 93/112) were aged over 61 years. 90.53% (n=86/95) of respondents agreed/strongly agreed that PA helps them to manage their COPD. There was a strong statistically significant relationship between those who wear PA monitoring devices and those who believe that being physically active can help them to manage their lung disease (p<0.001), however, in this survey, the use of PA monitors in those over 61 years was proportionally lower (21.11%, n=19/90) than those under 60 years (61.53%, n= 8/13). Respondents perceived social support as the most effective behaviour change intervention to influence PA behaviour (67.62%, n= 71/105), with counselling for PA perceived to be the least effective (13.33%, n=14/105). Conclusion People with COPD perceived that social support can influence their PA behaviour. The spontaneous use of PA monitoring devices was lower in older respondents than in younger respondents, however a strong relationship between using monitoring devices and perceived benefits of PA on COPD may exist overall.

A novel and facile oxygen-activated time-temperature indicator with wide temperature monitoring range and good stability based on the laccase-like nanozyme

BackgroundTime-Temperature Indicator (TTI) is an indicator device for real-time monitoring of the thermal history of the product. Due to the enzymatic reactions are affected by both time and temperature, enzymatic TTIs have been extensively studied and developed in recent years. However, enzymatic TTIs contain biologically active molecules (enzymes), which require high storage and use conditions. Most of them are designed to mix the system species together and irreversible reaction is undertaken. Nanozymes are the synthetic nanomaterials with similar biocatalytic functions as natural enzymes, which have extensive applications in analytical chemistry, biosensing, and environmental protection due to their facile synthesis, low cost, high stability and durability. ResultsThis work proposed to replace the natural laccase to laccase-like nanozyme, designed a novel and facile O2-activated time-temperature indicator for the first time. Nanozyme had excellent thermal and storage stability, which could maintain fabulous catalytic activity in the wide temperature range of 10–80 °C and after a long-term storage. Based on the O2 was required to participate in the oxidation of laccase-catalyzed substrates, a squeeze-type O2-activated TTI was designed by controlling O2 in the TTI system. The TTI was activated through extruding the O2-coated airbag ruptured and producing an irreversible color reaction. Combined with a smartphone to extract the chromaticity for portable visual real-time monitoring. Five sets of TTIs were prepared based on the concentration of nanozyme, and the activation energies (Ea) ranging from 28.45 to 72.85 kJ mol−1, which were able to be fitted to products with Ea ranging from 3.45 to 97.8 kJ mol−1 and the monitoring-time of less than 7 days. SignificanceCompared to the traditional enzymatic TTI, the TTIs designed based on nanozyme has the advantages of controlled activation, wider temperature monitor range and good stability. Providing a new approach to the development of real-time monitoring of smart devices.

Cerebral Microcirculation: Progress and Outlook of Laser Doppler Flowmetry in Neurosurgery and Neurointensive Care.

Laser Doppler flowmetry (LDF) is a well-established technique for the investigation of tissue microcirculation. Compared to skin, the use in the human brain is sparse. The measurement of cerebral microcirculation in neurointensive care and during neurosurgery is challenging and requires adaptation to the respective clinical setting. The aim of the review is to present state of the art and progress in neurosurgery and neurointensive care where LDF has proven useful and can find clinical importance in the investigation of cerebral microcirculation. The literature in the field is summarized and recent technical improvements regarding LDF systems and fiber optical probe designs for neurosurgical and neurocritical care described. By combining two signals from the LDF unit, the measurement of the microcirculation (Perfusion) and gray whiteness (TLI) of the brain tissue, the full potential of the device is achieved. For example, a forward-looking LDF-probe detects high-risk hemorrhage areas and gray-white matter boundaries along intraoperative trajectories during stereotactic neurosurgery. Proof of principles are given for LDF as a guidance tool in deep brain stimulation implantation, brain tumor needle biopsies, and as long-term monitoring device in neurocritical care. With well-designed fiber optical probes, surgical fixation, and signal processing for movement reduction, LDF monitoring of the cerebral microcirculation is successful up to 10 days. The use of LDF can be combined with other physiological measurement techniques, for example, fluorescence spectroscopy for identification of glioblastoma during tumor surgery. Fiber optics can also be used during magnetic resonance imaging (MRI). Despite the many advantages, fiber optical LDF has not yet reached its full potential in clinical neuro-applications. Multicenter studies are required to further evaluate LDF in neurosurgery and neurointensive care. In conclusion, the present status of LDF in neurosurgery and neurointensive care has been reviewed. By combining Perfusion and TLI with tailored probe designs the full potential of LDF can be achived in measuring cerebral microcirculation. This includes guidance during DBS implantation and needle biopsies, and long-term monitoring in neurocritical care.

Fiber Bragg Grating Pulse and Systolic Blood Pressure Measurement System Based on Mach-Zehnder Interferometer.

A fiber Bragg grating (FBG) pulse and systolic blood pressure (SBP) measurement system based on the edge-filtering method is proposed. The edge filter is the Mach-Zehnder interferometer (MZI) fabricated by two fiber couplers with a linear slope of 52.45 dBm/nm. The developed system consists of a broadband light source, an edge filter, fiber Bragg gratings (FBGs), a coarse wavelength-division multiplexer (CWDM), and signal-processing circuits based on a field-programmable gate array (FPGA). It can simultaneously measure pulse pulsations of the radial artery in the wrist at three positions: Cun, Guan and Chi. The SBP can be calculated based on the pulse transit time (PTT) principle. The measurement results compared to a standard blood pressure monitor showed the mean absolute error (MAE) and standard deviation (STD) of the SBP were 0.93 ± 3.13 mmHg. The system meets the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) equipment standards. The proposed system can achieve continuous real-time measurement of pulse and SBP and has the advantages of fast detection speed, stable performance, and no compression sensation for subjects. The system has important application value in the fields of human health monitoring and medical device development.

Sensitivity Approach for Blood Glucose Impedance Data Using the Geselowitz Theorem

The article presents a preclinical study focused on developing a non-invasive blood glucose monitoring device. Current glucose monitoring methods, such as capillary or venous tests, are inconvenient for frequent use, making continuous monitoring challenging. This study explores the BGP (Bruna Gabriela Pedro) model, which links electrical impedance to blood glucose levels, as a potential alternative. Using the Geselowitz Theorem and impedance spectroscopy in a 4-electrode configuration, the study investigates the relationship between blood conductivity and glucose concentration. Impedance spectra were recorded for five human blood samples with glucose concentrations between 106 and 188 mg/dL. These samples were housed in an insulating container with four stainless steel electrodes. Conductivity was calculated using the Geselowitz Theorem at 1.0, 3.9, and 24.9 kHz. A finite element model built in COMSOL was employed to assess electrode sensitivity, which had a maximum regression error of 3.75 %. The results demonstrated a sigmoid relationship between blood glucose concentration and conductivity, with impedance decreasing non-linearly as glucose levels increased. Sensitivity diminished for glucose concentrations exceeding 188 mg/dL. An increase of 82 mg/dL in glucose concentration led to conductivity changes of 1.14, 2.82, and 5.14 S/m at frequencies of 1.0, 3.9, and 24.9 kHz, respectively. The findings suggest that the BGP analytical model could be refined through the inclusion of additional data on glucose's impact on electrical impedance. These improvements could support the development of non-invasive glucose meters. The research holds significant clinical potential for the creation of a simple, cost-effective glucose monitoring device. Continuous glucose monitoring could enhance diagnostic accuracy and support better therapeutic decision-making, particularly in emergency care. The affordability and accessibility of such a device may benefit a broad patient base.

Three-dimensional interconnected nanofiber network derived from bacterial cellulose for strain sensing and energy harvesting

Flexible strain sensors have garnered widespread attention due to their potential applications, including human health monitoring, human-machine interfaces and intelligent robotics. However, the tradeoff between sensitivity and detection range needs to be considered. Herein, a dual-functional film based on bacterial cellulose is fabricated with a cost-effective freeze-drying and carbonization process, which is used for strain sensing and energy harvesting. The effect of the carbonization temperature on the structure is explored. Taking advantage of three-dimensional interconnected nanofiber of carbonized bacterial cellulose (CBC) network and the stretchability of the Ecoflex substrate, the optimized sensor demonstrates impressive strain sensing capabilities, featuring exceptional sensitivity (gauge factor = 100), large tolerable strain (100 %), swift response time (70 ms), and robust durability (3000 cycles). These features endow the CBC strain sensor with the capability to effectively discern and monitor multiple complex human activities, such as pulse rate and various human movements. Moreover, the CBC structure can serve as triboelectric nanogenerator (TENG) for energy harvesting. This work provides a green, efficient and cost-effective manufacturing method for the development of multifaceted wearable devices for human health monitoring and portable energy sources.

Nutrition Management in Children Less than 5 Years of Age with Glycogen Storage Disease Type I: Survey Results.

Background: Nutrition management for GSD Type I (GSDI; OMIM #232200, 232220) is complex, with the goal being to maintain euglycemia while minimizing metabolic derangements. Management guidelines were published in 2002 and 2014. However, there is limited information on the nuances of nutrition management and the unique feeding challenges of children. Methods: A REDCap survey focusing on staffing and current practices in the nutrition management of children with GSD I who were <5 years of age was sent to the metabolic dietitian's listserv and GMDI membership in 8/2023. Results: There were 21 North American respondents. In 17/21 clinics (81%), Prosobee® was the primary choice for infant formula. Dietitians used different methods to determine hourly glucose needs. Fasting recommendations ranged from 1 to 3 h, and the use of nighttime continuous feeding was common. Cornstarch was started between 6 and 12 months of age. Most clinics did not use Glycosade® for children <5 years of age. Oral motor dysfunction, gagging, and lack of interest in food were common. Continuous glucose monitoring (CGM) devices were recommended in 20 clinics (95%). Most clinics followed patients on an outpatient basis. All clinics provided a hypoglycemia management plan; however, there was wide variability in practice. Conclusion: This survey highlights the variability in the care of individuals <5 years of age with GSD I. Updated guidelines are needed to help address the unique nutrition challenges in this age group.

Applied experimental research on in-situ online monitoring instrument for soil radon in fault zone

As an emerging method for seismic precursory signals in underground fluid, the reliability and stability of in-situ online monitoring devices for soil radon are crucial performance indicators that are directly related to the successful implementation of continuous monitoring of soil radon in seismic areas. This study conducted laboratory testing and field applications of a new in-situ online monitoring instrument for seismic soil radon, utilizing the experimental testing conditions provided by the radon monitoring instrument detection platform of the China Earthquake Administration and the natural experimental site at Xianshuihe Fault Zone in the China Seismic Experimental Site. The results indicate that laboratory measurement repeatability of the instrument is 5.53%, the relative intrinsic error of radon volume response activity is 1.53%, and the response capability of hourly sampling at high radon volume response activity (greater than 1.0 × 105 Bq/m3) lags behind the standard instrument by 2 h, essentially meeting the requirements for seismic observation. Under field conditions, the instruments exhibit good synchronization in response at different depths at the same location. However, further improvements are needed to enhance the consistency of long-term operation in the field, as well as the adaptability to outdoor self-powering, data transmission, and environmental conditions.

Phytic acid-based super antifreeze multifunctional conductive hydrogel for human motion monitoring and energy harvesting devices

Conductive hydrogels have broad application prospects in the field of self-powered sensors and energy harvesting devices due to their good electrical conductivity and flexibility. However, at low temperatures, conductive hydrogels are usually frozen, resulting in problems such as poor electrical conductivity and flexibility, which seriously hinder the application of these fields. To address these challenges, phytic acid (PA) was employed as the crosslinker and antifreezing agent in this study. Polyvinyl alcohol (PVA), 2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS), chitosan (CS), and PA were used as raw materials to successfully synthesize PVA/AMPS/CS/PA (PACP) multifunctional conductive hydrogels with outstanding antifreeze and water retention properties (freezing point below −80 °C, 30-day water loss rate of 3.5%). In addition, PACP hydrogels exhibit exceptional electrical conductivity of up to 9.4 S/m, along with antibacterial and biocompatible properties, enabling their utilization as wearable sensors on human skin tissue. Notably, the PACP hydrogel-based triboelectric nanogenerator (PACP-TENG) excels in accurately monitoring human motion and powering small electronic devices, facilitating remote control of small light switches. The resulting open circuit voltage is as high as 314 V at 25 °C and about 110 V at low temperature. Therefore, PACP hydrogels with excellent properties are expected to expand their applications in these fields.

INTEGRATION OF TELEGRAM BOT AND UPTIME KUMA FOR WI-FI NETWORK MONITORING USING MIKROTIK

Wi-Fi network monitoring is a crucial aspect in ensuring the availability and security of widely used internet services. This research confirms the use of Telegram bots for notification integration with the Uptime-Kuma monitoring program and proxy devices for Wi-Fi network monitoring. The main router and network controller in this study were Mikrotik devices, while Uptime Kuma was used as a monitoring tool to track the performance and availability of the Wi-Fi network. When important events are discovered on the network, network administrators can receive quick notifications through integration with Telegram bots. In the context of Wi-Fi networks, the Security Policy Development Life Cycle (SPDLC) method is used to design relevant and effective security policies. It includes the stages of planning, implementation, monitoring, evaluation and regular updating of security policies to maintain optimal levels of security. The results show that the integration of Telegram bots with the Kuma Uptime monitoring tool can improve network availability. This allows quick reaction to Uptime and Downtime reports in network conditions, which record the percentage of time network services are available. Thus, administrators do not need to wait for complaints from users if the connection is suddenly lost, because changes in connection status will automatically send a notification to Telegram.

Signal Quality in Continuous Transcutaneous Bilirubinometry.

Bilirubin is a product of the metabolism of hemoglobin from red blood cells. Higher levels of bilirubin are a sign that either there is an unusual breaking down rate of red blood cells or the liver is not able to eliminate bilirubin, through bile, into the gastrointestinal tract. For adults, bilirubin is occasionally monitored through urine or invasive blood sampling, whilst all newborns are routinely monitored visually, or non-invasively with transcutaneous measurements (TcBs), due to their biological immaturity to conjugate bilirubin. Neonatal jaundice is a common condition, with higher levels of unconjugated bilirubin concentration having neurotoxic effects. Actual devices used in TcBs are focused on newborn populations, are hand-held, and, in some cases, operate in only two wavelengths, which does not necessarily guarantee reliable results over all skin tones. The same occurs with visual inspections. Based on that, a continuous bilirubin monitoring device for newborns is being developed to overcome visual inspection errors and to reduce invasive procedures. This device, operating optically with a mini-spectrometer in the visible range, is susceptible to patient movements and, consequently, to situations with a lower signal quality for reliable bilirubin concentration estimates on different types of skin. Therefore, as an intermediate development step and, based on skin spectra measurements from adults, this work addresses the device's placement status prediction as a signal quality indication index. This was implemented by using machine learning (ML), with the best performances being achieved by support vector machine (SVM) models, based on the spectra acquired on the arm and forehead areas.

Oncology Clinicians' Perspectives of a Remote Patient Monitoring Program: A Multi-Modal Case Study Approach.

Remote patient monitoring (RPM) aims to improve patient access to care and communication with clinical providers. Overall, understanding the usability of RPM applications and their influence on clinical care workflows is limited from the perspectives of clinician end users at a cancer center in the Northeast, United States. Explore the usability and functionality of RPM and elicit the perceptions and experiences of oncology clinicians using RPM for oncology patients after hospital discharge. The sample included 30 of 98 clinicians (31% response rate) managing at least five patients in the RPM program and responding to the m-Health Usability between March 2021- October 2021. Overall, clinicians responded positively to the survey. Item responses with the highest proportion of disagreement were explored further. A nested sample of five clinicians who responded to the study survey (30% response rate) participated in interview sessions conducted from November 2021 to February 2022, and averaged 60 minutes each. Survey responses highlighted that RPM was easy to use and learn and verified symptom alerts during follow-up phone calls. Areas to improve identified practice changes from reporting RPM alerts through digital portals and its influence on clinicians' workload burden. Interview sessions revealed three main themes: clinician understanding and usability constraints, patient constraints, and suggestions for improving the program. Subthemes for each theme were explored, characterizing technical and functional limitations that could be addressed to enhance efficiency, workflow, and user experience. Clinicians support the value of RPM for improving symptom management and engaging with providers. Functional changes to enhance the program's utility, such as input from patients about temporal changes in their symptoms and technical resources for home monitoring devices.

Artificial intelligence based real-time prediction of imminent heart failure hospitalisation in patients undergoing non-invasive telemedicine.

Remote patient management may improve prognosis in heart failure. Daily review of transmitted data for early recognition of patients at risk requires substantial resources that represent a major barrier to wide implementation. An automated analysis of incoming data for detection of risk for imminent events would allow focusing on patients requiring prompt medical intervention. We analysed data of the Telemedical Interventional Management in Heart Failure II (TIM-HF2) randomized trial that were collected during quarterly in-patient visits and daily transmissions from non-invasive monitoring devices. By application of machine learning, we developed and internally validated a risk score for heart failure hospitalisation within seven days following data transmission as estimate of short-term patient risk for adverse heart failure events. Score performance was assessed by the area under the receiver-operating characteristic (ROCAUC) and compared with a conventional algorithm, a heuristic rule set originally applied in the randomized trial. The machine learning model significantly outperformed the conventional algorithm (ROCAUC 0.855 vs. 0.727, p < 0.001). On average, the machine learning risk score increased continuously in the three weeks preceding heart failure hospitalisations, indicating potential for early detection of risk. In a simulated one-year scenario, daily review of only the one third of patients with the highest machine learning risk score would have led to detection of 95% of HF hospitalisations occurring within the following seven days. A machine learning model allowed automated analysis of incoming remote monitoring data and reliable identification of patients at risk of heart failure hospitalisation requiring immediate medical intervention. This approach may significantly reduce the need for manual data review.

Digital health and wearable devices for retinal disease monitoring

AbstractDigital health is wielding a growing influence across all areas of healthcare, encompassing various facets such as telemedicine, artificial intelligence (AI), and electronic healthcare records. In Ophthalmology, digital health innovations can be broadly divided into four categories: (i) self-monitoring home devices and apps, (ii) virtual and augmented reality visual aids, (iii) AI software, and (iv) wearables. Wearable devices can work in the background, collecting large amounts of objective data while we do our day-to-day activities, which may be ecologically more valid and meaningful to patients than that acquired in traditional hospital settings. They can be a watch, wristband, piece of clothing, glasses, cane, smartphone in our pocket, earphones, or any other device with a sensor that we carry with us. Focusing on retinal diseases, a key challenge in developing novel therapeutics has been to prove a meaningful benefit in patients’ lives and the creation of objective patient-centred endpoints in clinical trials. In this review, we will discuss wearable devices collecting different aspects of visual behaviour, visual field, central vision, and functional vision, as well as their potential implementation as outcome measures in research/clinical trial settings. The healthcare landscape is facing a paradigm shift. Clinicians have a key role of collaborating with the development and fine-tuning of digital health innovations, as well as identifying opportunities where they can be leveraged to enhance our understanding of retinal diseases and improve patient outcomes.

Three-dimensional evaluation of the responses of two species of flies (Diptera) to an indoor light trap

Abstract We used the Photonic Fence Monitoring Device (PFMD) to evaluate orientation by Musca domestica L. (Diptera: Muscidae), and Calliphora vicina Robineau-Desvoidy (Diptera: Calliphoridae) to the Zevo Flying Insect Trap Model 3. The PFMD’s dual cameras record infrared light (IR) reflected from a wavelength-specific fabric; insects do not reflect IR at the same wavelength and are tracked in 3 dimensions as moving objects. The plug-in trap emits ultraviolet and blue light from behind an opaque shield; attracted insects enter the space between the shield and the wall and are trapped on a sticky cartridge facing the wall. An experiment (N = 10) with replicates of approximately 40, 1- to 7-day-old mixed-sex flies of each species was conducted in a 6.1 m3 arena. Prior to turning the trap on, the fly movement was not directed toward the trap on the back wall of the arena, regardless of whether the overhead light was on or off. When the overhead light was off, the mean first catch of both species occurred within 5 min after the trap was turned on, and 33.1% and 41.8% of M. domestica and C. vicina, respectively, were caught. House flies flew toward the trap, many approaching from below, while C. vicina apparently walked or flew outside the field of view of the PFMD until they appeared on the vertical reflective surface, and then walked toward the trap from all directions. Our results show that the Zevo Trap attracts and catches flies, and that the PFMD can be used to track flying and walking flies.

Flexible, Electrochemical Skin-Like Platform for Inflammatory Biomarker Monitoring.

Addressing global challenges in wound management has greatly encouraged the emergence of home diagnosis and monitoring devices. This technological shift has accelerated the development of new skin patch sensors for continuous health monitoring. A key requirement is the creation of flexible platforms capable of mimicking human skin features. Here, for the first time, an innovative, highly adaptable electrochemical biosensor with molecularly imprinted polymers (MIPs) is customized for the detection of the inflammatory biomarker interleukin-6 (IL-6). The 3-electrode gold pattern is geometrically standardized onto a 6µm thick polyimide flexible membrane, an optically transparent, and biocompatible polymeric substrate. Subsequently, a biomimetic sensing layer specifically designed for the detection of IL-6 target is produced on these transducers. The obtained MIP biosensor shows a good linear response within the concentration range 50pgmL-1-50ngmL-1, with a low limit of detection (8pgmL-1). X-ray photoelectron spectroscopy, scanning electron microscopy, and Fourier transform infrared spectroscopy characterizations confirm the modifications of the flexible gold transducer. After optimization, the biosensing device shows remarkable potential in terms of sensitivity, selectivity, and reproducibility. Overall, the integration of a low-cost electrochemical sensor on biocompatible flexible polymers opens the way for a new generation of monitoring tools with higher accuracy, less invasiveness, and greater patient comfort.

Effects of Sterilization on Cellobiose Dehydrogenase and Glucose Oxidase Based Glucose Biosensors

AbstractResearch on implantable glucose biosensors is driven by the need for innovative medical devices for continuous glucose monitoring in patients with diabetes mellitus. However, biosensor sterilization is a step that is widely omitted during the process of innovation. To compare the effects of gamma irradiation and chemical treatment with ethylene oxide (carbon microarray electrodes are fabricated, functionalized with glucose oxidizing enzymes (cellobiose dehydrogenase CDH or glucose oxidase GOx), and coated with a specifically designed zwitterionic polymer prior to the sterilization step. Cyclic voltammetry in the presence of 100 mm glucose of the biosensors before and after sterilization shows that gamma irradiation with a low radiation rate (25 kGy, 260 Gy h−1) does not induce a sensor performance loss, unlike the EtO treatment. In addition, no cytotoxic by‐products are released after gamma sterilization. Based on these results obtained with both glucose oxidizing enzymes (CDH and GOx), gamma irradiation of the glucose biosensors with a low dose rate is preferable to exposure to EtO for biosensor terminal sterilization.