Non-invasive Monitoring Method Research Articles

Non-invasive method for blood glucose monitoring using ECG signal

Abstract Introduction: Tight glucose monitoring is crucial for diabetic patients by using a Continuous Glucose Monitor (CGM). The existing CGMs measure the Blood Glucose Concentration (BGC) from the interstitial fluid. These technologies are quite expensive, and most of them are invasive. Previous studies have demonstrated that hypoglycemia and hyperglycemia episodes affect the electrophysiology of the heart. However, they did not determine a cohort relationship between BGC and ECG parameters. Material and method: In this work, we propose a new method for determining the BGC using surface ECG signals. Recurrent Convolutional Neural Networks (RCNN) were applied to segment the ECG signals. Then, the extracted features were employed to determine the BGC using two mathematical equations. This method has been tested on 04 patients over multiple days from the D1namo dataset, using surface ECG signals instead of intracardiac signal. Results: We were able to segment the ECG signals with an accuracy of 94% using the RCNN algorithm. According to the results, the proposed method was able to estimate the BGC with a Mean Absolute Error (MAE) of 0.0539, and a Mean Squared Error (MSE) of 0.1604. In addition, the linear relationship between BGC and ECG features has been confirmed in this paper. Conclusion: In this paper, we propose the potential use of ECG features to determine the BGC. Additionally, we confirmed the linear relationship between BGC and ECG features. That fact will open new perspectives for further research, namely physiological models. Furthermore, the findings point to the possible application of ECG wearable devices for non-invasive continuous blood glucose monitoring via machine learning.

Early prediction of bronchopulmonary dysplasia: can noninvasive monitoring methods be essential?

Despite remarkable breakthroughs in diagnosis and treatment, the prevalence of bronchopulmonary dysplasia (BPD) in preterm infants and the consequent mortality have remained high over the last half-century. The pathophysiology of BPD is complicated, with several causes. In addition, infants with severe BPD are predisposed to a variety of complications that need multidisciplinary collaboration during hospitalisation and post-discharge home treatment. Consequently, early prediction, precise prevention and individualised management have become the cornerstones of therapeutic care of preterm infants with BPD, thereby improving patient survival and prognosis. BPD has an operational clinical description; however, it has various clinical phenotypes and endotypes, making accurate prediction challenging. Currently, most approaches for predicting BPD in preterm infants include invasive collection of biofluids, which is inappropriate in fragile neonates. Consequently, researchers and clinicians are becoming more interested in noninvasive monitoring for BPD prediction. Comprehensive assessments of pertinent research, however, remain scarce. In this review, we compared many noninvasive monitoring techniques that contribute to early prediction of BPD development in premature infants.

Hair Follicles as a Critical Model for Monitoring the Circadian Clock.

Clock (circadian) genes are heterogeneously expressed in hair follicles (HFs). The genes can be modulated by both the central circadian system and some extrinsic factors, such as light and thyroid hormones. These circadian genes participate in the regulation of several physiological processes of HFs, including hair growth and pigmentation. On the other hand, because peripheral circadian genes are synchronized with the central clock, HFs could provide a noninvasive and practical method for monitoring and evaluating multiple circadian-rhythm-related conditions and disorders among humans, including day and night shifts, sleep-wake disorders, physical activities, energy metabolism, and aging. However, due to the complexity of circadian biology, understanding how intrinsic oscillation operates using peripheral tissues only may be insufficient. Combining HF sampling with multidimensional assays such as detection of body temperature, blood samples, or certain validated questionnaires may be helpful in improving HF applications. Thus, HFs can serve as a critical model for monitoring the circadian clock and can help provide an understanding of the potential mechanisms of circadian-rhythm-related conditions; furthermore, chronotherapy could support personalized treatment scheduling based on the gene expression profile expressed in HFs.

The value of pulmonary artery acceleration time in evaluating pulmonary vascular disease in preterm infants with bronchopulmonary dysplasia.

Early screening and dynamic monitoring of pulmonary vascular disease (PVD) in bronchopulmonary dysplasia (BPD) high-risk infants is of great clinical significance. Pulmonary artery acceleration time (PAAT) is a reliable and non-invasive method for assessing PVD in children over 1 year, but to date, few studies have used PAAT to assess pulmonary hemodynamics of preterm infants, especially those with BPD. Through dynamic monitoring the main hemodynamic indicators reflected PVD after birth, this study aimed to assess the value of PAAT in evaluating early PVD in BPD infants. All 81 preterm infants at risk of BPD were divided into BPD and non-BPD groups according to whether BPD occurred. Clinical characteristics, PAAT, right ventricular ejection time (RVET) and other main hemodynamic indicators at four different time points after birth were studied and compared. PAAT and PAAT/RVET increased gradually within 72h after birth in the BPD group (p<.05), but the curve tended to be flat over time after 72h (p>.05). At PMA32 and 36weeks, the PAAT (49.7±4.8vs. 54.8±5.7, p=.001; 50.0±5.3vs. 57.0±5.3, p=.001) and PAAT/RVET (.33±.04vs..35±.03, p=.001; .34±.03vs. .37±.04, p=.001) in BPD group were significantly lower than those in the non-BPD group. PAAT and PAAT/RVET in the BPD group infants showed different change patterns compared to non-BPD group infants. PAAT can be used as a noninvasive and reliable screening method for screening and dynamic monitoring of PVD in BPD high-risk infants.

Enhancement of NH3 gas sensing with Ag-Pt co-catalyst on SnO2 nanofilm towards medical diagnosis

Exhaled breath analysis is a noninvasive diagnostic method for fatal disease monitoring and screening, which is recently gained extensive interest of researchers worldwide emphasizing on the development of effective chemiresistive gas sensor for practical application. Here, the Ag-Pt bimetallic nanoparticles were used to decorate nanofilms of SnO2 making different gas sensors with high performance. We found that the bimetal alloy improved the sensor performance significantly with super sensitivity as compared with the separate Ag and Pt catalyst. The right ratio of the bimetal made the sensor very sensitive to NH3, so that it was able to quickly (12 s) detect 1 parts-per-million of NH3 with a response of 4.31 at a temperature of 250 °C. The sensor limit of detection for NH3 was less than 10 parts-per-billion. The response of the sensor was negligibly affected by humidity and interfering gases. The results showed that the tiny, robust, and inexpensive sensor developed in this work can be used in breath analysis for early diagnosis via NH3 monitoring.

Admission Cardiotocography: Its Role in Predicting Perinatal Outcome in Term, Uncomplicated (Low Risk) Pregnant Women in Spontaneous Labour

Introduction: Labour admission cardiotocography (CTG) is commonly used non-invasive method of fetal monitoring in Sri Lanka. It may have a potentialto predict perinatal outcome in low-risk term pregnancies. Objectives: Objectives of the study were to determine the perinatal outcomes of normal, suspicious and pathological admission CTGs and role of labour admission cardiotocography as a predictive test for perinatal outcome in low-risk term pregnancies in spontaneous labour. Methods: This study was a prospective observational study done involving 445 low risk, term pregnancies in spontaneous labour. Labour admission CTG was performed in each pregnancy and categorized into normal, suspicious and pathological CTG according to criteria depicted by National Institute of Clinical Excellence (NICE) guideline 2007. Apgar score less than 7 at five minutes, resuscitation at birth, admission to neonatal intensive care unit (NICU), seizure within first 24 hours of birth and meconium-stained amniotic fluid were the primary outcome measures to assess fetal asphyxia. Mode of delivery in each category, nuchal cord at birth were also assessed. Results: Majority of participants were in 25-to-29-year age group and were nulliparous. Frequencies of normal, suspicious and pathological CTG were 74.8%, 18% and 7.2% respectively. Pathological CTG was significantly associated with low Apgar score compared to non-pathological CTG group (p 0.005) while other outcome measures were not significant. Rate of operative delivery was 68% in pathological group and 20.8% in non-pathological CTG group. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of labour admission CTG to detect fetal asphyxia were 51.85%, 95.69%, 43.75% and 96.85% respectively. Conclusions: Incidence of pathological labour admission CTG was 7.2%. Apgar score less than 7 at five minutes of birth was significantly associated with pathological CTG group compared to non-pathological CTG (p 0.05). Worsening of CTG from normal to pathological showed increasing rate of operative delivery. Even though sensitivity and positive predictive values of labour admission CTG were low, specificity and negative predictive values were high for detecting low Apgar score. Therefore, labour admission CTG has a value in excluding adverse perinatal outcomes in low-risk term pregnancies in spontaneous labour.

Biosensors and Sleep: The Future and Beyond

Biosensors have revolutionized nanotechnological development and are therefore the future ubiquitous devices for disease diagnosis monitoring treatment and health management. They provide a non-invasive method of continuous monitoring of various physiological signals like temperature heart rate blood pressure respiration rate and oxygen saturation and transmits that information to the patient and the physician. Thus their role in at-home detection of cases with obstructive sleep apnea OSA is significant which can easily replace the gold standard yet complex in-lab polysomnography PSG. The oral health care providers can be of great value to the team of sleep specialists when it comes to early detection and intervention with correct therapy for such patients. All the parameters that are studied in PSG can now be easily analyzed with the help of biosensors. However most of the sensing systems available today are extra-oral in nature and have no relation in anyway to the dental aspect of detection of OSA. Thus there is a vast space that is left unexplored in the world of biosensors when it comes to oral appliances which can be put into a pivotal role in diagnosing the undetected sleep apneic patients at a very early stage. This review paper presents an overview of the biosensors exploring their types functional modes and applications with particular emphasis on their potential application in diagnosing OSA.

Frequency-based leak signature investigation using acoustic sensors in urban water distribution networks

Cities worldwide have been plagued by water pipe leaks for many decades, resulting in financial losses, public health risks, and environmental impacts. Current practice still relies heavily on periodic and localized inspection rather than long-term continuous monitoring, and since water pipelines are buried underground, leaks can often go undetected for prolonged periods. Noninvasive acoustic-based methods for continuous pipeline monitoring have gained increasing popularity the past decade thanks to the recent advances in sensing and communication technology. Previous research indicates that hydrophones, in particular, are capable of effectively detecting leak-induced acoustic waves inside a water pipe. However, most studies to date have been limited to either controlled or field test-bed settings; hence, findings might not generalize well to real-world complex pipe networks. Through rigorous leak tests conducted in a real water distribution network and an extensive analysis of the field-collected acoustic signals, the current study aims to test the applicability of low-cost, non-intrusive hydrophones attached to fire hydrants for continuous pipe monitoring and leak detection. Continuous wavelet transform, power spectrum, and band power analyses were employed to identify the leak signature and distinguish normal from leak acoustic data in various leak scenarios. Results indicate that the acoustic signals generated by the simulated leaks in this field study are characterized by a consistent increase in the power of the frequency band 150–450 Hz primarily, whereas background noise levels and conditions significantly vary depending on the location of the sensor in the network. Realistic conditions in urban water distribution networks, including background noise, complicated topology, and varying pipe size and material, are still posing significant challenges for cost-effective and widespread implementation of acoustic-based sensors to achieve continuous monitoring in water pipe networks for leak detection. Even though further research and development is required to handle the highly variable conditions of real systems, the low-cost hydrophones tested in this work demonstrated potential in detecting low-flow leaks in simple and complex pipe topologies.

Performance improvement of cardiorespiratory measurements using pressure sensors with mechanical coupling techniques

Monitoring heart rate and breathing is essential in understanding the physiological processes for sleep analysis. Polysomnography (PSG) system have traditionally been used for sleep monitoring, but alternative methods can help to make sleep monitoring more portable in someone's home. This study conducted a series of experiments to investigate the use of pressure sensors placed under the bed as an alternative to PSG for monitoring heart rate and breathing during sleep. The following sets of experiments involved the addition of small rubber domes - transparent and black - that were glued to the pressure sensor. The resulting data were compared with the PSG system to determine the accuracy of the pressure sensor readings. The study found that the pressure sensor provided reliable data for extracting heart rate and respiration rate, with mean absolute errors (MAE) of 2.32 and 3.24 for respiration and heart rate, respectively. However, the addition of small rubber hemispheres did not significantly improve the accuracy of the readings, with MAEs of 2.3 bpm and 7.56 breaths per minute for respiration rate and heart rate, respectively. The findings of this study suggest that pressure sensors placed under the bed may serve as a viable alternative to traditional PSG systems for monitoring heart rate and breathing during sleep. These sensors provide a more comfortable and non-invasive method of sleep monitoring. However, the addition of small rubber domes did not significantly enhance the accuracy of the readings, indicating that it may not be a worthwhile addition to the pressure sensor system.

A Non-invasive Methods for Neonatal Jaundice Detection and Monitoring to Assess Bilirubin Level: A Review

Neonatal jaundice is a frequent cause of substantial illness and mortality in newborns. The newborn infant’s skin, eyes, and other tissues turn yellow because bilirubin contains a pigment or coloring. Jaundice that manifests in the first few days is highly dangerous and typically needs to be treated right away. It is typically “physiologic” when jaundice emerges on the second or third day. Hyperbilirubinemia refers to an abnormally high bilirubin level in the blood. During the decomposition of red blood cells, bilirubin is formed. Bilirubin can build up in the blood, bodily fluids, and other tissues of newborn babies because they are not naturally able to expel it. Kernicterus or irreversible brain damage can result from untreated jaundice if the abnormally high levels of bilirubin are not controlled. In cases of neonatal jaundice, there is currently a variety of estimating methods for measuring bilirubin levels. The goal of this research is to provide a thorough evaluation of various non-invasive frameworks for the identification of newborn jaundice. For this review article, a critical analysis has done by using 51 articles from 2009 to 2022 where all articles are based on the detection of neonatal jaundice. This literary work on non-invasive methods and neonatal jaundice results appear to be an understanding of the avant-garde procedures created and used in this domain. The review also compares and contrasts different non-invasive strategies for predicting an infant’s state of serum bilirubin based on different data such as social media data, and clinical data. At last, the open issues and future challenges of using a non-invasive method to better understand as well as diagnose the neonatal jaundice state of any individual were discussed. From the literature study, usually apparent that the utilization of non-invasive methods in neonatal jaundice has yielded noteworthy fulfillment within the regions of diagnosis, support, research, and clinical governance.

Fetal Electrocardiogram Extraction Using Dual-Path Source Separation of Single-Channel Non-Invasive Abdominal Recordings.

The development of a method for non-invasive monitoring of fetal electrocardiogram (FECG) signals from single-channel abdominal recordings. The dual-path source separation (DPSS) architecture is introduced for the simultaneous separation of fetal and maternal ECG signals from abdominal ECG recordings. DPSS initially denoises abdominal ECG (AECG) recordings using a generative dual-path long short-term memory (DP-LSTM) network. An inception module along with a series of DP-LSTM blocks is then employed to extract the masking maps associated with fetal and maternal components. Finally, these masking maps are weighted by the AECG recording to separate maternal and fetal ECG signals. The performance of this network is evaluated on 10 pregnancies from the fetal ECG synthetic database (FECGSYNDB), 22 cases of labor and pregnancy from the abdominal and direct fetal ECG database (ADFECGDB), and 69 pregnancies from set A of non-invasive FECG challenge (NIFECGC) datasets. F1-scores of 99.03%, 97.7%, and 95.3% are reported for the detection of fetal QRS complexes in FECGSYNDB, ADFECGDB, and NIFECGC respectively. DPSS technique is also evaluated in terms of separability of fetal and maternal clusters. According to the clustering-based analyses, the average purity index of 0.9750, Jaccard index of 0.9705, and Davies-Bouldin index of 0.7429 demonstrate the high source separation capability of DPSS. The achieved performance suggests that DPSS enables accurate single-channel FECG extraction, and can replace state-of-the-art source separation techniques for this purpose. This study signifies a fundamental step towards non-invasive fetal ECG monitoring systems, which favors at-home prenatal care.

Verified occurrence of Felis silvestris in Bohemia (Czech Republic) in 2010–2021 (Carnivora: Felidae)

In total, 616 reliable records (C1, C2 category sensu SCALP) of wildcat occurrence in Bohemia were collected and analysed in 11 monitoring seasons, “wildcat years” (WCY), 2010–2021. Camera-trapping data accounted for 95% of the dataset, the rest of the records were verified by the genetic analysis of several hair samples, scats, and tissue samples. The occurrence of the European wildcat was confirmed in eight sub-areas, more continuously in the forested border areas of southern and western Bohemia, and more sparsely in central and northern Bohemia. In total, the wildcat occurred at 73 different sites, in 35 mapping squares: four confirmed as category C1, 31 as category C2. The current occurrence in the western part of the Czech Republic is linked to that in neighbouring Germany. The development of modern non-invasive monitoring methods was crucial for the increase in detection of wildcat presence. However, both reintroduction and population increase in Bavaria and climactic change can also play a role as drivers of the recent spreading of the wildcat to our territory. Reproduction was confirmed in two sub-areas (Český les Mts., WCY 2021; Doupovské hory Mts., WCY 2020) and represents the first documented reproduction of the wildcat in Bohemia since the WWII. In some large areas such as the Šumava Mts., we observed a rather wider spatial activity, smaller numbers of individuals and more transient character of occurrence than in other (more restricted) areas, such as the Doupovské hory Mts., where we found higher population density and permanent occurrence with reproduction. Species-specific systematic camera-trapping and genetic monitoring in all areas with confirmed occurrence is highly recommended for the future.

Measurement of tissue oxygen saturation during arthroscopic surgery of knee with a tourniquet.

Tourniquets provide better tissue visibility during arthroscopic surgery. However, multiple postoperative adverse events associated with ischemia may be caused by excessive inflation pressure and duration. We aimed to evaluate the degree of tourniquet-induced ischemia using a noninvasive continuous real-time monitoring method and the relationship between changes in tissue oxygen saturation (StO2) and blood biochemical markers of ischemic injuries in patients undergoing arthroscopic knee surgery. This was a prospective observational study using near-infrared spectroscopy (NIRS). Data were collected from 29 consecutive patients who underwent arthroscopic procedures. Twenty-five patients underwent anterior cruciate ligament reconstruction, and four underwent meniscal repair. We investigated tourniquet-induced changes in StO2, monitored using NIRS, and blood biochemical markers of ischemic injuries. A significant decrease in the mean StO2 from the baseline was observed during tourniquet inflation in the operative legs. The average decrease in the mean StO2 was 58%. A comparison of mean StO2 between the nonoperative and operative legs before tourniquet deflation showed that mean values of StO2 in the operative legs were significantly lower than those in the nonoperative legs. No significant clinical relationships were observed between changes in StO2 and blood biochemical markers of ischemic injuries (creatine kinase) (p = 0.04, r = 0.38) or tourniquet duration (p = 0.05, r = 0.366). Our results demonstrated that StO2 could be used to evaluate tissue perfusion in real time but did not support the hypothesis that StO2 is a useful method for predicting the degree of tourniquet-induced injury during arthroscopic knee surgery.

Longitudinal monitoring of pancreatic islet damage in streptozotocin-treated mice with optical coherence microscopy.

Pancreatic islets regulate glucose homeostasis in the body, and their dysfunction is closely related to diabetes. Islet transplantation into the anterior chamber of the eye (ACE) was recently developed for both in vivo islet study and diabetes treatment. Optical coherence microscopy (OCM) was previously used to monitor ACE transplanted islets in non-obese diabetic (NOD) mice for detecting autoimmune attack. In this study, OCM was applied to streptozotocin (STZ)-induced diabetic mouse models for the early detection of islet damage. A custom extended-focus OCM (xfOCM) was used to image islet grafts in the ACE longitudinally during STZ-induced beta cell destruction together with conventional bright-field (BF) imaging and invasive glucose level measurement. xfOCM detected local structural changes and vascular degradation during the islet damage which was confirmed by confocal imaging of extracted islet grafts. xfOCM detection of islet damage was more sensitive than BF imaging and glucose measurement. Longitudinal xfOCM images of islet grafts were quantitatively analyzed. All these results showed that xfOCM could be used as a non-invasive and sensitive monitoring method for the early detection of deficient islet grafts in the ACE with potential applications to human subjects.

Bird feathers as a non-invasive method for ecotoxicological monitoring; a rapid review

The decline in animal population with resulting risk of eventual disruption of ecosystem functioning has necessitated moves towards non-invasive sampling methods for ecotoxicological studies. These efforts have focused on developing sampling methodologies geared towards prioritizing conservation of biodiversity. Using a rapid review approach, 106 articles covering peer-reviewed studies, theses, and manuscripts under peer-review quantifying contaminants in feathers were examined. Meta-analysis of extracted information (n=91) revealed that most studies on feather contaminants originate from Europe (47.6 %) and Asia (32.9%), with a higher occurrence of such studies between 2015 and 2020. The most utilized feather-type across studies were body feathers (28.6%) and tail feathers (20%). Majority of the studies (60.5%) used feathers alone to estimate contaminant exposure and uptake; 14.8% used feathers and blood, while 12.3% used feathers and soft tissues (liver, kidney, muscle etc.). Inferences from the review reveal that feathers as a non-invasive sampling method provide advantages by having contaminant concentrations that are relatable with internal organs of birds, captures information on ambient contaminant concentrations based on exogenous contributions and application for historic studies. However, some available data indicate that selective uptake of some metals in organs of species could significantly reduce the number of contaminants stored in feathers and may limit its accuracy for biomonitoring. Furthermore, the different degrees of external deposition of persistent organic contaminants (PCBs, PBDEs, etc) onto the feather surface due to differential degradability/metabolization may limit the use of feathers to estimate exogenous effects. Nonetheless, while feathers have been used successfully as a non-invasive method for ecotoxicological monitoring of metals, metalloids and organic pollutants, knowledge on bird ontogeny and contaminant-specific trends in feathers could improve the accuracy of monitoring. Further efforts towards broadening the impact and advancement of this field method in future studies of avian research especially in developing countries is recommended.

Sweat cortisol determination utilizing MXene and multi-walled carbon nanotube nanocomposite functionalized immunosensor

In this work, a highly selective and sensitive cortisol immunosensor based on MXene and multi-walled carbon nanotubes (MXene-MWCNTs) hybrid composite was proposed. The immunosensor was developed by screen printing technique on a flexible polyethyleneterephthalate (PET) substrate followed by modification of MXene-MWCNTs and anti-cortisol antibodies with EDC/NHS coupling agent. Owing to the large surface area and excellent conductivity of MXene-MWCNTs, the immunosensor exhibited a low detection limit and a wide linear range toward cortisol from 0.1 fg/mL to 1 µg/mL, which covered the normal range of free cortisol in sweat. Additionally, the immunosensor was applied to evaluate the cortisol level in human sweat samples, and the results were validated by a commercial chemiluminescence immunoassay (CLIA) assay. The present platform provides an effective method for non-invasive monitoring of human sweat cortisol levels, which may be well-suited for hormone screenings in healthy monitoring and medical diagnosis.

Prediction of major adverse cardiovascular events in patients with acute coronary syndrome: Development and validation of a non-invasive nomogram model based on autonomic nervous system assessment.

Disruption of the autonomic nervous system (ANS) can lead to acute coronary syndrome (ACS). We developed a nomogram model using heart rate variability (HRV) and other data to predict major adverse cardiovascular events (MACEs) following emergency coronary angiography in patients with ACS. ACS patients admitted from January 2018 to June 2020 were examined. Holter monitors were used to collect HRV data for 24 h. Coronary angiograms, clinical data, and MACEs were recorded. A nomogram was developed using the results of Cox regression analysis. There were 439 patients in a development cohort and 241 in a validation cohort, and the mean follow-up time was 22.80 months. The nomogram considered low-frequency/high-frequency ratio, age, diabetes, previous myocardial infarction, and current smoking. The area-under-the-curve (AUC) values for 1-year MACE-free survival were 0.790 (95% CI: 0.702-0.877) in the development cohort and 0.894 (95% CI: 0.820-0.967) in the external validation cohort. The AUCs for 2-year MACE-free survival were 0.802 (95% CI: 0.739-0.866) in the development cohort and 0.798 (95% CI: 0.693-0.902) in the external validation cohort. Development and validation were adequately calibrated and their predictions correlated with the observed outcome. Decision curve analysis (DCA) showed the model had good discriminative ability in predicting MACEs. Our validated nomogram was based on non-invasive ANS assessment and traditional risk factors, and indicated reliable prediction of MACEs in patients with ACS. This approach has potential for use as a method for non-invasive monitoring of health that enables provision of individualized treatment strategies.

Latest Research Findings on Prediction of Preeclampsia in Pregnant Women Based on Analysis of Cell-Free RNA in Peripheral Blood

Preeclampsia gravely threatens the health of mothers and infants. At present, treatment based on the relevant mechanisms of pathogenesis is still not available, and there is no independent reliable clinical index for early prediction of preeclampsia. According to recent studies, analysis of the cell-free RNA in the peripheral blood of pregnant women has shown that testing certain cell-free RNA levels can help predict in advance the occurrence of preeclampsia before clinical symptoms appear. In this paper, we described the status of research and progress in using maternal cell-free RNA analysis in predicting preeclampsia. In addition, we stated that cell-free RNA in peripheral blood may become a promising, real-time and non-invasive monitoring method that can be used to explore the mechanisms of pathogenesis and pathophysiology of preeclampsia and to identify different subtypes of preeclampsia.

A hybridized nano-porous carbon reinforced 3D graphene-based epidermal patch for precise sweat glucose and lactate analysis

Wearable electrochemical biosensors for perspiration analysis offer a promising non-invasive biomarker monitoring method. Herein, a functionalized hybridized nanoporous carbon (H-NPC)-encapsulated flexible 3D porous graphene-based epidermal patch was firstly fabricated for monitoring sweat glucose, lactate, pH, and temperature using simple, cost-effective, laser-engraved, and spray-coating techniques. The fabricated H-NPC-modified electrode significantly increased electrochemical surface area and electrocatalytic activity. Within the physiological sweat range (0–1.5 mM), the second-generation glucose sensor exhibited an excellent sensitivity of 82.7 μAmM−1cm−2 with 0.025 μM LOD. Moreover, the lactate biosensor exhibited an extraordinary linear range (0–56 mM) response owing to the incorporation of an outer diffusion limiting layer (DLL) that controls the lactate flux reaching the enzyme with comparable sensitivity (204 nAmM−1cm−2) and LOD (4 μM). Finally, we employed an analytical correction approach incorporating pH and temperature adjustments during on-body tests. In addition to connecting various carbon-based materials to limitless metal-organic frameworks as a transduction material, our research also paves the way for enabling these sensors to operate on pH and T correction independently while delivering accurate results.

Non-Invasive Probing of Winter Dormancy via Time-Frequency Analysis of Induced Chlorophyll Fluorescence in Deciduous Plants as Exemplified by Apple (Malus × domestica Borkh.).

Dormancy is a physiological state that confers winter hardiness to and orchestrates phenological phase progression in temperate perennial plants. Weather fluctuations caused by climate change increasingly disturb dormancy onset and release in plants including tree crops, causing aberrant growth, flowering and fruiting. Research in this field suffers from the lack of affordable non-invasive methods for online dormancy monitoring. We propose an automatic framework for low-cost, long-term, scalable dormancy studies in deciduous plants. It is based on continuous sensing of the photosynthetic activity of shoots via pulse-amplitude-modulated chlorophyll fluorescence sensors connected remotely to a data processing system. The resulting high-resolution time series of JIP-test parameters indicative of the responsiveness of the photosynthetic apparatus to environmental stimuli were subjected to frequency-domain analysis. The proposed approach overcomes the variance coming from diurnal changes of insolation and provides hints on the depth of dormancy. Our approach was validated over three seasons in an apple (Malus × domestica Borkh.) orchard by collating the non-invasive estimations with the results of traditional methods (growing of the cuttings obtained from the trees at different phases of dormancy) and the output of chilling requirement models. We discuss the advantages of the proposed monitoring framework such as prompt detection of frost damage along with its potential limitations.