AagingBase: a comprehensive database of anti-aging peptides.

The process of aging is an intrinsic and inevitable aspect of life that impacts every living organism. As biotechnological advancements continue to shape our understanding of medicine, peptide therapeutics have emerged as a promising strategy for anti-aging interventions. This is primarily due to their favorable attributes, such as low immunogenicity and cost-effective production. Peptide-based treatments have garnered widespread acceptance and interest in aging research, particularly in the context of age-related therapies. To effectively develop anti-aging treatments, a comprehensive understanding of the physicochemical characteristics of anti-aging peptides is essential. Factors such as amino acid composition, instability index, hydrophobic areas and other relevant properties significantly determine their efficacy as potential therapeutic agents. Consequently, the creation of 'AagingBase', a comprehensive database for anti-aging peptides, aims to facilitate research on aging by leveraging the potential of peptide therapies. AagingBase houses experimentally validated 282 anti-aging peptides collected from 54 research articles and 236 patents. Employing state-of-the-art computational techniques, the acquired sequences have undergone rigorous physicochemical calculations. Furthermore, AagingBase presents users with various informative analyses highlighting atomic compositions, secondary structure fractions, tertiary structure, amino acid compositions and frequencies. The database also offers advanced search and filtering options and similarity search, thereby aiding researchers in understanding their biological functions. Hence, the database enables efficient identification and prioritization of potential peptide candidates in geriatric medicine and holds immense potential for advancing geriatric medicine research and innovations. AagingBase can be accessed without any restriction. Database URL: https://project.iith.ac.in/cgntlab/aagingbase/.

Crosstalk-free graphene-liquid elastomer based printed sensors for unobtrusive respiratory monitoring.

Flexible strain sensors have garnered attraction in the human healthcare domain. However, caveats like crosstalk and noise associated with the output signal of such a sensor often limit the accuracy. Hence, developing a strain sensor via frugal engineering is critical, thereby warranting its mass utility. A stencil printable graphene/liquid elastomeric crosstalk-free strain sensor for unobtrusive respiratory monitoring is reported herein. Printing supports the frugality of the process and avoids complex fabrication. The sensor was mounted on a wearable mask, and the sensor console was fabricated. The console demonstrated the capability to detect the respiratory profile at room and low temperature (-26 °C) with an SNR of -12.85 dB. Developed sensors could nullify the impact of temperature and humidity and generate respiratory signals due to strain induced by breathing. A model experiment was conducted to support the fidelity of the strain mechanism. The console demonstrated excellent stability (over 500 cycles) with a sensitivity of -196.56 (0-0.17% strain) and 117.49 (0.17-0.34% strain). The console could accurately determine conditions like eupnea, tachypnoea, etc., and transmit the data wirelessly via Bluetooth. These findings solve major caveats in flexible sensor development by focusing on selectivity, sensitivity, and stability.

Image quality assessment of coronary artery segments using ultra-high resolution dual source photon-counting detector computed tomography.

PURPOSE: The study is intended to assess the image quality of ultra-high resolution (UHR) coronary computed tomography angiography (CCTA) performed on dual source photon-counting detector CT (PCD-CT). METHOD: Consecutive patients, who underwent clinically indicated CCTA on PCD-CT (UHR 120x 0.2 mm collimation), were included. CCTA images were reconstructed at 0.2 mm slice thickness with Bv40, Bv44, Bv48 and Bv56 kernels and quantum iterative reconstruction level 4. Contrast-to-noise (CNR) and signal-to-noise ratios (SNR) were quantified from contrast-enhanced blood and subcutaneous adipose tissue. All reconstructions were scored per coronary segment (18-segment model) for presence, image quality, motion artefacts, stack artefacts, plaque presence and composition, and stenosis degree. Image quality was scored by two independent observers. RESULTS: Sixty patients were included (median age 62 [25th - 75th percentile: 53-67] years, 45% male, median calcium score 62 [0-217]). The mean heart rate during scanning was 71 ± 11 bpm. Median CTDIvol was 19 [16-22]mGy and median DLP 243 [198-327]mGy.cm. The SNR was 9.3 ± 2.3 and the CNR was 11.7 ± 2.6. Of the potential 1080 coronary segments (60 patients x 18 segments), 255/256 (reader1/reader2) segments could not be assessed for being absent or non-evaluable due to size. Both readers scored 85% of the segments as excellent or very good (Intraclass Correlation Coefficient: 0.88 (95% CI: 0.87-0.90). Motion artefacts were present in 45(5%) segments, stack artefacts in 60(7%) segments and metal artefacts in 9(1%) segments. CONCLUSION: UHR dual-source PCD-CT CCTA provides excellent or very good image quality in 85% of coronary segments at relatively high heart rates at moderate radiation dose with only limited stack artefacts.

MyeloDB: a multi-omics resource for multiple myeloma.

Multiple myeloma (MM) is a common type of blood cancer affecting plasma cells originating from the lymphoid B-cell lineage. It accounts for about 10% of all hematological malignancies and can cause significant end-organ damage. The emergence of genomic technologies such as next-generation sequencing and gene expression analysis has opened new possibilities for early detection of multiple myeloma and identification of personalized treatment options. However, there remain significant challenges to overcome in MM research, including integrating multi-omics data, achieving a comprehensive understanding of the disease, and developing targeted therapies and biomarkers. The extensive data generated by these technologies presents another challenge for data analysis and interpretation. To bridge this gap, we have developed a multi-omics open-access database called MyeloDB. It includes gene expression profiling, high-throughput CRISPR-Cas9 screens, drug sensitivity resources profile, and biomarkers. MyeloDB contains 47 expression profiles, 3 methylation profiles comprising a total of 5630 patient samples and 25 biomarkers which were reported in previous studies. In addition to this, MyeloDB can provide significant insight of gene mutations in MM on drug sensitivity. Furthermore, users can download the datasets and conduct their own analyses. Utilizing this database, we have identified five novel genes, i.e., CBFB, MANF, MBNL1, SEPHS2, and UFM1 as potential drug targets for MM. We hope MyeloDB will serve as a comprehensive platform for researchers and foster novel discoveries in MM. MyeloDB Database URL: https://project.iith.ac.in/cgntlab/myelodb/ .

Anxiety Symptoms and Associated Psychological and Job-Related Factors Among Hospital Nurses.

OBJECTIVE: Recently, burnout and mental health issues regarding nurses are reported increasingly. This study aimed to investigate the prevalence of anxiety symptoms among hospital nurses and determine their association with psychological and job-related factors. METHODS: Data on demographics, job-related characteristics, burnout, Type A behavior patterns, self-esteem, and happiness were collected from 515 nurses working at a university hospital in Korea. Anxiety symptoms were assessed using the anxiety subscale of the Hospital Anxiety and Depression Scale, with scores of 8 or higher indicating the presence of anxiety symptoms. Demographic, job-related, and psychological factors were compared according to the presence of anxiety. Logistic regression was conducted to identify factors associated with anxiety symptoms. RESULTS: Two hundred and four (39.6%) participants had anxiety symptoms. Self-esteem and happiness were associated with a lower risk of anxiety symptoms, whereas burnout was associated with a higher risk of anxiety symptoms. Furthermore, being female, having a career of less than five years, and requiring counseling due to stress were associated with a higher risk of anxiety symptoms. Being younger, female, or a basic nurse; having a career of less than five years; partaking in shift work; experiencing job dissatisfaction; requiring counseling due to stress; being exposed to higher levels of burnout; and having lower levels of self-esteem and happiness were all found to be significantly correlated with anxiety symptoms. CONCLUSION: These findings suggest that promoting self-esteem and happiness while reducing burnout may be beneficial in preventing and managing anxiety symptoms among hospital nurses.

Synthesis of gallic acid-grafted epoxidized natural rubber and its role in self-healable flexible temperature sensors.

Developing a flexible temperature sensor with appreciable sensitivity is critical for advancing research related to flexible electronics. Although various flexible sensors are available commercially, most such temperature sensors are made from polymeric materials obtained from petrochemical resources. Such sensors will contribute to electronic waste and increase the carbon footprint after usage. While there are reports on various sensors made from sustainable polymers, research related to developing self-healable flexible temperature sensors made from sustainable polymers is significantly less. Herein, we report on developing a flexible temperature sensor made of gallic acid-grafted epoxidized natural rubber and multi-walled carbon nanotubes. Various spectroscopic and thermal techniques vetted the modification of the epoxidized natural rubber. The highest grafting of 20.9% was achieved in the selected window of stoichiometry. A self-healing behavior was achieved by leveraging the FeCl3 based metal-ligand crosslinking of the composite. The healing efficiency was noted to be 31.2% for the composite material. The fabricated sensor demonstrated an electrical resistance of 4.46 × 103 Ω, thereby warranting the composite to demonstrate an Ohmic behavior in the I-V plot. Appropriate data fitting suggested a variable range hopping mechanism as causation towards excellent electrical conduction. The temperature sensitivity and the thermal index of the developed sensor were noted to be -0.17% °C-1 and 781.2 K, respectively, in the temperature range of 30 °C to 50 °C. The proposed method of fabricating sustainable, high-strength, self-healable, and robust temperature sensors and conductors is a unique and value-added approach for next-generation flexible electronics.

Coronary calcium scoring on virtual non-contrast and virtual non-iodine reconstructions compared to true non-contrast images using photon-counting computed tomography.

OBJECTIVES: To compare coronary artery calcification (CAC) scores measured on virtual non-contrast (VNC) and virtual non-iodine (VNI) reconstructions computed from coronary computed tomography angiography (CCTA) using photon-counting computed tomography (PCCT) to true non-contrast (TNC) images. METHODS: We included 88 patients (mean age = 59 years ± 13.5, 69% male) who underwent a TNC coronary calcium scan followed by CCTA on PCCT. VNC images were reconstructed in 87 patients and VNI in 88 patients by virtually removing iodine from the CCTA images. For all reconstructions, CAC scores were determined, and patients were classified into risk categories. The overall agreement of the reconstructions was analyzed by Bland-Altman plots and the level of matching classifications. RESULTS: The median CAC score on TNC was 27.8 [0-360.4] compared to 8.5 [0.2-101.6] (p < 0.001) on VNC and 72.2 [1.3-398.8] (p < 0.001) on VNI. Bland-Altman plots depicted a bias of 148.8 (ICC = 0.82, p < 0.001) and - 57.7 (ICC = 0.95, p < 0.001) for VNC and VNI, respectively. Of all patients with CACTNC = 0, VNC reconstructions scored 63% of the patients correctly, while VNI scored 54% correctly. Of the patients with CACTNC > 0, VNC and VNI reconstructions detected the presence of coronary calcium in 90% and 92% of the patients. CACVNC tended to underestimate CAC score, whereas CACVNI overestimated, especially in the lower risk categories. According to the risk categories, VNC misclassified 55% of the patients, while VNI misclassified only 32%. CONCLUSION: Compared to TNC images, VNC underestimated and VNI overestimated the actual CAC scores. VNI reconstructions quantify and classify coronary calcification scores more accurately than VNC reconstructions. CLINICAL RELEVANCE STATEMENT: Photon-counting CT enables spectral imaging, which might obviate the need for non-contrast enhanced coronary calcium scoring, but optimization is necessary for the clinical implementation of the algorithms. KEY POINTS: • Photon-counting computed tomography uses spectral information to virtually remove the signal of contrast agents from contrast-enhanced scans. • Virtual non-contrast reconstructions tend to underestimate coronary artery calcium scores compared to true non-contrast images, while virtual non-iodine reconstructions tend to overestimate the calcium scores. • Virtual non-iodine reconstructions might obviate the need for non-contrast enhanced calcium scoring, but optimization is necessary for the clinical implementation of the algorithms.

Immunogenicity and protective efficacy of nanoparticle formulations of L-SseB against Salmonella infection.

Salmonella enterica, a Gram-negative pathogen, has over 2500 serovars that infect a wide range of hosts. In humans, S. enterica causes typhoid or gastroenteritis and is a major public health concern. In this study, SseB (the tip protein of the Salmonella pathogenicity island 2 type III secretion system) was fused with the LTA1 subunit of labile-toxin from enterotoxigenic E. coli to make the self-adjuvanting antigen L-SseB. Two unique nanoparticle formulations were developed to allow multimeric presentation of L-SseB. Mice were vaccinated with these formulations and protective efficacy determined via challenging the mice with S. enterica serovars. The polysaccharide (chitosan) formulation was found to elicit better protection when compared to the squalene nanoemulsion. When the polysaccharide formulation was used to vaccinate rabbits, protection from S. enterica challenge was elicited. In summary, L-SseB in a particulate polysaccharide formulation appears to be an attractive candidate vaccine capable of broad protection against S. enterica.

Evidence of Antibiotic Resistance and Virulence Factors in Environmental Isolates of Vibrio Species.

The outbreak of waterborne diseases such as cholera and non-cholera (vibriosis) is continuously increasing in the environment due to fecal and sewage discharge in water sources. Cholera and vibriosis are caused by different species of Vibrio genus which are responsible for acute diarrheal disease and soft tissue damage. Although incidences of cholera and vibriosis have been reported from the Vaishali district of Bihar, India, clinical or environmental strains have not been characterized in this region. Out of fifty environmental water samples, twelve different biochemical test results confirmed the presence of twenty Vibrio isolates. The isolates were found to belong to five different Vibrio species, namely V. proteolyticus, V. campbellii, V. nereis, V. cincinnatiensis, and V. harveyi. From the identified isolates, 65% and 45% isolates were found to be resistant to ampicillin and cephalexin, respectively. Additionally, two isolates were found to be resistant against six and four separately selected antibiotics. Furthermore, virulent hlyA and ompW genes were detected by PCR in two different isolates. Additionally, phage induction was also noticed in two different isolates which carry lysogenic phage in their genome. Overall, the results reported the identification of five different Vibrio species in environmental water samples. The isolates showed multiple antibacterial resistance, phage induction, and virulence gene profile in their genome.

Liver organoids as a primary human model to study HBV-mediated Hepatocellular carcinoma. A review.

Hepatitis B Virus (HBV) is the prevailing cause of chronic liver disease, which progresses to Hepatocellular carcinoma (HCC) in 75% of cases. It represents a serious health concern being the fourth leading cause of cancer-related mortality worldwide. Treatments available to date fail to provide a complete cure with high chances of recurrence and related side effects. The lack of reliable, reproducible, and scalable in vitro modeling systems that could recapitulate the viral life cycle and represent virus-host interactions has hindered the development of effective treatments so far. The present review provides insights into the current in-vivo and in-vitro models used for studying HBV and their major limitations. We highlight the use of three-dimensional liver organoids as a novel and suitable platform for modeling HBV infection and HBV-mediated HCC. HBV organoids can be expanded, genetically altered, patient-derived, tested for drug discovery, and biobanked. This review also provides the general guidelines for culturing HBV organoids and highlights their several prospects for HBV drug discovery and screening.

Photon-counting Detector CT in Patients Pre- and Post-Transcatheter Aortic Valve Replacement.

Photon-counting detector CT (PCD CT) has increasingly garnered interest in cardiothoracic imaging due to its high spatial resolution and ability to perform spectral imaging. CT plays an important role in the planning and postprocedural assessment of transcatheter aortic valve replacement (TAVR). Limitations of current CT technology resulting in blooming and metal artifacts may be addressed with PCD CT. This case series demonstrates the potential advantages of PCD CT in patients prior to and post-TAVR. In TAVR planning, PCD CT allowed for a detailed depiction of the aortic valve, aortic root, coronary arteries, and potential vascular access routes. The high-spatial-resolution reconstructions enabled assessment of hypoattenuating leaflet thickening and periprosthetic leakage for prosthetic valves. This study shows promising initial results, but further research is needed to determine the clinical impact of PCD CT in patients prior to and post-TAVR. Keywords: Transcatheter Aortic Valve Replacement, Cardiac, Coronary Arteries, Heart, Valves, Photon-counting Detector CT © RSNA, 2023 An earlier incorrect version appeared online. This article was corrected on October 27, 2023.

Photon-counting CT: Review of initial clinical results.

Photon-counting computed tomography (PCCT) is a new technology that enables higher spatial resolution compared to conventional CT techniques, energy resolved imaging and spectral post-processing. This leads to improved contrast-to-noise ratio, artifact and potential dose reduction as well as elimination of electronic noise. Since the introduction of clinical PCCT in 2021, a shift has been observed from solely pre-clinical studies to clinical research (i.e. use of PCCT imaging in humans). This review article is focused on the initial clinical results of PCCT by explaining the current PCCT systems, the applications themselves and, the challenges of PCCT.

Cross-Talk Signal Free Recyclable Thermoplastic Polyurethane/Graphene-Based Strain and Pressure Sensor for Monitoring Human Motions.

Developing a sensor that can read out cross-talk free signals while determining various active physiological parameters is demanding in the field of point-of-care applications. While there are a few examples of non-flexible sensors available, the management of electronic waste generated from such sensors is critical. Most of such available sensors are rigid in form factor and hence limit their usability in healthcare monitoring due to their poor conformity to human skin. Combining these facets, studies on the development of a recyclable cross-talk free flexible sensor for monitoring human motions and active parameters are far and few. In this work, we report on the development of a recyclable flexible sensor that can provide accurate data for detecting small changes in strain as well as pressure. The developed sensor could decipher the signals individually responsible due to strain as well as pressure. Hence, it can deliver a cross-talk free output. Thermoplastic polyurethane and graphene were selected as the model system. The thermoplastic polyurethane/graphene sensor exhibited a tensile strain sensitivity of GF ≃ 3.375 for 0-100% strain and 10.551 for 100-150% strain and a pressure sensitivity of ∼-0.25 kPa-1. We demonstrate the applicability of the strain sensor for monitoring a variety of human motions ranging from a very small strain of eye blinking to a large strain of elbow bending with unambiguous peaks and a very fast response and recovery time of 165 ms. The signals received are mostly electrical hysteresis free. To confirm the recyclability, the developed sensor was recycled up to three times. Marginal decrement in the sensitivity was noted with recycling without compromising the sensing capabilities. These findings promise to open up a new avenue for developing flexible sensors with lesser carbon footprints.

Immune and metabolic markers for identifying and investigating severe Coronavirus disease and Sepsis in children and young people (pSeP/COVID ChYP study): protocol for a prospective cohort study.

INTRODUCTION: Early recognition and appropriate management of paediatric sepsis are known to improve outcomes. A previous system's biology investigation of the systemic immune response in neonates to sepsis identified immune and metabolic markers that showed high accuracy for detecting bacterial infection. Further gene expression markers have also been reported previously in the paediatric age group for discriminating sepsis from control cases. More recently, specific gene signatures were identified to discriminate between COVID-19 and its associated inflammatory sequelae. Through the current prospective cohort study, we aim to evaluate immune and metabolic blood markers which discriminate between sepses (including COVID-19) from other acute illnesses in critically unwell children and young persons, up to 18 years of age. METHODS AND ANALYSIS: We describe a prospective cohort study for comparing the immune and metabolic whole-blood markers in patients with sepsis, COVID-19 and other illnesses. Clinical phenotyping and blood culture test results will provide a reference standard to evaluate the performance of blood markers from the research sample analysis. Serial sampling of whole blood (50 µL each) will be collected from children admitted to intensive care and with an acute illness to follow time dependent changes in biomarkers. An integrated lipidomics and RNASeq transcriptomics analyses will be conducted to evaluate immune-metabolic networks that discriminate sepsis and COVID-19 from other acute illnesses. This study received approval for deferred consent. ETHICS AND DISSEMINATION: The study has received research ethics committee approval from the Yorkshire and Humber Leeds West Research Ethics Committee 2 (reference 20/YH/0214; IRAS reference 250612). Submission of study results for publication will involve making available all anonymised primary and processed data on public repository sites. TRIAL REGISTRATION NUMBER: NCT04904523.

Enhancement of oxidative stability of soybean oil via nano-emulsification of eggplant peel extract: Process development and application.

To extend the oxidative stability of soybean oil with encapsulated natural antioxidants, eggplant peel-based water-in-oil (W/O) nanoemulsions were formulated. The nanoemulsions were developed with eggplant peel extract (1000-9000 ppm) and CR-310 emulsifier (8-10 %) via ultrasonication. Seven W/O nanoemulsion formulations exhibited high sedimentation stability (sedimentation index > 92.58 %), a mean droplet diameter < 100 nm and low polydispersity index (<0.25) during 30 days storage. These nanoemulsions achieved controlled release of polyphenols. The low conjugated diene and p-anisidine value (Schaal oven parameters) of the nanoemulsions compared to pure soybean oil and commercial soybean oil suggested that these W/O nanoemulsions restricted oxidation better than these oils. Moreover, they could control the oxidation of soybean oil for approximately 10-15 days under accelerated storage conditions. Further, the induction period in Rancimat also indicated that the nanoemulsions possessed higher oxidative stability compared to pure soybean oil while three nanoemulsions even exhibited higher induction period than commercial soybean oil.

Printable Graphene-Sustainable Elastomer-Based Cross Talk Free Sensor for Point of Care Diagnostics.

Developing sensors for monitoring physiological parameters such as temperature and strain for point of care (POC) diagnostics is critical for better care of the patients. Various commercial sensors are available to get the job done; however, challenges like the structural rigidity of such sensors confine their usage. As an alternative, flexible sensors have been looked upon recently. In most cases, flexible sensors cannot discriminate the signals from different stimuli. While there have been reports on the printable sensors providing cross-talk-free solutions, research related to developing sensors from a sustainable source providing discriminability between signals is not well-explored. Herein, we report the development of a stencil printable composition made of graphene and epoxidized natural rubber. The stencil printability index was vetted using rheological studies. Post usage, the developed sensor was dissolved in an organic solvent at room temperature. This, along with the choice of a sustainable elastomer, warrants the minimization of electronic waste and carbon footprint. The developed material demonstrated good conformability with the skin and could perceive and decouple the signals from temperature and strain without inducing any crosstalks. Using a representative volume element model, a comparison between experimental findings and computation studies was made. The developed sensors demonstrated gauge factors of -506 and 407 in the bending strain regimes of 0-0.04% and 0.04%-0.09%, respectively, while the temperature sensitivity was noted to be -0.96%/°C. The printed sensors demonstrated a multifunctional sensing behavior for monitoring various active physiological parameters ranging from temperature, strain, pulse, and breathing to auditory responses. Using a Bluetooth module, various parameters like temperature and strain could be monitored seamlessly in a smart-phone. The current development would be crucial to open new avenues to fabricate crosstalk-free sensors from sustainable sources for POC diagnostics.

Immune-metabolic adaptations in pregnancy: A potential stepping-stone to sepsis.

Physiological shifts during pregnancy predispose women to a higher risk of developing sepsis resulting from a maladapted host-response to infection. Insightful studies have delineated subtle point-changes to the immune system during pregnancy. Here, we present an overlay of these point-changes, asking what changes and when, at a physiological, cellular, and molecular systems-level in the context of sepsis. We identify distinct immune phases in pregnancy delineated by placental hormone-driven changes in homeostasis setpoints of the immune and metabolic systems that subtly mirrors changes observed in sepsis. We propose that pregnancy immune-metabolic setpoint changes impact feedback thresholds that increase risk for a maladapted host-response to infection and thus act as a stepping-stone to sepsis. Defining maternal immune-metabolic setpoint changes is not only vital for tailoring the right diagnostic tools for early management of maternal sepsis but will facilitate an unravelling of the pathophysiological pathways that predispose an individual to sepsis.

mSep: investigating physiological and immune-metabolic biomarkers in septic and healthy pregnant women to predict feto-maternal immune health - a prospective observational cohort study protocol.

INTRODUCTION: Maternal sepsis remains a leading cause of death in pregnancy. Physiological adaptations to pregnancy obscure early signs of sepsis and can result in delays in recognition and treatment. Identifying biomarkers that can reliably diagnose sepsis will reduce morbidity and mortality and antibiotic overuse. We have previously identified an immune-metabolic biomarker network comprising three pathways with a >99% accuracy for detecting bacterial neonatal sepsis. In this prospective study, we will describe physiological parameters and novel biomarkers in two cohorts-healthy pregnant women and pregnant women with suspected sepsis-with the aim of mapping pathophysiological drivers and evaluating predictive biomarkers for diagnosing maternal sepsis. METHODS AND ANALYSIS: Women aged over 18 with an ultrasound-confirmed pregnancy will be recruited to a pilot and two main study cohorts. The pilot will involve blood sample collection from 30 pregnant women undergoing an elective caesarean section. Cohort A will follow 100 healthy pregnant women throughout their pregnancy journey, with collection of blood samples from participants at routine time points in their pregnancy: week 12 'booking', week 28 and during labour. Cohort B will follow 100 pregnant women who present with suspected sepsis in pregnancy or labour and will have at least two blood samples taken during their care pathway. Study blood samples will be collected during routine clinical blood sampling. Detailed medical history and physiological parameters at the time of blood sampling will be recorded, along with the results of routine biochemical tests, including C reactive protein, lactate and white blood cell count. In addition, study blood samples will be processed and analysed for transcriptomic, lipidomic and metabolomic analyses and both qualitative and functional immunophenotyping. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Wales Research Ethics Committee 2 (SPON1752-19, 30 October 2019). TRIAL REGISTRATION NUMBER: NCT05023954.

Printable Carbon Nanotube-Liquid Elastomer-Based Multifunctional Adhesive Sensors for Monitoring Physiological Parameters.

Developing a printed elastomeric wearable sensor with good conformity and proper adhesion to skin, coupled with the capability of monitoring various physiological parameters, is very crucial for the development of point-of-care sensing devices with high precision and sensitivity. While there have been previous reports on the fabrication of elastomeric multifunctional sensors, research on the printable elastomeric multifunctional adhesive sensor is not very well explored. Herein, we report the development of a stencil printable multifunctional adhesive sensor fabricated in a solvent-free condition, which demonstrated the capability of having good contact with skin and its ability to function as a temperature and strain sensor. Functionalized liquid isoprene rubber was selected as the matrix while carboxylated multiwalled carbon nanotubes (c-CNTs) were used as the nanofiller. The selection of the above model compounds facilitated the printability and also helped the same composition to demonstrate stretchability and adhesiveness. A realistic three-dimensional microstructure (representative volume element model) was generated through a computational framework for the current c-CNT-liquid elastomer. Further computational simulations were performed to test and validate the correlation between electrical responses to that of experimental studies. Various physiological parameters like motion sensing, pulse, respiratory rate, and phonetics detection were detected by leveraging the electrically resistive nature of the sensor. This development route can be extended toward developing different innovative adhesives for point-of-care sensing applications.