Personal Monitoring Research Articles

Guidelines of the Brazilian Society of Surgical Oncology for anatomopathological, immunohistochemical, and molecular testing in female tumors.

Precision medicine has revolutionized oncology, providing more personalized diagnosis, treatment, and monitoring for patients with cancer. In the context of female-specific tumors, such as breast, ovarian, endometrial, and cervical cancer, proper tissue collection and handling are essential for obtaining tissue, immunohistochemical (IHC), and molecular data to guide therapeutic decisions. To establish guidelines for the collection and handling of tumor tissue, to enhance the quality of samples for histopathological, IHC, genomic, and molecular analyses. These guidelines are fundamental in informing therapeutic decisions in cancer treatment. The guidelines were developed by a multidisciplinary panel of renowned specialists between June 12, 2013 and February 12, 2024. Initially, the panel deliberated on critical and controversial topics related to conducting precision medicine studies focusing on female tumors. Subsequently, 22 pivotal topics were identified within the framework and assigned to groups. These groups reviewed relevant literature and drafted preliminary recommendations. Following this, the recommendations were reviewed by the coordinators and received unanimous approval. Finally, the groups made the final adjustments, classified the level of evidence, and ranked the recommendations. The collection of surgical samples requires minimum quality standards to enable histopathological, IHC, genomic, and molecular analyses. These analyses provide crucial data for informing therapeutic decisions, significantly impacting potential survival gains for patients with female tumors.

Assessment of PM2.5 Concentration at University Transit Bus Stops Using Low-Cost Aerosol Monitors by Student Commuters.

Particulate matter of 2.5 µm and smaller (PM2.5) is known to cause many respiratory health problems, such as asthma and heart disease. A primary source of PM2.5 is emissions from cars, trucks, and buses. Emissions from university transit bus systems could create zones of high PM2.5 concentration at their bus stops. This work recruited seven university students who regularly utilized the transit system to use a low-cost personal aerosol monitor (AirBeam) each time they arrived at a campus bus stop. Each participant measured PM2.5 concentrations every time they were at a transit-served bus stop over four weeks. PM2.5 concentration data from the AirBeam were compared with an ADR-1500 high-cost monitor and EPA PM2.5 reference measurements. This methodology allowed for identifying higher-than-average concentration zones at the transit bus stops compared to average measurements for the county. By increasing access to microenvironmental data, this project can contribute to public health efforts of personal protection and prevention by allowing individuals to measure and understand their exposure to PM2.5 at the bus stop. This work can also aid commuters, especially those with pre-existing conditions who use public transportation, in making more informed health decisions and better protecting themselves against new or worsening respiratory conditions.

Nanoarchitectonics of Fe single-atom catalyst modified with flexible wearable patch for sweat biomarker analysis

In personalized medical diagnostics and health monitoring, the analysis of biomarkers in sweat, such as uric acid (UA) and dopamine (DA), offers valuable insights into metabolic states. This study introduces a flexible wearable patch based on Fe single-atom catalysts (FeSAs) to simultaneously detect UA and DA in sweat for comprehensive health assessment. Our wearable patch demonstrated linear response ranges of 1–800 μM for UA and 1–500 μM for DA, with detection limits of 2.68 μM and 3.76 μM, and sensitivities of 0.015 μA μM−1 cm−2 and 0.0176 μA μM−1 cm−2, respectively. Additionally, we integrated agarose hydrogel into the wearable patches, optimizing sweat collection efficiency at agarose concentrations ranging from 2 % to 3.8 %. This innovation enables effective biomarker enrichment directly from the skin surface. In conclusion, our study presents an innovative FeSAs-based electrocatalyst capable of simultaneous detection of low-concentration UA and DA biomarkers.

Conjugation Linked PEDOT:PSS with Low Impedance and High Stretchability for Epidermal Electrophysiology.

Long-term epidermal recording of bioelectricity is of paramount importance for personal health monitoring. It requires stretchable and dry film electrodes that can be seamlessly integrated with skin. The simultaneous achievement of high conductivity and skin-like ductility of conducting materials is a prerequisite for reliable signal transduction at the dynamic interface, which is also the bottleneck of epidermal electrophysiology. Here, carbon nanotubes (CNTs) are introduced as "conjugation linkers" into a topologically plasticized conducting polymer (PEDOT:PSS). A thin-film electrode with high conductivity (≈3250Scm-1) and high stretchability (crack-onset strain>100%) is obtained. In particular, the conjugation linker enables the high volumetric capacitance and the low film resistance, both of which synergically reduce the interfacial impedance. The capabilities of this electrode is further demonstrated in the precise recording of various electrophysiological signals.

Cloud-Connected Patch-Worn Auscultation Device for Chest Sound Monitoring.

AbstractIn recent years, wearable electrocardiograms have risen in popularity as a solution for personal monitoring of heart activity. However, this technology has limitations in diagnostic capability and structural function monitoring. Meanwhile, auscultation of the heart remains a fundamental tool for physicians in diagnosis and monitoring of heart disease largely unaddressed in a convenient wearable format. The present work outlines a promising system currently under investigation, allowing user-initiated 10-second chest-sound recordings to be transmitted over Bluetooth-Low-Energy, with an innovative package design providing inherent noise reduction and a high signal-to-noise ratio. The device has been tested on healthy individuals, and system response has been validated against calibrated electrocardiogram recording equipment to analyze signal capture fidelity.Abstract Figure

Radiomics-Guided Deep Learning Networks Classify Differential Diagnosis of Parkinsonism.

The differential diagnosis between atypical Parkinsonian syndromes may be challenging and critical. We aimed to proposed a radiomics-guided deep learning (DL) model to discover interpretable DL features and further verify the proposed model through the differential diagnosis of Parkinsonian syndromes. We recruited 1495 subjects for 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) scanning, including 220 healthy controls and 1275 patients diagnosed with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA), or progressive supranuclear palsy (PSP). Baseline radiomics and two DL models were developed and tested for the Parkinsonian diagnosis. The DL latent features were extracted from the last layer and subsequently guided by radiomics. The radiomics-guided DL model outperformed the baseline radiomics approach, suggesting the effectiveness of the DL approach. DenseNet showed the best diagnosis ability (sensitivity: 95.7%, 90.1%, and 91.2% for IPD, MSA, and PSP, respectively) using retained DL features in the test dataset. The retained DL latent features were significantly associated with radiomics features and could be interpreted through biological explanations of handcrafted radiomics features. The radiomics-guided DL model offers interpretable high-level abstract information for differential diagnosis of Parkinsonian disorders and holds considerable promise for personalized disease monitoring.

Influence of Visual Stimulus Changes in a Virtual Environment on Postural Control: Focusing on a Hallway Walking Simulation

The purpose of this study was to clarify the effects of the standing center of gravity sway by providing visual stimulus information as if the subjects were walking in virtual reality (VR) and by monitoring conditions with different corridor widths. We included 25 healthy young individuals in our study. The center of gravity sway was measured during open- and closed-eye static standing using images of walking in corridors of different widths (780 and 1600 mm) presented on a VR and personal computer monitor (Monitor). The parameters measured for the center of gravity sway were swing path length (SPL), height of excursion (HoE), and width of excursion (WoE). The results showed that the SPL and HoE values were significantly greater in the VR group than those in the Monitor group. The greater center of gravity sway in the VR compared with the Monitor group can be attributed to the ability of the head-mounted VR display to cover the entire field of vision and its head-tracking function. There was no change in the center of gravity sway with respect to the corridor width, which may be because the width of the corridor alone did not provide sufficient visual stimulation to affect physical function. This research could lead to further studies which could impact the motivation of patients for rehabilitation therapies.

Wearable Voice Dosimetry System

The objective quantification of voice acoustic parameters is used for the diagnosis, monitoring, and treatment of voice disorders. Such assessments are carried out with specialised equipment within the doctor’s office. The controlled conditions employed are usually not those of the real environment of the patient. The results, although very informative, are specific to those measurement conditions and to the time when they were performed. A wearable voice monitoring system, based on an accelerometer to ensure the message, can overcome these limitations. We present a miniaturised, low-power, and low-cost wearable system to estimate and record voice fundamental frequency (F0), intensity and phonation time for long intervals in the everyday environment of the patient. It was tested on two subjects for up to two weeks of recording time. It was possible to identify distinct periods in vocal activity, such as normal, professional, demanding or hyperfunctional. It provided information on the workload that the vocal cords needed to cope with over time and when and to what extent that workload was concentrated. The proposed voice dosimetry system enables the extraction and recording of voice parameters for long periods of time in the everyday environment of the patient, allowing the objectification of vocal risk situations and personalised treatment and monitoring.

P-730 A feasibility study of the impact of the level of exposure to ambient air pollutants on outcomes of assisted reproductive technologies

Abstract Study question What is the impact of air pollution exposure on outcomes for couples having IVF treatment? Summary answer Environmental exposure to high levels of air pollutants may negatively influence IVF outcomes with potential implications for fertility treatment. What is known already Air pollutants are harmful substances in the atmosphere that have adverse effects on human health. Increased levels of air pollutants have been associated with respiratory disorders, cardiovascular disease, and increased morbidity in humans across all age groups. Existing evidence suggests that increased exposure to air pollutants may adversely affect fertility. The relationship between air pollutants and IVF outcomes remains poorly understood. Study design, size, duration This was an ethically approved prospective observational feasibility study conducted over a two-year period. Ten couples due to undergo an IVF cycle were recruited from a fertility centre in the UK. Environmental exposure to ambient air pollutant for particulate matter (PM) 2.5 and 10 micron size was measured using portable AirBeam monitors over the course of two weeks from commencement of the ovarian stimulation regime. Participants/materials, setting, methods Eligible participants were those aged 18-35 years old, undergoing fresh IVF, with a good ovarian reserve and ability to provide informed consent. Data of interest included: BMI, age, parity, ethnicity, smoking status. IVF data included: number of oocytes retrieved, embryo quality and cycle outcomes. AirBeam device data was extracted, analysed and correlated with IVF outcomes. Participants feedback was sought for qualitative input for future studies. Main results and the role of chance Total of 28,269 data points of ambient air pollutant data for PM 2.5 and 10 micron size were recorded amongst the ten participants. One participant was exposed to significantly high air pollutant levels during ovarian stimulation on certain days (PM2.5 - 81.06 µg/m³ and PM10 - 154.48 µg/m³) compared to standard annual air pollution level for the UK of 25 µg/m³ for PM2.5 and 40 µg/m³ for PM10. Two women did not have embryo transfer due to embryo arrest. Of those who had transfer, 50% (n = 4) had positive pregnancy tests however three experienced early pregnancy losses. At the time of writing there was one ongoing single viable pregnancy. On correlation of air quality data with clinical outcomes, the one participant who exhibited fluctuant very high exposure levels to the measured air pollutants, had unexpected low fertilization rate (20%) with IVF and no transfer due to embryo arrest. Of the nine participants returning the questionnaire feedback, all but one rated it acceptable to most acceptable to carry the device around. The main barrier was the size of device and battery life. All respondents were willing to recommend others to participate in a future similar study confirming feasibility to recruit. Limitations, reasons for caution As a feasibility study, with a limited sample size, our findings should be interpreted cautiously. The small cohort limits the generalisability of our results. Further research with larger sample sizes is required to validate our findings. Wider implications of the findings Understanding the impact of air pollutants on IVF outcomes is important for developing evidence-based guidance and interventions to optimise fertility treatment efficacy. Our study demonstrates the feasibility of personal air quality monitoring and emphasises the necessity for larger scale research and the practicality of pollutant exposure measurements in fertility treatments. Trial registration number REC reference: 21/NE/0233 IRAS project ID: 294240. Theramex BIRTH Grant

Lightweight, robust and conductive MXene/SiO2 nanofiber aerogels for excellent sensing and thermal management properties

Flexible pressure sensors embody outstanding mechanical and sensing performance, particularly in the fields of personal health monitoring and artificial intelligence, while catering to multifunctional applications resilient against harsh weather conditions. Among these, Ti3C2Tx MXene-based aerogel materials with high surface area and excellent conductivity have attracted a lot of attention. However, there are big challenges in improving the mechanical properties at low densities and designing multi-level pore structures. Herein, the prepared silane monomers (MP) are firstly synthesized by 3-(Trimethoxysilyl) propyl methacrylate (MPTES) and polyethylene glycol diacrylate (PEGDA), then polydopamine-modified silicon dioxide (PDA-SiO2) nanofibers employed with MXene nanosheets form covalent cross-linking nanofiber aerogels. The multi-level stable structure improves both mechanical strength and elasticity. The assembled MXene/MP/PDA-SiO2 pressure sensors exhibit a high sensitivity of −0.83 kPa−1, a rapid response time of 48 ms, a minimum 1 % strain detection limit, and reliable stability over 10,000 cycles. Furthermore, these sensors can be used for human motion detection and health diagnostics, and show good personal thermal management performance. This work holds a promising candidate for the next generation of multifunctional flexible electronic devices.

ChatGPT in orthodontics: limitations and possibilities

Abstract Artificial Intelligence (AI) simulates human intelligence in machines capable of rational response and actions. AI’s growth in healthcare, particularly in dentistry, has been remarkable in aiding clinical practices from appointment scheduling to treatment outcome predictions. In orthodontics, AI effectively handles tasks such as automated landmark detection, diagnosing orthodontic needs, assessing maxillary constriction, and selecting appliances. ChatGPT, an AI-based program by OpenAI, excels in generating human-like responses, making it useful across many applications, including those in dentistry. AI enhances personalised patient communication, supports diagnosis and decision-making, digitises patient data, and aids in disease prevention and treatment. In addition, ChatGPT offers support in personalised care, billing, and patient health monitoring. Patients benefit from its help in finding providers, scheduling initial appointments, accessing health information, improving healthcare access and service effectiveness. However, there are limitations. ChatGPT sometimes produces nonsensical responses and poses privacy risks associated with patient data. Generated medical advice might not therefore match professional expertise. Despite these issues, if trained properly, ChatGPT could significantly enhance medical knowledge dissemination. Future studies should weigh the benefits of AI against its risks, and users must verify AI-generated information with reliable sources to ensure effective patient care.

YOLO-Based Personal Protective Equipment Monitoring System for Workplace Safety

Occupational health and safety are of paramount importance in industrial environments and various work fields. In this context, tracking personal protective equipment (PPE) is highly necessary. This article investigates the performance and application of deep learning-based object detection models to enhance the accuracy and speed of tracking personal protective equipment for ensuring occupational health and safety. These models detect personal protective equipment in images, enabling monitoring of their correct usage and intervention when necessary. The study aims to minimize damage resulting from accidents through the use of protective equipment and to prevent possible accidents. In our study, a dataset consisting of 2581 images, encompassing different workplace environments and workers, was prepared. This dataset was evaluated for performance using deep learning models. Popular deep-learning models such as YOLO-NAS, YOLOv8, and YOLOv9 were utilized in the comparisons. During the training of the models, the number of epochs was kept consistent for fair comparison. Upon examining the results, it is observed that the YOLO-NAS and YOLOv9 models generally exhibit similar and high performance.

Viscoelastic Adhesive, Super-Conformable, and Semi-Flowable Liquid Metal Eutectogels for High-Fidelity Electrophysiological Monitoring.

Integrating gels with human skin through wearables provides unprecedented opportunities for health monitoring technology and artificial intelligence. However, most conductive hydrogels, organogels, and ionogels lack essential environmental stability, biocompatibility, and adhesion for reliable epidermal sensing. In this study, we have developed a liquid metal eutectogel simultaneously possessing superior viscoelasticity, semiflowability, and mechanical rigidity for low interfacial skin impedance, high skin adhesion, and durability. Liquid metal particles (LMPs) are employed to generate free radicals and gallium ions to accelerate the polymerization of acrylic acid monomers in a deep eutectic solvent (DES), obtaining highly viscoelastic polymer networks via physical cross-linking. In particular, graphene oxide (GO) is utilized to encapsulate the LMPs through a sonication-assisted electrostatic assembly to stabilize the LMPs in DES, which also enhances the mechanical toughness and regulates the rheological properties of the eutectogels. Our optimized semi-flowable eutectogel exhibits viscous fluid behavior at low shear rates, facilitating a highly conformable interface with hairy skin. Simultaneously, it demonstrates viscoelastic behavior at high shear rates, allowing for easy peel-off. These distinctive attributes enable the successful applications of on-skin adhesive strain sensing and high-fidelity human electrophysiological (EP) monitoring, showcasing the versatility of these ionically conductive liquid metal eutectogels in advanced personal health monitoring.

Knitting Elastic Conductive Fibers of MXene/Natural Rubber for Multifunctional Wearable Sensors.

Wearable electronic sensors have recently attracted tremendous attention in applications such as personal health monitoring, human movement detection, and sensory skins as they offer a promising alternative to counterparts made from traditional metallic conductors and bulky metallic conductors. However, the real-world use of most wearable sensors is often hindered by their limited stretchability and sensitivity, and ultimately, their difficulty to integrate into textiles. To overcome these limitations, wearable sensors can incorporate flexible conductive fibers as electrically active components. In this study, we adopt a scalable wet-spinning approach to directly produce flexible and conductive fibers from aqueous mixtures of Ti3C2Tx MXene and natural rubber (NR). The electrical conductivity and stretchability of these fibers were tuned by varying their MXene loading, enabling knittability into textiles for wearable sensors. As individual filaments, these MXene/NR fibers exhibit suitable conductivity dependence on strain variations, making them ideal for motivating sensors. Meanwhile, textiles from knitted MXene/NR fibers demonstrate great stability as capacitive touch sensors. Collectively, we believe that these elastic and conductive MXene/NR-based fibers and textiles are promising candidates for wearable sensors and smart textiles.

Survey on barriers to psychiatrists' use of clozapine for young people in Scotland and suggestions for reducing these.

The Mental Welfare Commission for Scotland published a report into the death of a young person, with recommendations for the Royal College of Psychiatry in Scotland Child and Adolescent Faculty; to explore if there were barriers to the use of Clozapine in young people in Scotland. A mixed-methods study was performed using a cross-sectional survey of clinicians working in child and adolescent psychiatry across Scotland, to determine attitudes towards clozapine use and the perceived barriers and facilitators to clozapine treatment. Results suggest that there may be a lack of clearly defined pathways within and between services, as well as a lack of resources provided for the necessary monitoring of a young person started on clozapine. Multiple respondents felt unskilled in clozapine initiation and had not accessed formal training. The most frequently mentioned themes for improving facilitation of clozapine prescription were that of increased resources and training. National policymakers including the Mental Welfare Commission, NHS Education for Scotland, and NHS Scotland should consider these findings to address the potential underutilisation of clozapine for people aged under 18 in services across Scotland. A review of current service provision should take place, with consideration of whether the facilitators to clozapine prescription which our study has highlighted could be implemented more effectively. This may help reduce identified barriers and increase clozapine prescription to those who would benefit from it, potentially improving outcomes for young people with treatment-resistant psychosis.

Ultrasensitive and highly selective NO2 gas sensing of porous MXene nanoribbon assemblies

Nitrogen dioxide (NO2), a potential source for acid rain and photochemical smog, is known to harm human health, plant growth and crop yield, and the environment. Therefore, designing a room temperature operable NO2 gas sensor with exceptional sensitivity and selectivity is extremely important. Herein, we report that Ti3C2Tx MXene (Tx = –OH, –O, –F, etc.) nanoribbons containing inbuilt anatase TiO2 on their surfaces achieve highly sensitive detection of NO2 gas at room temperature with negligible cross-responses to other gas analytes. The MXene nanoribbons' ability to form porous gas sensor film facilitates the efficient diffusion of gas molecules and the sufficient utilization of surface-active sites, leading to a high response of −87.5 % to 50 ppm NO2 gas exposure with a response time of 9.2 s at room temperature. Signifying the low concentration NO2 detection abilities, MXene nanoribbons displayed a response of −4.4 % towards 500 ppb NO2 exposure. MXene nanoribbons' NO2 gas sensing ability is carrier gas dependent and declines monotonically as operating temperature increases. In addition, the performance comparison experiments conducted at 50 ppm NO2 gas exposure suggest that the MXene nanoribbons' response is 14.3, 1.6, and 45.3 times higher than the responses of multilayer MXene, MXene-TiO2 nanoplate, and MXene-TiO2 nanoparticle structures, respectively. The explicit selectivity and high sensitivity of MXene nanoribbons toward NO2 gas are expected to provide exciting opportunities for personal safety and environmental monitoring.

Spatial and temporal determinants of particulate matter peak exposures during pregnancy and early postpartum

BackgroundFine particulate matter (PM2.5) exposure is an important environmental risk for maternal and children's health, with peak exposures especially those derived from primary combustion hypothesized to pose greater risk. Identifying PM2.5 peaks and their contributions to personal exposure remains challenging. This study measured personal PM2.5 exposure, characterized primary combustion peaks, and investigated their determinants during and after pregnancy and among Hispanic women in Los Angeles, CA. MethodsContinuous personal PM2.5 exposure, Global Positioning System geolocation, and ecological momentary assessment surveys were collected from 63 women for 4 consecutive days in their 1st trimester, 3rd trimester and 4–6 months postpartum. Based on the shape of PM2.5 time-series, primary combustion peaks were identified, characterized (number, duration, area under the curve [AUC]), and linked with locations they occurred in. Zero-inflated generalized mixed-effect models were used to examine the spatial and temporal determinants of PM2.5 peak exposures. ResultsA total of 490 PM2.5 peaks were identified from 618 person-days of monitoring. Spending an additional minute at parks and open spaces was related to smaller (AUC decreased 3.1 %, 95 % CI: 1.5 %–4.6 %) and shorter (duration decreased 1.7 %, 0.5 %–2.9 %) PM2.5 peak exposure. An additional minute in vehicular trips also related to smaller and shorter peak exposure (AUC and duration decreased 2.5 %, 1.2 %–3.7 % and 1.8 %, 1.0 %–2.6 %, respectively). However, an additional minute at industrial locations was associated with greater number (3.6 %, 2.0 %–5.2 %), AUC (1.6 %, 0.1 %–3.2 %) and duration (1.0 %, 0.0 %–2.1 %) of personal PM2.5 peak exposure. ConclusionsThis study demonstrates the potential to statistically identify exposure to primary combustion PM2.5 peaks and understand their determinants from personal monitoring data. Results suggest that visits to parks and open spaces may minimize PM2.5 peak exposures, while visiting industrial locations may increase them in and around pregnancy.

Development of Optical Nanosensors for Detection of Potassium Ions and Assessment of Their Biocompatibility with Corneal Epithelial Cells.

Imbalance of potassium-ion levels in the body can lead to physiological dysfunctions, which can adversely impact cardiovascular, neurological, and ocular health. Thus, quantitative measurement of potassium ions in a biological system is crucial for personal health monitoring. Nanomaterials can be used to aid in disease diagnosis and monitoring therapies. Optical detection technologies along with molecular probes emitting within the near-infrared (NIR) spectral range are advantageous for biological measurements due to minimal interference from light scattering and autofluorescence within this spectral window. Herein, we report the development of NIR fluorescent nanosensors, which can quantitatively detect potassium ions under biologically relevant conditions. The optical nanosensors were developed by using photoluminescent single-walled carbon nanotubes (SWCNTs) encapsulated in polymers that contain potassium chelating moieties. The nanosensors, polystyrene sulfonate [PSS-SWCNTs, nanosensor 1 (NS1)] or polystyrene-co-polystyrene sulfonate [PS-co-PSS-SWCNTs, nanosensor 2 (NS2)], exhibited dose-dependent optical responses to potassium ion level. The nanosensors demonstrated their biocompatibility via the evaluation of cellular viability, proliferation assays, and expression of cytokeratin 12 in corneal epithelial cells (CEpiCs). Interestingly, the nanosensors' optical characteristics and their responses toward CEpiCs were influenced by encapsulating polymers. NS2 exhibited a 10 times higher fluorescence intensity along with a higher signal-to-noise ratio as compared to NS1. NS2 showed an optical response to potassium ion level in solution within 5 min of addition and a limit of detection of 0.39 mM. Thus, NS2 was used for detailed investigations including potassium ion level detection in serum. NS2 showed a consistent response to potassium ions at the lower millimolar range in serum. These results on optical sensing along with biocompatibility show a great potential for nanotube sensors in biomedical research.

Evaluation of a pharmacist-led personal continuous glucose monitor workflow to improve glycemic management in an internal medicine clinic

BackgroundThe use of personal continuous glucose monitors (CGMs) in patients with diabetes has increased substantially and is expected to continue to increase as CGMs become more affordable and insurance plans improve coverage. The utilization of CGMs has improved diabetes management and reduced hypoglycemic events. ObjectivesTo create pharmacist-led personal CGM workflow and evaluate its impact on glycemic management in patients with diabetes. Practice DescriptionThe study took place at an Internal Medicine Clinic. The practice providers include 2 medical doctors, 5 physician assistants, 2 nurse practitioners, and 1 clinical pharmacist. Practice InnovationTo create and implement a sustainable pharmacy led CGM workflow for enhanced CGM use within an internal medicine clinic. Evaluation MethodsThis was a prospective, investigator-initiated pilot study conducted at an Atrium Health Internal Medicine clinic over 28 weeks. In this pilot, 42 patients were qualifying candidates with diabetes and personal CGM use. In addition, 30 patients were followed until study completion and included into final analysis. ResultsThe average baseline A1c was reduced from 8.3% to 7.1% over a 3- to 6-month period. The pharmacist-led CGM workflow revealed a statistically significant reduction in A1c from baseline by an average of 1.2% (95% CI −0.6 to −1.8, P = 0.0006). On average, patients were enrolled for 19.9 weeks and had an average of 5 visits during this time. During the study duration, 100 medications changes were implemented under the existing clinical pharmacist practitioner agreement between the pharmacists and the provider. Overall, 58 Current Procedural Terminology 95251 codes were billed yielding $7052.00 in billed CGM services for the clinic. This project generated 40.6 provider relative value units. ConclusionThe utilization of a pharmacist-led personal CGM workflow can improve diabetes outcomes.

Fabrication of multi-sensory Ti3C2Tx MXene/Nylon 6 composite fibers via interfacial deposition method

Here, we present a composite material in the form of Ti3C2Tx MXene/nylon 6 (MPA6) core-shell fibers. These fibers were synthesized through a process involving the systematic stacking of Ti3C2Tx MXene nanosheets to form a continuous film via interfacial self-assembly, followed by coating onto the surface of nylon 6 fibers. Notably, despite a minimal MXene coating of just 1.53 wt%, the MPA6 fibers exhibit remarkable electrical conductivity, reaching 11.39 ± 2.51 S/cm. The interwoven conductive network within the fabric's fibers contributes to its exceptional properties, including rapid response time (with a response time of 63 ms during pressing behavior), fatigue resistance (maintaining a stable response over 300 cycles), and consistent reproducibility of response during repeated cycles. With its increased sensitivity to various human activities, this composite fiber is well-suited for use as a wearable personal activity monitor. Additionally, its exceptional sensitivity to gravitational objects makes it a valuable tool for gravity detection, capable of detecting changes as small as 1 g.