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1. Highly Sensitive Wearable Sensor Based on (001)‐Orientated TiO ₂ for Real‐Time Electrochemical Detection of Dopamine, Tyrosine, and Paracetamol

   https://doi.org/10.1002/smll.202312238  

   Zhang, Tianyao; Zhu, Jia; Xie, Maowen; Meng, Ke; Yao, Guang; Pan, Taisong; Gao, Min; Cheng, Huanyu; Lin, Yuan (February 2024, Small)

   Abstract The concentration of dopamine (DA) and tyrosine (Tyr) reflects the condition of patients with Parkinson's disease, whereas moderate paracetamol (PA) can help relieve their pain. Therefore, real‐time measurements of these bioanalytes have important clinical implications for patients with Parkinson's disease. However, previous sensors suffer from either limited sensitivity or complex fabrication and integration processes. This work introduces a simple and cost‐effective method to prepare high‐quality, flexible titanium dioxide (TiO₂) thin films with highly reactive (001)‐facets. The as‐fabricated TiO₂film supported by a carbon cloth electrode (i.e., TiO₂–CC) allows excellent electrochemical specificity and sensitivity to DA (1.390 µA µM⁻¹ cm⁻²), Tyr (0.126 µA µM⁻¹ cm⁻²), and PA (0.0841 µA µM⁻¹ cm⁻²). More importantly, accurate DA concentration in varied pH conditions can be obtained by decoupling them within a single differential pulse voltammetry measurement without additional sensing units. The TiO₂–CC electrochemical sensor can be integrated into a smart diaper to detect the trace amount of DA or an integrated skin‐interfaced patch with microfluidic sampling and wireless transmission units for real‐time detection of the sweat Try and PA concentration. The wearable sensor based on TiO₂–CC prepared by facile manufacturing methods holds great potential in the daily health monitoring and care of patients with neurological disorders. 

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2. A Highly Sensitive and Long‐Term Stable Wearable Patch for Continuous Analysis of Biomarkers in Sweat

   https://doi.org/10.1002/adfm.202306117  

   Lorestani, Farnaz; Zhang, Xianzhe; Abdullah, Abu_Musa; Xin, Xin; Liu, Yushen; Rahman, Md_Mashfiqur; Biswas, Md_Abu_Sayeed; Li, Bowen; Dutta, Ankan; Niu, Zhenyuan; et al (September 2023, Advanced Functional Materials)

   Abstract Although increasing efforts have been devoted to the development of non‐invasive wearable electrochemical sweat sensors for monitoring physiological and metabolic information, most of them still suffer from poor stability and specificity over time and fluctuating temperatures. This study reports the design and fabrication of a long‐term stable and highly sensitive flexible electrochemical sensor based on nanocomposite‐modified porous graphene by facile laser treatment for detecting biomarkers such as glucose in sweat. The laser‐reduced and patterned stable conductive nanocomposite on the porous graphene electrode provides the resulting glucose sensor with an excellent sensitivity of 1317.69 µA mm⁻¹cm⁻²and an ultra‐low limit of detection of 0.079 µm. The sensor can also detect pH and exhibit extraordinary stability to maintain more than 91% sensitivity over 21 days in ambient conditions. Taken together with a temperature sensor based on the same material system, the dual glucose and pH sensor integrated with a flexible microfluidic sweat sampling network further results in accurate continuous on‐body glucose detection calibrated by the simultaneously measured pH and temperature. The low‐cost, highly sensitive, and long‐term stable platform could facilitate the early identification and continuous monitoring of different biomarkers for non‐invasive disease diagnosis and treatment evaluation. 

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3. Development of a nanocopper-decorated laser-scribed sensor for organophosphorus pesticide monitoring in aqueous samples

   https://doi.org/10.1007/s00604-022-05355-w  

   Bahamon-Pinzon, David; Moreira, Geisianny; Obare, Sherine; Vanegas, Diana (July 2022, Microchimica Acta)

   Abstract     Organophosphorus pesticides are widely used in industrial agriculture and have been associated with water pollution and negative impacts on local ecosystems and communities. There is a need for testing technologies to detect the presence of pesticide residues in water sources, especially in developing countries where access to standard laboratory methods is cost prohibitive. Herein, we outline the development of a facile electrochemical sensor for amperometric determination of organophosphorus pesticides in environmental water samples. A three-electrode system was fabricated via UV laser-inscribing on a polyimide film. The working electrode was functionalized with copper nanoparticles with affinity toward organophosphate compounds. The sensor showed a limit of detection (LOD) of 3.42 ± 1.69 µM for glyphosate, 7.28 ± 1.20 µM for glufosinate, and 17.78 ± 7.68 µM for aminomethylphosphonic acid (AMPA). Sensitivity was highest for glyphosate (145.52 ± 36.73 nA⋅µM −1 ⋅cm −2 ) followed by glufosinate (56.98 ± 10.87 nA⋅µM −1 ⋅cm −2 ), and AMPA (30.92 ± 8.51 nA⋅µM −1 ⋅cm −2 ). The response of the sensor is not significantly affected by the presence of several ions and organic molecules commonly present in natural water samples. The developed sensor shows promising potential for facilitating environmental monitoring of organophosphorus pesticide residues, which is a current need in several parts of the world. Graphical Abstract 

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4. Two-Dimensional Tellurium Nanosheets for the Efficient Nonenzymatic Electrochemical Detection of H2O2

   https://doi.org/10.3390/chemosensors12020017  

   Shringi, Amit Kumar; Kumar, Rajeev; Dennis, Netanya F.; Yan, Fei (February 2024, Chemosensors)

   This study reports, for the first time, the utilization of two-dimensional (2D) tellurium (Te) nanosheets for the efficient nonenzymatic detection of hydrogen peroxide (H2O2). H2O2 acts as a pivotal biomarker with widespread applications across environmental, biological, industrial, and food processing domains. However, an excessive accumulation of H2O2 in the body poses a severe threat to human life. Consequently, the imperative need for a selective, sensitive, and cost-effective sensing platform for H2O2 detection has gained paramount significance. Employing a low-cost and straightforward hydrothermal method, Te nanosheets were synthesized to address the escalating demand for a reliable detection platform. The as-synthesized Te nanosheets are characterized through Raman spectroscopy and atomic force microscopy techniques. The electrochemical performance of the Te nanosheets integrated onto a glassy carbon (Te-GC) electrode was thoroughly investigated using cyclic voltammetry, differential pulse voltammetry, and chronoamperometry. The experiments were designed to evaluate the response of the Te-GC electrode in the presence and absence of H2O2, alongside its performance in the detection of other pertinent interfering analytes. The sensor shows a limit of detection of 0.47 µM and a sensitivity of 27.2 µA µM−1 cm−2 towards H2O2. The outcomes of this study demonstrate the efficacy of Te nanosheets as a promising material for nonenzymatic H2O2 detection in urine samples. The simplicity and cost-effectiveness of the hydrothermal synthesis process, coupled with the notable electrochemical performance of the Te/GC electrode, highlight the potential of Te nanosheets in the development of a robust sensing platform. This research contributes to the ongoing efforts to enhance our capabilities in monitoring and detecting H2O2, fostering advancements in environmental, biomedical, and industrial applications. 

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5. Evaluation of GPT-4 ability to identify and generate patient instructions for actionable incidental radiology findings

   https://doi.org/10.1093/jamia/ocae117  

   Woo, Kar-mun_C; Simon, Gregory_W; Akindutire, Olumide; Aphinyanaphongs, Yindalon; Austrian, Jonathan_S; Kim, Jung_G; Genes, Nicholas; Goldenring, Jacob_A; Major, Vincent_J; Pariente, Chloé_S; et al (May 2024, Journal of the American Medical Informatics Association)

   Abstract ObjectivesTo evaluate the proficiency of a HIPAA-compliant version of GPT-4 in identifying actionable, incidental findings from unstructured radiology reports of Emergency Department patients. To assess appropriateness of artificial intelligence (AI)-generated, patient-facing summaries of these findings. Materials and MethodsRadiology reports extracted from the electronic health record of a large academic medical center were manually reviewed to identify non-emergent, incidental findings with high likelihood of requiring follow-up, further sub-stratified as “definitely actionable” (DA) or “possibly actionable—clinical correlation” (PA-CC). Instruction prompts to GPT-4 were developed and iteratively optimized using a validation set of 50 reports. The optimized prompt was then applied to a test set of 430 unseen reports. GPT-4 performance was primarily graded on accuracy identifying either DA or PA-CC findings, then secondarily for DA findings alone. Outputs were reviewed for hallucinations. AI-generated patient-facing summaries were assessed for appropriateness via Likert scale. ResultsFor the primary outcome (DA or PA-CC), GPT-4 achieved 99.3% recall, 73.6% precision, and 84.5% F-1. For the secondary outcome (DA only), GPT-4 demonstrated 95.2% recall, 77.3% precision, and 85.3% F-1. No findings were “hallucinated” outright. However, 2.8% of cases included generated text about recommendations that were inferred without specific reference. The majority of True Positive AI-generated summaries required no or minor revision. ConclusionGPT-4 demonstrates proficiency in detecting actionable, incidental findings after refined instruction prompting. AI-generated patient instructions were most often appropriate, but rarely included inferred recommendations. While this technology shows promise to augment diagnostics, active clinician oversight via “human-in-the-loop” workflows remains critical for clinical implementation. 

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