Laser-Induced Electrochemical Biosensor Modified with Graphene-Based Ink for Label-Free Detection of Alpha-Fetoprotein and 17ß-Estradiol.

In this research, a novel electrochemical biosensor is proposed based on inducing graphene formation on polyimide substrate via laser engraving. Graphene polyaniline (G-PANI) conductive ink was synthesized by planetary mixing and applied to the working zone of the developed sensor to effectively enhance the electrical signals. The laser-induced graphene (LIG) sensor was used to detect alpha-fetoprotein (AFP) and 17ß-Estradiol (E2) in the phosphate buffer saline (PBS) buffer and human serum. The electrochemical performance of the biosensor in determining these biomarkers was investigated by differential pulse voltammetry (DPV) and chronoamperometry (CA). In a buffer environment, alpha-fetoprotein (AFP) and 17ß-Estradiol detection range were 4-400 ng/mL and 20-400 pg/mL respectively. The experimental results showed a limit of detection (LOD) of 1.15 ng/mL and 0.96 pg/mL for AFP and estrogen, respectively, with an excellent linear range (R2 = 0.98 and 0.99). In addition, the designed sensor was able to detect these two types of biomarkers in human serum successfully. The proposed sensor exhibited excellent reproducibility, repeatability, and good stability (relative standard deviation, RSD = 0.96%, 1.12%, 2.92%, respectively). The electrochemical biosensor proposed herein is easy to prepare and can be successfully used for low-cost, rapid detection of AFP and E2. This approach provides a promising platform for clinical detection and is advantageous to healthcare applications.

Wearable Alcohol Monitoring Device for the Data-Driven Transcutaneous Alcohol Diffusion Model.

Wearable alcohol monitoring devices demand noninvasive, real-time measurement of blood alcohol content (BAC) reliably and continuously. A few commercial devices are available to determine BAC noninvasively by detecting transcutaneous diffused alcohol. However, they suffer from a lack of accuracy and reliability in the determination of BAC in real time due to the complex scenario of the human skin for transcutaneous alcohol diffusion and numerous factors (e.g., skin thickness, kinetics of alcohol, body weight, age, sex, metabolism rate, etc.). In this work, a transcutaneous alcohol diffusion model has been developed from real-time captured data from human wrists to better understand the kinetics of diffused alcohol from blood to different skin epidermis layers. Such a model will be a footprint to determine a base computational model in larger studies. Eight anonymous volunteers participated in this pilot study. A laboratory-built wearable blood alcohol content (BAC) monitoring device collected all the data to develop this diffusion model. The proton exchange membrane fuel cell (PEMFC) sensor was fabricated and integrated with an nRF51822 microcontroller, LMP91000 miniaturized potentiostat, 2.4 GHz transceiver supporting Bluetooth low energy (BLE), and all the necessary electronic components to build this wearable BAC monitoring device. The %BAC data in real time were collected using this device from these volunteers' wrists and stored in the end device (e.g., smartphone). From the captured data, we demonstrate how the volatile alcohol concentration on the skin varies over time by comparing the alcohol concentration in the initial stage (= 10 min) and later time (= 100 min). We also compare the experimental results with the outputs of three different input profiles: piecewise linear, exponential linear, and Hoerl, to optimize the developed diffusion model. Our results demonstrate that the exponential linear function best fits the experimental data compared to the piecewise linear and Hoerl functions. Moreover, we have studied the impact of skin epidermis thickness within ±20% and demonstrate that a 20% decrease in this thickness results in faster dynamics compared to thicker skin. The model clearly shows how the diffusion front changes within a skin epidermis layer with time. We further verified that 60 min was roughly the time to reach the maximum concentration, Cmax, in the stratum corneum from the transient analysis. Lastly, we found that a more significant time difference between BACmax and Cmax was due to greater alcohol consumption for a fixed absorption time.

Recent Progress and Challenges of Implantable Biodegradable Biosensors.

Implantable biosensors have evolved to the cutting-edge technology of personalized health care and provide promise for future directions in precision medicine. This is the reason why these devices stand to revolutionize our approach to health and disease management and offer insights into our bodily functions in ways that have never been possible before. This review article tries to delve into the important developments, new materials, and multifarious applications of these biosensors, along with a frank discussion on the challenges that the devices will face in their clinical deployment. In addition, techniques that have been employed for the improvement of the sensitivity and specificity of the biosensors alike are focused on in this article, like new biomarkers and advanced computational and data communicational models. A significant challenge of miniaturized in situ implants is that they need to be removed after serving their purpose. Surgical expulsion provokes discomfort to patients, potentially leading to post-operative complications. Therefore, the biodegradability of implants is an alternative method for removal through natural biological processes. This includes biocompatible materials to develop sensors that remain in the body over longer periods with a much-reduced immune response and better device longevity. However, the biodegradability of implantable sensors is still in its infancy compared to conventional non-biodegradable ones. Sensor design, morphology, fabrication, power, electronics, and data transmission all play a pivotal role in developing medically approved implantable biodegradable biosensors. Advanced material science and nanotechnology extended the capacity of different research groups to implement novel courses of action to design implantable and biodegradable sensor components. But the actualization of such potential for the transformative nature of the health sector, in the first place, will have to surmount the challenges related to biofouling, managing power, guaranteeing data security, and meeting today's rules and regulations. Solving these problems will, therefore, not only enhance the performance and reliability of implantable biodegradable biosensors but also facilitate the translation of laboratory development into clinics, serving patients worldwide in their better disease management and personalized therapeutic interventions.

Graphene Nanocomposite Ink Coated Laser Transformed Flexible Electrodes for Selective Dopamine Detection and Immunosensing.

Novel and flexible disposable laser-induced graphene (LIG) sensors modified with graphene conductive inks have been developed for dopamine and interleukin-6 (IL-6) detection. The LIG sensors exhibit high reproducibility (relative standard deviation, RSD = 0.76%, N = 5) and stability (RSD = 4.39%, N = 15) after multiple bendings, making the sensors ideal for wearable and stretchable bioelectronics applications. We have developed electrode coatings based on graphene conductive inks, poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (G-PEDOT:PSS) and polyaniline (G-PANI), for working electrode modification to improve the sensitivity and limit of detection (LOD). The selectivity of LIG sensors modified with the G-PANI ink is 41.47 times higher than that of the screen-printed electrode with the G-PANI ink modification. We have compared our fabricated bare laser-engraved Kapton sensor (LIG) with the LIG sensors modified with G-PEDOT (LIG/G-PEDOT) and G-PANI (LIG/G-PANI) conductive inks. We have further compared the performance of the fabricated electrodes with commercially available screen-printed electrodes (SPEs) and screen-printed electrodes modified with G-PEDOT:PSS (SPE/G-PEDOT:PSS) and G-PANI (SPE/G-PANI). SPE/G-PANI has a lower LOD of 0.632 µM compared to SPE/G-PEDOT:PSS (0.867 µM) and SPE/G-PANI (1.974 µM). The lowest LOD of the LIG/G-PANI sensor (0.4084 µM, S/N = 3) suggests that it can be a great alternative to measure dopamine levels in a physiological medium. Additionally, the LIG/G-PANI electrode has excellent LOD (2.6234 pg/mL) to detect IL-6. Also, the sensor is successfully able to detect ascorbic acid (AA), dopamine (DA), and uric acid (UA) in their ternary mixture. The differential pulse voltammetry (DPV) result shows peak potential separation of 229, 294, and 523 mV for AA-DA, DA-UA, and UA-AA, respectively.

Offloading the computational complexity of transfer learning with generic features.

Deep learning approaches are generally complex, requiring extensive computational resources and having high time complexity. Transfer learning is a state-of-the-art approach to reducing the requirements of high computational resources by using pre-trained models without compromising accuracy and performance. In conventional studies, pre-trained models are trained on datasets from different but similar domains with many domain-specific features. The computational requirements of transfer learning are directly dependent on the number of features that include the domain-specific and the generic features. This article investigates the prospects of reducing the computational requirements of the transfer learning models by discarding domain-specific features from a pre-trained model. The approach is applied to breast cancer detection using the dataset curated breast imaging subset of the digital database for screening mammography and various performance metrics such as precision, accuracy, recall, F1-score, and computational requirements. It is seen that discarding the domain-specific features to a specific limit provides significant performance improvements as well as minimizes the computational requirements in terms of training time (reduced by approx. 12%), processor utilization (reduced approx. 25%), and memory usage (reduced approx. 22%). The proposed transfer learning strategy increases accuracy (approx. 7%) and offloads computational complexity expeditiously.

Difference in 30-Day Readmission Rates After Laparoscopic Sleeve Gastrectomy Versus Laparoscopic Roux-En-Y Gastric Bypass: a Propensity Score Matched Study Using ACS NSQIP Data (2015-2019).

PURPOSE: There are very few studies that have compared the short-term outcomes of laparoscopic Roux-en-Y gastric bypass (LRYGB) and laparoscopic sleeve gastrectomy (LSG). Among short-term outcomes, hospital readmission after these procedures is an area for quality enhancement and cost reduction. In this study, we compared 30-day readmission rates after LSG and LRYGB through analyzing a nationalized dataset. In addition, we identified the reasons of readmission. MATERIALS AND METHODS: The current study was a retrospective analysis of data from National Surgical Quality Improvement Program (NSQIP) All adult patients, ≥ 18 years of age and who had LSG or LRYGB during 2014 to 2019 were included. Current Procedural Terminology (CPT) codes were used to identify the procedures. Multivariate logistic regressions were used to calculate propensity score adjusted odds ratios (ORs) for all cause 30-day re-admissions. RESULTS: There were 109,900 patients who underwent laparoscopic bariatric surgeries (67.5% LSG and 32.5% LRYGB). Readmissions were reported in 4168 (3.8%) of the patients and were more common among RYGB recipients compared to LSG (5.6% versus 2.9%, P < 0.001). The odds of 30-day readmissions were significantly higher among LRYGB group compared to LSG group (AOR, 2.20; 95% CI; 1.83, 2.64). In addition, variables such as age, chronic obstructive pulmonary disease, hypertension, bleeding disorders, blood urea nitrogen, SGOT, alkaline phosphatase, hematocrit, and operation time were significantly predicting readmission rates. CONCLUSIONS: Readmission rates were significantly higher among those receiving LRYGB, compared to LSG. Readmission was also affected by many patient factors. The factors could help patients and providers to make informed decisions for selecting appropriate procedures.

Identification of plasma proteins associated with oesophageal cancer chemotherapeutic treatment outcomes using SWATH-MS.

Oesophageal adenocarcinoma (OAC) is an aggressive cancer with a five-year survival of <15%. Current chemotherapeutic strategies only benefit a minority (20-30%) of patients and there are no methods available to differentiate between responders and non-responders. We performed quantitative proteomics using Sequential Window Acquisition of all THeoretical fragment-ion spectra-Mass Spectrometry (SWATH-MS) on albumin/IgG-depleted and non-depleted plasma samples from 23 patients with locally advanced OAC prior to treatment. Individuals were grouped based on tumour regression (TRG) score (TRG1/2/3 vs TRG4/5) after chemotherapy, and differentially abundant proteins were compared. Protein depletion of highly abundant proteins led to the identification of around twice as many proteins. SWATH-MS revealed significant quantitative differences in the abundance of several proteins between the two groups. These included complement c1q subunit proteins, C1QA, C1QB and C1QC, which were of higher abundance in the low TRG group. Of those that were found to be of higher abundance in the high TRG group, glutathione S-transferase pi (GSTP1) exhibited the lowest p-value and highest classification accuracy and Cohen's kappa value. Concentrations of these proteins were further examined using ELISA-based assays. This study provides quantitative information relating to differences in the plasma proteome that underpin response to chemotherapeutic treatment in oesophageal cancers. SIGNIFICANCE: Oesophageal cancers, including oesophageal adenocarcinoma (OAC) and oesophageal gastric junction cancer (OGJ), are one of the leading causes of cancer mortality worldwide. Curative therapy consists of surgery, either alone or in combination with adjuvant or neoadjuvant chemotherapy or radiation, or combination chemoradiotherapy regimens. There are currently no clinico-pathological means of predicting which patients will benefit from chemotherapeutic treatments. There is therefore an urgent need to improve oesophageal cancer disease management and treatment strategies. This work compared proteomic differences in OAC patients who responded well to chemotherapy as compared to those who did not, using quantitative proteomics prior to treatment commencement. SWATH-MS analysis of plasma (with and without albumin/IgG-depletion) from OAC patients prior to chemotherapy was performed. This approach was adopted to determine whether depletion offered a significant improvement in peptide coverage. Resultant datasets demonstrated that depletion increased peptide coverage significantly. Additionally, there was good quantitative agreement between commonly observed peptides. Data analysis was performed by adopting both univariate as well as multivariate analysis strategies. Differentially abundant proteins were identified between treatment response groups based on tumour regression grade. Such proteins included complement C1q sub-components and GSTP1. This study provides a platform for further work, utilising larger sample sets across different treatment regimens for oesophageal cancer, that will aid the development of 'treatment response prediction assays' for stratification of OAC patients prior to chemotherapy.

Triptolide promotes degradation of the unfolded gain-of-function Tp53R175H/Y220C mutant protein by initiating heat shock protein 70 transcription in non-small cell lung cancer.

Background: The mutation rate of the tumor protein P53 (TP53) has been reported to be greater than 50% in non-small cell lung cancer (NSCLC), and gain-of-function (GOF) mutations in unfolded P53 (TP53R175H and TP53Y220C) have been associated with poor prognosis. However, the best treatment for patients with NSCLC harboring unfolded mutant P53 (mutp53) remains unclear. Triptolide is a natural compound derived from Tripterygium wilfordii that has shown a strong antitumor effect in a variety of cancers. Our study aimed to explore the GOF mutations in unfolded mutp53 (TP53R175H and TP53Y220C) and to clarify the molecular mechanisms by which triptolide regulates the degradation of unfolded mutp53 proteins in NSCLC. Methods: Two unfolded proteins harboring TP53R175H and TP53Y220C mutations were selected to explore their functions in NSCLC progression. NCI-H1299 cells (TP53-null) were transfected with wild-type TP53 (TP53WT), TP53R175H, or TP53Y220C genes and treated with triptolide or a vehicle. Wound healing and transwell assays were performed to measure cell migration and invasion in vitro. Lung metastasis models were constructed through tail vein injection of mutant cells into BALB/c nude mice to evaluate the effect of triptolide on metastasis in vivo. Western blotting, quantitative real-time polymerase chain reaction (qRT-PCR), immunoprecipitation, and dual-luciferase reporter assays were performed to explore the relevant molecular mechanisms. Results: Our study revealed that triptolide treatment reduced TP53R175H levels and that the TP53Y220C mutation enhanced the invasion and migration of NCI-H1299 cells. Mechanistically, triptolide promoted TP53R175H and TP53Y220C protein proteasomal degradation mediated through the E3 ligase murine double minute 2 (MDM2) by directly interacting with heat shock protein 70 (HSP70). Moreover, by upregulating HSP70 transcription, triptolide contributed to the protein degradation of the GOF mutp53. Conclusions: Our study reports, for the first time, the mechanism underlying triptolide-regulated protein degradation of TP53R175H or TP53Y220C, which offers new insight into developing a better therapeutic strategy for patients with NSCLC who express the unfolded mutp53 GOF protein.

Lactate biosensing: The emerging point-of-care and personal health monitoring.

Lactate plays a crucial role in the anaerobic metabolic pathway of humans. In situations of oxygen deficit, its production increases; leading to several life-threatening conditions such as hemorrhage, respiratory failure, trauma or ischemia from lactate acidosis. Lactate level detection and point-of-care (POC) monitoring in a fast, accurate and non-invasive manner is ultimately important for many health care applications. Optical and electrochemical techniques are employed in lactate sensing to achieve high sensitivity and selectivity, miniaturization, portability, simplicity, and low cost. To improve the selectivity and sensitivity, two important enzymes, lactate oxidase (LOx) and lactate dehydrogenese (LDH) are employed. Conventional methods for lactate detection are not fast enough to be used in point-of-care or personal health monitoring settings. Moreover, the existing point-of-care lactate sensing tools follow invasive or partially invasive sampling protocols such as finger pricking. In this review, a comprehensive overview of different lactate biosensing devices is presented. Particularly, the state-of-the-art and prospects of wearable, non-invasive lactate sensing from different biofluids are discussed.

Multimodal technique to eliminate humidity interference for specific detection of ethanol.

Multimodal electrochemical technique incorporating both open circuit potential (OCP) and amperometric techniques have been conceptualized and implemented to improve the detection of specific analyte in systems where more than one analyte is present. This approach has been demonstrated through the detection of ethanol while eliminating the contribution of water in a micro fuel cell sensor system. The sensor was interfaced with LMP91000 potentiostat, controlled through MSP430F5529LP microcontroller to implement an auto-calibration algorithm tailored to improve the detection of alcohol. The sensor was designed and fabricated as a three electrode system with Nafion as a proton exchange membrane (PEM). The electrochemical signal of the interfering phase (water) was eliminated by implementing the multimodal electrochemical detection technique. The results were validated by comparing sensor and potentiostat performances with a commercial sensor and potentiostat respectively. The results suggest that such a sensing system can detect ethanol at concentrations as low as 5ppm. The structure and properties such as low detection limit, selectivity and miniaturized size enables potential application of this device in wearable transdermal alcohol measurements.

Recent advances in metamaterial split-ring-resonator circuits as biosensors and therapeutic agents.

Potential applications of thin film metamaterials are diverse and their realization to offer miniaturized waveguides, antennas and shielding patterns are on anvil. These artificially engineered structures can produce astonishing electromagnetic responses because of their constituents being engineered at much smaller dimensions than the wavelength of the incident electromagnetic wave, hence behaving as artificial materials. Such micro-nano dimensions of thin film metamaterial structures can be customized for various applications due to their exclusive responses to not only electromagnetic, but also to acoustic and thermal waves that surpass the natural materials' properties. In this paper, the recent major advancements in the emerging fields of diagnostics (sensors) and therapeutics involving thin film metamaterials have been reviewed and underlined; discussing their edge over conventional counterpart techniques; concentrating on their design considerations and feasible ways of achieving them. Challenges faced in sensitivity, precision, accuracy and factors that interfere with the degree of performance of the sensors are also dealt with, herein.

Fabrication and calibration of oxazine-based optic fiber sensor for detection of ammonia in water.

This paper presented the fabrication and calibration of a clad-modified evanescent based plastic optical fiber (POF) sensor for the detection of ammonia in both stagnant and dynamic aqueous media. This optochemical sensor was based on Oxazine 170 perchlorate (sensing material) and polydimethylsiloxane (PDMS) (protective material) thin layers. A special chemical solution was developed for the etching removal of cladding and a methodology for trapping moisture was exercised. Experimental results on dissolved ammonia detection exhibited short response time (≤10 s), low detection limit (minimum detection limit 1.4 ppm), high sensitivity, and excellent reversibility (over 99%).