A solid state electrolyte based enzymatic acetone sensor.

This paper introduces a novel solid-state electrolyte-based enzymatic sensor designed for the detection of acetone, along with an examination of its performance under various surface modifications aimed at optimizing its sensing capabilities. To measure acetone concentrations in both liquid and vapor states, cyclic voltammetry and amperometry techniques were employed, utilizing disposable screen-printed electrodes consisting of a platinum working electrode, a platinum counter electrode, and a silver reference electrode. Four different surface modifications, involving different combinations of Nafion (N) and enzyme (E) layers (N + E; N + E + N; N + N + E; N + N + E + N), were tested to identify the most effective configuration for a sensor that can be used for breath acetone detection. The sensor's essential characteristics, including linearity, sensitivity, reproducibility, and limit of detection, were thoroughly evaluated through a range of experiments spanning concentrations from 1 µM to 25 mM. Changes in acetone concentration were monitored by comparing currents readings at different acetone concentrations. The sensor exhibited high sensitivity, and a linear response to acetone concentration in both liquid and gas phases within the specified concentration range, with correlation coefficients ranging from 0.92 to 0.98. Furthermore, the sensor achieved a rapid response time of 30-50 s and an impressive detection limit as low as 0.03 µM. The results indicated that the sensor exhibited the best linearity, sensitivity, and limit of detection when four layers were employed (N + N + E + N).

The development of an electrochemical immunosensor utilizing chicken IgY anti-spike antibody for the detection of SARS-CoV-2.

This paper introduces a novel approach for detecting the SARS-CoV-2 recombinant spike protein combining a label free electrochemical impedimetric immunosensor with the use of purified chicken IgY antibodies. The sensor employs three electrodes and is functionalized with an anti-S IgY antibody, ELISA and immunoblot assays confirmed the positive response of chicken immunized with SARS-CoV2 S antigen. The developed immunosensor is effective in detecting SARS-CoV-2 in nasopharyngeal clinical samples from suspected cases. The key advantage of this biosensor is its remarkable sensitivity, and its capability of detecting very low concentrations of the target analyte, with a detection limit of 5.65 pg/mL. This attribute makes it highly suitable for practical point-of-care (POC) applications, particularly in low analyte count clinical scenarios, without requiring amplification. Furthermore, the biosensor has a wide dynamic range of detection, spanning from 11.56 to 740 ng/mL, which makes it applicable for sample analysis in a typical clinical setting.

Deep learning models for detecting respiratory pathologies from raw lung auscultation sounds.

In recent years deep learning models improve the diagnosis performance of many diseases especially respiratory diseases. This paper will propose an evaluation for the performance of different deep learning models associated with the raw lung auscultation sounds in detecting respiratory pathologies to help in providing diagnostic of respiratory pathologies in digital recorded respiratory sounds. Also, we will find out the best deep learning model for this task. In this paper, three different deep learning models have been evaluated on non-augmented and augmented datasets, where two different datasets have been utilized to generate four different sub-datasets. The results show that all the proposed deep learning methods were successful and achieved high performance in classifying the raw lung sounds, the methods were applied on different datasets and used either augmentation or non-augmentation. Among all proposed deep learning models, the CNN-LSTM model was the best model in all datasets for both augmentation and non-augmentation cases. The accuracy of CNN-LSTM model using non-augmentation was 99.6%, 99.8%, 82.4%, and 99.4% for datasets 1, 2, 3, and 4, respectively, and using augmentation was 100%, 99.8%, 98.0%, and 99.5% for datasets 1, 2, 3, and 4, respectively. While the augmentation process successfully helps the deep learning models in enhancing their performance on the testing datasets with a notable value. Moreover, the hybrid model that combines both CNN and LSTM techniques performed better than models that are based only on one of these techniques, this mainly refers to the use of CNN for automatic deep features extraction from lung sound while LSTM is used for classification.

Oocyte metabolic function, lipid composition, and developmental potential are altered by diet in older mares.

Dietary supplementation is the most feasible method to improve oocyte function and developmental potential in vivo. During three experiments, oocytes were collected from maturing, dominant follicles of older mares to determine whether short-term dietary supplements can alter oocyte metabolic function, lipid composition, and developmental potential. Over approximately 8 weeks, control mares were fed hay (CON) or hay and grain products (COB). Treated mares received supplements designed for equine wellness and gastrointestinal health, flaxseed oil, and a proprietary blend of fatty acid and antioxidant support (reproductive support supplement (RSS)) intended to increase antioxidant activity and lipid oxidation. RSS was modified for individual experiments with additional antioxidants or altered concentrations of n-3 to n-6 fatty acids. Oocytes from mares supplemented with RSS when compared to COB had higher basal oxygen consumption, indicative of higher aerobic metabolism, and proportionately more aerobic to anaerobic metabolism. In the second experiment, oocytes collected from the same mares prior to (CON) and after approximately 8 weeks of RSS supplementation had significantly reduced oocyte lipid abundance. In the final experiment, COB was compared to RSS supplementation, including RSS modified to proportionately reduce n-3 fatty acids and increase n-6 fatty acids. The ability of sperm-injected oocytes to develop into blastocysts was higher for RSS, regardless of fatty acid content, than for COB. We demonstrated that short-term diet supplementation can directly affect oocyte function in older mares, resulting in oocytes with increased metabolic activity, reduced lipid content, and increased developmental potential.

Equine maternal aging affects oocyte lipid content, metabolic function and developmental potential.

Advanced maternal age is associated with a decline in fertility and oocyte quality. We used novel metabolic microsensors to assess effects of mare age on single oocyte and embryo metabolic function, which has not yet been similarly investigated in mammalian species. We hypothesized that equine maternal aging affects the metabolic function of oocytes and in vitro-produced early embryos, oocyte mitochondrial DNA (mtDNA) copy number, and relative abundance of metabolites involved in energy metabolism in oocytes and cumulus cells. Samples were collected from preovulatory follicles from young (≤14 years) and old (≥20 years) mares. Relative abundance of metabolites in metaphase II oocytes (MII) and their respective cumulus cells, detected by liquid and gas chromatography coupled to mass spectrometry, revealed that free fatty acids were less abundant in oocytes and more abundant in cumulus cells from old vs young mares. Quantification of aerobic and anaerobic metabolism, respectively measured as oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) in a microchamber containing oxygen and pH microsensors, demonstrated reduced metabolic function and capacity in oocytes and day-2 embryos originating from oocytes of old when compared to young mares. In mature oocytes, mtDNA was quantified by real-time PCR and was not different between the age groups and not indicative of mitochondrial function. Significantly more sperm-injected oocytes from young than old mares resulted in blastocysts. Our results demonstrate a decline in oocyte and embryo metabolic activity that potentially contributes to the impaired developmental competence and fertility in aged females.

Design of a multi-sensor platform for integrating extracellular acidification rate with multi-metabolite flux measurement for small biological samples.

Rates of cellular oxygen consumption (OCR) and extracellular acidification (ECAR) are widely used proxies for mitochondrial oxidative phosphorylation (OXPHOS) and glycolytic rate in cell metabolism studies. However, ECAR can result from both oxidative metabolism (carbonic acid formation) and glycolysis (lactate release), potentially leading to erroneous conclusions about metabolic substrate utilization. Co-measurement of extracellular glucose and lactate flux along with OCR and ECAR can improve the accuracy and provide better insight into cellular metabolic processes but is currently not feasible with any commercially available instrumentation. Herein, we present a miniaturized multi-sensor platform capable of real-time monitoring of OCR and ECAR along with extracellular lactate and glucose flux for small biological samples such as single equine embryos. This multiplexed approach enables validation of ECAR resulting from OXPHOS versus glycolysis, and expression of metabolic flux ratios that provide further insight into cellular substrate utilization. We demonstrate expected shifts in embryo metabolism during development and in response to OXPHOS inhibition as a model system for monitoring metabolic plasticity in very small biological samples. Furthermore, we also present a preliminary interference analysis of the multi-sensor platform to allow better understanding of sensor interference in the proposed multi-sensor platform. The capability of the platform is illustrated with measurements of multi-metabolites of single-cell equine embryos for assisted reproduction technologies. However, this platform has a wide potential utility for analyzing small biological samples such as single cells and tumor biopsies for immunology and cancer research applications.