Systematic design and evaluation of aptamers for VEGF and PlGF biomarkers of Preeclampsia.

Preeclampsia is a potentially life-threatening condition for both mother and baby, characterized by hypertension and potential organ damage. Early diagnosis is crucial to mitigate its adverse health effects. Traditional diagnostic methods, which focus on late-manifesting symptoms like hypertension and proteinuria, underscore the need for molecular diagnostic approaches for timely detection. This study successfully designs and evaluates novel aptamers with high specificity and affinity for Vascular Endothelial Growth Factor (VEGF) and Placental Growth Factor (PlGF), biomarkers closely associated with preeclampsia. Using molecular docking, molecular dynamics simulations, and BioLayer Interferometry (BLI), we identified aptamers that demonstrated strong binding affinities, comparable or superior to traditional antibodies. Our findings suggest that these aptamers have the potential to be integrated into cost-effective, point-of-care diagnostic tools, significantly improving early detection and intervention strategies for preeclampsia. The robust performance of these aptamers marks a pivotal step toward the development of more reliable and accessible diagnostic solutions, with implications for better maternal and fetal health outcomes.

Atomic vacancies of molybdenum disulfide nanoparticles stimulate mitochondrial biogenesis.

Diminished mitochondrial function underlies many rare inborn errors of energy metabolism and contributes to more common age-associated metabolic and neurodegenerative disorders. Thus, boosting mitochondrial biogenesis has been proposed as a potential therapeutic approach for these diseases; however, currently we have a limited arsenal of compounds that can stimulate mitochondrial function. In this study, we designed molybdenum disulfide (MoS2) nanoflowers with predefined atomic vacancies that are fabricated by self-assembly of individual two-dimensional MoS2 nanosheets. Treatment of mammalian cells with MoS2 nanoflowers increased mitochondrial biogenesis by induction of PGC-1α and TFAM, which resulted in increased mitochondrial DNA copy number, enhanced expression of nuclear and mitochondrial-DNA encoded genes, and increased levels of mitochondrial respiratory chain proteins. Consistent with increased mitochondrial biogenesis, treatment with MoS2 nanoflowers enhanced mitochondrial respiratory capacity and adenosine triphosphate production in multiple mammalian cell types. Taken together, this study reveals that predefined atomic vacancies in MoS2 nanoflowers stimulate mitochondrial function by upregulating the expression of genes required for mitochondrial biogenesis.

Label-free detection of Giardia lamblia cysts using a deep learning-enabled portable imaging flow cytometer.

We report a field-portable and cost-effective imaging flow cytometer that uses deep learning and holography to accurately detect Giardia lamblia cysts in water samples at a volumetric throughput of 100 mL h-1. This flow cytometer uses lens free color holographic imaging to capture and reconstruct phase and intensity images of microscopic objects in a continuously flowing sample, and automatically identifies Giardia lamblia cysts in real-time without the use of any labels or fluorophores. The imaging flow cytometer is housed in an environmentally-sealed enclosure with dimensions of 19 cm × 19 cm × 16 cm and weighs 1.6 kg. We demonstrate that this portable imaging flow cytometer coupled to a laptop computer can detect and quantify, in real-time, low levels of Giardia contamination (e.g., <10 cysts per 50 mL) in both freshwater and seawater samples. The field-portable and label-free nature of this method has the potential to allow rapid and automated screening of drinking water supplies in resource limited settings in order to detect waterborne parasites and monitor the integrity of the filters used for water treatment.

Sensing of electrolytes in urine using a miniaturized paper-based device.

Analyzing electrolytes in urine, such as sodium, potassium, calcium, chloride, and nitrite, has significant diagnostic value in detecting various conditions, such as kidney disorder, urinary stone disease, urinary tract infection, and cystic fibrosis. Ideally, by regularly monitoring these ions with the convenience of dipsticks and portable tools, such as cellphones, informed decision making is possible to control the consumption of these ions. Here, we report a paper-based sensor for measuring the concentration of sodium, potassium, calcium, chloride, and nitrite in urine, accurately quantified using a smartphone-enabled platform. By testing the device with both Tris buffer and artificial urine containing a wide range of electrolyte concentrations, we demonstrate that the proposed device can be used for detecting potassium, calcium, chloride, and nitrite within the whole physiological range of concentrations, and for binary quantification of sodium concentration.

Computational cytometer based on magnetically modulated coherent imaging and deep learning.

Detecting rare cells within blood has numerous applications in disease diagnostics. Existing rare cell detection techniques are typically hindered by their high cost and low throughput. Here, we present a computational cytometer based on magnetically modulated lensless speckle imaging, which introduces oscillatory motion to the magnetic-bead-conjugated rare cells of interest through a periodic magnetic force and uses lensless time-resolved holographic speckle imaging to rapidly detect the target cells in three dimensions (3D). In addition to using cell-specific antibodies to magnetically label target cells, detection specificity is further enhanced through a deep-learning-based classifier that is based on a densely connected pseudo-3D convolutional neural network (P3D CNN), which automatically detects rare cells of interest based on their spatio-temporal features under a controlled magnetic force. To demonstrate the performance of this technique, we built a high-throughput, compact and cost-effective prototype for detecting MCF7 cancer cells spiked in whole blood samples. Through serial dilution experiments, we quantified the limit of detection (LoD) as 10 cells per millilitre of whole blood, which could be further improved through multiplexing parallel imaging channels within the same instrument. This compact, cost-effective and high-throughput computational cytometer can potentially be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.