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Dissolved Oxygen (DO) in water enables marine life. Measuring the prevalence of DO in a body of water is an important part of sustainability efforts because low oxygen levels are a primary indicator of contamination and distress in bodies of water. Therefore, aquariums and aquaculture of all types are in need of near real-time dissolved oxygen monitoring and spend a lot of money on purchasing and maintaining DO meters that are either expensive, inefficient, or manually operated—in which case they also need to ensure that manual readings are taken frequently which is time consuming. Hence a cost-effective and sustainable automated Internet of Things (IoT) system for this task is necessary and long overdue. DOxy, is such an IoT system under research and development at Santa Clara University's Ethical, Pragmatic, and Intelligent Computing (EPIC) Laboratory which utilizes cost-effective, accessible, and sustainable Sensing Units (SUs) for measuring the dissolved oxygen levels present in bodies of water which send their readings to a web based cloud infrastructure for storage, analysis, and visualization. DOxy's SUs are equipped with a High-sensitivity Pulse Oximeter meant for measuring dissolved oxygen levels in human blood, not water. Hence a number of parallel readings of water samples were gathered by both the High-sensitivity Pulse Oximeter and a standard dissolved oxygen meter. Then, two approaches for relating the readings were investigated. In the first, various machine learning models were trained and tested to produce a dynamic mapping of sensor readings to actual DO values. In the second, curve-fitting models were used to produce a successful conversion formula usable in the DOxy SUs offline. Both proved successful in producing accurate results. [ABSTRACT FROM AUTHOR]

Oxidative stress is one of the most important environmental exposures associated with psychiatric disorders, but the underlying molecular mechanisms remain to be elucidated. In a previous study, we observed a substantial alteration of the gene expression landscape in neuron-like cells that were differentiated from SH-SY5Y cells after or during exposure to oxidative stress, with a subset of dysregulated genes being enriched for neurodevelopmental processes. To further explore the regulatory mechanisms that might account for such profound perturbations, we have now applied small RNA-sequencing to investigate changes in the expression of miRNAs. These molecules are known to play crucial roles in brain development and response to stress through their capacity to suppress gene expression and influence complex biological networks. Through these analyses, we observed more than a hundred differentially expressed miRNAs, including 80 previously reported to be dysregulated in psychiatric disorders. The seven most influential miRNAs associated with pre-treatment exposure, including miR-138-5p, miR-96-5p, miR-34c-5p, miR-1287-5p, miR-497-5p, miR-195-5p, and miR-16-5p, supported by at least 10 negatively correlated mRNA connections, formed hubs in the interaction network with 134 genes enriched with neurobiological function, whereas in the co-treatment condition, miRNA-mRNA interaction pairs were enriched in cardiovascular and immunity-related disease ontologies. Interestingly, 12 differentially expressed miRNAs originated from the DLK1-DIO3 location, which encodes a schizophrenia-associated miRNA signature. Collectively, our findings suggest that early exposure to oxidative stress, before and during prenatal neuronal differentiation, might increase the risk of mental illnesses in adulthood by disturbing the expression of miRNAs that regulate neurodevelopmentally significant genes and networks. [ABSTRACT FROM AUTHOR]

Aims: Optimum timing of pacemaker implantation following cardiac surgery is a clinical challenge. European and American guidelines recommend observation, to assess recovery of atrioventricular block (AVB) (up to 7 days) and sinus node (5 days to weeks) after cardiac surgery. This study aims to determine rates of cardiac implantable electronic devices (CIEDs) implants post-surgery at a high-volume tertiary centre over 3 years. Implant timing, patient characteristics and outcomes at 6 months including pacemaker utilization were assessed.Methods and Results: All cardiac operations (n = 5950) were screened for CIED implantation following surgery, during the same admission, from 2015 to 2018. Data collection included patient, operative, and device characteristics; pacing utilization and complications at 6 months. A total of 250 (4.2%) implants occurred; 232 (3.9%) for bradycardia. Advanced age, infective endocarditis, left ventricle systolic impairment, and valve surgery were independent predictors for CIED implants (P < 0.0001). Relative risk (RR) of CIED implants and proportion of AVB increased with valve numbers operated (single-triple) vs. non-valve surgery: RR 5.4 (95% CI 3.9-7.6)-21.0 (11.4-38.9) CIEDs. Follow-up pacing utilization data were available in 91%. Significant utilization occurred in 82% and underutilization (<1% A and V paced) in 18%. There were no significant differences comparing utilization rates in early (≤day 5 post-operatively) vs. late implants (P = 0.55).Conclusion: Multi-valve surgery has a particularly high incidence of CIED implants (14.9% double, 25.6% triple valve). Age, left ventricle systolic impairment, endocarditis, and valve surgery were independent predictors of CIED implants. Device underutilization was infrequent and uninfluenced by implant timing. Early implantation (≤5 days) should be considered in AVB post-multi-valve surgery. [ABSTRACT FROM AUTHOR]

Nanoparticle‐based therapeutic formulations are being increasingly explored for the treatment of various ailments. Despite numerous advances, the success of nanoparticle‐based technologies in treating brain diseases has been limited. Translational hurdles of nanoparticle therapies are attributed primarily to their limited ability to cross the blood–brain barrier (BBB), which is one of the body's most exclusive barriers. Several efforts have been focused on developing affinity‐based agents and using them to increase nanoparticle accumulation at the brain endothelium. Very little is known about the role of fundamental physical parameters of nanoparticles such as size, shape, and flexibility in determining their interactions with and penetration across the BBB. Using a three‐dimensional human BBB microfluidic model (μHuB), we investigate the impact of these physical parameters on nanoparticle penetration across the BBB. To gain insights into the dependence of transport on nanoparticle properties, two separate parameters were measured: the number of nanoparticles that fully cross the BBB and the number that remain associated with the endothelium. Association of nanoparticles with the brain endothelium was substantially impacted by their physical characteristics. Hard particles associate more with the endothelium compared to soft particles, as do small particles compared to large particles, and spherical particles compared to rod‐shaped particles. Transport across the BBB also exhibited a dependence on nanoparticle properties. A nonmonotonic dependence on size was observed, where 200 nm particles exhibited higher BBB transport compared to 100 and 500 nm spheres. Rod‐shaped particles exhibited higher BBB transport when normalized by endothelial association and soft particles exhibited comparable transport to hard particles when normalized by endothelial association. Tuning nanoparticles' physical parameters could potentially enhance their ability to cross the BBB for therapeutic applications. [ABSTRACT FROM AUTHOR]