Efficacy and tolerance of cannabidiol in the treatment of epilepsy in patients with Rett syndrome.

We aim to assess the efficacy and tolerance of cannabidiol as adjunctive therapy for Rett syndrome (RTT) patients with epilepsy. We conducted a longitudinal observational study through a monocentric cohort of 46 patients with RTT. Patients were recruited from March 2020 to October 2022 and were treated with Epidyolex® (cannabidiol, CBD, 100 mg/mL oral solution). In our cohort, 26 patients had associated epilepsy (26/46 [56%]), and 10/26 (38%) were treated with CBD, in combination with clobazam in 50% of cases. The median dose at their last follow-up was 15 mg/kg/day. The median treatment duration was 13 months (range: 1-32 months). CBD reduced the incidence of seizures in seven out of 10 patients (70%) with one seizure-free patient, two patients with a reduction of seizures of more than 75%, and four patients with a decrease of more than 50%. No aggravation of symptoms or adverse effects were observed. Only one patient experienced a transitory drooling and somnolence episode at the CBD initiation. Half of the patients showed a reduction in agitation and/or anxiety attacks, and an improvement in spasticity was reported in 4/10 (40%) of patients. CBD appears to have potential therapeutic value for the treatment of drug-resistant epilepsy in Rett syndrome. CBD is well tolerated and, when used in combination with clobazam, may increase the effectiveness of clobazam alone.

ReBeatICG: Real-time Low-Complexity Beat-to-beat Impedance Cardiogram Delineation Algorithm.

This work presents ReBeatICG, a real-time, low-complexity beat-to-beat impedance cardiography (ICG) delineation algorithm that allows hemodynamic parameters monitoring. The proposed procedure relies only on the ICG signal compared to most algorithms found in the literature that rely on synchronous electrocardiogram signal (ECG) recordings. ReBeatICG was designed with implementation on an ultra-low-power microcontroller (MCU) in mind. The detection accuracy of the developed algorithm is tested against points manually labeled by cardiologists. It achieves a detection Gmean accuracy of 94.9%, 98.6%, 90.3%, and 84.3% for the B, C, X, and O characteristic points, respectively. Furthermore, several hemodynamic parameters were calculated based on annotated characteristic points and compared with values generated from the cardiologists' annotations. ReBeatICG achieved mean error rates of 0.11 ms, 9.72 ms, 8.32 ms, and 3.97% for HR, LVET, IVRT, and relative C-point amplitude, respectively.

An Affordable Microsphere-Based Device for Visual Assessment of Water Quality.

This work developed a prototype of an affordable, long-term water quality detection device that provides a visual readout upon detecting bacterial contamination. This device prototype consists of: (1) enzyme-releasing microspheres that lyse bacteria present in a sample, (2) microspheres that release probes that bind the DNA of the lysed bacteria, and (3) a detector region consisting of gold nanoparticles. The probes bind bacterial DNA, forming complexes. These complexes induce aggregation of the gold nanoparticles located in the detector region. The nanoparticle aggregation process causes a red to blue color change, providing a visual indicator of contamination being detected. Our group fabricated and characterized microspheres made of poly (ε-caprolactone) that released lysozyme (an enzyme that degrades bacterial cell walls) and hairpin DNA probes that bind to regions of the Escherichiacoli genome over a 28-day time course. The released lysozyme retained its ability to lyse bacteria. We then showed that combining these components with gold nanoparticles followed by exposure to an E. coli-contaminated water sample (concentrations tested-106 and 108 cells/mL) resulted in a dramatic red to blue color change. Overall, this device represents a novel low-cost system for long term detection of bacteria in a water supply and other applications.

Electrospun biomaterial scaffolds with varied topographies for neuronal differentiation of human-induced pluripotent stem cells.

In this study, we investigated the effect of micro and nanoscale scaffold topography on promoting neuronal differentiation of human induced pluripotent stem cells (iPSCs) and directing the resulting neuronal outgrowth in an organized manner. We used melt electrospinning to fabricate poly (ε-caprolactone) (PCL) scaffolds with loop mesh and biaxial aligned microscale topographies. Biaxial aligned microscale scaffolds were further functionalized with retinoic acid releasing PCL nanofibers using solution electrospinning. These scaffolds were then seeded with neural progenitors derived from human iPSCs. We found that smaller diameter loop mesh scaffolds (43.7 ± 3.9 µm) induced higher expression of the neural markers Nestin and Pax6 compared to thicker diameter loop mesh scaffolds (85 ± 4 µm). The loop mesh and biaxial aligned scaffolds guided the neurite outgrowth of human iPSCs along the topographical features with the maximum neurite length of these cells being longer on the biaxial aligned scaffolds. Finally, our novel bimodal scaffolds also supported the neuronal differentiation of human iPSCs as they presented both physical and chemical cues to these cells, encouraging their differentiation. These results give insight into how physical and chemical cues can be used to engineer neural tissue.