Thin-film conformal fluorescent SU8-phenylenediamine.

The SU8 polymer is a negative photoresist widely used to produce high-quality coatings, with controllable thicknesses ranging from nanometers to millimeters, depending on fabrication protocols. Apart from conventional use cases in microelectronics and fluidics, SU8 is quite an attractive platform in nanophotonics. This material, being straightforwardly processed by ultraviolet lithography, is transparent to wavelengths longer than 500 nm. However, introducing fluorescent agents within the SU8 matrix remains a challenge owing to its high hydrophobicity. Here, we develop a process, where colorful quantum dots co-participate in the polymerization process by epoxide amination and become a part of a new fluorescent material - SU8-phenylenediamine. Through comprehensive characterization methods, including XPS and 1H-NMR analyses, we demonstrate that m-PD covalently binds to SU8 epoxy sites with its molecular amine, virtually forming a new material and not just a mixture of two compounds. After characterizing the new strongly fluorescent platform, thin 300 nm films were created on several surfaces, including a conformal coverage of a nanofluidic capillary. This new process provides opportunities to incorporate various functional molecules into optoelectronic devices without the need for multistep deposition and surface functionalization.

Avocado seed waste bioconversion into poly(3-hydroxybutyrate) by using Cobetia amphilecti and ethyl levulinate as a green extractant.

The avocado processing industry produces up to 1.3M tons of agro-waste annually. Chemical analysis of avocado seed waste (ASW) revealed that it is rich in carbohydrates (464.7 ± 21.4 g kg-1) and proteins (37.2 ± 1.5 g kg-1). Optimized microbial cultivation of Cobetia amphilecti using an acid hydrolysate of ASW, generated poly(3-hydroxybutyrate) (PHB) in a 2.1 ± 0.1 g L-1 concentration. The PHB productivity of C. amphilecti cultivated on ASW extract was 17.5 mg L-1 h-1. The process in which a novel ASW substrate was utilized has been further augmented by using ethyl levulinate as a sustainable extractant. This process achieved 97.4 ± 1.9 % recovery yield and 100 ± 1 % purity (measured by TGA, NMR, and FTIR) of the target PHB biopolymer, along with a high and relatively uniform PHB molecular weight (Mw = 1831 kDa, Mn = 1481 kDa, Mw/Mn = 1.24) (measured by gel permeation chromatography), compared to PHB polymer extracted by chloroform (Mw = 389 kDa, Mn = 297 kDa, Mw/Mn = 1.31). This is the first example of ASW utilization as a sustainable and inexpensive substrate for PHB biosynthesis and ethyl levulinate as an efficient and green extractant of PHB from a single bacterial biomass.

Turning mannitol-rich agricultural waste to poly(3-hydroxybutyrate) with Cobetia amphilecti fermentation and recovery with methyl levulinate as a green solvent.

The present study explored the use of mannitol and mannitol-rich agro-industrial wastes as substrates for PHB production by Cobetia amphilecti isolated from the green Ulva sp. seaweed. Cultivation of C. amphilecti on mannitol, celery, and olive leaves (OLs) waste led to 4.20, 6.00, and 5.16 g L-1 of cell dry mass (CDM), 76.3, 25.5, and 12.0% of PHB content in CDM and 3.2, 1.53, and 0.62 g L-1 of PHB concentration, respectively; which suggested that they can be exploited as carbon substrates for the production of PHB. Extraction of PHB from C. amphilecti cultures by solubilization in the green solvent methyl levulinate (ML) (2% w/w, 140 °C, 1 h) indicated that the recovery yield and purity of PHB are above 97 and 90% w/w, respectively. The use of ML could be an attractive method for the recovery of PHB when safe and non-toxic solvents are required.

Marine bacteria associated with the green seaweed Ulva sp. for the production of polyhydroxyalkanoates.

This work aimed to isolate a series of bacterial strains associated with the green seaweed Ulva sp. and evaluate their capability to manufacture PHA. The effect of the type of supplemented sugars found to be in macroalgae, on the growth and PHA productivity of the strains was studied. Analysis of the 16S rRNA gene sequence of the isolated strains revealed that the PHA-producing bacteria were phylogenetically related to the genus Cobetia, Bacillus, Pseudoaltermonas and Sulfitobacter, which showed high PHA contents among the isolates. The highest PHA content was observed in the case of Cobetia strain, with up to 61% w/w in the presence of mannitol and 12% w/w on Ulva sp. acid hydrolysate as a substrate.

Automated thermal imaging for the detection of fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) comprises a spectrum of progressive liver pathologies, ranging from simple steatosis to non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis. A liver biopsy is currently required to stratify high-risk patients, and predicting the degree of liver inflammation and fibrosis using non-invasive tests remains challenging. Here, we sought to develop a novel, cost-effective screening tool for NAFLD based on thermal imaging. We used a commercially available and non-invasive thermal camera and developed a new image processing algorithm to automatically predict disease status in a small animal model of fatty liver disease. To induce liver steatosis and inflammation, we fed C57/black female mice (8 weeks old) a methionine-choline deficient diet (MCD diet) for 6 weeks. We evaluated structural and functional liver changes by serial ultrasound studies, histopathological analysis, blood tests for liver enzymes and lipids, and measured liver inflammatory cell infiltration by flow cytometry. We developed an image processing algorithm that measures relative spatial thermal variation across the skin covering the liver. Thermal parameters including temperature variance, homogeneity levels and other textural features were fed as input to a t-SNE dimensionality reduction algorithm followed by k-means clustering. During weeks 3,4, and 5 of the experiment, our algorithm demonstrated a 100% detection rate and classified all mice correctly according to their disease status. Direct thermal imaging of the liver confirmed the presence of changes in surface thermography in diseased livers. We conclude that non-invasive thermal imaging combined with advanced image processing and machine learning-based analysis successfully correlates surface thermography with liver steatosis and inflammation in mice. Future development of this screening tool may improve our ability to study, diagnose and treat liver disease.