Mixed-metal Ionothermal Synthesis of Metallophthalocyanine Covalent Organic Frameworks for CO Capture and Conversion.

Phthalocyanines (PCs) are intriguing building blocks owing to their stability, physicochemical and catalytic properties. Although PC-based polymers have been reported before, many suffer from relatively low stability, crystallinity, and low surface areas. Utilizing a mixed-metal salt ionothermal approach, we report the synthesis of a series of metallophthalocyanine-based covalent organic frameworks (COFs) starting from 1,2,4,5-tetracyanobenzene and 2,3,6,7-tetracyanoanthracene to form the corresponding COFs named M-pPPCs and M-anPPCs, respectively.

Evolutionary and experimental assessment of novel markers for detection of Xanthomonas euvesicatoria in plant samples.

Background: Bacterial spot-causing xanthomonads (BSX) are quarantine phytopathogenic bacteria responsible for heavy losses in tomato and pepper production. Despite the research on improved plant spraying methods and resistant cultivars, the use of healthy plant material is still considered as the most effective bacterial spot control measure. Therefore, rapid and efficient detection methods are crucial for an early detection of these phytopathogens.

Identification of Xanthomonas fragariae, Xanthomonas axonopodis pv. phaseoli, and Xanthomonas fuscans subsp. fuscans with novel markers and using a dot blot platform coupled with automatic data analysis.

Phytosanitary regulations and the provision of plant health certificates still rely mainly on long and laborious culture-based methods of diagnosis, which are frequently inconclusive. DNA-based methods of detection can circumvent many of the limitations of currently used screening methods, allowing a fast and accurate monitoring of samples. The genus Xanthomonas includes 13 phytopathogenic quarantine organisms for which improved methods of diagnosis are needed.

Automatic analysis of macroarrays images.

The analysis of dot blot (macroarray) images is currently based on the human identification of positive/negative dots, which is a subjective and time consuming process. This paper presents a system for the automatic analysis of dot blot images, using a pre-defined grid of markers, including a number of ON and OFF controls. The geometric deformations of the input image are corrected, and the individual markers detected, both tasks fully automatically.

Automatic detection of molecular markers in digital images.

Labeled molecular markers are an important tool in molecular biology. This work presents a method for the automatic identification of molecular markers in dot blot images. The method detects the location of markers in the image and their size.

An automatic Method to identify and extract information of DNA bands in Gel Electrophoresis images.

This paper presents a system for the automatic processing of Digital Images obtained from Gel Electrophoresis. The system identifies automatically the number and the location of lanes in the digital image, as well as the location of bands on each lane, without any intervention from the user. A reference lane with a know substance is used to compute the molecular weight of the observed (unknown) bands.