Micro-/Nano-Scale Materials for Biochemical Analysis

Nanomaterials fabricated via soft lithography has provided many useful tools for biology. The most commonly used material in soft lithography is poly(dimethylsiloxane) (PDMS).

Increasing the Protein Amount of Chlorella vulgaris [Chlorphyta] Strains Isolated from Different Fresh Water Ponds

Chlorella vulgaris is a single-cell, spherical green algae and one of the microalgae on which many applied studies are conducted. In the present study, five strains displaying fast and efficient reproduction were chosen among 11 C. vulgaris strains isolated from different fresh water ponds and their cell numbers and the amount of chlorophyll a, protein, lipid, cellulose and carbohydrate were examined. The main goal of the study is to investigate increasing the biochemical contents especially the protein content of C. vulgaris strains in different mediums. In the present study, cell densities were determined through cell count for five days. In parallel with cell count, their chlorophyll a content was determined. The highest cell density was observed with C. vulgaris TOH （Tourism and Hotel Management Pond） strain as 5.5 × 104 h/mL, and the chlorophyll a content as 4.3 × 102 mg/m3. The highest intracellular protein amount was determined with C. vulgaris GUH （Gazi University Rectorship Pond） （0.061 g/100 mL） and the highest lipid amount was attained with C. vulgaris UIK （Ulus Construction Well） strain as 0.019 g/100 mL. The process of increasing the intracellular protein amount in C. vulgaris GUH strain was carried out in Prat, Yagojinski and Chlorella medium. The results indicated that Chlorella medium increased the intracellular protein amount.

Conservation of Leaves of a Medicinal Plant of Western Algeria （Pistacia atlantica）

In our context, and in the goal to valorize the Pistacia atlantica species Desfthat grows spontaneously in Algeria occidental except the coastline, and that is used by the nomadic populations in their daily consumptions, we are thinking about drying its leaves. Here, the biochemical analysis of dried leaves ofPistacia atlantica is determined, the sorption is other ms are of great importance in the food industry, especially in the drying; the sorption isotherms of pistachio leaves were measured by the gravimetric method at three temperatures 40, 50 and 60 ℃. The equilibrium was achieved after eight days for desorption and seven days for adsorption with water activity ranging from 5% to 90%. Only the GAB and Peleg models were found to be the most suitable for describing the sorption curves. The isosteric heat of sorption of Pistacia atlantica leaves decreases with an increase in moisture content and was found to be an exponential function of moisture content for adsorption and desorption. The pistachio leaves could be considered as a rich natural source of valuable nutriments （carbohydrates, proteins and lipids）; lipid fraction is equal to 2.25%; proteins are the second macronutriment that predominates in these sheets： 4.35%; accordingly carbohydrates content was about 25.77%.

Nanofluidics for single-cell analysis

Living single-cell analysis is vital for cell biology, disease pathology, drug discovery and medical treatment. It is of great significance to reveal the law of creature and to explore the mechanism of serious disease. The conventional single cell analysis focuses on a large number of cells or cell lysis, in order to obtain the average information about cells. Therefore, it fails to analyze the real-time and continuous data of differences between the individual cells, thus limiting the development of many fields, such as biomedical. Nanofluidics based biochemical analysis exhibits advantages over conventional methods in terms of small sample volume, rapid turnaround time, straightforward operation, and efficient processing,which has been widely used in complex operations such as single cell capture, separation and single cell detection. Here we review the recent developments of nanofluidic technologies for single-cell analysis,with emphasis on cell trapping, treatment, and biochemical studies. The potential of nanofluidics-based single-cell analysis is discussed.

Isolation of a Tomato Protease that May Be Involved in Proteolysis of 1-Aminocyclopropane-l-Carboxylate Synthase

1-aminocyclopropane- 1-carboxylate （ACC） synthase is a principal enzyme that catalyses the committed step in phytohormone ethylene biosynthesis. Previous evidence indicates that the hypervariable C-terminus of ACC synthase is most likely to be processed proteolytically in vivo. However, the protease responsible has not been identified thus far. In the present study, we detected proteolytic activity against ACC synthase （LeACS2） in tomato （Lycopersicon esculentum Mill.） fruit extract based on a newly established in vitro assay system. Purification of the protease through DEAE, gel filtration and MonoQ chromatography resulted in considerable enrichment of a 64-kDa protein species. Subsequent biochemical analysis of the purified tomato protease revealed that the optimal conditions for its proteolytic activity were at pH 8.0 and at 37 ~C. In addition, the protease activity was blocked completely by the metalloprotease inhibitor 1,10-phenanthroline. The present study represents the first report on the isolation of an ACC synthase- processing protease from plant tissues.

Advances in Liquid Chromatography-Mass Spectrometry-Based Lipidomics: A Look Ahead

Lipidomics is a subfield of metabolic phenotyping that focuses on high-throughput profiling and quantification of lipids.Essential roles of lipidomics in translational and clinical research have emerged,especially over the past decade.Most lipidomic pipelines have been developed using mass spectrometry(MS)-based methods.Because of the complexity of the data,generally,computational demands are much higher in untargeted lipidomic studies.In the current paper,we primarily discussed the recent advances in untargeted liquid chromatography-mass spectrometry-based lipidomics,covering various facets from analytical strategies to functional interpretations.The current practice of tandem MS-based lipid annotation in untargeted lipidomics studies was demonstrated.Notably,we highlighted the essential characteristics of machine learning models,together with a data partitioning strategy,to facilitate appropriate modeling and validation in metabolic phenotyping studies.Critical aspects of data sharing were briefly mentioned.Finally,certain recommendations were suggested toward more standardized and sustainable lipidomics analysis strategies as independent platforms,and as members of the omics family.