Cationic amphiphilic Zn-porphyrin with high antifungal photodynamic potency.

Photodynamic therapy (PDT) is a promising alternative approach particularly attractive for treatment of localized fungal infections. It is based on compounds, photosensitizers (PSs), which when excited with visible light, generate reactive species that ultimately cause cell death. Such species have short lifespans; as a consequence, efficiency and selectivity of the PDT treatment depend mainly on the properties of the PSs. This study is the first to explore the effect of cationic porphyrin-based photosensitizers on Saccharomyces cerevisiae, a member of the fungus kingdom. The study investigates which properties of the PS are essential for efficient antifungal PDT. Cationic Zn(ii) meso-tetrakis(N-alkylpyridinium-2-yl)porphyrins (ZnP) with identical tetrapyrrole core and photo-physical properties, but with different substituents at the meso positions of the porphyrin ring were studied. Attaching six-carbon aliphatic chains to the four pyridyl nitrogens at all meso positions to the porphyrin ring produced a highly photo-efficient amphiphilic, water soluble PS, with minimal dark toxicity. It was taken up by the yeast cells and upon illumination suppressed metabolism by inactivating cytoplasmic and mitochondrial enzymes, and compromising plasma membrane barrier function. At low concentrations (up to 5 µM) the tetrahexyl derivative was a much more powerful antifungal agent than the commercially available chlorin e6. The more lipophilic tetraoctyl analog was also highly photo-efficient but displayed strong dark toxicity, presumably due to higher lipophilicity which might affect the lipid bilayer of membranes. Results presented here can assist the design of antifungal agents whose biological action depends on efficient and rapid uptake by the cells.

Application of Unsupervised Learning for the Evaluation of Burial Behavior of Geomaterials in Peatlands: Case of Lignin Moieties Yielded by Alkaline Oxidative Cleavage.

Tropical Peatlands accumulate organic matter (OM) and a significant source of carbon dioxide (CO2) and methane (CH4) under anoxic conditions. However, it is still ambiguous where in the peat profile these OM and gases are produced. The composition of organic macromolecules that are present in peatland ecosystems are mainly lignin and polysaccharides. As greater concentrations of lignin are found to be strongly related to the high CO2 and CH4 concentrations under anoxic conditions in the surface peat, the need to study the degradation of lignin under anoxic and oxic conditions has emerged. In this study, we found that the "Wet Chemical Degradation" approach is the most preferable and qualified to evaluate the lignin degradation in soils accurately. Then, we applied PCA for the molecular fingerprint consisting of 11 major phenolic sub-units produced by alkaline oxidation using cupric oxide (II) along with alkaline hydrolysis of the lignin sample presented in the investigated peat column called "Sagnes". The development of various characteristic indicators for lignin degradation state on the basis of the relative distribution of lignin phenols was measured by chromatography after CuO-NaOH oxidation. In order to achieve this aim, the so-called Principal Component Analysis (PCA) has been applied for the molecular fingerprint composed of the phenolic sub-units, yielded by CuO-NaOH oxidation. This approach aims to seek the efficiency of the already available proxies and potentially create new ones for the investigation of lignin burial along a peatland. Lignin phenol vegetation index (LPVI) is used for comparison. LPVI showed a higher correlation with PC1 rather than PC2. This confirms the potential of the application of LPVI to decipher vegetation change, even in a dynamic system as the peatland. The population is composed of the depth peat samples, and the variables are the proxies and relative contributions of the 11 yielded phenolic sub-units.

Assessment of the Efficiency of Chemical and Thermochemical Depolymerization Methods for Lignin Valorization: Principal Component Analysis (PCA) Approach.

Energy demand and the use of commodity consumer products, such as chemicals, plastics, and transportation fuels, are growing nowadays. These products, which are mainly derived from fossil resources and contribute to environmental pollution and CO2 emissions, will be used up eventually. Therefore, a renewable inexhaustible energy source is required. Plant biomass resources can be used as a suitable alternative source due to their green, clean attributes and low carbon emissions. Lignin is a class of complex aromatic polymers. It is highly abundant and a major constituent in the structural cell walls of all higher vascular land plants. Lignin can be used as an alternative source for fine chemicals and raw material for biofuel production. There are many chemical processes that can be potentially utilized to increase the degradation rate of lignin into biofuels or value-added chemicals. In this study, two lignin degradation methods, CuO-NaOH oxidation and tetramethyl ammonium hydroxide (TMAH) thermochemolysis, will be addressed. Both methods showed a high capacity to produce a large molecular dataset, resulting in tedious and time-consuming data analysis. To overcome this issue, an unsupervised machine learning technique called principal component analysis (PCA) is implemented.