A new extracellular chitinase (ChiA-Pt70) was produced and purified from a newly isolated Paenibacillus timonensis strain LK-DZ15. The maximum chitinase activity recorded after 44-h of incubation at 30°C was 11,500 U/mL. Pure enzyme was obtained after ammonium sulphate precipitation (40-70%) followed by sequential column chromatographies on fast performance liquid chromatography (FPLC) and high performance liquid chromatography (HPLC). Based on matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF/MS) analysis, the purified enzyme is a monomer with a molecular mass of 70,166.11 kDa. The sequence of the 25 NH₂-terminal residues of the mature ChiA-70 showed high homology with Paenibacillus GH-18 chitinases family. Optimal activity was achieved at pH 4.5 and 80°C. The pure enzyme was completely inhibited by p-chloromercuribenzoic acid (p-CMB) and N-ethylmaleimide (NEM). Chitinase activity was high on colloidal chitin, chitin azure, glycol chitin, glycol chitosane, chitotriose, and chito-oligosaccharide while it did not hydrolyse chitibiose and amylose. Furthermore, thin-layer chromatography (TLC) analysis from enzymatic catalyzed hydrolysis of chitin-oligosaccharides showed that ChiA-Pt70 acted as an endo-splitting enzyme. Its K_m and k_cat values were 0.611 mg colloidal chitin/mL and 87,800 s^-1, respectively. Interestingly, its catalytic efficiency was higher than those of chitinases ChiA-Mt45 from Melghiribacillus thermohalophilus strain Nari2A^T, ChiA-Hh59 from Hydrogenophilus hirchii strain KB-DZ44, Chitodextrinase^® from Streptomyces griseus, and N-acetyl-β-glucosaminidase^® from Trichoderma viride. Therefore, ChiA-Pt70 exhibited remarkable biochemical properties suggesting that it is suitable for the enzymatic degradation of chitin.

A novel bacterial strain was isolated from the highest summit of the Djurdjura Mountains in Kabylia (Algeria) at altitudes of about 23 km. For a long time, scientists have investigated in familiar world to identify novel microbial biocatalysts. However, the mountain soil has been shown as an almost entire reserve of novel enzymes with interesting properties for industrial and environmental applications. Paenibacillus sp. as a genus of facultative anaerobic bacteria is widespread in nature. Many species of this genus produce different enzymes used in biodegradation, textiles, bakery, food industry, stationery, biopharmaceutical industries and in many other domains. Thus, the strain LKDZ15 was isolated from Tikjda, in the Djurdjura Mountains, Algeria. The identification of this newly isolated bacterium was carried out using morphological, physiological, and biochemical characteristics. In addition, the 16S rDNA gene was also amplified and sequenced. All the data obtained with regards to the physiological and biochemical properties of the isolate, confirmed that the LKDZ15 strain belonged to the Paenibacillus genus. Moreover, the nucleotide sequence and blast analyses confirmed that the LKDZ15 strain (GenBank accession no.: MK734103) was closely related to those of the Paenibacillus strains. All the results obtained strongly suggested that this new isolate should be assigned as Paenibacillus timonensis strain LKDZ15.

Meteorological measurements for weather forecasting and climatology have been carried out on a regular basis for centuries. There are several meteorological parameters like temperature, rainfall, humidity, speed of the wind etc. By studying and observing these parameters one can tell about the air pollution of an area or maybe the humidity present in the atmosphere. One can also predict cyclones or any natural calamities related to it. Numerous methodologies and strategies have been adopted for the analysis of these parameters. However, the data acquired can only be evaluated and interpreted after having statistically recorded medium-term and long-term atmospheric conditions. One of the most efficient tools for analysis is the soft computing techniques. These techniques have numerous advantages, as these techniques can be used for prediction studies and also for finding out any trends or patterns. In this paper, several soft computing techniques like linear regression, logistic regression, k-nearest neighbor, random forest regression (RFR) and support vector regression (SVR) are used for modeling of these meteorological parameters and a comparative analysis has been shown. The linear regression technique is giving very poor results for the modeling of most of the parameters. RFR and SVR mostly showing high accuracy rates for most of the meteorological parameters and these two techniques are quite efficient in comparison to other methods for showing the trend.

Engineered magnetic nanoparticles have great potential in environmental since they are aiding the separation of a contaminant from aqueous solution by using an external magnetic field. Therefore, in this study, nano sized ferrous-ferric oxide, and ferrous-ferric-silicon dioxide-NH2 were synthesized using a co-precipitation and sol-gel methods, respectively. The nanomaterial was used as an adsorbent for the removal of lead ions from aqueous solution. The nanomaterial was characterized by using TEM and FT-IR techniques. Batch adsorption experiment at room temperature were applied to determine the optimum contact time to remove heavy metal ions from aqueous solution. Consequently, time dependency study showed that the highest removal occurred about two hours contact between adsorbent and lead ions. The removal capacity of the nanomaterial adsorbent was about 78%.

Interfaces are crucially important in pharmaceutics, biotechnology and biomedicine. There is a growing need for specific interfacial consideration that is using routinely to solve pharmaceutical problems. In order to meet manufacturing challenges and develop new better performing pharmaceutical products with improved qualities, knowledge of surface tension (σ) is of utmost importance. The experimental determination of this property has several limitations, such as the high time invested and the consumption of considerable amounts of sample. In the recent years, constant increase in the performance of hardware and software transformed quantitative structure property relationship (QSPR) into powerful and widely used model for the
prediction of many biological, toxicological and physicochemical properties in the field of medicinal chemistry. The aim of the present work was to find a QSPR model for prediction of surface tension of non-steroidal anti-inflammatory drugs (NSAIDs). To do this, a training series, consisting of 300 compounds, was constructed. By the ACD-Labs and MODESLAB, the simplified representation, surface tension value and molecular descriptors of each
compound in the series were obtained. An initial mathematical model of log σ, obtained using the Multiple Lineal Regression method (MLR) of SPSS, was optimized and validate through BuildQSAR program. The final model showed a good predictive power, results which suggest their use as part of the design and development of NSAIDs.

Hydrogels can display a wide variety of chemical and physical properties that enable them as nanostructured scaffolds for tissue engineering. Yet, single-component hydrogels have inherent limitations. To enhance and reinforce the versatility of the single component, different multi-component hydrogels have been designed and characterized. The influence of the nanoscascale of the systems on their macroscopic response was assessed, demonstrating that with a proper composition, multifunctional hybrid hydrogels can be optimally designed and successfully developed.

Bioceramic nanoparticles have a variety of characteristics that make them an ideal material for hard tissue engineering. However, knowing their success within the fluids of the human body is vital to fully comprehend their behaviour. The interaction of hydroxyapatite nanorods (HA) and bovine serum albumin (BSA) was investigated in order to accomplish this task. Using a variety of techniques, the key features of the physiological interaction between BSA and hydroxyapatite nanoparticle are discussed. Experimental data were collected using specific approaches to determine critical parameters including rates, affinities, and stoichiometries.

In this study, we aimed to optimize the cultural and nutritional conditions for protease production by Lysinibacillus fusiformis strain C250R in submerged fermentation process using statistical methodology. The most significant factors (gruel, wheat bran, yeast extract, and FeSO₄) were identified by Plackett-Burman design. Response surface methodology (RSM) was used to determine the optimum levels of the screened factors and their interaction. Under the optimized conditions, protease yield 3045 U/mL was 4.5 folds higher than those obtained by the use of the initial conditions (680 U/mL). Additionally, this research demonstrated that the protease activity of strain C250R has a high detergent compatibility and an excellent stain removal compared to Alcalase Ultra 2.5 L; which offers an interesting potential for its application in the laundry detergent industry.

Coccoloba cowellii Britton (Polygonaceae) is an endemic and critically endangered plant that only grows in Camagüey, province of Cuba. In this study a total of 13 compounds were identified in a methanolic leaf extract, employing a dereplication of the UHPLC-HRMS data by means of Feature-Based Molecular Networking (FBMN) analysis in the Global Natural Products Social Molecular (GNPS) Network, together with the results obtained from the MS-DIAL software, the interpretation of the MS/MS data and comparison with the literature. The major constituents were glucuronides and glycosides of myricetin and quercetin, as well as epichatechin-3-O-gallate, catechin, epicatechin and gallic acid, all of them being reported for the first time in C. cowellii leaves. The constituents identified highlight the potential of C. cowellii leaves, increasing the interest in the implementation of conservation strategies for this endangered species.