Overview of milling techniques for improving the solubility of poorly water-soluble drugs

Milling involves the application of mechanical energy to physically break down coarse particles to finer ones and is regarded as a“topedown”approach in the production of fine particles.Fine drug particulates are especially desired in formulations designed for parenteral,respiratory and transdermal use.Most drugs after crystallization may have to be comminuted and this physical transformation is required to various extents,often to enhance processability or solubility especially for drugs with limited aqueous solubility.The mechanisms by which milling enhances drug dissolution and solubility include alterations in the size,specific surface area and shape of the drug particles as well as millinginduced amorphization and/or structural disordering of the drug crystal(mechanochemical activation).Technology advancements in milling now enable the production of drug micro-and nano-particles on a commercial scale with relative ease.This review will provide a background on milling followed by the introduction of common milling techniques employed for the micronization and nanonization of drugs.Salient information contained in the cited examples are further extracted and summarized for ease of reference by researchers keen on employing these techniques for drug solubility and bioavailability enhancement.

Compaction of coated multi-particulates

There has been a strong interest for controlled release solid dosage forms,and to achieve controlled release,coating of particulates is often attempted to modify drug release.Due to the disadvantages of coated single-unit dosage forms,such as occurrences of dose dumping and local irritation,coated multiparticulates are often preferred.However,coated multiparticulates are often filled into capsules.Compressed tablet dosage form is more desirable than capsules as the unit production costs of tablets are lower and tablet presses are more common.

Scaled Dilation of DropBlock Optimization in Convolutional Neural Network for Fungus Classification

Image classification always has open challenges for computer vision research.Nowadays,deep learning has promoted the development of this field,especially in Convolutional Neural Networks(CNNs).This article proposes the development of efficiently scaled dilation of DropBlock optimization in CNNs for the fungus classification,which there are five species in this experiment.The proposed technique adjusts the convolution size at 35,45,and 60 with the max-polling size 2×2.The CNNs models are also designed in 12 models with the different BlockSizes and KeepProp.The proposed techniques provide maximum accuracy of 98.30%for the training set.Moreover,three accurate models,called Precision,Recall,and F1-score,are employed to measure the testing set.The experiment results expose that the proposed models achieve to classify the fungus and provide an excellent accuracy compared with the previous techniques.Furthermore,the proposed techniques can reduce the CNNs structure layer,directly affecting resource and time computation.

Preparation of slab-shaped lactose carrier particles for dry powder inhalers by air jet milling

Dry powder inhalers are often formulated by attaching micronized drug particles onto carrier particles, which are generally lactose. In this study, commercially available lactose was air jet milled to produce unique slab-like coarse carrier particles, which have larger and rougher surfaces compared to other commercially available lactose. Two key processing factors, i.e.,classifier speed and jet milling pressure, were systematically investigated. The largest fraction of slab-like particles in the resulting powder was obtained at a classifier speed of 3000 rpm.The slab-like coarse carrier particles are expected to exhibit superior performance than commercial lactose due to their unique surface properties.

Irrigation's effect and applied selection on the fiber quality of Ethyl MethaneSulfonate(EMS)treated upland cotton(Gossypium hirsutum L.)

Background: Producing rainfed cotton(Gossypium hirsutum L.) with high fiber quality has been challenging in the Texas High Plains because of extended periods of insufficient rainfall during sensitive boll developmental stages.Genetic variation created by Ethyl MethaneSulfonate(EMS) mutagen has successfully improved fiber quality of cotton. However, little is known about the effect of water deficit environments on fiber quality. Three EMS treated populations were advanced from the first to the fourth generation(M1 to M4) as bulk harvested populations. In2014, single-plant divergent selection was applied based on perceived morphological and agronomic differences seen during and at the end of the season.Results: Analyses from these selections in 2014-2016 showed significant(P< 0.05) improvement between and within populations for fiber traits(micronaire, length, strength, uniformity, and elongation) when compared with the original non-treated EMS source; some selections were found to have excellent fiber quality under diverse irrigationregimes.Conclusions: Some of these selections are being considered for germplasm release and could be useful for improving the fiber quality of cotton under water limited conditions, thereby helping to ensure the long-term survival of the cotton industry on the Texas High Plains.

Target detection and recognition in SAR imagery based on KFDA

Current research on target detection and recognition from synthetic aperture radar （SAR） images is usually carried out separately. It is difficult to verify the ability of a target recognition algorithm for adapting to changes in the environment. To realize the whole process of SAR automatic target recognition （ATR）, es- pecially for the detection and recognition of vehicles, an algorithm based on kernel fisher discdminant analysis （KFDA） is proposed. First, in order to make a better description of the difference be- tween the background and the target, KFDA is extended to the detection part. Image samples are obtained with a dual-window approach and features of the inner and outer window samples are extracted by using KFDA. The difference between the features of inner and outer window samples is compared with a threshold to determine whether a vehicle exists. Second, for the target area, we propose an improved KFDA-IMED （image Euclidean distance） combined with a support vector machine （SVM） to recognize the vehicles. Experimental results validate the performance of our method. On the detection task, our proposed method obtains not only a high detection rate but also a low false alarm rate without using any prior information. For the recognition task, our method overcomes the SAR image aspect angle sensitivity, reduces the requirements for image preprocessing and improves the recogni- tion rate.

Multivariate Study and Analysis of the Production of Citric Acid from Dates by Surface Method

The production of citric acid from dates of the date palm Phoenix dactilifera was studied using a full factorial design with two design variables;Aspergillus niger strain, and starter juice treatment. Analyses of data have shown that mould type and the interaction between Aspergillus niger strain + juice treatment had significant effect (P ≥ 0.05) on the final total acidity. It was also found that all design variables and the interaction between them had significant effect (P ≥ 0.05) on the final pH and Total Soluble Solids. The highest total acidity expressed as citric acid was achieved with a commercial strain of Aspergillus niger, and filtered and centrifuged date juice.

Valorization of Asparagus leafy by-product by ionic-liquid extraction and characterization of bioactive compounds in the extracts

Asparagus(Asparagus officinalis)is a high-value low-calorie vegetable with array of bioactive compounds.Asparagus processing nevertheless generates substantial quantity of by-products;their valorization is of utmost importance for the sustainability of the industry.Here,feasibility of using four imidazolium-based ionic liquids and their combinations as well as water and methanol to extract bioactive compounds from asparagus leafy by-product was investigated.Effectiveness of ultrasound-microwave-assisted heating to augment extraction was also assessed.1-ethyl-3-methylimidazolium-bromide(EMIMBr)resulted in the highest extraction yield of rutin(25.7 mg/g),which is the most abundant compound in the by-product;such a yield was comparable to that achievable via methanol extraction.Ultrasound-microwave-assisted extraction did not show significant improvement in rutin yield when EMIMBr was used.Interestingly,although methanolic extract exhibited slightly higher content of rutin,it also contained the higher number of impurities;EMIMBr extract contained less impurities with higher relative content of rutin(70.9%)than that in methanolic extract(67.7%).This could be a milestone in extraction work for an efficient purification.

Effect of SiO_(2)on loss of catalysis of inherent metallic species in CO_(2)gasification of coke from lignite

Inherent metallic species retained by coal char or coke,such as Na and Ca,behave as catalysts in gasification.The char/coke normally contains inherent SiO_(2),which can react with the inherent catalysts to form silicates,resulting in catalyst deactivation over the range of pyrolysis,carbonization and gasification,and thereby reducing the char/coke reactivity.The present authors simulated the inherent catalyst deactivation experimentally by blending a Victorian lignite with SiO_(2),briquetting the SiO_(2)/lignite blend,carbonizing the briquette,and then gasifying the coke with CO_(2).The kinetic analysis of the gasification employed a comprehensive model,which assumed progress in parallel of non-catalytic and catalytic gasification.The model quantitatively described the measured kinetics of the coke gasification with different SiO_(2)contents over a range of coke conversion up to 99.9%.The kinetic analysis revealed that the SiO_(2)deactivated substantial and entire portions of the most active catalyst and its precursor,respectively,before the gasification(i.e.,during the carbonization).The catalyst deactivation also occurred during the gasification,but mainly following a self-deactivation mechanism that involved no silicates formation.

GC-MS法测定Calophyllum inophyllum L.中的红厚壳素(英文)

AIM:To establish a GC-MS method for the determination of calophyllolide in Calophyllum inophyllum L.and its application in quality control of natural medicine.METHODS:Methanolic extract from Calophyllum inophyllum L.was prepared.Calophyllolide was isolated,purified and then identified to serve as a chemical marker for development and validation a GC-MS method according to ICH guideline and USP.The established method was proved to be useful in quality control with the aid of Principle Component Analysis (PCA),a multivariate data analysis technique.RESULTS:The proposed method was selective against mass spectral deconvoluting software AMDIS32.The linear range was from 3.125-50 μg·mL-1.The RSD of intra-and inter-day precision variations were less than 3% and the mean recovery was (101.22±1.98)% (RSD=1.95%).PCA was used to indicate a differentiation of batches in production as well as proving that calophyllolide has influence on the discrimination of extracts from different batches.CONCLUSION:The proposed capillary gas chromatography/mass spectrometric method for the determination of calophyllolide obtained from resin of Calophyllum inophyllum L.nut oil showed its suitability,simplicity,rapidity and precision,and it can be used for chemical assay.This is the first time such a technique was reported in literature.The multivariate data analysis technique was employed to provide an extensive but inclusive method for quality control of the extracts,to ensure consistency for batch to batch of extracts to be used for product development.