Feature Transformation Framework for Enhancing Compactness and Separability of Data Points in Feature Space for Small Datasets

Compactness and separability of data points are two important properties that contribute to the accuracy of machine learning tasks such as classification and clustering. We propose a framework that enhances the goodness criteria of the two properties by transforming the data points to a subspace in the same feature space, where data points of the same class are most similar to each other. Most related research about feature engineering in the input data points space relies on manually specified transformation functions. In contrast, our work utilizes a fully automated pipeline, in which the transformation function is learnt via an autoencoder for extraction of latent representation and multi-layer perceptron (MLP) regressors for the feature mapping. We tested our framework on both standard small datasets and benchmark-simulated small datasets by taking small fractions of their samples for training. Our framework consistently produced the best results in all semi-supervised clustering experiments based on K-means and different seeding techniques, with regards to clustering metrics and execution time. In addition, it enhances the performance of linear support vector machine (LSVM) and artificial neural network (ANN) classifier, when embedded as a preprocessing step before applying the classifiers

Feature Transformation Framework for Enhancing Compactness and Separability of Data Points in Feature Space for Small Datasets

Compactness and separability of data points are two important properties that contribute to the accuracy of machine learning tasks such as classification and clustering. We propose a framework that enhances the goodness criteria of the two properties by transforming the data points to a subspace in the same feature space, where data points of the same class are most similar to each other. Most related research about feature engineering in the input data points space relies on manually specified transformation functions. In contrast, our work utilizes a fully automated pipeline, in which the transformation function is learnt via an autoencoder for extraction of latent representation and multi-layer perceptron (MLP) regressors for the feature mapping. We tested our framework on both standard small datasets and benchmark-simulated small datasets by taking small fractions of their samples for training. Our framework consistently produced the best results in all semi-supervised clustering experiments based on K-means and different seeding techniques, with regards to clustering metrics and execution time. In addition, it enhances the performance of linear support vector machine (LSVM) and artificial neural network (ANN) classifier, when embedded as a preprocessing step before applying the classifiers

Photonic DNA-Chromophore Nanowire Networks: Harnessing Multiple Supramolecular Assembly Modes

Photonic DNA nanostructures are typically prepared by the assembly of multiple sequences of long DNA strands that are conjugated covalently to various dye molecules. Herein we introduce a noncovalent method for the construction of porphyrin-containing DNA nanowires and their networks that uses the programmed assembly of a single, very short, oligodeoxyribonucleotide sequence. Specifically, our strategy exploits a number of supramolecular binding modalities (including DNA base-pairing, metal-ion coordination, and β-cyclodextrin-adamantane derived host–guest interactions) for simultaneous nanowire assembly and porphyrin incorporation. Furthermore, we also show that the resultant DNA-porphyrin assembly can be further functionalized with a complementary “off-the-shelf” DNA binding dye resulting in photonic structures with broadband absorption and energy transfer capabilities

Synthesis and Molecular Docking of Some Novel 3-Thiazolyl-Coumarins as Inhibitors of VEGFR-2 Kinase

One crucial strategy for the treatment of breast cancer involves focusing on the Vascular Endothelial Growth Factor Receptor (VEGFR-2) signaling system. Consequently, the development of new (VEGFR-2) inhibitors is of the utmost importance. In this study, novel 3-thiazolhydrazinylcoumarins were designed and synthesized via the reaction of phenylazoacetylcoumarin with various hydrazonoyl halides and α-bromoketones. By using elemental and spectral analysis data (IR, 1H-NMR, 13C-NMR, and Mass), the ascribed structures for all newly synthesized compounds were clarified, and the mechanisms underlying their formation were delineated. The molecular docking studies of the resulting 6-(phenyldiazenyl)-2H-chromen-2-one (3, 6a–e, 10a–c and 12a–c) derivatives were assessed against VEGFR-2 and demonstrated comparable activities to that of Sorafenib (approved medicine) with compounds 6d and 6b showing the highest binding scores (−9.900 and −9.819 kcal/mol, respectively). The cytotoxicity of the most active thiazole derivatives 6d, 6b, 6c, 10c and 10a were investigated for their human breast cancer (MCF-7) cell line and normal cell line LLC-Mk2 using MTT assay and Sorafenib as the reference drug. The results revealed that compounds 6d and 6b exhibited greater anticancer activities (IC50 = 10.5 ± 0.71 and 11.2 ± 0.80 μM, respectively) than the Sorafenib reference drug (IC50 = 5.10 ± 0.49 μM). Therefore, the present study demonstrated that thiazolyl coumarins are potential (VEGFR-2) inhibitors and pave the way for the synthesis of additional libraries based on the reported scaffold, which could eventually lead to the development of efficient treatment for breast cancer

Mechanochemical Synthesis and Molecular Docking Studies of New Azines Bearing Indole as Anticancer Agents

The development of new approaches for the synthesis of new bioactive heterocyclic derivatives is of the utmost importance for pharmaceutical industry. In this regard, the present study reports the green synthesis of new benzaldazine and ketazine derivatives via the condensation of various carbonyl compounds (aldehydes and ketones with the 3-(1-hydrazineylideneethyl)-1H-indole using the grinding method with one drop of acetic acid). Various spectroscopic techniques were used to identify the structures of the synthesized derivatives. Furthermore, the anticancer activities of the reported azine derivatives were evaluated against colon, hepatocellular, and breast carcinoma cell lines using the MTT technique with doxorubicin as a reference medication. The findings suggested that the synthesized derivatives exhibited potential anti-tumor activities toward different cell lines. For example, 3c, 3d, 3h, 9, and 13 exhibited interesting activity with an IC50 value of 4.27–8.15 µM towards the HCT-116 cell line as compared to doxorubicin (IC50 = 5.23 ± 0.29 µM). In addition, 3c, 3d, 3h, 9, 11, and 13 showed excellent cytotoxic activities (IC50 = 4.09–9.05 µM) towards the HePG-2 cell line compared to doxorubicin (IC50 = 4.50 ± 0.20 µM), and 3d, 3h, 9, and 13 demonstrated high potency (IC50 = 6.19–8.39 µM) towards the breast cell line (MCF-7) as compared to the reference drug (IC50 = 4.17 ± 0.20 µM). The molecular interactions between derivatives 3a-h, 7, 9, 11, 13, and the CDK-5 enzyme (PDB ID: 3IG7) were studied further using molecular docking indicating a high level of support for the experimental results. Furthermore, the drug-likeness analysis of the reported derivatives indicated that derivative 9 (binding affinity = −8.34 kcal/mol) would have a better pharmacokinetics, drug-likeness, and oral bioavailability as compared to doxorubicin (−7.04 kcal/mol). These results along with the structure–activity relationship (SAR) of the reported derivatives will pave the way for the design of additional azines bearing indole with potential anticancer activities

Conjugation of Aspergillus flavipes Taxol with Porphyrin Increases the Anticancer Activity of Taxol and Ameliorates Its Cytotoxic Effects

Taxol is one of the potential anticancer drugs; however, the yield of Taxol and its cytotoxicity are common challenges. Thus, manipulating the Taxol biosynthetic pathway from endophytic fungi, in addition to chemical modification with biocompatible polymers, is the challenge. Four fungal isolates, namely, Aspergillus flavipes, A. terreus, A. flavus, and A. parasiticus, were selected from our previous study as potential Taxol producers, and their potency for Taxol production was evaluated in response to fluconazole and silver nitrate. A higher Taxol yield was reported in the cultures of A. flavipes (185 mu g/L) and A. terreus (66 mu g/L). With addition of fluconazole, the yield of Taxol was increased 1.8 and 1.2-fold for A. flavipes and A. terreus, respectively, confirming the inhibition of sterol biosynthesis and redirecting the geranyl phosphate pool to terpenoids synthesis. A significant inhibition of ergosterol biosynthesis by A. flavipes with addition of fluconazole was observed, correlating with the increase on Taxol yield. To increase the Taxol solubility and to reduce its cytotoxicity, Taxol was modified via chemical conjugation with porphyrin, and the degree of conjugation was checked from the Thin layer chromatography and UV spectral analysis. The antiproliferative activity of native and modified Taxol conjugates was evaluated; upon porphyrin conjugation, the activity of Taxol towards HepG2 was increased 1.5-fold, while its cytotoxicity to VERO cells was reduced 3-fold

From the mine to cancer therapy: natural and biodegradable theranostic silicon nanocarriers from diatoms for sustained delivery of chemotherapeutics

Drug delivery using synthetic nanoparticles including porous silicon has been extensively used to overcome the limitations of chemotherapy. However, their synthesis has many challenges such as lack of scalability, high cost, and the use of toxic materials with concerning environmental impact. Nanoscale materials obtained from natural resources are an attractive option to address some of these disadvantages. In this paper, a new mesoporous biodegradable silicon nanoparticle (SiNP) drug carrier obtained from natural diatom silica mineral available from the mining industry is presented. Diatom silica structures are mechanically fragmented and converted into SiNPs by simple and scalable magnesiothermic reduction process. Results show that SiNPs have many desirable properties including high surface area, high drug loading capacity, strong luminescence, biodegradability, and no cytotoxicity. The in-vitro release results from SiNPs loaded with anticancer drugs (doxorubicin) demonstrate a pH-dependent and sustained drug release with enhanced cytotoxicity against cancer cells. The cells study using doxorubicin loaded SiNPs shows a significantly enhanced cytotoxicity against cancer cells compared with free drug, suggesting their considerable potential as theranostic nanocarriers for chemotherapy. Their low-cost manufacturing using abundant natural materials and outstanding chemotherapeutic performance has made them as a promising alternative to synthetic nanoparticles for drug delivery applications.Shaheer Maher, Tushar Kumeria, Ye Wang, Gagandeep Kaur, Dina Fathalla, Gihan Fetih, Abel Santos, Fawzia Habib, Andreas Evdokiou, Dusan Losi

Purification and biochemical characterization of taxadiene synthase from bacillus koreensis and stenotrophomonas maltophilia

Taxadiene synthase (TDS) is the rate-limiting enzyme of Taxol biosynthesis that cyclizes the geranylgeranyl pyrophosphate into taxadiene. Attenuating Taxol productivity by fungi is the main challenge impeding its industrial application; it is possible that silencing the expression of TDS is the most noticeable genomic feature associated with Taxol-biosynthetic abolishing in fungi. As such, the characterization of TDS with unique biochemical properties and autonomous expression that is independent of transcriptional factors from the host is the main challenge. Thus, the objective of this study was to kinetically characterize TDS from endophytic bacteria isolated from different plants harboring Taxol-producing endophytic fungi. Among the recovered 23 isolates, Bacillus koreensis and Stenotrophomonas maltophilia achieved the highest TDS activity. Upon using the Plackett–Burman design, the TDS productivity achieved by B. koreensis (18.1 µmol/mg/min) and S. maltophilia (14.6 µmol/mg/min) increased by ~2.2-fold over the control. The enzyme was purified by gel-filtration and ion-exchange chromatography with ~15 overall folds and with molecular subunit structure 65 and 80 kDa from B. koreensis and S. maltophilia, respectively. The chemical identity of taxadiene was authenticated from the GC-MS analyses, which provided the same mass fragmentation pattern of authentic taxadiene. The tds gene was screened by PCR with nested primers of the conservative active site domains, and the amplicons were sequenced, displaying a higher similarity with tds from T. baccata and T. brevifolia. The highest TDS activity by both bacterial isolates was recorded at 37–40 °C. The Apo-TDSs retained ~50% of its initial holoenzyme activities, ensuring their metalloproteinic identity. The activity of purified TDS was completely restored upon the addition of Mg2+, confirming the identity of Mg2+ as a cofactor. The TDS activity was dramatically reduced upon the addition of DTNB and MBTH, ensuring the implementation of cysteine-reactive thiols and ammonia groups on their active site domains. This is the first report exploring the autonomous robust expression TDS from B. koreensis and S. maltophilia with a higher affinity to cyclize GGPP into taxadiene, which could be a novel platform for taxadiene production as intermediary metabolites of Taxol biosynthesis