Synthesis, anticancer activity, and molecular docking of half-sandwich iron(II) cyclopentadienyl complexes with maleimide and phosphine or phosphite ligands.

In these studies, we designed and investigated the potential anticancer activity of five iron(II) cyclopentadienyl complexes bearing different phosphine and phosphite ligands. All complexes were characterized with spectroscopic analysis viz. NMR, FT-IR, ESI-MS, UV-Vis, fluorescence, XRD (for four complexes) and elemental analyses. For biological studies, we used three types of cells-normal peripheral blood mononuclear (PBM) cells, leukemic HL-60 cells and non-small-cell lung cancer A549 cells. We evaluated cell viability and DNA damage after cell incubation with these complexes. We observed that all iron(II) complexes were more cytotoxic for HL-60 cells than for A549 cells. The complex CpFe(CO)(P(OPh)3)(η1-N-maleimidato) 3b was the most cytotoxic with IC50 = 9.09 µM in HL-60 cells, IC50 = 19.16 µM in A549 and IC50 = 5.80 µM in PBM cells. The complex CpFe(CO)(P(Fu)3)(η1-N-maleimidato) 2b was cytotoxic only for both cancer cell lines, with IC50 = 10.03 µM in HL-60 cells and IC50 = 73.54 µM in A549 cells. We also found the genotoxic potential of the complex 2b in both types of cancer cells. However, the complex CpFe(CO)2(η1-N-maleimidato) 1 which we studied previously, was much more genotoxic than complex 2b, especially for A549 cells. The plasmid relaxation assay showed that iron(II) complexes do not induce strand breaks in fully paired ds-DNA. The DNA titration experiment showed no intercalation of complex 2b into DNA. Molecular docking revealed however that complexes CpFe(CO)(PPh3) (η1-N-maleimidato) 2a, 2b, 3b and CpFe(CO)(P(OiPr)3)(η1-N-maleimidato) 3c have the greatest potential to bind to mismatched DNA. Our studies demonstrated that the iron(II) complex 1 and 2b are the most interesting compounds in terms of selective cytotoxic action against cancer cells. However, the cellular mechanism of their anticancer activity requires further research.

A membrane targeted multifunctional cationic nanoparticle conjugated fusogenic nanoemulsion (CFusoN): induced membrane depolarization and lipid solubilization to accelerate the killing of Staphylococcus aureus.

Bacterial infections caused by Staphylococcus aureus are one of the growing concerns for human health care management globally. Antibiotic-associated adverse effects and the emergence of bacterial resistant strains necessitate the development of an alternative yet effective approach. Nanoemulsion-based therapy has emerged as a potential therapeutic strategy to combat bacterial infestation. Herein, we designed a cationic metal nanoparticle-conjugated fusogenic nanoemulsion (CFusoN) as a lipid solubilizing nanovesicle for the effective treatment of S. aureus infection with a killing efficiency of 99.999%. The cationic nanoparticle-conjugated nanoemulsion (viz. NECNP) (24.4 ± 2.9 mV) electrostatically bound with the negatively charged bacterial cell membrane (-10.2 ± 3.7 mV) causing alteration of the bacterial surface charge. The fluorometric and flow cytometry studies confirmed the bacterial membrane depolarization and altered cell membrane permeability leading to cell death. The atomic force microscopic studies further demonstrated the damage of the cellular ultrastructure, while the transmission electron microscopic image and membrane lipid solubilization analysis depicted the solubilization of the bacterial membrane lipid bilayer along with the leakage of the intracellular contents. The cell membrane fatty acid analysis revealed that the methyl esters of palmitic acid, stearic acid and octadecadienoic acid isomers were solubilized after the treatment of S. aureus with CFusoN. The bactericidal killing efficiency of CFusoN is proposed to occur through the synergistic efficacy of the targeted attachment of CNP to the bacterial cells along with the lipid solubilization property of NE. Interestingly, NECNP didn't elicit any in vitro hemolytic activity or cytotoxicity against red blood cells (RBCs) and L929 fibroblast cells, respectively, at its bactericidal concentration. Furthermore, a porcine skin wound infection model exhibited the enhanced wound cleansing potency of CFusoN in comparison to the commercially available wound cleansers. The obtained antibacterial activity, biocompatibility and skin wound disinfection efficacy of the NECNP demonstrated the formulation of a cell targeted CFusoN as a promising translatable strategy to combat bacterial infection.

Attention-UNet architectures with pretrained backbones for multi-class cardiac MR image segmentation.

Segmentation architectures based on deep learning proficient extraordinary results in medical imaging technologies. Computed tomography (CT) images and Magnetic Resonance Imaging (MRI) in diagnosis and treatment are increasing and significantly support the diagnostic process by removing the bottlenecks of manual segmentation. Cardiac Magnetic Resonance Imaging (CMRI) is a state-of-the-art imaging technique used to acquire vital heart measurements and has received extensive attention from researchers for automatic segmentation. Deep learning methods offer high-precision segmentation but still pose several difficulties, such as pixel homogeneity in nearby organs. The motivated study using the attention mechanism approach was introduced for medical images for automated algorithms. The experiment focuses on observing the impact of the attention mechanism with and without pretrained backbone networks on the UNet model. For the same, three networks are considered: Attention-UNet, Attention-UNet with resnet50 pretrained backbone and Attention-UNet with densenet121 pretrained backbone. The experiments are performed on the ACDC Challenge 2017 dataset. The performance is evaluated by conducting a comparative analysis based on the Dice Coefficient, IoU Coefficient, and cross-entropy loss calculations. The Attention-UNet, Attention-UNet with resnet50 pretrained backbone, and Attention-UNet with densenet121 pretrained backbone networks obtained Dice Coefficients of 0.9889, 0.9720, and 0.9801, respectively, along with corresponding IoU scores of 0.9781, 0.9457, and 0.9612. Results compared with the state-of-the-art methods indicate that the methods are on par with, or even superior in terms of both the Dice coefficient and Intersection-over-union.

Rational design of antimicrobial peptide conjugated graphene-silver nanoparticle loaded chitosan wound dressing.

Wound dressing with poor antibacterial properties, the tendency to adhere to the wound site, poor mechanical strength, and lack of porosity and flexibility are the major cause of blood loss, delayed wound repair, and sometimes causes death during the trauma or injury. In such cases, hydrogel-based antibacterial wound dressing would be a boon to the existing dressing as the moist environment will maintain the cooling temperate and proper exchange of atmosphere around the wound. In the present study, the multifunctional graphene with silver and ε-Poly-l-lysine reinforced into the chitosan matrix (CGAPL) was prepared as a nanobiocomposite wound dressing. The contact angle measurement depicted the hydrophilic property of CGAPL nanobiocomposite dressing (water contact angle 42°), while the mechanical property was 78.9 MPa. The antibacterial and cell infiltration study showed the antimicrobial property of CGAPL nanobiocomposite wound dressing. It also demonstrated no cytotoxicity to the L929 fibroblast cells. Chorioallantoic Membrane (CAM) assay showed the pro-angiogenic potential of CGAPL nanobiocomposite wound dressing. In-vitro scratch wound assay confirmed the migration of cells and increased cell adhesion and proliferation within 18 h of culture on the surface of CGAPL nanobiocomposite dressing. Later, the in-vivo study in the Wistar rat model showed that CGAPL nanobiocomposite dressing significantly enhanced the wound healing process as compared to the commercially available wound dressing Tegaderm (p-value <0.01) and Fibroheal@Ag (p-value <0.005) and obtained complete wound closure in 14 days. Histology study further confirmed the complete healing process, re-epithelization, and thick epidermis tissue formation. The proposed CGAPL nanobiocomposite wound dressing thus offers a novel wound dressing material with an efficient and faster wound healing property.

Epoch and accuracy based empirical study for cardiac MRI segmentation using deep learning technique.

Cardiac magnetic resonance imaging (CMRI) is a non-invasive imaging technique to analyse the structure and function of the heart. It was enhanced considerably over several years to deliver functional information for diagnosing and managing cardiovascular disease. CMRI image delivers non-invasive, clear access to the heart and great vessels. The segmentation of CMRI provides quantification parameters such as myocardial viability, ejection fraction, cardiac chamber volume, and morphological details. In general, experts interpret the CMR images by delineating the images manually. The manual segmentation process is time-consuming, and it has been observed that the final observation varied with the opinion of the different experts. Convolution neural network is a new-age technology that provides impressive results compared to manual ones. In this study convolution neural network model is used for the segmentation task. The neural network parameters have been optimized to perform on the novel data set for accurate predictions. With other parameters, epochs play an essential role in training the network, as the network should not be under-fitted or over-fitted. The relationship between the hyperparameter epoch and accuracy is established in the model. The model delivers the accuracy of 0.88 in terms of the IoU coefficient.

Piano-stool ruthenium(II) complexes with maleimide and phosphine or phosphite ligands: synthesis and activity against normal and cancer cells.

In these studies, we designed and investigated cyto- and genotoxic potential of five ruthenium cyclopentadienyl complexes bearing different phosphine and phosphite ligands. All of the complexes were characterized with spectroscopic analysis (NMR, FT-IR, ESI-MS, UV-vis, fluorescence and XRD (for two compounds)). For biological studies, we used three types of cells - normal peripheral blood mononuclear (PBM) cells, leukemic HL-60 cells and doxorubicin-resistance HL-60 cells (HL-60/DR). We compared the results obtained with those obtained for the complex with maleimide ligand CpRu(CO)2(η1-N-maleimidato) 1, which we had previously reported. We observed that the complexes CpRu(CO)(PPh3)(η1-N-maleimidato) 2a and CpRu(CO)(P(OEt)3)(η1-N-maleimidato) 3a were the most cytotoxic for HL-60 cells and non-cytotoxic for normal PBM cells. However, complex 1 was more cytotoxic for HL-60 cells than complexes 2a and 3a (IC50 = 6.39 µM vs. IC50 = 21.48 µM and IC50 = 12.25 µM, respectively). The complex CpRu(CO)(P(OPh)3)(η1-N-maleimidato) 3b is the most cytotoxic for HL-60/DR cells (IC50 = 104.35 µM). We found the genotoxic potential of complexes 2a and 3a only in HL-60 cells. These complexes also induced apoptosis in HL-60 cells. Docking studies showed that complexes 2a and CpRu(CO)(P(Fu)3)(η1-N-maleimidato) 2b have a small ability to degrade DNA, but they may cause a defect in DNA damage repair mechanisms leading to cell death. This hypothesis is corroborated with the results obtained in the plasmid relaxation assay in which ruthenium complexes bearing phosphine and phosphite ligands induce DNA breaks.

Surgical Management of an Infant with Nonresolving Pneumonia.

We describe a 3-month-old baby who presented with a nonresolving pneumonia which failed to respond to antibiotic therapy. An underlying congenital pulmonary adenomatous malformation was suspected. On thoracotomy, she was found to have a tuberculous mediastinal abscess which was drained. Mediastinal abscess is a rare occurrence in childhood tuberculosis.

Inhibitory potential of iRGD peptide-conjugated garcinol-loaded biodegradable nanoparticles in rat colorectal carcinoma.

Targeted drug delivery has become attention in chemotherapy during the last decade. The principle of chemotherapy seeks maximum effect to the desired site and the minimum impact to other undesired sites of action. The nanoparticulated drug delivery system progressed a lot in this aspect in the last twenty years. Plant-derived natural products and their semisynthetic analogues boosted chemotherapy through their excellent mechanistic approach to killing cancer cells. Keeping in mind the available molecular targets in colorectal carcinoma (CRC), in this article, we proposed a peptide conjugated novel polymeric nanoparticle to deliver garcinol against colorectal carcinoma. Integrin binding peptide iRGD, sequence c(CRGDKGPDC), has been selected as a targeting moiety, as most CRC overexpress integrins. We encapsulated garcinol in biodegradable polymeric nanoparticle (PLGA)-conjugated with iRGD peptide on the particles' surface, and analyzed its (iRGD-GAR-NP's) in vitro and in vivo antineoplastic potential against CRC in a comparative way with gracinol (GAR) and garcinol-loaded PLGA nanoparticles (GAR-NP). In vitro cellular studies on human CRC cell lines, HCT116 and HT-29, revealed the superior cytotoxic potential of iRGD-GAR-NP over GAR and GAR-NP. The IC50 value on HCT116 cells was reduced by 2.3 times compared to GAR upon the application of iRGD-GAR-NP. At equivalent doses, iRGD-GAR-NP induced higher apoptosis in HCT116 cells and caused blockage of cell cycle at G0/G1 phase of the same. iRGD-GAR-NP increased the apoptotic population of HCT116 cells by 2.5 times compared to GAR. In vivo biodistribution study uncoiled the ability of GAR-NP and iRGD-GAR-NP to accumulate in the colons of dimethyl hydrazine-induced CRC-bearing Sprague-Dawely (SD) rats. In vivo antitumor efficacy study demonstrated the better effect of iRGD-GAR-NP to reduce CRC tumor progression in experimental animals. The survival rate of animals was also increased by 166% in the case of iRGD-GAR-NP compared to CRC-bearing animals received no treatment.

Bioinspired Cationic-Aromatic Copolymer for Strong and Reversible Underwater Adhesion.

Developing new underwater glue adhesives with robust and repeatable adhesion to various surfaces is promising and useful in marine life and medical treatments. In this work, we developed a novel glue based on a copolymer with a cation-co-aromatic sequence where the cationic units contain both catechol and positively charged sites. The glue consists of a crosslinked copolymer of poly(2-hydroxy-3-phenoxypropyl acrylate-co-3-(5-(3,4 dihydroxyphenyl)-4-oxo-3 N-pentyl)imidazolium) bromide in dimethyl sulfoxide. Solidification of the glue, triggered by contact with water, undergoes a coacervation stage and causes a drastic growth of its mechanical properties over time. The glue demonstrates fast-developing, strong, and repeatable underwater adhesion to different materials and can maintain its strength for a long time. The adhesion strength tends to increase with the surface energy of the substrate material, to a maximum value of 160 kPa found in plywood. Experiments conducted in aqueous media with different pH and ionic strengths, including physiological conditions and seawater, showed an even stronger adhesion than that evolved in deionized water. Thus, the developed glue is a promising candidate for use in marine life, tissue adhesives, and other freshwater and saline water applications.

A Comprehensive Survey on the Detection, Classification, and Challenges of Neurological Disorders.

Neurological disorders (NDs) are becoming more common, posing a concern to pregnant women, parents, healthy infants, and children. Neurological disorders arise in a wide variety of forms, each with its own set of origins, complications, and results. In recent years, the intricacy of brain functionalities has received a better understanding due to neuroimaging modalities, such as magnetic resonance imaging (MRI), magnetoencephalography (MEG), and positron emission tomography (PET), etc. With high-performance computational tools and various machine learning (ML) and deep learning (DL) methods, these modalities have discovered exciting possibilities for identifying and diagnosing neurological disorders. This study follows a computer-aided diagnosis methodology, leading to an overview of pre-processing and feature extraction techniques. The performance of existing ML and DL approaches for detecting NDs is critically reviewed and compared in this article. A comprehensive portion of this study also shows various modalities and disease-specified datasets that detect and records images, signals, and speeches, etc. Limited related works are also summarized on NDs, as this domain has significantly fewer works focused on disease and detection criteria. Some of the standard evaluation metrics are also presented in this study for better result analysis and comparison. This research has also been outlined in a consistent workflow. At the conclusion, a mandatory discussion section has been included to elaborate on open research challenges and directions for future work in this emerging field.