Iron oxide nanoparticles and derivatives for biomedical imaging and application in cancer diagnosis and siRNA therapy

This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the Makedonia Palace Hotel, Thessaloniki in Greece. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, Aristotle University of Thessaloniki, University of Thessaly, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute.Our studies have focused on the application of imaging-capable nanoparticulate agents for the delivery of small RNA-based tumor therapy. One example includes magnetic nanoparticles (MN), which have traditionally been utilized as contrast agents for magnetic resonance imaging. The probes typically consist of a dextran-coated superparamagnetic iron oxide core (for magnetic resonance imaging), labeled with Cy5.5 dye (for near-infrared in vivo optical imaging), and conjugated to synthetic small interfering RNA (siRNA) molecules targeting model or therapeutic genes. We have explored the potential of these nanoparticles as delivery modules for small interfering RNA to tumors. Furthermore, we have investigated the feasibility of combining the imaging and delivery capabilities of these nanoparticles for the tracking of siRNA bioavailability. The versatile functionalization potential of MN has allowed us to control properties of the agents, such as uptake mechanism and target organ distribution. The tumoral accumulation of MNsiRNA results in a remarkable level of target-gene down-regulation. Repeated treatment with MN-siBIRC5, targeting the tumor-specific anti-apoptotic gene, birc5, leads to the induction of apoptosis in the tumors and an overall reduction in tumor growth rate. More recently, we have synthesized a second generation of nanoparticles, which combine the capability for high-resolution magnetic resonance imaging with detection by ultrasensitive surface enhanced Raman scattering

Morphological characterization of the venom apparatus in the wolf spider Lycosa singoriensis (Laxmann, 1770)

The wolf spider Lycosa singoriensis (Laxmann, 1770) (Lycosidae: Araneae) is distributed throughout central and eastern Europe, including Russia, Kazakhistan and Turkey. This study describes the venom apparatus morphology of L. singoriensis through scanning electron microscopy (SEM). Its structure follows the general architecture observed in other spiders. Generally, a venom apparatus is composed by a pair of venom glands and chelicerae. L. singoriensis chelicerae are robust and consist of a stout basis and a movable apical segment (fang). The fang rests in a groove on the basal segment that is covered by different types of hair. L. singoriensis venom glands present equal size and measure about 4 mm in length. Each gland is enclosed by irregular muscular layers

Combined Small Interfering RNA Therapy and In Vivo Magnetic Resonance Imaging in Islet Transplantation

OBJECTIVE Recent advances in human islet transplantation are hampered by significant graft loss shortly after transplantation and inability to follow islet fate directly. Both issues were addressed by utilizing a dual-purpose therapy/imaging small interfering RNA (siRNA)-nanoparticle probe targeting apoptotic-related gene caspase-3. We expect that treatment with the probe would result in significantly better survival of transplanted islets, which could be monitored by in vivo magnetic resonance imaging (MRI). RESEARCH DESIGN AND METHODS We synthesized a probe consisting of therapeutic (siRNA to human caspase-3) and imaging (magnetic iron oxide nanoparticles, MN) moieties. In vitro testing of the probe included serum starvation of the islets followed by treatment with the probe. Caspase-3 gene silencing and protein expression were determined by RT-PCR and Western blot, respectively. In vivo studies included serial MRI of NOD-SCID mice transplanted with MN-small interfering (si)Caspase-3–labeled human islets under the left kidney capsule and MN-treated islets under the right kidney capsule. RESULTS Treatment with MN-siCaspase-3 probe resulted in decrease of mRNA and protein expression in serum-starved islets compared with controls. In vivo MRI showed that there were significant differences in the relative volume change between MN-siCaspase-3–treated grafts and MN-labeled grafts. Histology revealed decreased caspase-3 expression and cell apoptosis in MN-siCaspase-3–treated grafts compared with the control side. CONCLUSIONS Our data show the feasibility of combining siRNA therapy and in vivo monitoring of transplanted islets in mice. We observed a protective effect of MN-siCaspase-3 in treated islets both in vitro and in vivo. This study could potentially aid in increasing the success of clinical islet transplantation

Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) methods in medical images may result in the loss of critical clinical information and/or the appearance of false information. To assess this, the focus was on the angular resolution of dMRI and a clinical trial was conducted on migraine, specifically between episodic and chronic migraine patients. The number of gradient directions had an impact on white matter analysis results, with statistically significant differences between groups being drastically reduced when using 21 gradient directions instead of the original 61. Fourteen teams from different institutions were tasked to use DL to enhance three diffusion metrics (FA, AD and MD) calculated from data acquired with 21 gradient directions and a b-value of 1000 s/mm2. The goal was to produce results that were comparable to those calculated from 61 gradient directions. The results were evaluated using both standard image quality metrics and Tract-Based Spatial Statistics (TBSS) to compare episodic and chronic migraine patients. The study results suggest that while most DL techniques improved the ability to detect statistical differences between groups, they also led to an increase in false positive. The results showed that there was a constant growth rate of false positives linearly proportional to the new true positives, which highlights the risk of generalization of AI-based tasks when assessing diverse clinical cohorts and training using data from a single group. The methods also showed divergent performance when replicating the original distribution of the data and some exhibited significant bias. In conclusion, extreme caution should be exercised when using AI methods for harmonization or synthesis in clinical studies when processing heterogeneous data in clinical studies, as important information may be altered, even when global metrics such as structural similarity or peak signal-to-noise ratio appear to suggest otherwise

Hormone Receptor Expression and Activity for Different Tumour Locations in Patients with Advanced and Recurrent Endometrial Carcinoma

Background: Response to hormonal therapy in advanced and recurrent endometrial cancer (EC) can be predicted by oestrogen and progesterone receptor immunohistochemical (ER/PR-IHC) expression, with response rates of 60% in PR-IHC &gt; 50% cases. ER/PR-IHC can vary by tumour location and is frequently lost with tumour progression. Therefore, we explored the relationship between ER/PR-IHC expression and tumour location in EC. Methods: Pre-treatment tumour biopsies from 6 different sites of 80 cases treated with hormonal therapy were analysed for ER/PR-IHC expression and classified into categories 0–10%, 10–50%, and &gt;50%. The ER pathway activity score (ERPAS) was determined based on mRNA levels of ER-related target genes, reflecting the actual activity of the ER receptor. Results: There was a trend towards lower PR-IHC (33% had PR &gt; 50%) and ERPAS (27% had ERPAS &gt; 15) in lymphogenic metastases compared to other locations (p = 0.074). Hematogenous and intra-abdominal metastases appeared to have high ER/PR-IHC and ERPAS (85% and 89% ER-IHC &gt; 50%; 64% and 78% PR-IHC &gt; 50%; 60% and 71% ERPAS &gt; 15, not significant). Tumour grade and previous radiotherapy did not affect ER/PR-IHC or ERPAS. Conclusions: A trend towards lower PR-IHC and ERPAS was observed in lymphogenic sites. Verification in larger cohorts is needed to confirm these findings, which may have implications for the use of hormonal therapy in the future.</p

Hormone Receptor Expression and Activity for Different Tumour Locations in Patients with Advanced and Recurrent Endometrial Carcinoma

Background: Response to hormonal therapy in advanced and recurrent endometrial cancer (EC) can be predicted by oestrogen and progesterone receptor immunohistochemical (ER/PR-IHC) expression, with response rates of 60% in PR-IHC &gt; 50% cases. ER/PR-IHC can vary by tumour location and is frequently lost with tumour progression. Therefore, we explored the relationship between ER/PR-IHC expression and tumour location in EC. Methods: Pre-treatment tumour biopsies from 6 different sites of 80 cases treated with hormonal therapy were analysed for ER/PR-IHC expression and classified into categories 0–10%, 10–50%, and &gt;50%. The ER pathway activity score (ERPAS) was determined based on mRNA levels of ER-related target genes, reflecting the actual activity of the ER receptor. Results: There was a trend towards lower PR-IHC (33% had PR &gt; 50%) and ERPAS (27% had ERPAS &gt; 15) in lymphogenic metastases compared to other locations (p = 0.074). Hematogenous and intra-abdominal metastases appeared to have high ER/PR-IHC and ERPAS (85% and 89% ER-IHC &gt; 50%; 64% and 78% PR-IHC &gt; 50%; 60% and 71% ERPAS &gt; 15, not significant). Tumour grade and previous radiotherapy did not affect ER/PR-IHC or ERPAS. Conclusions: A trend towards lower PR-IHC and ERPAS was observed in lymphogenic sites. Verification in larger cohorts is needed to confirm these findings, which may have implications for the use of hormonal therapy in the future.</p

Prognostic significance of IL-6 and IL-8 ascites levels in ovarian cancer patients

<p>Abstract</p> <p>Background</p> <p>The acellular fraction of epithelial ovarian cancer (EOC) ascites promotes <it>de novo </it>resistance of tumor cells and thus supports the idea that tumor cells may survive in the surrounding protective microenvironment contributing to disease recurrence. Levels of the pro-inflammatory cytokines IL-6 and IL-8 are elevated in EOC ascites suggesting that they could play a role in tumor progression.</p> <p>Methods</p> <p>We measured IL-6 and IL-8 levels in the ascites of 39 patients with newly diagnosed EOC. Commercially available enzyme-linked immunosorbent assay (ELISA) was used to determine IL-6 and IL-8 ascites levels. Ascites cytokine levels were correlated with clinicopathological parameters and progression-free survival.</p> <p>Results</p> <p>Mean ascites levels for IL-6 and IL-8 were 6419 pg/ml (SEM: 1409 pg/ml) and 1408 pg/ml (SEM: 437 pg/ml) respectively. The levels of IL-6 and IL-8 in ascites were significantly lower in patients that have received prior chemotherapy before the surgery (Mann-Whitney U test, <it>P </it>= 0.037 for IL-6 and <it>P </it>= 0.008 for IL-8). Univariate analysis revealed that high IL-6 ascites levels (<it>P </it>= 0.021), serum CA125 levels (<it>P </it>= 0.04) and stage IV (<it>P </it>= 0.009) were significantly correlated with shorter progression-free survival. Including these variables in a multivariate analysis revealed that elevated IL-6 levels (<it>P </it>= 0.033) was an independent predictor of shorter progression-free survival.</p> <p>Conclusion</p> <p>Elevated IL-6, but not IL-8, ascites level is an independent predictor of shorter progression-free survival.</p

blaKPC and rmtB on a single plasmid in Enterobacter amnigenus and Klebsiella pneumoniae isolates from the same patient

Enterobacter amnigenus (EA76) and Klebsiella pneumoniae (KP76) isolates with multidrug-resistant (MDR) patterns were identified from the same patient in the neurosurgery department of our hospital. An outbreak of MDR K. pneumoniae had also occurred in this department. To characterize the resistance mechanism and molecular epidemiology of these isolates, sequential experiments including antimicrobial susceptibility testing, polymerase chain reaction (PCR), plasmid analysis, pulsed field gel electrophoresis (PFGE), and multilocus sequence typing (MLST) were performed. EA76 and KP76 were resistant to all of the antibiotics tested, except colistin and tigecycline. blaKPC-2, blaTEM-1, blaSHV-12, blaCTX-M-3, blaCTX-M-14, and rmtB genes were identified in both isolates, with blaKPC-2, blaTEM-1, blaCTX-M-14, and rmtB being co-carried on one plasmid in each isolate. Further analysis showed different restriction patterns between the two KPC-carrying plasmids. Of the 11 carbapenem-resistant isolates found in the outbreak, all were resistant to all of the β-lactams tested, with 63.64% (7/11) also exhibiting resistance to aminoglycosides and 72.73% (8/11) exhibiting resistance to quinolones. PCR analysis and molecular typing of the 11 K. pneumoniae strains revealed that the seven aminoglycoside-resistant isolates shared the same antibiotic-resistant gene pattern and identical or one-band-difference PFGE profiles relative to KP76. In addition, all of the eight aminoglycoside-resistant isolates, including KP76, belonged to the national epidemic clone ST11. The overall results indicate the emergence of E. amnigenus and outbreak of ST11 K. pneumoniae, with both co-harboring blaKPC and rmtB genes on a single plasmid in our neurosurgery wards

Suffix-specific RNAi Leads to Silencing of F Element in Drosophila melanogaster

Separate conserved copies of suffix, a short interspersed Drosophila retroelement (SINE), and also divergent copies in the 3′ untranslated regions of the three genes, have already been described. Suffix has also been identified on the 3′ end of the Drosophila non-LTR F element, where it forms the last conserved domain of the reverse transcriptase (RT). In our current study, we show that the separate copies of suffix are far more actively transcribed than their counterparts on the F element. Transcripts from both strands of suffix are present in RNA preparations during all stages of Drosophila development, providing the potential for the formation of double-stranded RNA and the initiation of RNA interference (RNAi). Using in situ RNA hybridization analysis, we have detected the expression of both sense and antisense suffix transcripts in germinal cells. These sense and antisense transcripts are colocalized in the primary spermatocytes and in the cytoplasm of the nurse cells, suggesting that they form double-stranded RNA. We performed further analyses of suffix-specific small RNAs using northern blotting and SI nuclease protection assays. Among the total RNA preparations isolated from embryos, larvae, pupae and flies, suffix-specific small interfering RNAs (siRNAs) were detected only in pupae. In wild type ovaries, both the siRNAs and longer suffix-specific Piwi-interacting RNAs (piRNAs) were observed, whereas in ovaries of the Dicer-2 mutant, only piRNAs were detected. We further found by 3′ RACE that in pupae and ovaries, F element transcripts lacking the suffix sequence are also present. Our data provide direct evidence that suffix-specific RNAi leads to the silencing of the relative LINE (long interspersed element), F element, and suggests that SINE-specific RNA interference could potentially downregulate a set of genes possessing SINE stretches in their 5′ or 3′ non-coding regions. These data also suggest that double stranded RNAs possessing suffix are processed by both RNAi and an additional silencing mechanism

Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson's disease and schizophrenia

Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided