Bi-Objective Community Detection (BOCD) in Networks using Genetic Algorithm

A lot of research effort has been put into community detection from all corners of academic interest such as physics, mathematics and computer science. In this paper I have proposed a Bi-Objective Genetic Algorithm for community detection which maximizes modularity and community score. Then the results obtained for both benchmark and real life data sets are compared with other algorithms using the modularity and MNI performance metrics. The results show that the BOCD algorithm is capable of successfully detecting community structure in both real life and synthetic datasets, as well as improving upon the performance of previous techniques.Comment: 11 pages, 3 Figures, 3 Tables. arXiv admin note: substantial text overlap with arXiv:0906.061

Molecular analysis of sarcomeric and non-sarcomeric genes in patients with hypertrophic cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is a common genetic heart disorder characterized by unexplained left ventricle hypertrophy associated with non-dilated ventricular chambers. Several genes encoding heart sarcomeric proteins have been associated to HCM, but a small proportion of HCM patients harbor alterations in other non-sarcomeric loci. The variable expression of HCM seems influenced by genetic modifier factors and new sequencing technologies are redefining the understanding of genotype–phenotype relationships, even if the interpretations of the numerous identified variants pose several challenges. Methods and results: We investigated 62 sarcomeric and non-sarcomeric genes in 41 HCM cases and in 3 HCM-related disorders patients. We employed an integrated approach that combines multiple tools for the prediction, annotation and visualization of functional variants. Genotype–phenotype correlations were carried out for inspecting the involvement of each gene in age onset and clinical variability of HCM. The 80% of the non-syndromic patients showed at least one rare non-synonymous variant (nsSNV) and among them, 58% carried alterations in sarcomeric loci, 14% in desmosomal and 7% in other non-sarcomeric ones without any sarcomere change. Statistical analyses revealed an inverse correlation between the number of nsSNVs and age at onset, and a relationship between the clinical variability and number and type of variants. Conclusions: Our results extend the mutational spectrum of HCM and contribute in defining the molecular pathogenesis and inheritance pattern(s) of this condition. Besides, we delineate a specific procedure for the identification of the most likely pathogenetic variants for a next generation sequencing approach embodied in a clinical context

Crizotinib-induced antitumour activity in human alveolar rhabdomyosarcoma cells is not solely dependent on ALK and MET inhibition

BACKGROUND: Rhabdomyosarcoma (RMS) is the most commonly diagnosed malignant soft tissue tumour in children and adolescents. Aberrant expression of Anaplastic Lymphoma Kinase (ALK) and MET gene has been implicated in the malignant progression of RMS, especially in the alveolar subtype. This observation suggests that crizotinib (PF-02341066), a kinase inhibitor against ALK and MET, may have a therapeutic role in RMS, although its antitumour activity in this malignancy has not yet been studied. METHODS: RH4 and RH30 alveolar RMS (ARMS) cell lines were treated with crizotinib and then assessed by using proliferation, viability, migration and colony formation assays. Multiple approaches, including flow cytometry, immunofluorescence, western blotting and siRNA-based knock-down, were used in order to investigate possible molecular mechanisms linked to crizotinib activity. RESULTS: In vitro treatment with crizotinib inhibited ALK and MET proteins, as well as Insulin-like Growth Factor 1 Receptor (IGF1R), with a concomitant robust dephosphorylation of AKT and ERK, two downstream kinases involved in RMS cell proliferation and survival. Exposure to crizotinib impaired cell growth, and accumulation at G2/M phase was attributed to an altered expression and activation of checkpoint regulators, such as Cyclin B1 and Cdc2. Crizotinib was able to induce apoptosis and autophagy in a dose-dependent manner, as shown by caspase-3 activation/PARP proteolytic cleavage down-regulation and by LC3 activation/p62 down-regulation, respectively. The accumulation of reactive oxygen species (ROS) seemed to contribute to crizotinib effects in RH4 and RH30 cells. Moreover, crizotinib-treated RH4 and RH30 cells exhibited a decreased migratory/invasive capacity and clonogenic potential. CONCLUSIONS: These results provide a further insight into the molecular mechanisms affected by crizotinib in ARMS cells inferring that it could be a useful therapeutic tool in ARMS cancer treatment

Triple positive breast cancer. A distinct subtype?

Breast cancer is a heterogeneous disease, and within the HER-2 positive subtype this is highly exemplified by the presence of substantial phenotypical and clinical heterogeneity, mostly related to hormonal receptor (HR) expression. It is well known how HER-2 positivity is commonly associated with a more aggressive tumor phenotype and decreased overall survival and, moreover, with a reduced benefit from endocrine treatment. Preclinical studies corroborate the role played by functional crosstalks between HER-2 and estrogen receptor (ER) signaling in endocrine resistance and, more recently, the activation of ER signaling is emerging as a possible mechanism of resistance to HER-2 blocking agents. Indeed, HER-2 positive breast cancer heterogeneity has been suggested to underlie the variability of response not only to endocrine treatments, but also to HER-2 blocking agents. Among HER-2 positive tumors, HR status probably defines two distinct subtypes, with dissimilar clinical behavior and different sensitivity to anticancer agents. The triple positive subtype, namely, ER/PgR/Her-2 positive tumors, could be considered the subset which most closely resembles the HER-2 negative/HR positive tumors, with substantial differences in biology and clinical outcome. We argue on whether in this subgroup the "standard" treatment may be considered, in selected cases, i.e., small tumors, low tumor burden, high expression of both hormonal receptors, an overtreatment. This article review the existing literature on biologic and clinical data concerning the HER-2/ER/PgR positive tumors, in an attempt to better define the HER-2 subtypes and to optimize the use of HER-2 targeted agents, chemotherapy and endocrine treatments in the various subsets

Fasting glucose and body mass index as predictors of activity in breast cancer patients treated with everolimus-exemestane: the EverExt study

Evidence on everolimus in breast cancer has placed hyperglycemia among the most common high grade adverse events. Anthropometrics and biomarkers of glucose metabolism were investigated in a observational study of 102 postmenopausal, HR + HER2- metastatic breast cancer patients treated with everolimus-exemestane in first and subsequent lines. Best overall response (BR) and clinical benefit rate (CBR) were assessed across subgroups defined upon fasting glucose (FG) and body mass index (BMI). Survival was estimated by Kaplan-Meier method and log-rank test. Survival predictors were tested in Cox models. Median follow up was 12.4 months (1.0-41.0). The overall cohort showed increasing levels of FG and decreasing BMI (p < 0.001). Lower FG fasting glucose at BR was more commonly associated with C/PR or SD compared with PD (p < 0.001). We also observed a somewhat higher BMI associated with better response (p = 0.052). More patients in the lowest FG category achieved clinical benefit compared to the highest (p < 0.001), while no relevant differences emerged for BMI. Fasting glucose at re-assessment was also predictive of PFS (p = 0.037), as confirmed in models including BMI and line of therapy (p = 0.049). Treatment discontinuation was significantly associated with changes in FG (p = 0.014). Further research is warranted to corroborate these findings and clarify the underlying mechanisms

Obstetric near-miss cases among women admitted to intensive care units in Italy

Objective. Maternal near-miss defines a narrow category of morbidity encompassing potentially life-threatening episodes. The purpose of this study was to detect near-miss instances among women admitted to intensive care units or coronary units, analyze associated causes, and compute absolute and specific maternal morbidity rates in six Italian regions. Design. Observational retrospective study. Setting. Six Italian regions representing 49% of all resident Italian women aged 15-49 years. Population. The study population included all pregnant women aged 15-49 years admitted to intensive care units or coronary care units in the participating regions. Cases were defined as women aged 15-49 years resident in the participating regions, with one or more hospitalizations in intensive care for pregnancy or any pregnancy outcome between 2004 and 2005. Methods. Cases were identified through the Hospital Discharge Database. Enrolled cases were diagnosed according to the 9th International Classification of Diseases. Main outcome measure. Maternal near-miss rate (number of women experiencing an admission to intensive care units/all women with live or stillborn babies). Results. A total of 1259 near-miss cases were identified and the total maternal near-miss rate was 2.0/1000 deliveries. Seventy percent of the women were admitted to intensive care units or coronary units after a cesarean section. The leading associated risk factors were obstetric hemorrhage/disseminated intravascular coagulation (40%) and hypertensive disorders of pregnancy (29%). Conclusions. Monitoring of near-miss morbidity in conjunction with mortality surveillance could help to identify effective preventive measures for potentially life-threatening episodes

Multimodal laminar characterization of visual areas along the cortical hierarchy

Understanding the relationship between brain structure and function is a central goal in neuroscience. While post-mortem studies using microscopic techniques have provided detailed insights into the brain’s cytoarchitectonic and myeloarchitectonic patterns, linking these structural findings to functional outcomes remains challenging. Magnetic resonance imaging (MRI) has emerged as a powerful non-invasive tool for studying both structure and function, but discrepancies in spatial resolution between structural and functional imaging, especially in layer-fMRI, complicate the interpretation of functional results. In this study, we explore how visual cortical hierarchy relates to microscopic and mesoscopic laminar features. Focusing on visual areas that span progressive hierarchical levels, V1, V2, V3, and hMT+, we apply a multimodal approach combining post-mortem histology, post-mortem and in-vivo quantitative MRI (qMRI), and resting-state layer-fMRI. Using the open-access post-mortem AHEAD dataset, which integrates histological and qMRI contrasts from the same brain samples, we bridge microscopic observations with qMRI data. In parallel, we incorporate high-resolution Embedded Image MRI and resting-state layer-fMRI from the same participant, allowing for a comparative analysis of laminar profiles across cortical depth. For computing laminar profiles, we developed an analysis pipeline that bridges histology images, mesoscopic qMRI, and layer-fMRI. Our findings highlight parvalbumin laminar profiles (reflecting interneuron parvalbumin density) as the most discriminative feature for differentiating brain areas. Additionally, we report laminar quantitative Embedded Image profiles from post-mortem and in-vivo data, together with Embedded Image-weighted resting-state layer-fMRI, all of which exhibit a similar overall shape across modalities. Using our methodological framework, a similar laminar characterization can be extended to study other brain regions. Generative models for layer fMRI will benefit from incorporating these new empirical microstructural (parvalbumin) and physical quantitative Embedded Image data, leading to more area-specific and accurate models

Characterisation of laminar and vascular spatiotemporal dynamics of CBV and BOLD signals using VASO and ME-GRE at 7T in humans

Interpretation of cortical laminar functional magnetic resonance imaging (fMRI) activity requires detailed knowledge of the spatiotemporal haemodynamic response across vascular compartments due to the well-known vascular biases (e.g. the draining veins). Further complications arise from the spatiotemporal hemodynamic response that differs depending on the duration of stimulation. This information is crucial for future studies using depth-dependent cerebral blood volume (CBV) measurements, which promise higher specificity for the cortical microvasculature than the blood oxygenation level dependent (BOLD) contrast. To date, direct information about CBV dynamics with respect to stimulus duration, cortical depth and vasculature is missing in humans. Therefore, we characterized the cortical depth-dependent CBV-haemodynamic responses across a wide set of stimulus durations with 0.9 mm isotropic spatial and 0.785 seconds effective temporal resolution in humans using slice-selective slabinversion vascular space occupancy (SS-SI VASO). Additionally, we investigated signal contributions from macrovascular compartments using fine-scale vascular information from multiecho gradient-echo (ME-GRE) data at 0.35 mm isotropic resolution. In total, this resulted in >7.5h of scanning per participant (n=5). We have three major findings: (I) While we could demonstrate that 1 second stimulation is viable using VASO, more than 12 seconds stimulation provides better CBV responses in terms of specificity to microvasculature, but durations beyond 24 seconds of stimulation may be wasteful for certain applications. (II) We observe that CBV responses show dilation patterns across the cortex. (III) While we found increasingly strong BOLD signal responses in vessel-dominated voxels with longer stimulation durations, we found increasingly strong CBV signal responses in vessel-dominated voxels only until 4 second stimulation durations. After 4 seconds, only the signal from non-vessel dominated voxels kept increasing. This might explain why CBV responses are more specific to the underlying neuronal activity for long stimulus durations

Microfluidic tools for enhanced characterization of therapeutic stem cells and prediction of their potential antimicrobial secretome

Antibiotic resistance is creating enormous attention on the development of new antibiotic-free therapy strategies for bacterial diseases. Mesenchymal stromal stem cells (MSCs) are the most promising candidates in current clinical trials and included in several cell-therapy protocols. Together with the well-known immunomodulatory and regenerative potential of the MSC secretome, these cells have shown direct and indirect anti-bacterial effects. However, the low reproducibility and standardization of MSCs from different sources are the current limitations prior to the purification of cell-free secreted antimicrobial peptides and exosomes. In order to improve MSC characterization, novel label-free functional tests, evaluating the biophysical properties of the cells, will be advan-tageous for their cell profiling, population sorting, and quality control. We discuss the potential of emerging microfluidic technologies providing new insights into density, shape, and size of live cells, starting from heterogeneous or 3D cultured samples. The prospective application of these technologies to studying MSC populations may contribute to developing new biopharmaceutical strategies with a view to naturally overcoming bacterial defense mechanisms