Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction

Reverse engineering of gene regulatory networks (GRNs) is the process of estimating genetic interactions of a cellular system from gene expression data. In this paper, we propose a novel hybrid systematic algorithm based on neurofuzzy network for reconstructing GRNs from observational gene expression data when only a medium-small number of measurements are available. The approach uses fuzzy logic to transform gene expression values into qualitative descriptors that can be evaluated by using a set of defined rules. The algorithm uses neurofuzzy network to model genes effects on other genes followed by four stages of decision making to extract gene interactions. One of the main features of the proposed algorithm is that an optimal number of fuzzy rules can be easily and rapidly extracted without overparameterizing. Data analysis and simulation are conducted on microarray expression profiles of S. cerevisiae cell cycle and demonstrate that the proposed algorithm not only selects the patterns of the time series gene expression data accurately, but also provides models with better reconstruction accuracy when compared with four published algorithms: DBNs, VBEM, time delay ARACNE, and PF subjected to LASSO. The accuracy of the proposed approach is evaluated in terms of recall and F-score for the network reconstruction task

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Unsupervised learning via self-organization: a dynamic approach

To aid in intelligent data mining, this book introduces a new family of unsupervised algorithms that have a basis in self-organization, yet are free from many of the constraints typical of other well known self-organizing architectures. It then moves through a series of pertinent real world applications with regards to the processing of multimedia data from its role in generic image processing techniques such as the automated modeling and removal of impulse noise in digital images, to problems in digital asset management, and its various roles in feature extraction, visual enhancement, segmentation, and analysis of microbiological image data

Burkholderia pseudomallei capsule exacerbates respiratory melioidosis but does not afford protection against antimicrobial signaling or bacterial killing in human olfactory ensheathing cells

Melioidosis, caused by the bacterium Burkholderia pseudomallei, is an often severe infection that regularly involves respiratory disease following inhalation exposure. Intranasal (i.n.) inoculation of mice represents an experimental approach used to study the contributions of bacterial capsular polysaccharide I (CPS I) to virulence during acute disease. We used aerosol delivery of B. pseudomallei to establish respiratory infection in mice and studied CPS I in the context of innate immune responses. CPS I improved B. pseudomallei survival in vivo and triggered multiple cytokine responses, neutrophil infiltration, and acute inflammatory histopathology in the spleen, liver, nasal-associated lymphoid tissue, and olfactory mucosa (OM). To further explore the role of the OM response to B. pseudomallei infection, we infected human olfactory ensheathing cells (OECs) in vitro and measured bacterial invasion and the cytokine responses induced following infection. Human OECs killed >90% of the B. pseudomallei in a CPS I-independent manner and exhibited an antibacterial cytokine response comprising granulocyte colony-stimulating factor, tumor necrosis factor alpha, and several regulatory cytokines. In-depth genome-wide transcriptomic profiling of the OEC response by RNA-Seq revealed a network of signaling pathways activated in OECs following infection involving a novel group of 378 genes that encode biological pathways controlling cellular movement, inflammation, immunological disease, and molecular transport. This represents the first antimicrobial program to be described in human OECs and establishes the extensive transcriptional defense network accessible in these cells. Collectively, these findings show a role for CPS I in B. pseudomallei survival in vivo following inhalation infection and the antibacterial signaling network that exists in human OM and OECs

Burkholderia pseudomallei Capsule Exacerbates Respiratory Melioidosis but Does Not Afford Protection against Antimicrobial Signaling or Bacterial Killing in Human Olfactory Ensheathing Cells

g Melioidosis, caused by the bacterium Burkholderia pseudomallei, is an often severe infection that regularly involves respiratory disease following inhalation exposure. Intranasal (i.n.) inoculation of mice represents an experimental approach used to study the contributions of bacterial capsular polysaccharide I (CPS I) to virulence during acute disease. We used aerosol delivery of B. pseudomallei to establish respiratory infection in mice and studied CPS I in the context of innate immune responses. CPS I improved B. pseudomallei survival in vivo and triggered multiple cytokine responses, neutrophil infiltration, and acute inflammatory histopathology in the spleen, liver, nasal-associated lymphoid tissue, and olfactory mucosa (OM). To further explore the role of the OM response to B. pseudomallei infection, we infected human olfactory ensheathing cells (OECs) in vitro and measured bacterial invasion and the cytokine responses induced following infection. Human OECs killed >90% of the B. pseudomallei in a CPS I-independent manner and exhibited an antibacterial cytokine response comprising granulocyte colony-stimulating factor, tumor necrosis factor alpha, and several regulatory cytokines. In-depth genome-wide transcriptomic profiling of the OEC response by RNA-Seq revealed a network of signaling pathways activated in OECs following infection involving a novel group of 378 genes that encode biological pathways controlling cellular movement, inflammation, immunological disease, and molecular transport. This represents the first antimicrobial program to be described in human OECs and establishes the extensive transcriptional defense network accessible in these cells. Collectively, these findings show a role for CPS I in B. pseudomallei survival in vivo following inhalation infection and the antibacterial signaling network that exists in human OM and OECs

Cerebral venous thrombosis after vaccination against COVID-19 in the UK: a multicentre cohort study

BackgroundA new syndrome of vaccine-induced immune thrombotic thrombocytopenia (VITT) has emerged as a rare side-effect of vaccination against COVID-19. Cerebral venous thrombosis is the most common manifestation of this syndrome but, to our knowledge, has not previously been described in detail. We aimed to document the features of post-vaccination cerebral venous thrombosis with and without VITT and to assess whether VITT is associated with poorer outcomes.MethodsFor this multicentre cohort study, clinicians were asked to submit all cases in which COVID-19 vaccination preceded the onset of cerebral venous thrombosis, regardless of the type of vaccine, interval between vaccine and onset of cerebral venous thrombosis symptoms, or blood test results. We collected clinical characteristics, laboratory results (including the results of tests for anti-platelet factor 4 antibodies where available), and radiological features at hospital admission of patients with cerebral venous thrombosis after vaccination against COVID-19, with no exclusion criteria. We defined cerebral venous thrombosis cases as VITT-associated if the lowest platelet count recorded during admission was below 150 × 109 per L and, if the D-dimer was measured, the highest value recorded was greater than 2000 μg/L. We compared the VITT and non-VITT groups for the proportion of patients who had died or were dependent on others to help them with their activities of daily living (modified Rankin score 3–6) at the end of hospital admission (the primary outcome of the study). The VITT group were also compared with a large cohort of patients with cerebral venous thrombosis described in the International Study on Cerebral Vein and Dural Sinus Thrombosis.FindingsBetween April 1 and May 20, 2021, we received data on 99 patients from collaborators in 43 hospitals across the UK. Four patients were excluded because they did not have definitive evidence of cerebral venous thrombosis on imaging. Of the remaining 95 patients, 70 had VITT and 25 did not. The median age of the VITT group (47 years, IQR 32–55) was lower than in the non-VITT group (57 years; 41–62; p=0·0045). Patients with VITT-associated cerebral venous thrombosis had more intracranial veins thrombosed (median three, IQR 2–4) than non-VITT patients (two, 2–3; p=0·041) and more frequently had extracranial thrombosis (31 [44%] of 70 patients) compared with non-VITT patients (one [4%] of 25 patients; p=0·0003). The primary outcome of death or dependency occurred more frequently in patients with VITT-associated cerebral venous thrombosis (33 [47%] of 70 patients) compared with the non-VITT control group (four [16%] of 25 patients; p=0·0061). This adverse outcome was less frequent in patients with VITT who received non-heparin anticoagulants (18 [36%] of 50 patients) compared with those who did not (15 [75%] of 20 patients; p=0·0031), and in those who received intravenous immunoglobulin (22 [40%] of 55 patients) compared with those who did not (11 [73%] of 15 patients; p=0·022).InterpretationCerebral venous thrombosis is more severe in the context of VITT. Non-heparin anticoagulants and immunoglobulin treatment might improve outcomes of VITT-associated cerebral venous thrombosis. Since existing criteria excluded some patients with otherwise typical VITT-associated cerebral venous thrombosis, we propose new diagnostic criteria that are more appropriate