Analysis of flow cytometric aneuploid DNA histograms: validation of an automatic procedure against ad hoc experimental data

In this paper we present an improved version of a method for the automatic analysis of flow cytometric DNA histograms from samples containing a mixture of two cell populations. The procedure is tested against two sets of ad hoc experimental data, obtained by mixing cultures of cell lines in different known proportions. The potentialities of the method are enlightened and discussed with regard to its capability of recovering the population percentages, the DNA index and the G0/G1, S, G2+M phase fractions of each population. On the basis of the obtained results, the procedure appears to be a promising tool in the flow cytometric data analysis and, in particular, in problems of diagnosis and prognosis of tumor diseases

Global convergence technique for the Newton method with periodic Hessian evaluation.

The problem of globalizing the Newton method when the actual Hessian matrix is not used at every iteration is considered. A stabilization technique is studied that employs a new line search strategy for ensuring the global convergence under mild assumptions. Moreover, an implementable algorithmic scheme is proposed, where the evaluation of the second derivatives is conditioned to the behavior of the algorithm during the minimization process and the local convexity properties of the objective function. This is done in order to obtain a significant computational saving, while keeping acceptable the unavoidable degradation in convergence speed. The numerical results reported indicate that the method described may be employed advantageously in all applications where the computation of the Hessian matrix is highly time consuming

Efficient training of RBF neural networks for pattern recognition.

The problem of training a radial basis function (RBF) neural network for distinguishing two disjoint sets in Rn is considered. The network parameters can be determined by minimizing an error function that measures the degree of success in the recognition of a given number of training patterns. In this paper, taking into account the specific feature of classification problems, where the goal is to obtain that the network outputs take values above or below a fixed threshold, we propose an approach alternative to the classical one that makes us of the least-squares error function. In particular, the problem is formulated in terms of a system of nonlinear inequalities, and a suitable error function, which depends only on the violated inequalities, is defined. Then, a training algorithm based on this formulation is presented. Finally, the results obtained by applying the algorithm to two test problems are compared with those derived by adopting the commonly used least-squares error function. The results show the effectiveness of the proposed approach in RBF network training for pattern recognition, mainly in terms of computational time saving

Continuous global optimization for protein structure analysis

Optimization methods are a powerful tool in protein structure analysis. In this paper we show that they can be profitably used to solve relevant problems in drug design such as the comparison and recognition of protein binding sites and the protein-peptide docking. Binding sites recognition is generally based on geometry often combined with physico-chemical properties of the site whereas the search for correct protein-peptide docking is often based on the minimization of an interaction energy model. We show that continuous global optimization methods can be used to solve the above problems and show some computational results

Threshold-Free Population Analysis Identifies Larger DRG Neurons to Respond Stronger to NGF Stimulation

Sensory neurons in dorsal root ganglia (DRG) are highly heterogeneous in terms of cell size, protein expression, and signaling activity. To analyze their heterogeneity, threshold-based methods are commonly used, which often yield highly variable results due to the subjectivity of the individual investigator. In this work, we introduce a threshold-free analysis approach for sparse and highly heterogeneous datasets obtained from cultures of sensory neurons. This approach is based on population estimates and completely free of investigator-set parameters. With a quantitative automated microscope we measured the signaling state of single DRG neurons by immunofluorescently labeling phosphorylated, i.e., activated Erk1/2. The population density of sensory neurons with and without pain-sensitizing nerve growth factor (NGF) treatment was estimated using a kernel density estimator (KDE). By subtraction of both densities and integration of the positive part, a robust estimate for the size of the responsive subpopulations was obtained. To assure sufficiently large datasets, we determined the number of cells required for reliable estimates using a bootstrapping approach. The proposed methods were employed to analyze response kinetics and response amplitude of DRG neurons after NGF stimulation. We thereby determined the portion of NGF responsive cells on a true population basis. The analysis of the dose dependent NGF response unraveled a biphasic behavior, while the study of its time dependence showed a rapid response, which approached a steady state after less than five minutes. Analyzing two parameter correlations, we found that not only the number of responsive small-sized neurons exceeds the number of responsive large-sized neurons—which is commonly reported and could be explained by the excess of small-sized cells—but also the probability that small-sized cells respond to NGF is higher. In contrast, medium-sized and large-sized neurons showed a larger response amplitude in their mean Erk1/2 activity

Oncologic Outcomes of Incidental Versus Biopsy-diagnosed Grade Group 1 Prostate Cancer:A Multi-institutional Study

Background and objective: Patients diagnosed with grade group (GG) 1 prostate cancer (PCa) following treatment for benign disease (“incidental” PCa) are typically managed with active surveillance (AS). It is not known how their outcomes compare with those observed in patients diagnosed with GG1 on biopsy. We aimed at determining whether long-term oncologic outcomes of AS for patients with GG1 PCa differ according to the type of diagnosis: incidental versus biopsy detected. Methods: A retrospective, multi-institutional analysis of PCa patients with GG1 on AS at eight institutions was conducted. Competing risk analyses estimated the incidence of metastases, PCa mortality, and conversion to treatment. As a secondary analysis, we estimated the risk of GG ≥2 on the first follow-up biopsy according to the type of initial diagnosis. Key findings and limitations: A total of 213 versus 1900 patients with incidental versus biopsy-diagnosed GG1 were identified. Patients with incidental cancers were followed with repeated biopsies and multiparametric magnetic resonance imaging less frequently than those diagnosed on biopsy. The 10-yr incidence of treatment was 22% for incidental cancers versus 53% for biopsy (subdistribution hazard ratio [sHR] 0.34, 95% confidence interval [CI] 0.26–0.46, p &lt; 0.001). Distant metastases developed in one patient with incidental cancer versus 17 diagnosed on biopsy and were diagnosed with molecular imaging in 13 (72%) patients. The 10-yr incidence of metastases was 0.8% for patients with incidental PCa and 2% for those diagnosed on biopsy (sHR 0.35, 95% CI 0.05–2.54, p = 0.3). The risk of GG ≥2 on the first follow-up biopsy was low if the initial diagnosis was incidental (7% vs 22%, p &lt; 0.001). Conclusions and clinical implications: Patients with GG1 incidental PCa should be evaluated further to exclude aggressive disease, preferably with a biopsy. If no cancer is found on biopsy, then they should receive the same follow-up of a patient with a negative biopsy. Further research should confirm whether imaging and biopsies can be avoided if postoperative prostate-specific antigen is low (&lt;1–2 ng/ml). Patient summary: We compared the outcomes of patients with low-grade prostate cancer on active surveillance according to the type of their initial diagnosis. Patients who have low-grade cancer diagnosed on a procedure to relieve urinary symptoms (incidental prostate cancer) are followed less intensively and undergo curative-intended treatment less frequently. We also found that patients with incidental prostate cancer are more likely to have no cancer on their first follow-up biopsy than patients who have low-grade cancer initially diagnosed on a biopsy. These patients have a more favorable prognosis than their biopsy-detected counterparts and should be managed the same way as patients with negative biopsies if they undergo a subsequent biopsy that shows no cancer.</p

Oncologic Outcomes of Incidental Versus Biopsy-diagnosed Grade Group 1 Prostate Cancer: A Multi-institutional Study

Background and objective: Patients diagnosed with grade group (GG) 1 prostate cancer (PCa) following treatment for benign disease (“incidental” PCa) are typically managed with active surveillance (AS). It is not known how their outcomes compare with those observed in patients diagnosed with GG1 on biopsy. We aimed at determining whether long-term oncologic outcomes of AS for patients with GG1 PCa differ according to the type of diagnosis: incidental versus biopsy detected. Methods: A retrospective, multi-institutional analysis of PCa patients with GG1 on AS at eight institutions was conducted. Competing risk analyses estimated the incidence of metastases, PCa mortality, and conversion to treatment. As a secondary analysis, we estimated the risk of GG ≥2 on the first follow-up biopsy according to the type of initial diagnosis. Key findings and limitations: A total of 213 versus 1900 patients with incidental versus biopsy-diagnosed GG1 were identified. Patients with incidental cancers were followed with repeated biopsies and multiparametric magnetic resonance imaging less frequently than those diagnosed on biopsy. The 10-yr incidence of treatment was 22% for incidental cancers versus 53% for biopsy (subdistribution hazard ratio [sHR] 0.34, 95% confidence interval [CI] 0.26–0.46, p < 0.001). Distant metastases developed in one patient with incidental cancer versus 17 diagnosed on biopsy and were diagnosed with molecular imaging in 13 (72%) patients. The 10-yr incidence of metastases was 0.8% for patients with incidental PCa and 2% for those diagnosed on biopsy (sHR 0.35, 95% CI 0.05–2.54, p = 0.3). The risk of GG ≥2 on the first follow-up biopsy was low if the initial diagnosis was incidental (7% vs 22%, p < 0.001). Conclusions and clinical implications: Patients with GG1 incidental PCa should be evaluated further to exclude aggressive disease, preferably with a biopsy. If no cancer is found on biopsy, then they should receive the same follow-up of a patient with a negative biopsy. Further research should confirm whether imaging and biopsies can be avoided if postoperative prostate-specific antigen is low (<1–2 ng/ml). Patient summary: We compared the outcomes of patients with low-grade prostate cancer on active surveillance according to the type of their initial diagnosis. Patients who have low-grade cancer diagnosed on a procedure to relieve urinary symptoms (incidental prostate cancer) are followed less intensively and undergo curative-intended treatment less frequently. We also found that patients with incidental prostate cancer are more likely to have no cancer on their first follow-up biopsy than patients who have low-grade cancer initially diagnosed on a biopsy. These patients have a more favorable prognosis than their biopsy-detected counterparts and should be managed the same way as patients with negative biopsies if they undergo a subsequent biopsy that shows no cancer