Elevated serum matrix metalloproteinase 9 (MMP-9) concentration predicts the presence of colorectal neoplasia in symptomatic patients

Early detection of polyps or colorectal carcinoma can reduce colorectal carcinoma-associated deaths. Previous studies have demonstrated raised serum levels of matrix metalloproteinase 9 (sMMP-9) in a range of cancers. The aim of this study was to investigate the role of sMMP-9 levels in identifying colorectal neoplasia. Consenting patients donated a blood sample and were assessed by proforma-led history and physical examination. Samples were analysed for sMMP-9 concentration (enzyme-linked immuno-sorbant assay) and compared to final diagnoses. Logistic regression modelling determined independent factors associated with neoplasia. A total of 365 patients were recruited of whom 300 were analysed, including 46 normal controls. A total of 27 significant adenomas and 63 malignancies were identified. The median sMMP-9 concentration was 443ng ml−1 (IQR: 219–782; mean: 546). Patients with neoplasia had significantly elevated sMMP-9 levels (P<0.001). Logistic regression modelling identified elevated log(sMMP-9) as the most significant predictor of neoplasia (χ2=38.33, P<0.001). Other significant factors were age, sex, smoking history, abdominal pain and weight loss. The model accurately predicted neoplasia in 77.3% of cases. Sensitivity and specificity were 77.9 and 77.1%. sMMP-9 estimation can accurately stratify patient to low- or high-risk cohorts. Serum sampling is a potential means of avoiding unnecessary colonoscopy and reducing patient anxiety, iatrogenic morbidity and mortality, and cost

Burst-Time-Dependent Plasticity Robustly Guides ON/OFF Segregation in the Lateral Geniculate Nucleus

Spontaneous retinal activity (known as “waves”) remodels synaptic connectivity to the lateral geniculate nucleus (LGN) during development. Analysis of retinal waves recorded with multielectrode arrays in mouse suggested that a cue for the segregation of functionally distinct (ON and OFF) retinal ganglion cells (RGCs) in the LGN may be a desynchronization in their firing, where ON cells precede OFF cells by one second. Using the recorded retinal waves as input, with two different modeling approaches we explore timing-based plasticity rules for the evolution of synaptic weights to identify key features underlying ON/OFF segregation. First, we analytically derive a linear model for the evolution of ON and OFF weights, to understand how synaptic plasticity rules extract input firing properties to guide segregation. Second, we simulate postsynaptic activity with a nonlinear integrate-and-fire model to compare findings with the linear model. We find that spike-time-dependent plasticity, which modifies synaptic weights based on millisecond-long timing and order of pre- and postsynaptic spikes, fails to segregate ON and OFF retinal inputs in the absence of normalization. Implementing homeostatic mechanisms results in segregation, but only with carefully-tuned parameters. Furthermore, extending spike integration timescales to match the second-long input correlation timescales always leads to ON segregation because ON cells fire before OFF cells. We show that burst-time-dependent plasticity can robustly guide ON/OFF segregation in the LGN without normalization, by integrating pre- and postsynaptic bursts irrespective of their firing order and over second-long timescales. We predict that an LGN neuron will become ON- or OFF-responsive based on a local competition of the firing patterns of neighboring RGCs connecting to it. Finally, we demonstrate consistency with ON/OFF segregation in ferret, despite differences in the firing properties of retinal waves. Our model suggests that diverse input statistics of retinal waves can be robustly interpreted by a burst-based rule, which underlies retinogeniculate plasticity across different species