An Exploratory Study of Field Failures

Field failures, that is, failures caused by faults that escape the testing phase leading to failures in the field, are unavoidable. Improving verification and validation activities before deployment can identify and timely remove many but not all faults, and users may still experience a number of annoying problems while using their software systems. This paper investigates the nature of field failures, to understand to what extent further improving in-house verification and validation activities can reduce the number of failures in the field, and frames the need of new approaches that operate in the field. We report the results of the analysis of the bug reports of five applications belonging to three different ecosystems, propose a taxonomy of field failures, and discuss the reasons why failures belonging to the identified classes cannot be detected at design time but shall be addressed at runtime. We observe that many faults (70%) are intrinsically hard to detect at design-time

Genome-wide association analysis of genetic generalized epilepsies implicates susceptibility loci at 1q43, 2p16.1, 2q22.3 and 17q21.32

Genetic generalized epilepsies (GGEs) have a lifetime prevalence of 0.3% and account for 20-30% of all epilepsies. Despite their high heritability of 80%, the genetic factors predisposing to GGEs remain elusive. To identify susceptibility variants shared across common GGE syndromes, we carried out a two-stage genome-wide association study (GWAS) including 3020 patients with GGEs and 3954 controls of European ancestry. To dissect out syndrome-related variants, we also explored two distinct GGE subgroups comprising 1434 patients with genetic absence epilepsies (GAEs) and 1134 patients with juvenile myoclonic epilepsy (JME). Joint Stage-1 and 2 analyses revealed genome-wide significant associations for GGEs at 2p16.1 (rs13026414, Pmeta = 2.5 × 10−9, OR[T] = 0.81) and 17q21.32 (rs72823592, Pmeta = 9.3 × 10−9, OR[A] = 0.77). The search for syndrome-related susceptibility alleles identified significant associations for GAEs at 2q22.3 (rs10496964, Pmeta = 9.1 × 10−9, OR[T] = 0.68) and at 1q43 for JME (rs12059546, Pmeta = 4.1 × 10−8, OR[G] = 1.42). Suggestive evidence for an association with GGEs was found in the region 2q24.3 (rs11890028, Pmeta = 4.0 × 10−6) nearby the SCN1A gene, which is currently the gene with the largest number of known epilepsy-related mutations. The associated regions harbor high-ranking candidate genes: CHRM3 at 1q43, VRK2 at 2p16.1, ZEB2 at 2q22.3, SCN1A at 2q24.3 and PNPO at 17q21.32. Further replication efforts are necessary to elucidate whether these positional candidate genes contribute to the heritability of the common GGE syndrome

Hyperresponsivity in migraine: a network dysfunction or an analytic cognitive style-connected feature?

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Do seizures and epileptic activity worsen epilepsy and deteriorate cognitive function?

International audienceRelevant to the definition of epileptic encephalopathy (EE) is the concept that the epileptic activity itself may contribute to bad outcomes, both in terms of epilepsy and cognition, above and beyond what might be expected from the underlying pathology alone, and that these can worsen over time. The review of the clinical and experimental evidence that seizures or interictal electroencephalography (EEG) discharges themselves can induce a progression toward more severe epilepsy and a regression of brain function leads to the following conclusions: The possibility of seizure-dependent worsening is by no means a general one but is limited to some types of epilepsy, namely mesial temporal lobe epilepsy (MTLE) and EEs. Clinical and experimental data concur in indicating that prolonged seizures/status epilepticus (SE) are a risky initial event that can set in motion an epileptogenic process leading to persistent, possibly drug-refractory epilepsies. The mechanisms for SE-related epileptogenic process are incompletely known; they seem to involve inflammation and/or glutamatergic transmission. The evidence of the role of recurrent individual seizures in sustaining epilepsy progression is ambiguous. The correlation between high seizure frequency and bad outcome does not necessarily demonstrate a cause-effect relationship, rather high seizure frequency and bad outcome can both depend on a particularly aggressive epileptogenic process. The results of EE studies challenge the idea of a common seizure-dependent mechanism for epilepsy progression/intellectual deterioration

Effect of different concentrations of PHT on I_NaP evoked using inactivating prepulses of different durations.

<p>Panels A and B show the dose response curves with prepulses of 200 ms (A) or 500 ms (B); higher concentrations of PHT have not been used because of its solubility limits, and the maximal block was not reached. The solid lines are fit to rectangular hyperbolas that gave apparent IC₅₀ values of 28 and 18 µM and apparent maximal block of 24 and 26% respectively. All of the PHT concentrations used induced a statistically significant reduction of I_NaP peak amplitude with both 200 and 500 ms inactivating prepulses, as shown in C (**p<0.01; *** = p<0.001; ANOVA test).</p

Effect of PHT on the voltage-dependence of I_NaP inactivation.

<p>A, effect of 100 µM PHT on the activation curve; the inset shows the stimulus protocol (prepulses were 10 s in duration; ramps had a slope of 50 mV s⁻¹). Panels B, C and D show the current peaks evoked after different prepulses in a representative neuron. In the presence of PHT, the currents evoked after inactivating prepulses at −40 and −20 mV are clearly reduced with respect to those evoked under control conditions, and partially recover during PHT washout.</p

Effect of PHT on the development of I_NaP inactivation.

<p>Effect of 100 µM PHT on I_NaP evoked without (leftmost traces) and with inactivating prepulses to −20 mV lasting from 100 ms to 10 seconds in a representative layer V neuron. The arrows indicate the peak current evoked using depolarizing ramp stimuli under control conditions (left) and in the presence of 100 µM PHT (right). Development of I_NaP inactivation in layers II/III (B) and V (C) at −20 mV and in layer V at +40 mV (D) on a semi-logarithmic scale, under control conditions (open triangles) and in the presence of 100 PHT µM (black triangles); the data points were fit to bi-exponential functions with a baseline (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055329#pone-0055329-t001" target="_blank">Table 1</a>).</p

Effect of PHT on recovery from I_NaP inactivation.

<p>A, representative traces in control (above) and with 100 μM PHT (below) recorded after a 20 s-long inactivating prepulse to −10 mV and a recovery period at −80 mV of 1 ms, 1000 ms, 4000 ms, 10000 ms and 40000 ms (see stimulus in B). B, plot showing average recovery in control (black triangles) and with 100 μM PHT (hollow triangles). The lines are single exponentials obtained averaging the parameters of the fits of the single cells (see text for details).</p