Machine learning for automatic prediction of the quality of electrophysiological recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert electrophysiologists. Generalisation performance is then assessed on unseen data, classified by the same or by another expert. We observe that the learning machine can be equally, if not more, consistent in its judgements as individual experts amongst each other. Best performance is achieved for a limited number of informative features; the optimal feature set being different from one data set to another. With 80–90% of correct judgements, the performance of the system is very promising within the data sets of each expert but judgments are less reliable when it is used across sets of recordings from different experts. We conclude that the proposed approach is relevant to the selection of electrophysiological recordings, provided parameters are adjusted to different types of experiments and to individual experimenters

UBE2L6/UBCH8 and ISG15 attenuate autophagy in esophageal cancer cells

Esophageal cancer remains a poor prognosis cancer due to advanced stage of presentation and drug resistant disease. To understand the molecular mechanisms influencing response to chemotherapy, we examined genes that are differentially expressed between drug sensitive, apoptosis competent esophageal cancer cells (OE21, OE33, FLO-1) and those which are more resistant and do not exhibit apoptosis (KYSE450 and OE19). Members of the ISG15 (ubiquitin-like) protein modification pathway, including UBE2L6 and ISG15, were found to be more highly expressed in the drug sensitive cell lines. In this study, we evaluated the contribution of these proteins to the response of drug sensitive cells. Depletion of UBE2L6 or ISG15 with siRNA did not influence caspase-3 activation or nuclear fragmentation following treatment with 5-fluorouracil (5-FU). We assessed autophagy by analysis of LC3II expression and Cyto-ID staining. Depletion of either ISG15 or UBE2L6 resulted in enhanced endogenous autophagic flux. An increase in autophagic flux was also observed following treatment with cytotoxic drugs (5-FU, rapamycin). In ISG15 depleted cells, this increase in autophagy was associated with improved recovery of drug treated cells. In contrast, UBE2L6 depleted cells, did not show enhanced recovery. UBE2L6 may therefore influence additional targets that limit the pro-survival effect of ISG15 depletion. These data identify UBE2L6 and ISG15 as novel inhibitors of autophagy, with the potential to influence chemosensitivity in esophageal cancer cells

New investigations into the stability of Mesna using LC-MS/MS and NMR

Both LC-MS/MS and NMR analyses confirmed the instability of Mesna and its conversion into Dimesna

LC3B globular structures correlate with survival in esophageal adenocarcinoma

Background: Esophageal adenocarcinoma has the fastest growing incidence of any solid tumor in the Western world. Prognosis remains poor with overall five-year survival rates under 25 %. Only a limited number of patients benefit from chemotherapy and there are no biomarkers that can predict outcome. Previous studies have indicated that induction of autophagy can influence various aspects of tumor cell biology, including chemosensitivity. The objective of this study was to assess whether expression of the autophagy marker (LC3B) correlated with patient outcome. Methods: Esophageal adenocarcinoma tumor tissue from two independent sites, was examined retrospectively. Tumors from 104 neoadjuvant naïve patients and 48 patients post neoadjuvant therapy were assembled into tissue microarrays prior to immunohistochemical analysis. Kaplan-Meier survival curves and log-rank tests were used to assess impact of LC3B expression on survival. Cox regression was used to examine association with clinical risk factors. Results: A distinct globular pattern of LC3B expression was found to be predictive of outcome in both patient groups, irrespective of treatment (p < 0.001). Multivariate analysis found that this was a strong independent predictor of poor prognosis (p < 0.001). Conclusions: This distinctive staining pattern of LC3B represents a novel prognostic marker for resectable esophageal adenocarcinoma

Macdonald Polynomials and level two Demazure modules for affine sln+1\mathfrak{sl}_{n+1}

We define a family of symmetric polynomials $G_{\nu,\lambda}(z_1,\cdots, z_{n+1},q)$ indexed by a pair of dominant integral weights. The polynomial $G_{\nu,0}(z,q)$ is the specialized Macdonald polynomial and we prove that $G_{0,\lambda}(z,q)$ is the graded character of a level two Demazure module associated to the affine Lie algebra $\widehat{\mathfrak{sl}}_{n+1}$. Under suitable conditions on $(\nu,\lambda)$ (which includes the case when $\nu=0$ or $\lambda=0$) we prove that $G_{\nu,\lambda}(z,q)$ is Schur positive and give explicit formulae for them in terms of Macdonald polynomials

Quantitative and Qualitative Assessment of Interrogation Expectations

Interrogation expectations (IE) is a construct that suggests expectations of custodial interrogations affect suspects’ Miranda waiver decisions while under interrogation. Prior research has examined IE quantitatively but there has been no prior research examining IE qualitatively. This current research conducted both a quantitative and qualitative analysis of IE using a sample of 335 participants from the United States. This research took the form of an online survey using Prolific (www.prolific.co) to recruit participants, Qualtrics (www.qualtrics.com) to record data, and SPSS and Nvivo to analyze quantitative qualitative data. It was hypothesized that substantial individual variation in IE will be found in the sample, and variations are associated with demographic variables (specifically race/ethnicity, age and arrest history). Qualitative data were assessed in order to shed further light on the relationship of IE to the Miranda waiver decision and other relevant findings. Substantial individual variability in IE was found among the sample and, only age and years lived in the U.S were found to be significant predictors of IE

A rare case of acute lymphoblastic leukemia in a patient with light chain (AL) amyloidosis treated with lenalidomide.

Lenalidomide belongs to a novel class of drugs called Immunomodulators which are now being used for the treatment of plasma cell dyscrasias with variable degrees of efficacy and toxicity. Though Second Primary Malignancies (SPM) have been a concern with its use, the benefits of the treatment outweigh the risks. The leukemogenic risk seems to be potentiated especially when combined with alkylating agents and the SPMs documented are predominantly myeloblastic. To date there are no reported cases of new lymphocytic leukemias in AL amyloidosis, regardless of whether undergone treatment or not. We present a case of AL amylodosis who was treated with lenalidomide and subsequently developed acute lymphoblastic leukemia