Constitution of Dalbergin. Part V. A further study of 4-phenyl coumarins

This article does not have an abstract

Refined conditions for V-shaped optimal sequencing on a single machine to minimize total completion time under combined effects

We address single machine scheduling problems for which the actual processing times of jobs are subject to various effects, including a positional effect, a cumulative effect and their combination. We review the known results on the problems to minimize the makespan, the sum of the completion times and their combinations and identify the problems for which an optimal sequence cannot be found by simple priority rules such as SPT (Shortest Processing Time) and/or LPT (Longest Processing Time). Typically, these are problems to minimize the sum of the completion times under a deterioration effect, and we verify under which conditions for these problems an optimal permutation is V-shaped (an LPT subsequence followed by an SPT subsequence). We demonstrate that previously used techniques for proving that an optimal sequence is V- shaped are not properly justified. We use the corrected method to describe a wide range of problems with a pure positional effect and a combination of a cumulative effect with a positional effect for which an optimal sequence is V-shaped. On other hand, we show that even the refined approach has its limitations

Converging evidence points towards a role of insulin signaling in regulating compulsive behavior.

Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder with childhood onset, and is characterized by intrusive thoughts and fears (obsessions) that lead to repetitive behaviors (compulsions). Previously, we identified insulin signaling being associated with OCD and here, we aim to further investigate this link in vivo. We studied TALLYHO/JngJ (TH) mice, a model of type 2 diabetes mellitus, to (1) assess compulsive and anxious behaviors, (2) determine neuro-metabolite levels by 1 H magnetic resonance spectroscopy (MRS) and brain structural connectivity by diffusion tensor imaging (DTI), and (3) investigate plasma and brain protein levels for molecules previously associated with OCD (insulin, Igf1, Kcnq1, and Bdnf) in these subjects. TH mice showed increased compulsivity-like behavior (reduced spontaneous alternation in the Y-maze) and more anxiety (less time spent in the open arms of the elevated plus maze). In parallel, their brains differed in the white matter microstructure measures fractional anisotropy (FA) and mean diffusivity (MD) in the midline corpus callosum (increased FA and decreased MD), in myelinated fibers of the dorsomedial striatum (decreased FA and MD), and superior cerebellar peduncles (decreased FA and MD). MRS revealed increased glucose levels in the dorsomedial striatum and increased glutathione levels in the anterior cingulate cortex in the TH mice relative to their controls. Igf1 expression was reduced in the cerebellum of TH mice but increased in the plasma. In conclusion, our data indicates a role of (abnormal) insulin signaling in compulsivity-like behavior

Diagnostic model development for schizophrenia based on peripheral blood mononuclear cell subtype-specific expression of metabolic markers

A significant proportion of the personal and economic burden of schizophrenia can be attributed to the late diagnosis or misdiagnosis of the disorder. A novel, objective diagnostic approaches could facilitate the early detection and treatment of schizophrenia and improve patient outcomes. In the present study, we aimed to identify robust schizophrenia-specific blood biomarkers, with the goal of developing an accurate diagnostic model. The levels of selected serum and peripheral blood mononuclear cell (PBMC) markers relevant to metabolic and immune function were measured in healthy controls (n?=?26) and recent-onset schizophrenia patients (n?=?36) using multiplexed immunoassays and flow cytometry. Analysis of covariance revealed significant upregulation of insulin receptor (IR) and fatty acid translocase (CD36) levels in T helper cells (F?=?10.75, P?=?0.002, Q?=?0.024 and F?=?21.58, P?=?2.8?×?10?5, Q?=?0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F?=?21.46, P?=?2.9?×?10?5, Q?=?0.0004). The most robust predictors, monocyte GLUT1 and T helper cell CD36, were used to develop a diagnostic model, which showed a leave-one-out cross-validated area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI: 0.66?0.92). The diagnostic model was validated in two independent datasets. The model was able to distinguish first-onset, drug-naïve schizophrenia patients (n?=?34) from healthy controls (n?=?39) with an AUC of 0.75 (95% CI: 0.64?0.86), and also differentiated schizophrenia patients (n?=?22) from patients with other neuropsychiatric conditions, including bipolar disorder, major depressive disorder and autism spectrum disorder (n?=?68), with an AUC of 0.83 (95% CI: 0.75?0.92). These findings indicate that PBMC-derived biomarkers have the potential to support an accurate and objective differential diagnosis of schizophrenia.ACKNOWLEDGEMENTS: We are grateful to the participants and their families for their cooperation in this study. We would like to thank blood donors and the clinical centres, for the provision of biological samples, in addition, to supporting staff at the affiliated institutions. We also thank IDIVAL biobank (Inés Santiuste and Jana Arozamena) and UMCU Biobank for clinical sample and data preparation, as well as the PAFIP members for the data collection. This work was supported by the Stanley Medical Research Institute (grant number: 12T-008) and the Dutch Research Council (NWO; grant number: 40–00812–98–12154) received by IES; by grants to SB from the Stanley Medical Research Institute (SMRI) and the Engineering and Physical Sciences Research Council UK (EPSRC); and by grants to BC-F: SAF2016–76046-R and SAF2013–46292-R (MINECO) and PI16/00156 (ISCIII and FEDER)

Exploring peripheral biomarkers of response to simvastatin supplementation in schizophrenia

Schizophrenia is one of the most debilitating mental disorders, and its diagnosis and treatment present significant challenges. Several clinical trials have previously evaluated the effectiveness of simvastatin, a lipid-lowering medication, as a novel add-on treatment for schizophrenia. However, treatment effects varied highly between patients and over time. In the present study, we aimed to identify biomarkers of response to simvastatin in recent-onset schizophrenia patients. To this end, we profiled relevant immune and metabolic markers in patient blood samples collected in a previous clinical trial (ClinicalTrials.gov: NCT01999309) before simvastatin add-on treatment was initiated. Analysed sample types included serum, plasma, resting-state peripheral blood mononuclear cells (PBMCs), as well as PBMC samples treated ex vivo with immune stimulants and simvastatin. Associations between the blood readouts and clinical endpoints were evaluated using multivariable linear regression. This revealed that changes in insulin receptor (IR) levels induced in B-cells by ex vivo simvastatin treatment inversely correlated with in vivo effects on cognition at the primary endpoint of 12 months, as measured using the Brief Assessment of Cognition in Schizophrenia scale total score (standardised β ± SE = -0.75 ± 0.16, P = 2.2 × 10 -4, Q = 0.029; n = 21 patients). This correlation was not observed in the placebo group (β ± SE = 0.62 ± 0.39, P = 0.17, Q = 0.49; n = 14 patients). The candidate biomarker explained 53.4 % of the variation in cognitive outcomes after simvastatin supplementation. Despite the small sample size, these findings suggest a possible interaction between the insulin signalling pathway and cognitive effects during simvastatin therapy. They also point to opportunities for personalized schizophrenia treatment through patient stratification

Identification of Stage-Specific Breast Markers using Quantitative Proteomics

YesMatched healthy and diseased tissues from breast cancer patients were analyzed by quantitative proteomics. By comparing proteomic profiles of fibroadenoma (benign tumors, three patients), DCIS (noninvasive cancer, three patients), and invasive ductal carcinoma (four patients), we identified protein alterations that correlated with breast cancer progression. Three 8-plex iTRAQ experiments generated an average of 826 protein identifications, of which 402 were common. After excluding those originating from blood, 59 proteins were significantly changed in tumor compared with normal tissues, with the majority associated with invasive carcinomas. Bioinformatics analysis identified relationships between proteins in this subset including roles in redox regulation, lipid transport, protein folding, and proteasomal degradation, with a substantial number increased in expression due to Myc oncogene activation. Three target proteins, cofilin-1 and p23 (increased in invasive carcinoma) and membrane copper amine oxidase 3 (decreased in invasive carcinoma), were subjected to further validation. All three were observed in phenotype-specific breast cancer cell lines, normal (nontransformed) breast cell lines, and primary breast epithelial cells by Western blotting, but only cofilin-1 and p23 were detected by multiple reaction monitoring mass spectrometry analysis. All three proteins were detected by both analytical approaches in matched tissue biopsies emulating the response observed with proteomics analysis. Tissue microarray analysis (361 patients) indicated cofilin-1 staining positively correlating with tumor grade and p23 staining with ER positive status; both therefore merit further investigation as potential biomarkers.Cyprus Research Promotion Foundation, Yorkshire Cancer Researc

The Bases of Effective Coordination in Decentralized Multiagent Systems

Coordination is a recurring theme in multiagent systems design. We consider the problem of achieving coordination in a system where the agents make autonomous decisions based solely on local knowledge. An open theoretical issue is what goes into achieving effective coordination? There is some folklore about the importance of the knowledge held by the different agents, but the rest of the rich agent landscape has not been explored in depth. The present paper seeks to delineate the different components of an abstract architecture for agents that influence the effectiveness of coordination. Specifically, it proposes that the extent of the choices available to the agents as well as the extent of the knowledge shared by them are both important for understanding coordination in general. These lead to a richer view of coordination that supports a more intuitive set of claims. This paper supports its conceptual conclusions with experimental results based on simulation. 1 Introduction The coor..

Handling Semantic Exceptions in the Large: A Multiagent Approach

We consider semantic exceptions, which arise when a task yields results that are incorrect, inconsistent with related tasks, or incomplete. Semantic exceptions are especially prominent in the large, i.e., when we construct and execute a workflow. A workflow is a composite computation with several interoperating components and interacting processes. Detecting and resolving semantic exceptions is critical to the functioning of a workflow, especially when its member activities are autonomous, heterogeneous, long-lived, and interact in subtle ways. Unfortunately, present workflow techniques offer little support for exceptions. For modeling, they provide few abstractions beyond activity charts. For enactment, they are not flexible enough to allow a component to detect and resolve semantic exceptions properly. We describe a multiagent approach for handling semantic exceptions. Our approach is based on high-level abstractions such as commitments, a process metamodel that accommodates commitm..