Neuro-Silicon Interface of a Hirudo Medicinalis Retzius Cell Integrated With Field Effect Transistor

The focus of this thesis was to measure the intracellular voltage of a living neural cell using a silicon transistor. The coupling of neurological tissues with silicon devices is of interest to the fields of neurology, neuroscience, electrophysiology and cellular biology. In previous work by Peter Fromherz, single neurons were successfully coupled to transistors [1]. This thesis aims to show proof of concept of the fabrication of a simple neuro-silicon interface using wafer processing methods currently available at Cal Poly. The types of transistors and cells used, the methods for dissecting and preparing the cells, the electrophysiology methods for validating the experiments, and portions of the design of the junction were based on Fromherz’s 1991 work. Other aspects were revised to be compatible with technologies available at Cal Poly. Leech Retzius cells were isolated and cultured from Hirudo Medicinalis and joined to the gate oxide of a P-channel field effect transistor using SU-8 photoresist wells treated with poly-l-lysine. Transistors were operated in strong inversion and source-drain currentfluctuations were observed that correlated with action potentials of the current clamped Retzius cell. Further work is needed to develop better junctions that can reliably couple action potentials. This work lays a foundation for neuro-silicon interface fabrication at Cal Poly

External validation of a predictive model of survival after cytoreductive nephrectomy for metastatic renal cell carcinoma.

INTRODUCTION: Recent trials have emphasized the importance of a precise patient selection for cytoreductive nephrectomy (CN). In 2013, a nomogram was developed for pre- and postoperative prediction of the probability of death (PoD) after CN in patients with metastatic renal cell carcinoma. To date, the single-institutional nomogram which included mostly patients from the cytokine era has not been externally validated. Our objective is to validate the predictive model in contemporary patients in the targeted therapy era. METHODS: Multi-institutional European and North American data from patients who underwent CN between 2006 and 2013 were used for external validation. Variables evaluated included preoperative serum albumin and lactate dehydrogenase levels, intraoperative blood transfusions (yes/no) and postoperative pathologic stage (primary tumour and nodes). In addition, patient characteristics and MSKCC risk factors were collected. Using the original calibration indices and quantiles of the distribution of predictions, Kaplan-Meier estimates and calibration plots of observed versus predicted PoD were calculated. For the preoperative model a decision curve analysis (DCA) was performed. RESULTS: Of 1108 patients [median OS of 27 months (95% CI 24.6-29.4)], 536 and 469 patients had full data for the validation of the pre- and postoperative models, respectively. The AUC for the pre- and postoperative model was 0.68 (95% CI 0.62-0.74) and 0.73 (95% CI 0.68-0.78), respectively. In the DCA the preoperative model performs well within threshold survival probabilities of 20-50%. Most important limitation was the retrospective collection of this external validation dataset. CONCLUSIONS: In this external validation, the pre- and postoperative nomograms predicting PoD following CN were well calibrated. Although performance of the preoperative nomogram was lower than in the internal validation, it retains the ability to predict early death after CN

Serotonin, genetic variability, behaviour, and psychiatric disorders - a review

Brain monoamines, and serotonin in particular, have repeatedly been shown to be linked to different psychiatric conditions such as depression, anxiety, antisocial behaviour, and dependence. Many studies have implicated genetic variability in the genes encoding monoamine oxidase A (MAOA) and the serotonin transporter (5HTT) in modulating susceptibility to these conditions. Paradoxically, the risk variants of these genes have been shown, in vitro, to increase levels of serotonin, although many of the conditions are associated with decreased levels of serotonin. Furthermore, in adult humans, and monkeys with orthologous genetic polymorphisms, there is no observable correlation between these functional genetic variants and the amount or activity of the corresponding proteins in the brain. These seemingly contradictory data might be explained if the association between serotonin and these behavioural and psychiatric conditions were mainly a consequence of events taking place during foetal and neonatal brain development. In this review we explore, based on recent research, the hypothesis that the dual role of serotonin as a neurotransmitter and a neurotrophic factor has a significant impact on behaviour and risk for neuropsychiatric disorders through altered development of limbic neurocircuitry involved in emotional processing, and development of the serotonergic neurons, during early brain development

Genes Involved in Systemic and Arterial Bed Dependent Atherosclerosis - Tampere Vascular Study

BACKGROUND: Atherosclerosis is a complex disease with hundreds of genes influencing its progression. In addition, the phenotype of the disease varies significantly depending on the arterial bed. METHODOLOGY/PRINCIPAL FINDINGS: We characterized the genes generally involved in human advanced atherosclerotic (AHA type V-VI) plaques in carotid and femoral arteries as well as aortas from 24 subjects of Tampere Vascular study and compared the results to non-atherosclerotic internal thoracic arteries (n=6) using genome-wide expression array and QRT-PCR. In addition we determined genes that were typical for each arterial plaque studied. To gain a comprehensive insight into the pathologic processes in the plaques we also analyzed pathways and gene sets dysregulated in this disease using gene set enrichment analysis (GSEA). According to the selection criteria used (>3.0 fold change and p-value <0.05), 235 genes were up-regulated and 68 genes down-regulated in the carotid plaques, 242 genes up-regulated and 116 down-regulated in the femoral plaques and 256 genes up-regulated and 49 genes down-regulated in the aortic plaques. Nine genes were found to be specifically induced predominantly in aortic plaques, e.g., lactoferrin, and three genes in femoral plaques, e.g., chondroadherin, whereas no gene was found to be specific for carotid plaques. In pathway analysis, a total of 28 pathways or gene sets were found to be significantly dysregulated in atherosclerotic plaques (false discovery rate [FDR] <0.25). CONCLUSIONS: This study describes comprehensively the gene expression changes that generally prevail in human atherosclerotic plaques. In addition, site specific genes induced only in femoral or aortic plaques were found, reflecting that atherosclerotic process has unique features in different vascular beds

Machine learning for optimized buildings morphosis

International audienceThe world is rapidly urbanizing, with an increasing number of new building constructions. This involves increasing the world's energy consumption and its associated greenhouse gas emissions. Computational tools are playing an increasing impact on the architectural design process. Recently, Machine learning (ML) has been applied to building design and has evinced its potential to improve building performance. This paper tries to review the use of ML for the building morphosis. We then forecast the use of machine learning for building optimized morphosis in the early design stage particularly for ensuring summer shading and winter solar access between neighbors

External validation of a predictive model of survival after cytoreductive nephrectomy for metastatic renal cell carcinoma.

INTRODUCTION: Recent trials have emphasized the importance of a precise patient selection for cytoreductive nephrectomy (CN). In 2013, a nomogram was developed for pre- and postoperative prediction of the probability of death (PoD) after CN in patients with metastatic renal cell carcinoma. To date, the single-institutional nomogram which included mostly patients from the cytokine era has not been externally validated. Our objective is to validate the predictive model in contemporary patients in the targeted therapy era. METHODS: Multi-institutional European and North American data from patients who underwent CN between 2006 and 2013 were used for external validation. Variables evaluated included preoperative serum albumin and lactate dehydrogenase levels, intraoperative blood transfusions (yes/no) and postoperative pathologic stage (primary tumour and nodes). In addition, patient characteristics and MSKCC risk factors were collected. Using the original calibration indices and quantiles of the distribution of predictions, Kaplan-Meier estimates and calibration plots of observed versus predicted PoD were calculated. For the preoperative model a decision curve analysis (DCA) was performed. RESULTS: Of 1108 patients [median OS of 27 months (95% CI 24.6-29.4)], 536 and 469 patients had full data for the validation of the pre- and postoperative models, respectively. The AUC for the pre- and postoperative model was 0.68 (95% CI 0.62-0.74) and 0.73 (95% CI 0.68-0.78), respectively. In the DCA the preoperative model performs well within threshold survival probabilities of 20-50%. Most important limitation was the retrospective collection of this external validation dataset. CONCLUSIONS: In this external validation, the pre- and postoperative nomograms predicting PoD following CN were well calibrated. Although performance of the preoperative nomogram was lower than in the internal validation, it retains the ability to predict early death after CN