Project description:We quantify the effects of electrical stimulation on murine cells at the cellular and transcriptomic level using single cell RNA-sequencing. We characterize circulating cells and compare them to unstimulated circulating cells.
Project description:Rationale: Throughout the years, there has been a rapid change in the perioperative protocols and procedures surrounding colorectal surgery. Upon the introduction of the Enhanced Recovery After Surgery (ERAS) program in Western countries, an improvement in postoperative outcomes was seen. Nowadays, researchers focus on further improving the current standard ERAS programs enabling an accelerated version hereof.
Objective: The aim of this study is to investigate the feasibility and safety of a 23-hour accelerated ERAS protocol (ERAS 2.0) for patients undergoing colorectal surgery compared to a retrospective cohort of patients who followed ERAS 1.0 for colorectal surgery. In this ERAS 2.0 protocol, patients undergoing colorectal surgery will be discharged within 23 hours after surgery.
Study design: This study is an investigator-initiated, single-center prospective study.
Study population: Patients aged ≥ 18 years ≤ 80 undergoing surgical resection for colorectal pathology that meet the eligibility criteria will be invited to participate in this study.
Intervention: Adhering to a strict multidisciplinary and multifaceted ERAS 2.0 protocol, patients receiving elective colorectal surgery will be discharged 23-hours after surgery.
Main study parameters/endpoints: Rate of the successful and safe application of the 23-hour accelerated ERAS 2.0 protocol for patients undergoing elective colorectal surgery. Success rate will be measured in readmission rate and safety will be measured with rate of serious adverse events (Clavien Dindo ≥3b). Success rate (feasibility) will also be measured in percentage of patients who were not able to be discharged 23 hours after surgery.
Project description:The aim of the study is to identify a pattern of chemoresistive sensors able to recognise the presence of a tumoral pathology from a health state through the analysis of Volatile Organic Compounds inside the specimen.
The chemoresistive nanostructured sensors are into an innovative patented device SCENT B1 which can analyse different specimens: blood samples, tissue biopsies, cell cultures.
In this study SCENT B1 wil be used to compare the measures of:
* tumoral and health tissues taken from different neoplasms after their surgical resection
* blood samples from healthy and tumor affected people
* pre and post- operative blood samples of tumor affected people
Project description:Metabolic sensors are microbial strains modified such that biomass formation correlates with the availability of specific target metabolites. These sensors are essential for bioengineering (e.g. in growth-coupled selection of synthetic pathways), but their design is often time-consuming and low-throughput. In contrast, in silico analysis can accelerate their development. We present a systematic workflow for designing, implementing, and testing versatile metabolic sensors using Escherichia coli as a model. Glyoxylate, a key metabolite in synthetic CO2 fixation and carbon-conserving pathways, served as the test molecule. Through iterative screening of a compact metabolic reconstruction, we identified non-trivial growth-coupled designs that resulted in six metabolic sensors with different glyoxylate-to-biomass ratios. These metabolic sensors had a linear correlation between biomass formation and glyoxylate concentration spanning three orders of magnitude and were further adapted for glycolate sensing. We demonstrate the utility of these sensors in pathway engineering (implementing a synthetic route for one-carbon assimilation via glyoxylate) and environmental applications (quantifying glycolate produced by photosynthetic microalgae). The versatility and ease of implementation of this workflow make it suitable for designing and building multiple metabolic sensors for diverse biotechnological applications.
Project description:Improved Smart-Seq for sensitive full-length transcriptome profiling in single cells. Cells of four different origins were profiled using commercial SMARTer and compared to five variants of an improved protocol (Smart-Seq2).
Project description:We describe Smart-seq-total, a method capable of assaying a broad spectrum of coding and non-coding RNA from a single cell. Built upon the template-switch mechanism, Smart-seq-total bears the key feature of its predecessor, Smart-seq2, namely, the ability to capture full-length transcripts with high yield and quality. It outperforms current poly(A)–independent total RNA-seq protocols by capturing transcripts of a broad size range, thus, allowing us to simultaneously analyze protein-coding, long non-coding, microRNA and other non-coding RNA from single cells. We used Smart-seq-total to analyze the total RNAome of human primary fibroblasts, HEK293T and MCF7 cells as well as that of induced murine embryonic stem cells differentiated into embryoid bodies. We show that simultaneous measurement of non-coding RNA and mRNA from the same cell enables elucidation of new roles of non-coding RNA throughout essential processes such as cell cycle or lineage commitment. Moreover, we show that cell types can be distinguished based on the abundance of non-coding transcripts only.