Validation Of Novel Technique Research Articles

Studying Cardiac Neural Network Dynamics: Challenges and Opportunities for Scientific Computing.

Neural control of the heart involves continuous modulation of cardiac mechanical and electrical activity to meet the organism’s demand for blood flow. The closed-loop control scheme consists of interconnected neural networks with central and peripheral components working cooperatively with each other. These components have evolved to cooperate control of various aspects of cardiac function, which produce measurable “functional” outputs such as heart rate and blood pressure. In this review, we will outline fundamental studies probing the cardiac neural control hierarchy. We will discuss how computational methods can guide improved experimental design and be used to probe how information is processed while closed-loop control is operational. These experimental designs generate large cardio-neural datasets that require sophisticated strategies for signal processing and time series analysis, while presenting the usual large-scale computational challenges surrounding data sharing and reproducibility. These challenges provide unique opportunities for the development and validation of novel techniques to enhance understanding of mechanisms of cardiac pathologies required for clinical implementation.

Artificial intelligence for the management of pancreatic diseases.

Novel artificial intelligence techniques are emerging in all fields of healthcare, including gastroenterology. The aim of this review is to give an overview of artificial intelligence applications in the management of pancreatic diseases. We performed a systematic literature search in PubMed and Medline up to May 2020 to identify relevant articles. Our results showed that the development of machine‐learning based applications is rapidly evolving in the management of pancreatic diseases, guiding precision medicine in clinical, endoscopic and radiologic settings. Before implementation into clinical practice, further research should focus on the external validation of novel techniques, clarifying the accuracy and robustness of these models.

Validation of novel technique in 3d printed hepatic model in hepatobiliary surgery: A pilot study 'liv3dprint'

Validation of novel technique in 3d printed hepatic model in hepatobiliary surgery: A pilot study 'liv3dprint'

Optimizing microbiome sequencing for small intestinal aspirates: validation of novel techniques through the REIMAGINE study

BackgroundThe human small intestine plays a central role in the processes of digestion and nutrient absorption. However, characterizations of the human gut microbiome have largely relied on stool samples, and the associated methodologies are ill-suited for the viscosity and low microbial biomass of small intestine samples. As part of the REIMAGINE study to examine the specific roles of the small bowel microbiome in human health and disease, this study aimed to develop and validate methodologies to optimize microbial analysis of the small intestine.ResultsSubjects undergoing esophagogastroduodenoscopy without colon preparation for standard of care were prospectively recruited, and ~ 2 ml samples of luminal fluid were obtained from the duodenum using a custom sterile aspiration catheter. Samples of duodenal aspirates were either untreated (DA-U, N = 127) or pretreated with dithiothreitol (DA-DTT, N = 101), then cultured on MacConkey agar for quantitation of aerobic gram-negative bacteria, typically from the class Gammaproteobacteria, and on blood agar for quantitation of anaerobic microorganisms. DA-DTT exhibited 2.86-fold greater anaerobic bacterial counts compared to DA-U (P = 0.0101), but were not statistically different on MacConkey agar.DNA isolation from DA-U (N = 112) and DA-DTT (N = 43) samples and library preparation for 16S rRNA gene sequencing were also performed using modified protocols. DA-DTT samples exhibited 3.81-fold higher DNA concentrations (P = 0.0014) and 4.18-fold higher 16S library concentrations (P < 0.0001) then DA-U samples. 16S rRNA gene sequencing revealed increases in the detected relative abundances of obligate and facultative anaerobes in DA-DTT samples, including increases in the genera Clostridium (false discovery rate (FDR) P = 4.38E-6), Enterococcus (FDR P = 2.57E-8), Fusobacterium (FDR P = 0.02) and Bacteroides (FDR P = 5.43E-9). Detected levels of Gram-negative enteropathogens from the phylum Proteobacteria, such as Klebsiella (FDR P = 2.73E-6) and Providencia (FDR P < 0.0001) (family Enterobacteriaceae) and Pseudomonas (family Pseudomonadaceae) (FDR P = 0.04), were also increased in DA-DTT samples.ConclusionsThis study validates novel DTT-based methodology which optimizes microbial culture and 16S rRNA gene sequencing for the study of the small bowel microbiome. The microbial analyses indicate increased isolation of facultative and obligate anaerobes from the mucus layer using these novel techniques.

Cancer Monitoring Methods

Methods for cancer monitoring and early detection of the disease are of the utmost importance and represent one of the most active areas of current research. Cancer monitoring is crucial not only for early initial diagnosis of the disease, but also for followup of therapy outcome. Despite being well developed, most methods for cancer monitoring are unsuitable for clinical use because they either are insufficiently accurate, not sensitive enough, or require a lengthy complicated analysis. There is a great necessity for more effective cancer monitoring methods that can improve cancer management in routine clinical setting and increase treatment effectiveness. Advances in this field of research are based on a more detailed understanding of the fundamental biological mechanisms involved in the disease process, as well as on advances in genomic, transcriptomic, proteomic, and metabolomic research. This special issue encompasses articles on the state of the art, advantages and disadvantages, current limitations, and future perspectives of cancer monitoring methods. Dr. D. Musio with colleagues and Dr. B. Kasper with colleagues present advanced imaging methods in clinical followup of response to therapy. Dr. G. Bertino with colleagues, as well as Dr. P. Mirabelli and Dr. M. Incoronato, offer new insight into the use of some traditional cancer biomarkers in clinical and laboratory practice. The works of Dr. P. Sadlecki with colleagues, Dr. R. Zappacosta with colleagues, and Dr. S. Farivar with colleagues deal with the analysis of protein cancer biomarkers in different types of samples. Of special interest are the articles that report on development, implementation, and validation of novel techniques for cancer monitoring, by Dr. C.-F. Chen with colleagues and Dr. I. Macchia and colleagues. We would like to thank the authors for their excellent contributions to this special issue. We hope that this issue will be useful to the experts of all profiles dealing with cancer in both clinical and laboratory setting. Aleksandra Nikolic Oronza Antonietta Botrugno Jelena Urosevic Natasa Tosic

EGFR gene status in cytological samples of nonsmall cell lung carcinoma

In nonsmall cell lung cancer (NSCLC), the development and clinical application of tyrosine kinase inhibitors (TKIs) targeting the epidermal growth factor receptor (EGFR) has required the investigation of EGFR status by gene copy number and/or mutation analysis. This review aimed to present the current knowledge of the use of cytological specimens for EGFR testing in lung cancer. A systematic computerized search was performed of the MEDLINE(R) and EMBASE databases to identify articles reporting the use of cytological samples for determining EGFR status in NSCLC. Data were extracted from 30 original articles. An additional 19 reviews, consensus statements, and editorials were selected from 175 retrieved papers. Different techniques using cell blocks, scraped cells from archival slides, and fresh cells have shown promising results and include fluorescent in situ hybridization (FISH), direct sequencing, and quantitative polymerase chain reaction (PCR), with similar or higher accuracy and sensitivity than surgical specimens. Preservation and quality of the extracted DNA seem to matter more than the actual number of tumor cells present in the samples. However, major issues still reside in the amount of material, the interference from background non-neoplastic cells, and standardization of parameters for cytological samples. This analysis provided evidence that cytological material is suitable for detecting EGFR status using several different methodologies and preparations. New prospective, clinical studies are encouraged for collection and handling of cytological samples as well as for validation of novel techniques in large cohorts.