Current Gold Standard Approach Research Articles

The Evolving Role of Novel Imaging Techniques for Radiotherapy Planning

The ability to visualise cancer with imaging has been crucial to the evolution of modern radiotherapy (RT) planning and delivery. And as evolving RT technologies deliver increasingly precise treatment, the importance of accurate identification and delineation of disease assumes ever greater significance. However, innovation in imaging technology has matched that seen with RT delivery platforms, and novel imaging techniques are a focus of much research activity. How these imaging modalities may alter and improve the diagnosis and staging of cancer is an important question, but already well served by the literature. What is less clear is how novel imaging techniques may influence and improve practical and technical aspects of RT planning and delivery. In this review, current gold standard approaches to integration of imaging, and potential future applications of bleeding-edge imaging technology into RT planning pathways are explored.

Methods for assessing cardiac myofilament calcium sensitivity.

Myofilament calcium (Ca2+) sensitivity is one of several mechanisms by which force production of cardiac muscle is modulated to meet the ever-changing demands placed on the heart. Compromised Ca2+ sensitivity is associated with pathologies, which makes it a parameter of interest for researchers. Ca2+ Sensitivity is the ratio of the association and dissociation rates between troponin C (TnC) and Ca2+. As it is not currently possible to measure these rates in tissue preparations directly, methods have been developed to infer myofilament sensitivity, typically using some combination of force and Ca2+ measurements. The current gold-standard approach constructs a steady-state force-Ca2+ relation by exposing permeabilised muscle samples to a range of Ca2+ concentrations and uses the half-maximal concentration as a proxy for sensitivity. While a valuable method for steady-state investigations, the permeabilisation process makes the method unsuitable when examining dynamic, i.e., twitch-to-twitch, changes in myofilament sensitivity. The ability of the heart to transiently adapt to changes in load is an important consideration when evaluating the impact of disease states. Alternative methods have been proffered, including force-Ca2+ phase loops, potassium contracture, hybrid experimental-modelling and conformation-based fluorophore approaches. This review provides an overview of the mechanisms underlying myofilament Ca2+ sensitivity, summarises existing methods, and explores, with modelling, whether any of them are suited to investigating dynamic changes in sensitivity. We conclude that a method that equips researchers to investigate the transient change of myofilament Ca2+ sensitivity is still needed. We propose that such a method will involve simultaneous measurements of cytosolic Ca2+ and TnC activation in actively twitching muscle and a biophysical model to interpret these data.

MetaNovo: An open-source pipeline for probabilistic peptide discovery in complex metaproteomic datasets.

Microbiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focused search sequence databases based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing only targets the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. Here we describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored sequence databases for target-decoy searches directly at the proteome level, enabling metaproteomic analyses without prior expectation of sample composition or metagenomic data generation and compatible with standard downstream analysis pipelines. We compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome sequence database-but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic sequence database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying an experimental sample contaminant without prior expectation. By estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence databases to search. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic sequence database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself.

A multicenter, case-control study of a novel multi-target fecal DNA test for colorectal cancer detection.

26 Background: Globally, colorectal cancer (CRC) is the fourth most frequently occurring cancer and is the second leading cause of cancer-related deaths. Early detection and diagnosis of pre-cancer lesions and CRCs at curable stages could prevent the disease or improve patient survival. Colonoscopy, the current gold-standard approach for CRC screening, is an invasive procedure, and novel non-invasive alternatives are needed. Methods: In present study, we developed a novel multi-target fecal DNA based assay, which integrates detection of two stool DNA (sDNA) methylation markers by quantitative methylation-specific PCR (qMSP) and immunochemical fecal occult blood test. We performed a multi-center case-control study to validate the diagnostic performance of this novel multi-target assay. Thus far, we collected stool specimens from a total of 784 subjects including CRC, advanced adenoma, nonadvanced neoplasms and individuals with negative findings on colonoscopy from six sites across China. All participants underwent colonoscopy; the stool specimens were tested with the multi-target fecal DNA test as well as a quantitative FIT test (OC FIT-CHEK, Eiken) in parallel in order to perform head-to-head comparison of the test performance of both assays. Results: The multi-target fecal DNA test demonstrated a higher sensitivity (96.1%) than FIT (85.3%) for CRCs (n=204). Meanwhile, 20 of 39 (51.3%) patients with advanced adenoma tested positive by the fecal DNA test, which was remarkably superior to FIT (7 of 39 tested positive, 17.9%). Among 541 participants with nonadvanced neoplasms or negative findings on colonoscopy, the specificity of the DNA test was 86.9%, compared with a specificity of 93.1% achieved by FIT. Within the control group, the DNA test and FIT yielded a specificity of 90.5% and 94.9% respectively for individuals with negative results on colonoscopy. Conclusions: The novel multi-target fecal DNA test exhibited notably superior sensitivity for both CRC and advanced adenoma cases than the commercially quantitative FIT test, while sacrificing some specificity. Our results suggest that this novel multi-target fecal based test may be used as an effective tool for early detection and pre-screening of CRC. Prospective study will be conducted to further evaluate the clinical performance and cost-effectiveness of this assay.

Review: cellularity in bone marrow autografts for bone and fracture healing.

The use of autografts, as primary cell and tissue source, is the current gold standard approach to treat critical size bone defects and nonunion defects. The unique mixture of the autografts, containing bony compartments and bone marrow (BM), delivers promising results. Although BM mesenchymal stromal cells (BM-MSCs) still represent a major target for various healing approaches in current preclinical research and respective clinical trials, their occurrence in the human BM is typically low. In vitro expansion of this cell type is regulatory challenging as well as time and cost intensive. Compared with marginal percentages of resident BM-MSCs in BM, BM mononuclear cells (BM-MNCs) contained in BM aspirates, concentrates, and bone autografts represent a readily available abundant cell source, applicable within hours during surgical procedures without the need for time-consuming and regulatory challenging cell expansion. This benefit is one reason why autografting has become a clinical standard procedure. However, the exact anatomy and cellularity of BM-MNCs in humans, which is strongly correlated to their unique mode of action and wide application range remains to be elucidated. The aim of this review was to present an overview of the current knowledge on these specific cell types found in human BM, emphasize the contribution of BM-MNCs in bone healing, highlight donor site dependence, and discuss limitations in the current isolation and subsequent characterization procedures. Hereby, the most recent and relevant examples of human BM-MNC cell characterization, flow cytometric analyses, and findings are summarized, with a strong focus on bone therapy.

Rapid purification and enrichment of viral particles using self-propelled micromotors.

Virus infections remain one of the principal causes of morbidity and mortality worldwide. The current gold standard approach for diagnosing pathogens requires access to reverse transcription-polymerase chain reaction (RT-PCR) technology. However, separation and enrichment of the targets from complex and diluted samples remains a major challenge. In this work, we proposed a micromotor-based sample preparation concept for the efficient separation and concentration of target viral particles before PCR. The micromotors are functionalized with antibodies with a 3D polymer linker and are capable of self-propulsion by the catalytic generation of oxygen bubbles for selective and positive virus enrichment. This strategy significantly improves the enrichment efficiency and recovery rate of virus (up to 80% at 104 tu mL-1 in a 1 mL volume within just 6 min) without external mixing equipment. The method allows the Ct value in regular PCR tests to appear 6-7 cycles earlier and a detection limit of 1 tu mL-1 for the target virus from swap samples. A point-of-need test kit is designed based on the micromotors which can be readily applied to pretreat a large volume of samples.

SmokeMon: Unobtrusive Extraction of Smoking Topography Using Wearable Energy-Efficient Thermal.

Smoking is the leading cause of preventable death worldwide. Cigarette smoke includes thousands of chemicals that are harmful and cause tobacco-related diseases. To date, the causality between human exposure to specific compounds and the harmful effects is unknown. A first step in closing the gap in knowledge has been measuring smoking topography, or how the smoker smokes the cigarette (puffs, puff volume, and duration). However, current gold-standard approaches to smoking topography involve expensive, bulky, and obtrusive sensor devices, creating unnatural smoking behavior and preventing their potential for real-time interventions in the wild. Although motion-based wearable sensors and their corresponding machine-learned models have shown promise in unobtrusively tracking smoking gestures, they are notorious for confounding smoking with other similar hand-to-mouth gestures such as eating and drinking. In this paper, we present SmokeMon, a chest-worn thermal-sensing wearable system that can capture spatial, temporal, and thermal information around the wearer and cigarette all day to unobtrusively and passively detect smoking events. We also developed a deep learning-based framework to extract puffs and smoking topography. We evaluate SmokeMon in both controlled and free-living experiments with a total of 19 participants, more than 110 hours of data, and 115 smoking sessions achieving an F1-score of 0.9 for puff detection in the laboratory and 0.8 in the wild. By providing SmokeMon as an open platform, we provide measurement of smoking topography in free-living settings to enable testing of smoking topography in the real world, with potential to facilitate timely smoking cessation interventions.

Compact portable sources of high-LET radiation: Validation and potential application for galactic cosmic radiation countermeasure discovery

Implementation of a systematic program for galactic cosmic radiation (GCR) countermeasure discovery will require convenient access to ground-based space radiation analogs. The current gold standard approach for GCR simulation is to use a particle accelerator for sequential irradiation with ion beams representing different GCR components. This has limitations, particularly for studies of non-acute responses, strategies that require robotic instrumentation, or implementation of complex in vitro models that are emerging as alternatives to animal experimentation. Here we explore theoretical and practical issues relating to a different approach to provide a high-LET radiation field for space radiation countermeasure discovery, based on use of compact portable sources to generate neutron-induced charged particles. We present modeling studies showing that DD and DT neutron generators, as well as an AmBe radionuclide-based source, generate charged particles with a linear energy transfer (LET) distribution that, within a range of biological interest extending from about 10 to 200 keV/μm, resembles the LET distribution of reference GCR radiation fields experienced in a spacecraft or on the lunar surface. We also demonstrate the feasibility of using DD neutrons to induce 53BP1 DNA double-strand break repair foci in the HBEC3-KT line of human bronchial epithelial cells, which are widely used for studies of lung carcinogenesis. The neutron-induced foci are larger and more persistent than X ray-induced foci, consistent with the induction of complex, difficult-to-repair DNA damage characteristic of exposure to high-LET (>10 keV/μm) radiation. We discuss limitations of the neutron approach, including low fluence in the low LET range (<10 keV/μm) and the absence of certain long-range features of high charge and energy particle tracks. We present a concept for integration of a compact portable source with a multiplex microfluidic in vitro culture system, and we discuss a pathway for further validation of the use of compact portable sources for countermeasure discovery.

Mixture density networks for the indirect estimation of reference intervals

BackgroundReference intervals represent the expected range of physiological test results in a healthy population and are essential to support medical decision making. Particularly in the context of pediatric reference intervals, where recruitment regulations make prospective studies challenging to conduct, indirect estimation strategies are becoming increasingly important. Established indirect methods enable robust identification of the distribution of “healthy” samples from laboratory databases, which include unlabeled pathologic cases, but are currently severely limited when adjusting for essential patient characteristics such as age. Here, we propose the use of mixture density networks (MDN) to overcome this problem and model all parameters of the mixture distribution in a single step.ResultsEstimated reference intervals from varying settings with simulated data demonstrate the ability to accurately estimate latent distributions from unlabeled data using different implementations of MDNs. Comparing the performance with alternative estimation approaches further highlights the importance of modeling the mixture component weights as a function of the input in order to avoid biased estimates for all other parameters and the resulting reference intervals. We also provide a strategy to generate partially customized starting weights to improve proper identification of the latent components. Finally, the application on real-world hemoglobin samples provides results in line with current gold standard approaches, but also suggests further investigations with respect to adequate regularization strategies in order to prevent overfitting the data.ConclusionsMixture density networks provide a promising approach capable of extracting the distribution of healthy samples from unlabeled laboratory databases while simultaneously and explicitly estimating all parameters and component weights as non-linear functions of the covariate(s), thereby allowing the estimation of age-dependent reference intervals in a single step. Further studies on model regularization and asymmetric component distributions are warranted to consolidate our findings and expand the scope of applications.

Current surgical treatment options for liver metastasis

Current surgical treatment options for liver metastasis Abstract. Metastasis are the most frequent hepatic tumors. Although current treatment regimens focus highly on interdisciplinarity and are individualized, surgical resection remains the only curative treatment and represents the current gold standard approach. Advances in surgical, systemic and interventional treatment within the last years have resulted in a multidisciplinary therapy, individualized for each patient depending on their disease stage and condition. With these advancements, initially non-resectable liver metastasis can now be candidates for a surgical approach. Neoadjuvant chemotherapy, minimal invasive ablation, two- or multi-staged resections of the liver with or without portal vein embolization have contributed to this development. Advances in surgical and perioperative treatment also account for significantly increased overall survival.

Moving shear stress towards the clinic: preclinical comparison of optical coherence tomography-based versus angiography-based time-averaged wall shear stress estimations

Abstract Introduction Identification of coronary atherosclerotic plaques at risk of causing future acute coronary syndromes remains a major unmet clinical challenge. The addition of vessel biomechanics to intracoronary imaging derived evaluation of plaque morphology, improves identification of plaques likely to develop high risk features. We and others have developed a framework for intracoronary imaging (optical coherence tomography [OCT]) based 3D reconstructions of coronary arteries for computational fluid dynamics (CFD) simulations of shear stress, which are considered the current gold standard approach for quantification of coronary arterial haemodynamics. However, these approaches are time consuming and computationally intensive, resulting in a barrier to clinical uptake. Purpose Determination of time averaged wall shear stress (TAWSS) based on 3D coronary geometries from non-invasive 3D Quantitative Coronary Angiography (3D-QCA) has recently been developed (Pie Medical Imaging, Netherlands), which enables results of shear stress simulations to be available within 30 minutes. We sought to compare TAWSS determined from 3D-QCA with gold standard OCT-based CFD simulations in both normal and stenotic arteries in minipigs. Methods 15 normal and 5 stenotic minipig coronary arteries were studied. Anatomically matched 3D arterial geometries were reconstructed from 3D-QCA and OCT using common centrelines. Boundary conditions for simulations included directly measured inlet blood velocities; parabolic inlet flow profiles, zero pressure outlet; no-slip arterial walls; blood density: 1.05 g/ml; blood dynamic viscosity: 0.035 g/cm.s. Blood was modelled as Newtonian. 3D-QCA TAWSS was obtained with a Kratos Multi-Physics CFD solver. OCT-based simulations were performed using Abaqus/CFD v6.14. TAWSS was calculated for 80 axially matched segments for both methods (1200 and 400 paired comparisons for normal and stenotic arteries, respectively). Data were analysed using Bland-Altman and Wilcoxon matched-pairs signed ranked tests. Results Computation times for 3D-QCA and OCT-based CFD were approximately 30 minutes and 2 hours respectively. Axial profiles of TAWSS were similar between the two methods and there was agreement in TAWSS magnitudes and narrow 95% limits of agreement (Figure 1 and Figure 2). Using co-registered TAWSS maps generated by each method, we find similar spatial regional distributions of TAWSS in both normal and stenotic arteries. Conclusions Our data suggest that 3D-QCA based TAWSS is feasible in both normal and stenotic arteries. Spatial TAWSS distributions between the two methods are similar with agreement in matched TAWSS comparisons, though there are some small systematic differences in the absolute values of TAWSS, due to different resultant arterial geometries. These encouraging data suggest that further clinical evaluation of rapid TAWSS from 3D-QCA is warranted, which may facilitate clinical adoption of TAWSS assessment. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Medical Research Council

Detecting Spurious Correlations With Sanity Tests for Artificial Intelligence Guided Radiology Systems.

Artificial intelligence (AI) has been successful at solving numerous problems in machine perception. In radiology, AI systems are rapidly evolving and show progress in guiding treatment decisions, diagnosing, localizing disease on medical images, and improving radiologists' efficiency. A critical component to deploying AI in radiology is to gain confidence in a developed system's efficacy and safety. The current gold standard approach is to conduct an analytical validation of performance on a generalization dataset from one or more institutions, followed by a clinical validation study of the system's efficacy during deployment. Clinical validation studies are time-consuming, and best practices dictate limited re-use of analytical validation data, so it is ideal to know ahead of time if a system is likely to fail analytical or clinical validation. In this paper, we describe a series of sanity tests to identify when a system performs well on development data for the wrong reasons. We illustrate the sanity tests' value by designing a deep learning system to classify pancreatic cancer seen in computed tomography scans.

Evaluation of interpretation methods to improve accuracy of the prenatal BACs-on-Beads™ assay in prenatal diagnosis.

Prenatal BACs-on-Beads™ (PNBoBs™) technology has been approved for use in routine clinical prenatal diagnosis in numerous countries. However, the influence of data interpretation on the accuracy of the results remains to be evaluated. The present study aimed to determine the accuracy of existing data interpretation approaches and develop an optimization method to improve the performance of the PNBoBs™ assay in prenatal diagnosis. A total of 2,289 prenatal cases with known karyotypes and raw ratio data from PNBoBs™ assays were recruited for the present study. Positive results, according to the data interpretation methods used for the PNBoBs™ test, were validated against current gold-standard approaches. Statistical analyses were then performed to evaluate the accuracy of existing methods in data interpretation to provide a basis for the optimization of a follow-up approach. Among the existing methods, the ‘trimmed standard deviation threshold’ approach had the highest sensitivity and false-positive rates, with 98.1 and 4.2%, respectively. The ‘n-1 or greater probes’ rule had the highest specificity (99.7%) and the second-highest false-negative rate (11.5%). The method optimized in the present study provided a reasonable balance between sensitivity (98.1%) and specificity (99.6%) with regards to the interpretation of the data obtained from the PNBoBs™ assay. The results indicated that the present optimization method outperforms existing approaches in data interpretation for the PNBoBs™ assay, and as a result, may reduce unnecessary verification turnaround time and cost in prenatal diagnosis.

Abstract 5125: Evaluation of differential peptide loading on TMT-based proteomic on phosphoproteomic data quality in an AML model

Abstract Mass Spectrometry based proteomics profiling has become a powerful tool for broad quantification of proteins and their post-translational modifications for cancer research. Due to extensive efforts in the field to benchmark and standardize complex workflows, particularly those of the Clinical Proteomics Tumor Analysis Consortium (CPTAC), proteomics is now moving into clinical research. Reliable and reproducible quantification of &amp;gt; 10,000 proteins and &amp;gt;30,000 phosphosites is now routinely attainable from mammalian tissue samples. Integration of deep-scale proteomics analysis of human tumors with genomic data has been shown to improve specificity for identifying pathway alterations caused by tumor associated mutations. Furthermore, phosphoproteome measurements provide information on pathway activation not discernible from genetic measurements and thus provides unique insights for potential therapeutic targets. A substantial challenge in the field of clinical proteomics is obtaining the sufficiently large clinical specimens necessary for deep coverage of the proteome. This challenge is particularly acute in the case of phosphoproteomics, which requires 100-fold more material than global profiling due to the low stoichiometry of the modification. The current gold standard approach for clinical proteomics employs a tandem mass tags (TMT) isobaric labeling approach to achieve deep quantitative proteomic and phosphoproteomic measurements. In this approach, 10 or 11 patient samples are labeled with unique isobaric labels, mixed in equal proportion, and fractionated prior to liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. This creates a second challenge since very often due to external variables, differing quantities of protein are obtainable for patients within the same study. In these cases, the analysts need to decide whether to exclude sample-limited patients, reduce the protein loading per patient for the study, or to include that individual patient at reduced protein loading. In this study, we set out to interrogate the impact of differential channel loading on global and phosphoproteomics results using an established clinical workflow. First, we determined protein yields from patient samples of decreasing cell count. We then used these results to design a 2 TMT plex experiment to explore a range of peptide loadings that we expect to encounter in executing a clinical proteomics experiment. The results were examined for protein/phosphosite coverage and various aspects of quantitative reproducibility. Our results provide a thorough examination of the impacts of differential channel loading and provide researchers with a resource to make informed decisions concerning their study design. Citation Format: Paul D. Piehowski, Yang Wang, James A. Sanford, Joshua R. Hansen, Marina A. Gritsenko, Vladislav A. Petyuk, Karl K. Weitz, Cristina Tognon, Wei-Jun Qian, Tao Liu, Brian J. Druker, Karin D. Rodland. Evaluation of differential peptide loading on TMT-based proteomic on phosphoproteomic data quality in an AML model [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5125.

Tandem detection of organic and inorganic gunshot residues using LC–MS and SEM-EDS

Gunshot residue (GSR) is a valuable form of forensic trace evidence in the investigation of firearms crime. The current gold-standard approach does not include the analysis of organic components of the residues, which may be a deficiency, particularly in cases where there is little to no inorganic gunshot residue (IGSR) present or its attribution to a firearm source is ambiguous. A solvent extraction method was used for the extraction of organic GSR (OGSR) from the most common sampling device used to collect IGSR (i.e., SEM stubs with double-sided carbon adhesive tape). It was found that extraction did not significantly disturb inorganic GSR present on stubs, which raises the possibility that a valuable, comprehensive tandem analysis of both organic and inorganic GSR may be implemented using a single and commonly used residue collection device.The organic extract was analysed using Ultra High Performance Liquid Chromatography coupled to an Ion Trap Mass Spectrometer using Electrospray Ionisation (UHPLC-ESI-MS/MS), with preliminary results indicating that organic components can be extracted and detected at levels appropriate to casework GSR analysis. Testing of traces collected from the hands of recent shooters showed detection of stabiliser compounds typical of OGSR, which were confirmed to be present in the test ammunition’s propellant. Total analysis time is approximately 30min per specimen, including preparation, instrumental analysis and data review.As the first step in the examination of GSR stubs in relation to a shooting case, extraction of organics and analysing them for the presence of OGSR may bring two operational benefits. First, that approach may be a useful way to determine which stubs warrant priority examination for IGSR, and second, it offers the possibility of providing relatively rapid case information to investigators.

Nicotinamide riboside supplementation to improve skeletal muscle mitochondrial health and whole-body glucose homeostasis: does it actually work in humans?

Nicotinamide riboside supplementation to improve skeletal muscle mitochondrial health and whole-body glucose homeostasis: does it actually work in humans?

Rapid detection of bacterial infections using nanotechnology-based point-of-care sensor with Raman spectroscopy

Background: Mass gathering is a risk factor for infectious diseases transmission. Therefore, rapid detection of infections is highly desirable. The current gold standard approach to detect bacterial infections in clinical samples (biological fluids) requires three days of bacterial culture to obtain the diagnosis and antibiotic sensitivity results1. This approach, although very accurate results in considerable delay in initiating proper treatment which increases the transmission of infection, mainly hospital-acquired infections. Therefore, rapid detection of infection would lead to rapid clinical interventions, which mitigate the spread of infection and support antibiotic stewardship consequently reducing the burden of hospital-acquired infections. The goal of this research is to develop a highly innovative sensor (point-of-care device) for rapid detection of bacterial infections in biological fluids. This project will also focus on identifying unique SERS spectra of bacterial infections commonly associated with mass gathering and early detection of antibiotic resistant bacteria. Methods: The proposed biosensor is a culture-free diagnostic method utilizing nanotechnology-based fabricated silver nanorod arrays (AgNR) as a substrate for the Surface Enhanced Raman Spectroscopy. Results: We reported the proof-of-concept study using this novel SERS-based diagnostic where we showed that rapid detection of bacterial biomarkers in sputum and exhaled breath condensates (EBC) from patients with cystic fibrosis2,3. We further identified unique SERS spectra of various bacterial siderophores and small molecule metabolites. Conclusion: This method is highly sensitive, fast, cheap, and can be implemented at the bedside using a portable (hand-held) Raman spectroscope.

Rapid Molecular Diagnostics for Acute Myeloid Leukemia Using Single-Molecule Sequencing

Introduction: Acute Myeloid Leukemia (AML) is a genetically heterogeneous disease, associated with mutations in a well-established set of genes that affect myeloid cell differentiation and proliferation. While treatment options were limited for many decades, many new pharmacological treatments in the form of small molecule inhibitors have been developed in recent years. In order to be effective, many of these inhibitors require the presence of specific biomarkers that must be detected with appropriate genetic screening assays. Genetic studies may also inform conventional care plans. The cost and time of genetic testing can be limiting factor, delaying the start of treatment and often requiring referral to larger regional medical center. Such delays can result in increased morbidities and mortality in this patient population, making faster and more accessible genetic testing highly relevant. Methods: We have developed a rapid single-molecule sequencing-based assay which requires minimal laboratory equipment, while providing same-day results. We utilized amplification-based library preparation to generate sequencing libraries for the Oxford Nanopore Technologies MinION instrument. We have combined rapid library preparation, real-time single-molecule sequencing, and novel computational analysis algorithms to rapidly screen patient blood samples for the presence of actionable biomarkers. In this study, we analyzed samples from 48 AML patients with known mutational statuses to evaluate the performance of our approach. For our proof of principle assay, we included seven molecular targets (six hotspot mutations; one duplication) in five AML-associated genes (DNMT3A, FLT3, IDH1, IDH2, and JAK2). We compared the accuracy of our assay to current gold standard approaches which include Illumina-based short-read sequencing and capillary electrophoresis. Results and Discussion: Our assay exhibited equal or superior accuracy compared to the current gold standard approaches, while providing results significantly faster (in less than 6 hours). Each of the 48 samples were correctly classified by mutational status, with the detected variant allele frequency exhibiting high correlation (R2 for mutational hotspots ranging from a low of 0.84 to a high of 0.99) between our Nanopore-based assay and the control Illumina-based assay. Our custom FLT3-ITD detection algorithm correctly identified 24/24 samples as ITD positive, with insertion lengths matching expected peak lengths from capillary electropherogram testing and highly concordant allelic ratios. In contrast, an assay using Illumina sequencing data correctly detected only 6/24 ITD positive samples. Therefore, we conclude that our assay provides superior variant detection accuracy, significantly shorter time to results (4-6 hours instead of days), and at an expected cost of below $250/sample when utilizing single-sample Flongle flow cells. Critically, this procedure is accessible beyond tertiary care academic medical centers and could be deployed at the point-of-care in smaller hospitals, physician offices, and resource-constrained settings worldwide. Disclosures No relevant conflicts of interest to declare.

Multiplex shRNA Screening of Germ Cell Development by in Vivo Transfection of Mouse Testis

Spermatozoa are one of the few mammalian cell types that cannot be fully derived in vitro, severely limiting the application of modern genomic techniques to study germ cell biology. The current gold standard approach of characterizing single-gene knockout mice is slow as generation of each mutant line can take 6–9 months. Here, we describe an in vivo approach to rapid functional screening of germline genes based on a new nonsurgical, nonviral in vivo transfection method to deliver nucleic acids into testicular germ cells. By coupling multiplex transfection of short hairpin RNA (shRNA) constructs with pooled amplicon sequencing as a readout, we were able to screen many genes for spermatogenesis function in a quick and inexpensive experiment. We transfected nine mouse testes with a pilot pool of RNA interference (RNAi) against well-characterized genes to show that this system is highly reproducible and accurate. With a false negative rate of 18% and a false positive rate of 12%, this method has similar performance as other RNAi screens in the well-described Drosophila model system. In a separate experiment, we screened 26 uncharacterized genes computationally predicted to be essential for spermatogenesis and found numerous candidates for follow-up studies. Finally, as a control experiment, we performed a long-term selection screen in neuronal N2a cells, sampling shRNA frequencies at five sequential time points. By characterizing the effect of both libraries on N2a cells, we show that our screening results from testis are tissue-specific. Our calculations indicate that the current implementation of this approach could be used to screen thousands of protein-coding genes simultaneously in a single mouse testis. The experimental protocols and analysis scripts provided will enable other groups to use this procedure to study diverse aspects of germ cell biology ranging from epigenetics to cell physiology. This approach also has great promise as an applied tool for validating diagnoses made from medical genome sequencing, or designing synthetic biological sequences that can act as potent and highly specific male contraceptives.

Overview and perspectives of mesenchymal stem cell therapy in intensive care medicine

Development of innovative therapies in intensive care medicine is particularly important since diseases as sepsis, acute respiratory distress syndrome (ARDS) and acute renal injury (AKI) have an elevated morbidity and mortality in spite of current gold-standard approaches. Mesenchymal stem cells (MSC) may have a promising role due to their properties in immunomodulation, tissue reparation and microbial clearance. Preclinical data and results of a systematic review of PubMed, PMC and ClinicalTrials.gov have been included to review the role of MSC therapy in sepsis, ARDS and AKI. A description of MSC biology, sources and benefits in preclinical models was included. A phase I/II clinical trial (RCT) is recruiting neutropenic patients with septic shock. In ARDS, the START trial (Stem cells in ARDS Treatment) is a phase I/II study of bone marrow-derived human MSC (hMSC) that is currently recruiting patients. In AKI, a phase I study has demonstrated the safety of hMSCs infusion in patients undergoing cardiac surgery with high risk to develop AKI. A phase II study is still active. The results of these studies will determine the real feasibility of MSC therapy in critically ill patients.