Diagnostic Accuracy of a Handheld Ultrasound vs a Cart-based Model: A Randomized Clinical Trial.

Introduction: Numerous studies have demonstrated the accuracy of point-of-care ultrasound (POCUS). Portable, handheld devices have expanded the clinical scope of POCUS at a fraction of the cost of traditional, cart-based models. There is a paucity of data assessing the diagnostic accuracy of portable devices. Our objective in this study was to compare the diagnostic accuracy of a portable device with a cart-based model. Methods: This was an institutional review board-approved, observational, prospective, randomized clinical trial (NCT05196776) of a convenience sample of adult patients who presented to a university-based health system. Patients who required a cardiac, lung, renal, aorta, or biliary POCUS were randomized to a portable device or to a cart-based model. We hypothesized that the cart-based model would have a 90% diagnostic accuracy vs 70% for the handheld device. To detect a 20% difference, the sample size was calculated to be 98, with 49 patients randomized to each arm. We used standard 2x2 tables to calculate test characteristics with 95% confidence intervals (CI). Results: A total of 110 patients were enrolled, with 56 patients randomized to the cart-based model and 54 to the handheld device. The sensitivity, specificity, and diagnostic accuracy of the cart-based vs handheld were 77.8% (40-97.2) vs 92.9% (66.1-99.8), 91.5% (79.6-97.6) vs 92.3% (79.1-98.4%), and 89.3% (78.1-96) vs 92.5% (81.8-97.9), respectively. Conclusion: The diagnostic accuracy of a portable, handheld device is similar to that of a cart-based model.

Quantification and persistence of COVID-19 virus in recently deceased individuals before and after embalming.

The COVID-19 pandemic severely affected the medical education worldwide. The infection risk for medical students and healthcare personnel who work with COVID-19 positive cadavers or tissues remains unclear. Moreover, COVID-19 positive cadavers have been rejected by medical schools, adversely impacting the continuum of medical education. Herein, the viral genome abundance in tissues from four COVID-19 positive donors before and after embalming were compared. Tissue samples were collected from the lungs, liver, spleen, and brain both pre- and postembalming. The possible presence of infectious COVID-19 was determined by inoculating human tissue homogenates onto a monolayer of human A549-hACE2 cells and observing for cytopathic effects up to 72 h postinoculation. A real- time quantitative reverse transcription polymerase chain reaction was performed to quantify COVID-19 present in culture supernatants. Fully intact viral genome sequence was possible to obtain in samples with higher levels of virus, even several days postmortem. The embalming procedure described above substantially reduces the abundance of viable COVID-19 genomes in all tissues, sometimes even to undetectable levels. However, in some cases, COVID-19 RNA can still be detected, and a cytopathic effect can be seen both pre- and postembalmed tissues. This study suggests that embalmed COVID-19 positive cadavers might be used safely with appropriate precautions followed in gross anatomy laboratories and in clinical and scientific research. Deep lung tissue is the best specimen to test for the virus. If the tests on the lung tissues are negative, there is a very low likelihood that other tissues will show positive results.

Tracheal Transection-A Novel Airway Management.

Background Traumatic injury of the trachea is rare, especially complete transection. Its operative revision requires an interdisciplinary approach. Case Description We hereby present a rare case of complete transection of the trachea by accident. To stabilize the patient and to allow for safe surgery, veno-venous extracorporeal support was initiated via the subclavian artery and the femoral vein. The patient was subsequently operated, and the trachea re-anastomosed with favorable outcome. Conclusion This rare case of an accidental transection of the trachea shows the importance of a good emergency rescue chain and the ability to facilitate interdisciplinary approaches in tertiary hospitals.

Time-resolved transcriptome analysis and lipid pathway reconstruction of the oleaginous green microalga Monoraphidium neglectum reveal a model for triacylglycerol and lipid hyperaccumulation.

BACKGROUND: Oleaginous microalgae are promising production hosts for the sustainable generation of lipid-based bioproducts and as bioenergy carriers such as biodiesel. Transcriptomics of the lipid accumulation phase, triggered efficiently by nitrogen starvation, is a valuable approach for the identification of gene targets for metabolic engineering. RESULTS: An explorative analysis of the detailed transcriptional response to different stages of nitrogen availability was performed in the oleaginous green alga Monoraphidium neglectum. Transcript data were correlated with metabolic data for cellular contents of starch and of different lipid fractions. A pronounced transcriptional down-regulation of photosynthesis became apparent in response to nitrogen starvation, whereas glucose catabolism was found to be up-regulated. An in-depth reconstruction and analysis of the pathways for glycerolipid, central carbon, and starch metabolism revealed that distinct transcriptional changes were generally found only for specific steps within a metabolic pathway. In addition to pathway analyses, the transcript data were also used to refine the current genome annotation. The transcriptome data were integrated into a database and complemented with data for other microalgae which were also subjected to nitrogen starvation. It is available at https://tdbmn.cebitec.uni-bielefeld.de. CONCLUSIONS: Based on the transcriptional responses to different stages of nitrogen availability, a model for triacylglycerol and lipid hyperaccumulation is proposed, which involves transcriptional induction of thioesterases, differential regulation of lipases, and a re-routing of the central carbon metabolism. Over-expression of distinct thioesterases was identified to be a potential strategy to increase the oleaginous phenotype of M. neglectum, and furthermore specific lipases were identified as potential targets for future metabolic engineering approaches.

Nuclear transformation and functional gene expression in the oleaginous microalga Monoraphidium neglectum.

Photosynthetic microalgae hold great promise as non-food feedstocks for the sustainable production of a range of bio-products and genetic engineering is an increasingly important strategy to improve the natural cellular features. For the vast majority of microalgal strains, however, genetic engineering is not yet possible and the establishment of efficient genetic tools for a broad range of microalgal species is an important task to reach biotechnological success. Stable DNA transformation is one of the crucial steps for most genetic engineering approaches. In this context, we report the first successful and stable nuclear genetic transformation of the biotechnologically promising oleaginous microalga M. neglectum. Transformation was achieved by electroporation and the efficiency could progressively be improved by implementation of an additional cell pretreatment step, aiming at weakening the rigid natural cell wall. Furthermore, a first reporter transgene was established for M. neglectum. As a result of this work, genetic engineering strategies now become accessible which are required to successfully establish M. neglectum as a novel host for biotechnological applications.

Label-free in vivo analysis of intracellular lipid droplets in the oleaginous microalga Monoraphidium neglectum by coherent Raman scattering microscopy.

Oleaginous photosynthetic microalgae hold great promise as non-food feedstocks for the sustainable production of bio-commodities. The algal lipid quality can be analysed by Raman micro-spectroscopy, and the lipid content can be imaged in vivo in a label-free and non-destructive manner by coherent anti-Stokes Raman scattering (CARS) microscopy. In this study, both techniques were applied to the oleaginous microalga Monoraphidium neglectum, a biotechnologically promising microalga resistant to commonly applied lipid staining techniques. The lipid-specific CARS signal was successfully separated from the interfering two-photon excited fluorescence of chlorophyll and for the first time, lipid droplet formation during nitrogen starvation could directly be analysed. We found that the neutral lipid content deduced from CARS image analysis strongly correlated with the neutral lipid content measured gravimetrically and furthermore, that the relative degree of unsaturation of fatty acids stored in lipid droplets remained similar. Interestingly, the lipid profile during cellular adaption to nitrogen starvation showed a two-phase characteristic with initially fatty acid recycling and subsequent de novo lipid synthesis. This works demonstrates the potential of quantitative CARS microscopy as a label-free lipid analysis technique for any microalgal species, which is highly relevant for future biotechnological applications and to elucidate the process of microalgal lipid accumulation.

The interplay of light and oxygen in the reactive oxygen stress response of Chlamydomonas reinhardtii dissected by quantitative mass spectrometry.

Light and oxygen are factors that are very much entangled in the reactive oxygen species (ROS) stress response network in plants, algae and cyanobacteria. The first obligatory step in understanding the ROS network is to separate these responses. In this study, a LC-MS/MS based quantitative proteomic approach was used to dissect the responses of Chlamydomonas reinhardtii to ROS, light and oxygen employing an interlinked experimental setup. Application of novel bioinformatics tools allow high quality retention time alignment to be performed on all LC-MS/MS runs increasing confidence in protein quantification, overall sequence coverage and coverage of all treatments measured. Finally advanced hierarchical clustering yielded 30 communities of co-regulated proteins permitting separation of ROS related effects from pure light effects (induction and repression). A community termed redox(II) was identified that shows additive effects of light and oxygen with light as the first obligatory step. Another community termed 4-down was identified that shows repression as an effect of light but only in the absence of oxygen indicating ROS regulation, for example, possibly via product feedback inhibition because no ROS damage is occurring. In summary the data demonstrate the importance of separating light, O2 and ROS responses to define marker genes for ROS responses. As revealed in this study, an excellent candidate is DHAR with strong ROS dependent induction profiles.

pyGCluster, a novel hierarchical clustering approach.

SUMMARY: pyGCluster is a clustering algorithm focusing on noise injection for subsequent cluster validation. The reproducibility of a large amount of clusters obtained with agglomerative hierarchical clustering is assessed. Furthermore, a multitude of different distance-linkage combinations are evaluated. Finally, highly reproducible clusters are meta-clustered into communities. Graphical illustration of the results as node and expression maps is implemented. AVAILABILITY AND IMPLEMENTATION: pyGCluster requires Python 2.7, it is freely available at http://pyGCluster.github.io and published under MIT license. Dependencies are NumPy, SciPy and optionally fastcluster and rpy2. CONTACT: christan@fufezan.net SUPPLEMENTARY INFORMATION: Supplementary data is available at Bioinformatics online and at http://pyGCluster.github.io.

The metabolic status drives acclimation of iron deficiency responses in Chlamydomonas reinhardtii as revealed by proteomics based hierarchical clustering and reverse genetics.

Iron is a crucial cofactor in numerous redox-active proteins operating in bioenergetic pathways including respiration and photosynthesis. Cellular iron management is essential to sustain sufficient energy production and minimize oxidative stress. To produce energy for cell growth, the green alga Chlamydomonas reinhardtii possesses the metabolic flexibility to use light and/or carbon sources such as acetate. To investigate the interplay between the iron-deficiency response and growth requirements under distinct trophic conditions, we took a quantitative proteomics approach coupled to innovative hierarchical clustering using different "distance-linkage combinations" and random noise injection. Protein co-expression analyses of the combined data sets revealed insights into cellular responses governing acclimation to iron deprivation and regulation associated with photosynthesis dependent growth. Photoautotrophic growth requirements as well as the iron deficiency induced specific metabolic enzymes and stress related proteins, and yet differences in the set of induced enzymes, proteases, and redox-related polypeptides were evident, implying the establishment of distinct response networks under the different conditions. Moreover, our data clearly support the notion that the iron deficiency response includes a hierarchy for iron allocation within organelles in C. reinhardtii. Importantly, deletion of a bifunctional alcohol and acetaldehyde dehydrogenase (ADH1), which is induced under low iron based on the proteomic data, attenuates the remodeling of the photosynthetic machinery in response to iron deficiency, and at the same time stimulates expression of stress-related proteins such as NDA2, LHCSR3, and PGRL1. This finding provides evidence that the coordinated regulation of bioenergetics pathways and iron deficiency response is sensitive to the cellular and chloroplast metabolic and/or redox status, consistent with systems approach data.

Pairwise agonist scanning-flow cytometry (PAS-FC) measures inside-out signaling and patient-specific response to combinatorial platelet agonists.

Understanding the response of cells to multiple stimuli is vital for predicting donor specific responses and better understanding the signaling pathways involved. This is of particular importance in platelets because exposure of phosphatidylserine (PS) occurs upon costimulation but not with a single agonist. Here, we describe a multiplexed pairwise agonist scanning-flow cytometry (PAS-FC) method of measuring platelet inside-out responses to all pairs of six platelet agonists (convulxin, SFLLRN, AYPGKF, ADP, U46619, and PGE(2)) used at their EC(50) concentrations. These agonists allowed exploration of platelet signaling downstream of GPVI, PAR-1, PAR-4, P2Y(1), P2Y(12), TP, and IP receptors. The three-color flow cytometry method simultaneously measured integrin α(IIb)ß(3) activation with PAC-1 antibody, P-selectin exposure (via α granule release) with anti-P-selectin, and PS exposure with annexin V. These responses were consistent across a healthy male donor pool. In duplicate measurements with each donor, 4 of the 10 donors had a sufficiently unique 45-parameter (15 pairs × 3 colors) phenotype to self-cluster (P < 0.001). This method has the potential for efficiently scanning for patient specific responses across a broad agonist-receptor space.

Multiscale prediction of patient-specific platelet function under flow.

During thrombotic or hemostatic episodes, platelets bind collagen and release ADP and thromboxane A(2), recruiting additional platelets to a growing deposit that distorts the flow field. Prediction of clotting function under hemodynamic conditions for a patient's platelet phenotype remains a challenge. A platelet signaling phenotype was obtained for 3 healthy donors using pairwise agonist scanning, in which calcium dye-loaded platelets were exposed to pairwise combinations of ADP, U46619, and convulxin to activate the P2Y(1)/P2Y(12), TP, and GPVI receptors, respectively, with and without the prostacyclin receptor agonist iloprost. A neural network model was trained on each donor's pairwise agonist scanning experiment and then embedded into a multiscale Monte Carlo simulation of donor-specific platelet deposition under flow. The simulations were compared directly with microfluidic experiments of whole blood flowing over collagen at 200 and 1000/s wall shear rate. The simulations predicted the ranked order of drug sensitivity for indomethacin, aspirin, MRS-2179 (a P2Y(1) inhibitor), and iloprost. Consistent with measurement and simulation, one donor displayed larger clots and another presented with indomethacin resistance (revealing a novel heterozygote TP-V241G mutation). In silico representations of a subject's platelet phenotype allowed prediction of blood function under flow, essential for identifying patient-specific risks, drug responses, and novel genotypes.

Stability of gene contributions and identification of outliers in multivariate analysis of microarray data.

BACKGROUND: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes. RESULTS: In this study, we developed a computationally efficient algorithm for: i) the assessment of the significance of gene contributions and ii) the identification of sample outliers in multivariate analysis of microarray data. The approach is based on the use of resampling methods including bootstrapping and jackknifing. A statistical package of R functions was developed. This package includes tools for both inferring the statistical significance of gene contributions and identifying outliers among samples. CONCLUSION: The methodology was successfully applied to three published data sets with varying levels of signal intensities. Its relevance was compared with alternative methods. Overall, it proved to be particularly effective for the evaluation of the stability of microarray data.