The rising rate of preprints and publications, combined with persistent inadequate reporting practices and problems with study design and execution, have strained the traditional peer review system. Automated screening tools could potentially enhance peer review by helping authors, journal editors, and reviewers to identify beneficial practices and common problems in preprints or submitted manuscripts. Tools can screen many papers quickly, and may be particularly helpful in assessing compliance with journal policies and with straightforward items in reporting guidelines. However, existing tools cannot understand or interpret the paper in the context of the scientific literature. Tools cannot yet determine whether the methods used are suitable to answer the research question, or whether the data support the authors' conclusions. Editors and peer reviewers are essential for assessing journal fit and the overall quality of a paper, including the experimental design, the soundness of the study's conclusions, potential impact and innovation. Automated screening tools cannot replace peer review, but may aid authors, reviewers, and editors in improving scientific papers. Strategies for responsible use of automated tools in peer review may include setting performance criteria for tools, transparently reporting tool performance and use, and training users to interpret reports.

Background: Score-based survival prediction in patients with advanced heart failure (HF) is complicated. Easy-to-use prognostication tools could inform clinical decision-making and palliative care delivery.

Objective: To compare the prognostic utility of the Seattle HF model (SHFM), the surprise question (SQ), and the number of HF hospitalizations (NoH) within the last 12 months for predicting 1-year survival in patients with advanced HF.

Methods: We retrospectively analyzed data from a cluster-randomized controlled trial of advanced HF patients, predominantly with reduced ejection fraction. Primary outcome was the prognostic discrimination of SHFM, SQ (“Would you be surprised if this patient were to die within 1 year?”) answered by HF cardiologists, and NoH, assessed by receiver operating characteristic (ROC) curve analysis. Optimal cut-offs were calculated using Youden’s index (SHFM: <86% predicted 1-year survival; NoH ≥ 2).

Results: Of 535 subjects, 82 (15.3%) had died after 1-year of follow-up. SHFM, SQ, and NoH yielded a similar area under the ROC curve [SHFM: 0.65 (0.60–0.71 95% CI); SQ: 0.58 (0.54–0.63 95% CI); NoH: 0.56 (0.50–0.62 95% CI)] and similar sensitivity [SHFM: 0.76 (0.65–0.84 95% CI); SQ: 0.84 (0.74–0.91 95% CI); NoH: 0.56 (0.45–0.67 95% CI)]. As compared to SHFM, SQ had lower specificity [SQ: 0.33 (0.28–0.37 95% CI) vs. SHFM: 0.55 (0.50–0.60 95% CI)] while NoH had similar specificity [0.56 (0.51–0.61 95% CI)]. SQ combined with NoH showed significantly higher specificity [0.68 (0.64–0.73 95% CI)].

Conclusion: SQ and NoH yielded comparable utility to SHFM for 1-year survival prediction among advanced HF patients, are easy-to-use and could inform bedside decision-making.

Phase transitions are a common phenomenon in condensed matter and act as a critical degree of freedom that can be employed to tailor the mechanical or electronic properties of materials. Understanding the fundamental mechanisms of the thermodynamics and kinetics of phase transitions is, thus, at the core of modern materials design. Conventionally, studies of phase transitions have, to a large extent, focused on pristine bulk phases. However, realistic materials exist in a complex form; their microstructures consist of different point and extended defects. The presence of defects impacts the thermodynamics and kinetics of phase transitions, but has been commonly ignored or treated separately. In recent years, with the significant advances in theoretical and experimental techniques, there has been an increasing research interest in modeling and characterizing how defects impact or even dictate phase transitions. The present review systematically discusses the recent progress in understanding the kinetics of defect-characterized phase transitions, derives the key mechanisms underlying these phase transitions, and envisions the remaining challenges and fruitful research directions. We hope that these discussions and insights will help to inspire future research and development in the field.

Path sampling approaches have become invaluable tools to explore the mechanisms and dynamics of the so-called rare events that are characterized by transitions between metastable states separated by sizable free energy barriers. Their practical application, in particular to ever more complex molecular systems, is, however, not entirely trivial. Focusing on replica exchange transition interface sampling (RETIS) and forward flux sampling (FFS), we discuss a range of analysis tools that can be used to assess the quality and convergence of such simulations, which is crucial to obtain reliable results. The basic ideas of a step-wise evaluation are exemplified for the study of nucleation in several systems with different complexities, providing a general guide for the critical assessment of RETIS and FFS simulations.

Vossian Antonomasia (VA) is a well-known stylistic device based on attributing a certain property to a person by relating them to another person who is famous for this property. Although the morphological and semantic characteristics of this phenomenon have long been the subject of linguistic research, little is known about its distribution. In this paper, we describe end-to-end approaches for detecting and extracting VA expressions from large news corpora in order to study VA more broadly. We present two types of approaches: binary sentence classifiers that detect whether or not a sentence contains a VA expression, and sequence tagging of all parts of a VA on the word level, enabling their extraction. All models are based on neural networks and outperform previous approaches, best results are obtained with a fine-tuned BERT model. Furthermore, we study the impact of training data size and class imbalance by adding negative (and possibly noisy) instances to the training data. We also evaluate the models' performance on out-of-corpus and real-world data and analyze the ability of the sequence tagging model to generalize in terms of new entity types and syntactic patterns.

We present an atomistic study of heterogeneous nucleation in Ni employing transition path sampling, which reveals a template precursor-mediated mechanism of crystallization. Most notably, we find that the ability of tiny templates to modify the structural features of the liquid and promote the formation of precursor regions with enhanced bond-orientational order is key to determining their nucleation efficiency and the polymorphs that crystallize. Our results reveal an intrinsic link between structural liquid heterogeneity and the nucleating ability of templates, which significantly advances our understanding toward the control of nucleation efficiency and polymorph selection.

The two elements, yttrium and holmium, form a geochemical twin pair as their cations possess equivalent ratios of charge to radius. However, despite their equal electrostatics, a subtle difference in their fluoride or chloride affinity is known within solutions. In this work, we investigated whether this affinity gap is also present within the solid phase and how it depends on the surface configuration. We modeled adsorptions onto β-YF3 (waimirite) and isostructural β-HoF3 by periodic density functional theory. To draw conclusions on the affinity toward fluoride and chloride vs. water, adsorbates of HF, HCl, or H2O onto any of the four highly abundant surfaces of (010), (100), (011), and (101) were studied. Among others, the conformational landscape was explored by 200 ps of ab initio molecular dynamics. For stoichiometric surfaces of both MF3, we indeed found stronger adsorptions for HF than HCl. All (hkl)⋅H2O showed slightly stronger adsorption energies for HoF3, while for HF and HCl, the metal preferences varied by the surface. While (100) showed the strongest preference for HoF3, (101) preferred YF3 by the same magnitude.

Marek’s disease virus (MDV), an Alphaherpesvirus belonging to the genus Mardivirus, causes T cell lymphomas in chickens and remains one of the greatest threats to poultry production worldwide. While losses caused by Marek’s disease have been reduced through live-attenuated vaccines, field strains have increased in virulence over recent decades. MDV research has led to a profound understanding of virus-induced pathogenesis and tumor development [1,2,3]. Our goal with this Microorganisms Special Issue on Marek’s disease virus was to collect manuscripts that would provide deeper insights into MDV infection, lytic replication, and latency in vitro and in vivo. Moreover, we assembled reports that provide novel data on pathogenesis, immune system interactions, as well as state-of-the-art concepts to identify approaches to control MDV infections. We were happy to edit seven research articles, three short communications, and a review article on these diverse aspects of MDV infections.

Carbon-based materials doped with metal and nitrogen (M-N-Cs) have promising potential in electrocatalytic applications with the advantage of material sustainability. MN4 motifs incorporated into a carbon lattice are generally known to be responsible for the activity of these materials. While many computational studies assume the tetrapyridinic MN4 motifs, recent studies have elucidated the role of tetrapyrrolic MN4 motifs in electrocatalysis. Using density functional theory, we constructed and compared various structural models to study the incorporation of tetrapyrrolic and tetrapyridinic MN4 motifs in 2D carbon materials and analyzed the type of interactions between each metal species and the N4 site. We further quantified the relative affinity of various metal species to the two types of N4 site. Upon analysis of energies, bond lengths, electronic population and charges, we found that metals that exhibit highly ionic binding characters have a greater affinity towards tetrapyrrolic MN4 motifs compared to species that participate in covalent interactions with the π-system. Furthermore, the binding strength of each species in the N4 site depend on the electronegativity as well as the availability of orbitals for accepting electrons from the π-system.

Acinetobacter baumannii is especially known as a cause of nosocomial infections worldwide. It shows intrinsic and acquired resistances to numerous antimicrobial agents, which can render the treatment difficult. In contrast to the situation in human medicine, there are only few studies focusing on A. baumannii among livestock. In this study, we have examined 643 samples from turkeys reared for meat production, including 250 environmental and 393 diagnostic samples, for the presence of A. baumannii. In total, 99 isolates were identified, confirmed to species level via MALDI-TOF-MS and characterised with pulsed-field gel electrophoresis. Antimicrobial and biocide susceptibility was tested by broth microdilution methods. Based on the results, 26 representative isolates were selected and subjected to whole-genome sequencing (WGS). In general, A. baumannii was detected at a very low prevalence, except for a high prevalence of 79.7% in chick-box-papers (n = 118) of one-day-old turkey chicks. The distributions of the minimal inhibitory concentration values were unimodal for the four biocides and for most of the antimicrobial agents tested. WGS revealed 16 Pasteur and 18 Oxford sequence types, including new ones. Core genome MLST highlighted the diversity of most isolates. In conclusion, the isolates detected were highly diverse and still susceptible to many antimicrobial agents.

Staphylococcus epidermidis has emerged as the most important pathogen in infections related to indwelling medical devices, and although these infections are not life-threatening, their frequency and the fact that they are extremely difficult to treat represent a serious burden on the public health system. Treatment is complicated by specific antibiotic resistance genes and the formation of biofilms. Hence, novel therapeutic strategies are needed to fight these infections. A novel bacteriophage CUB-EPI_14 specific to the bacterial species S. epidermidis was isolated from sewage and characterized genomically and phenotypically. Its genome contains a total of 46,098 bp and 63 predicted genes, among which some have been associated with packaging and lysis-associated proteins, structural proteins, or DNA- and metabolism-associated proteins. No lysogeny-associated proteins or known virulence proteins were identified in the phage genome. CUB-EPI_14 showed stability over a wide range of temperatures (from -20 degrees C to 50 degrees C) and pH values (pH 3-pH 12) and a narrow host range against S. epidermidis. Potent antimicrobial and antibiofilm activities were observed when the phage was tested against a highly susceptible bacterial isolate. These encouraging results open the door to new therapeutic opportunities in the fight against resilient biofilm-associated infections caused by S. epidermidis.

Introduction: Estimates of future disease burden supports public health decision-making. Multistate modeling of chronic diseases is still limited despite a long history of mathematicalmodeling of diseases.We introduce a discrete time approach to the illness- death model and a recursion formula, which can be utilized to project chronic disease burden. We further illustrate an example of the technique applied to anxiety disorders in Germany.

Materials and Equipment: The illness-death model is a multistate model that relates prevalence, incidence, mortality, and remission. A basic recursion formula that considers prevalence, incidence, mortality among the susceptible, and mortality among the diseased can be applied to irreversible chronic diseases such as diabetes. Among several mental disorders, remission plays a key role and thus an extended recursion formula taking remission into account is derived.

Methods: Using the Global Burden of Disease Study 2019 data and population projections from the Federal Statistical Office of Germany, a total number of individuals with anxiety disorders by sex in Germany from 2019 to 2030 was projected. Regression models were fitted to historical data for prevalence and incidence. Differential mortality risks were modeled based on empirical evidence. Remission was estimated from prevalence, incidence, and mortality, applying the extended recursion formula. Sex- and age-specific prevalence of 2019 was given as the initial value to estimate the total number of individuals with anxiety disorders for each year up to 2030. Projections were alsomade through simple extrapolation of prevalence for comparison.

Results: From 2019 to 2030, we estimated a decrease of 52,114 (−1.3%) individuals with anxiety disorders among women, and an increase of 166,870 (+8.5%) cases among men, through the illness-death model approach. With prevalence extrapolation, an increase of 381,770 (+9.7%) among women and an increase of 272,446 (+13.9%) among men were estimated. Discussion: Application of the illness-death model with discrete time steps is possible for both irreversible chronic diseases and diseases with possible remissions, such as anxiety disorders. The technique provides a framework for disease burden prediction. The example provided here can form a basis for running simulations under varying transition probabilities.

Simple Summary: Splenomegaly is a feature of a broad range of diseases including hematological malignancies and non-neoplastic conditions. However, the morphological appearance of an enlarged spleen alone does not necessarily reveal the underlying cause. The application of deep learning could deliver new quantitative imaging biomarkers to identify the underlying etiology of splenomegaly. In this study, a deep learning model was developed to automatically segment and classify splenomegaly in patients with malignant lymphoma versus patients with cirrhotic portal hypertension based on CT images. This model could help identify the underlying disease and triaging malignant cases to ensure timely diagnosis and treatment.

Abstract: Splenomegaly is a common cross-sectional imaging finding with a variety of differential diagnoses. This study aimed to evaluate whether a deep learning model could automatically segment the spleen and identify the cause of splenomegaly in patients with cirrhotic portal hypertension versus patients with lymphoma disease. This retrospective study included 149 patients with splenomegaly on computed tomography (CT) images (77 patients with cirrhotic portal hypertension, 72 patients with lymphoma) who underwent a CT scan between October 2020 and July 2021. The dataset was divided into a training (n = 99), a validation (n = 25) and a test cohort (n = 25). In the first stage, the spleen was automatically segmented using a modified U-Net architecture. In the second stage, the CT images were classified into two groups using a 3D DenseNet to discriminate between the causes of splenomegaly, first using the whole abdominal CT, and second using only the spleen segmentation mask. The classification performances were evaluated using the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). Occlusion sensitivity maps were applied to the whole abdominal CT images, to illustrate which regions were important for the prediction. When trained on the whole abdominal CT volume, the DenseNet was able to differentiate between the lymphoma and liver cirrhosis in the test cohort with an AUC of 0.88 and an ACC of 0.88. When the model was trained on the spleen segmentation mask, the performance decreased (AUC = 0.81, ACC = 0.76). Our model was able to accurately segment splenomegaly and recognize the underlying cause. Training on whole abdomen scans outperformed training using the segmentation mask. Nonetheless, considering the performance, a broader and more general application to differentiate other causes for splenomegaly is also conceivable.

Simple Summary: Colorectal cancer (CRC) belongs to the top three most common malignancies and is one of the deadliest cancers worldwide. Advancements in the understanding of CRC pathophysiology can lead to the development of novel treatments preventing cancer progression while prolonging overall survival. Numerous studies have shown a role for the biological clock in the regulation of cancer hallmarks and in CRC. However, the mechanistic link between the circadian clock and CRC progression is not fully understood. In the current study, we aimed to investigate the effects of a genetically disrupted clock on cancer properties using different CRC cell lines, with a focus on metastasis-related components. Our results demonstrate a reciprocal interplay between the circadian clock and the metastasis associated gene MACC1 (metastasis-associated in colon cancer 1), pointing to the circadian clock-regulation of CRC invasiveness. A circadian MACC1 expression, as shown by our data, may be considered to optimize MACC1-targeted CRC treatment.

Abstract: The circadian clock coordinates the timing of several cellular processes including transcription, the cell cycle, and metabolism. Disruptions in the clock machinery trigger the abnormal regulation of cancer hallmarks, impair cellular homeostasis, and stimulate tumourigenesis. Here we investigated the role of a disrupted clock by knocking out or knocking down the core-clock (CC) genes ARNTL, PER2 or NR1D1 in cancer progression (e.g., cell proliferation and invasion) using colorectal cancer (CRC) cell lines HCT116, SW480 and SW620, from different progression stages with distinct clock phenotypes, and identified mechanistic links from the clock to altered cancer-promoting cellular properties. We identified MACC1 (metastasis-associated in colon cancer 1), a known driver for metastasis and an EMT (epithelial-to-mesenchymal transition)-related gene, to be significantly differentially expressed in CC manipulated cells and analysed the effect of MACC1 manipulation (knockout or overexpression) in terms of circadian clock phenotype as well as cancer progression. Our data points to a bi-directional MACC1-circadian clock interplay in CRC, via CC genes. In particular, knocking out MACC1 reduced the period of oscillations, while its overexpression increased it. Interestingly, we found the MACC1 protein to be circadian expressed in HCT116 WT cells, which was disrupted after the knockout of CC genes, and identified a MACC1-NR1D1 protein-protein interaction. In addition, MACC1 manipulation and CC knockout altered cell invasion properties of HCT116 cells, pointing to a regulation of clock and cancer progression in CRC, possibly via the interaction of MACC1 with core-clock genes.

Simple Summary: All fields of healthcare were adversely affected by the COVID-19 pandemic. In this study, we sought to understand the effects of COVID-19 on hospitalizations for intracranial meningioma resection using a large database. We compared hospitalization rates as well as hospital outcomes such as Clavien-Dindo grade IV complications, in-hospital mortality, and prolonged length of stay for intracranial meningioma resection during 2019 and 2020. Our findings showed that though hospitalization rates decreased slightly during the COVID-19 pandemic, hospital outcomes were not adversely affected. The findings of our study show that with adequate planning and preparations, better hospital outcomes could be sustained even during healthcare emergencies such as COVID-19 pandemic. Our findings assure that neurosurgery practice in the US ensured the best quality of care to their patients even during COVID-19 pandemic.

Abstract: Purpose: To assess the effects of COVID-19 on hospitalizations for intracranial meningioma resection using a large database.

Methods: We conducted a retrospective analysis of the California State Inpatient Database (SID) 2019 and 2020. All adult (18 years or older) hospitalizations were included for the analysis. The primary outcomes were trends in hospitalization for intracranial meningioma resection between 2019 and 2020. Secondary outcomes were Clavien-Dindo grade IV complications, in-hospital mortality, and prolonged length of stay, which was defined as length of stay >= 75 percentile.

Results: There were 3,173,333 and 2,866,161 hospitalizations in 2019 and 2020, respectively (relative decrease, 9.7%), of which 921 and 788 underwent intracranial meningioma resection (relative decrease, 14.4%). In 2020, there were 94,114 admissions for COVID-19 treatment. Logistic regression analysis showed that year in which intracranial meningioma resection was performed did not show significant association with Clavien-Dindo grade IV complications and in-hospital mortality (OR, 1.23, 95% CI: 0.78-1.94) and prolonged length of stay (OR, 1.05, 95% CI: 0.84-1.32).

Conclusion: Our findings show that neurosurgery practice in the US successfully adapted to the unforeseen challenges posed by COVD-19 and ensured the best quality of care to the patients.

Simple Summary: For patients undergoing multimodal treatment for colorectal liver metastases (CLM), the development of sinusoidal obstruction syndrome (SOS) as a side effect of oxaliplatin-based chemotherapy may endanger the prospects after liver resection. In this study, we aimed to investigate possible protective effects of an additional preoperative inhibition of vascular endothelial growth factor (VEGF) on the occurrence of SOS and its implications on liver function and regeneration after liver resection. After successful establishment of a novel murine model of SOS, we were able to show a reduced incidence of SOS after additive treatment with a VEGF inhibitor. Changes in the VEGF pathway, namely in the expression of VEGF receptor-2 (VEGF-R2), may be responsible for these findings. By preventing the incidence of SOS, the inhibition of VEGF may help to reduce morbidity after liver resection for patients with CLM. Further clinical studies are needed to corroborate our results.

Abstract: (1) Background: Sinusoidal obstruction syndrome (SOS) after oxaliplatin-based chemotherapy is associated with unfavorable outcomes after partial hepatectomy for colorectal liver metastases (CLM). Bevacizumab, a monoclonal antibody against vascular endothelial growth factor (VEGF), may prevent SOS development. We investigated the impact of VEGF-inhibition on the development of SOS in a murine model.

(2) Methods: Male wild-type and CD39-null mice received oxaliplatin, additional anti-VEGF (OxAV), or controls, and were sacrificed or subjected to major partial hepatectomy (MH). Specimen were used for histological analysis of SOS. Liver damage was assessed by plasma transaminases. The VEGF pathway was elucidated by quantitative PCR of liver tissue and protein analysis of plasma.

(3) Results: Mice treated with oxaliplatin developed SOS. Concomitant anti-VEGF facilitated a reduced incidence of SOS, but not in CD39-null mice. SOS was associated with increased plasma VEGF-A and decreased hepatocyte growth factor (HGF). After OxAV treatment, VEGF-R2 was upregulated in wild-type but downregulated in CD39-null mice. Oxaliplatin alone was associated with higher liver damage after MH than in mice with concomitant VEGF-inhibition.

(4) Conclusions: We established a murine model of oxaliplatin-induced SOS and provided novel evidence on the protective effect of VEGF-inhibition against the development of SOS that may be associated with changes in the pathway of VEGF and its receptor VEGF-R2.

Simple Summary: Oncological follow-up after liver transplantation for cholangiocellular carcinoma must consider the risk of recurrence. Immunosuppressive medication with so-called mTOR inhibitors seems to have a tumor-suppressive effect, as improved survival has been shown under this medication for patients with recurrent hepatocellular carcinoma after liver transplantation. The aim of our study was to investigate recurrence and survival in relation to tumor type and type of immunosuppression for cholangiocellular carcinoma after liver transplantation. The time from liver transplantation to recurrence and survival after cancer recurrence were endpoints of the study. Significant improvement in survival for recurrent cholangiocellular carcinoma was seen after surgical resection and reduction in immunosuppression, while N1 status at transplantation and histological Grading >1 were associated with worse outcomes.

Abstract: Liver transplantation (LT) for cholangiocarcinoma (CCA), or biliary tract cancer (BTC), remains controversial regarding high recurrence rates and poor prognosis. Oncological follow-up may benefit from tumor-inhibiting properties of mTOR inhibitors (mTORI), shown with improved survival for recurrent hepatocellular carcinoma (HCC) patients after LT. The aim of this study was to investigate the recurrence and survival in relation to tumor type and type of immunosuppression (IS). LT patients with CCA or mixed HCC/CCA (mHCC/CCA) (n = 67) were retrospectively analyzed. Endpoints were the time from LT to recurrence (n = 44) and survival after recurrence. Statistically significant impairment in survival for recurrent CCA (rCCA) was shown in patients not eligible for surgical resection (HR 2.46 (CI: 1.2-5.1; p = 0.02). Histological proven grading >1 and N1 status at initial transplantation were associated with impaired survival (HR 0.13 (CI: 0.03-0.58); p < 0.01 and HR 3.4 (CI: 1.0-11.65); p = 0.05). Reduced IS after tumor recurrence improved survival (HR 4.2/CI: 1.3-13.6; p = 0.02). MTORI initiation before recurrence or after had no significant impact on survival. Our data thereby indicate, similar to findings in recurrent HCC after LT, that patients with rCCA after LT benefit from a reduction in IS upon recurrence.

Simple Summary: Detection of circulating tumor cells (CTCs) in blood can be used to diagnose cancer or monitor treatment response for various cancers. However, these cells are rare in the bloodstream in the early stages of cancers, and it, therefore, remains a technical challenge to isolate them. To overcome the limitations of a blood draw, we introduce a minimally invasive device, called the BMProbe (TM), for the isolation of CTCs directly from the bloodstream. Thereby a large volume of blood is screened. This study first shows how the geometry of the in vivo BMProbe (TM) causes improved cell deposition conditions. We then performed a verification of the in vivo device using blood samples from lung cancer patients. The results indicate the functionality of the BMProbe (TM) to isolate CTCs in blood samples. The future step is to use the BMProbe (TM) in various types of cancer patients to detect CTCs.

Abstract: Circulating tumor cells (CTCs) exist in low quantities in the bloodstream in the early stages of cancers. It, therefore, remains a technical challenge to isolate them in large enough quantities for a precise diagnosis and downstream analysis. We introduce the BMProbe (TM), a minimally invasive device that isolates CTCs during a 30-minute incubation in the median cubital vein. The optimized geometry of the device creates flow conditions for improved cell deposition. The CTCs are isolated using antibodies that are bound to the surface of the BMProbe (TM). In this study, flow experiments using cell culture cells were conducted. They indicate a 31 times greater cell binding efficiency of the BMProbe (TM) compared to a flat geometry. Further, the functionality of isolating CTCs from patient blood was verified in a small ex vivo study that compared the cell count from seven non-small-cell lung carcinoma (NSCLC) patients compared to nine healthy controls with 10 mL blood samples. The median cell count was 1 in NSCLC patients and 0 in healthy controls. In conclusion, the BMProbe (TM) is a promising method to isolate CTCs in large quantities directly from the venous bloodstream without removing blood from a patient. The future step is to verify the functionality in vivo.