Risk SNP-Mediated Promoter-Enhancer Switching Drives Prostate Cancer through lncRNA PCAT19.

The prostate cancer (PCa) risk-associated SNP rs11672691 is positively associated with aggressive disease at diagnosis. We showed that rs11672691 maps to the promoter of a short isoform of long noncoding RNA PCAT19 (PCAT19-short), which is in the third intron of the long isoform (PCAT19-long). The risk variant is associated with decreased and increased levels of PCAT19-short and PCAT19-long, respectively. Mechanistically, the risk SNP region is bifunctional with both promoter and enhancer activity. The risk variants of rs11672691 and its LD SNP rs887391 decrease binding of transcription factors NKX3.1 and YY1 to the promoter of PCAT19-short, resulting in weaker promoter but stronger enhancer activity that subsequently activates PCAT19-long. PCAT19-long interacts with HNRNPAB to activate a subset of cell-cycle genes associated with PCa progression, thereby promoting PCa tumor growth and metastasis. Taken together, these findings reveal a risk SNP-mediated promoter-enhancer switching mechanism underlying both initiation and progression of aggressive PCa.

Development and Validation of a Protein Risk Score for Mortality in Heart Failure : A Community Cohort Study.

BACKGROUND: Heart failure (HF) is a complex clinical syndrome with high mortality. Current risk stratification approaches lack precision. High-throughput proteomics could improve risk prediction. Its use in clinical practice to guide the management of patients with HF depends on validation and evidence of clinical benefit. OBJECTIVE: To develop and validate a protein risk score for mortality in patients with HF. DESIGN: Community-based cohort. SETTING: Southeast Minnesota. PARTICIPANTS: Patients with HF enrolled between 2003 and 2012 and followed through 2021. MEASUREMENTS: A total of 7289 plasma proteins in 1351 patients with HF were measured using the SomaScan Assay (SomaLogic). A protein risk score was derived using least absolute shrinkage and selection operator regression and temporal validation in patients enrolled between 2003 and 2007 (development cohort) and 2008 and 2012 (validation cohort). Multivariable Cox regression was used to examine the association between the protein risk score and mortality. The performance of the protein risk score to predict 5-year mortality risk was assessed using calibration plots, decision curves, and relative utility analyses and compared with a clinical model, including the Meta-Analysis Global Group in Chronic Heart Failure mortality risk score and N-terminal pro-B-type natriuretic peptide. RESULTS: The development (n = 855; median age, 78 years; 50% women; 29% with ejection fraction <40%) and validation cohorts (n = 496; median age, 76 years; 45% women; 33% with ejection fraction <40%) were mostly similar. In the development cohort, 38 unique proteins were selected for the protein risk score. Independent of ejection fraction, the protein risk score demonstrated good calibration, reclassified mortality risk particularly at the extremes of the risk distribution, and showed greater clinical utility compared with the clinical model. LIMITATION: Participants were predominantly of European ancestry, potentially limiting the generalizability of the findings to different patient populations. CONCLUSION: Validation of the protein risk score demonstrated good calibration and evidence of predicted benefits to stratify the risk for death in HF superior to that of clinical methods. Further studies are needed to prospectively evaluate the score's performance in diverse populations and determine risk thresholds for interventions. PRIMARY FUNDING SOURCE: Division of Intramural Research at the National Heart, Lung, and Blood Institute of the National Institutes of Health.

ACE2 and TMPRSS2 SARS-CoV-2 infectivity genes: deep mutational scanning and characterization of missense variants.

The human angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) proteins play key roles in the cellular internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the coronavirus responsible for the coronavirus disease of 2019 (COVID-19) pandemic. We set out to functionally characterize the ACE2 and TMPRSS2 protein abundance for variant alleles encoding these proteins that contained non-synonymous single-nucleotide polymorphisms (nsSNPs) in their open reading frames (ORFs). Specifically, a high-throughput assay, deep mutational scanning (DMS), was employed to test the functional implications of nsSNPs, which are variants of uncertain significance in these two genes. Specifically, we used a 'landing pad' system designed to quantify the protein expression for 433 nsSNPs that have been observed in the ACE2 and TMPRSS2 ORFs and found that 8 of 127 ACE2, 19 of 157 TMPRSS2 isoform 1 and 13 of 149 TMPRSS2 isoform 2 variant proteins displayed less than ~25% of the wild-type protein expression, whereas 4 ACE2 variants displayed 25% or greater increases in protein expression. As a result, we concluded that nsSNPs in genes encoding ACE2 and TMPRSS2 might potentially influence SARS-CoV-2 infectivity. These results can now be applied to DNA sequence data for patients infected with SARS-CoV-2 to determine the possible impact of patient-based DNA sequence variation on the clinical course of SARS-CoV-2 infection.

Exploring the single-cell immune landscape of kidney allograft inflammation using imaging mass cytometry.

Kidney allograft inflammation, mostly attributed to rejection and infection, is an important cause of graft injury and loss. Standard histopathological assessment of allograft inflammation provides limited insights into biological processes and the immune landscape. Here, using imaging mass cytometry with a panel of 28 validated biomarkers, we explored the single-cell landscape of kidney allograft inflammation in 32 kidney transplant biopsies and 247 high-dimensional histopathology images of various phenotypes of allograft inflammation (antibody-mediated rejection, T cell-mediated rejection, BK nephropathy, and chronic pyelonephritis). Using novel analytical tools, for cell segmentation, we segmented over 900 000 cells and developed a tissue-based classifier using over 3000 manually annotated kidney microstructures (glomeruli, tubules, interstitium, and arteries). Using PhenoGraph, we identified 11 immune and 9 nonimmune clusters and found a high prevalence of memory T cell and macrophage-enriched immune populations across phenotypes. Additionally, we trained a machine learning classifier to identify spatial biomarkers that could discriminate between the different allograft inflammatory phenotypes. Further validation of imaging mass cytometry in larger cohorts and with more biomarkers will likely help interrogate kidney allograft inflammation in more depth than has been possible to date.

Mendelian randomization in hepatology: A review of principles, opportunities, and challenges.

Mendelian randomization has become a popular tool to assess causal relationships using existing observational data. While randomized controlled trials are considered the gold standard for establishing causality between exposures and outcomes, it is not always feasible to conduct a trial. Mendelian randomization is a causal inference method that uses observational data to infer causal relationships by using genetic variation as a surrogate for the exposure of interest. Publications using the approach have increased dramatically in recent years, including in the field of hepatology. In this concise review, we describe the concepts, assumptions, and interpretation of Mendelian randomization as related to studies in hepatology. We focus on the strengths and weaknesses of the approach for a non-statistical audience, using an illustrative example to assess the causal relationship between body mass index and NAFLD.

Using absorbance detection for hs-SV-AUC characterization of adeno-associated virus.

Data are presented demonstrating that absorbance detection can be used during high-speed sedimentation velocity analytical ultracentrifugation (hs-SV-AUC) experiments to characterize the size distribution of adeno-associated virus (AAV) drug products accurately. Advantages and limitations of being able to use this detector in this specific type of SV-AUC experiment are discussed.

Rapid high-resolution size distribution protocol for adeno-associated virus using high speed SV-AUC.

Simulated SV-AUC data for an adeno-associated virus (AAV) sample consisting of four components having closely spaced sedimentation coefficients were used to develop a high-speed protocol that optimized the size distribution analysis resolution. The resulting high speed (45K rpm) SV-AUC (hs-SV-AUC) protocol poses several experimental challenges: 1) the need for rapid data acquisition, 2) increased potential for optical artifacts from steep and fast moving boundaries and 3) the increased potential for convection. To overcome these challenges the protocol uses interference detection at low temperatures and data that are confined to a limited radial-time window. In addition to providing higher resolution AAV SV-AUC data and very short run times (<20 min after temperature equilibration), the need to match the sample and reference solvent composition and meniscus positions is relaxed making interference detection as simple to employ as absorbance detection. Finally, experimental data comparing hs-SV-AUC (at 45K rpm) with standard low-speed (15K rpm) SV-AUC on the same AAV sample demonstrate the size distribution resolution improvement. These experiments also validate the use of a radial-time window and show how quickly data can be acquired using the hs-SV-AUC protocol.

Tranexamic Acid Use in the Surgical Arena: A Narrative Review.

INTRODUCTION: Tranexamic acid (TXA) is a potent antifibrinolytic drug that inhibits the activation of plasmin by plasminogen. While not a new medication, TXA has quickly gained traction across a variety of surgical subspecialties to prevent and treat bleeding. Knowledge on the use of this drug is essential for the modern surgeon to continue to provide excellent care to their patients. METHODS: A comprehensive review of the PubMed database was conducted of articles published within the last 10 y (2014-2024) relating to TXA and its use in various surgical subspecialties. Seminal studies regarding the use of TXA older than 10 y were included from the author's archives. RESULTS: Indications for TXA are not limited to trauma alone, and TXA is utilized across a variety of surgical subspecialties from neurosurgery to hepatic surgery to control hemorrhage. Overall, TXA is well tolerated with common dose-dependent adverse effects, including headache, nasal symptoms, dizziness, nausea, diarrhea, and fatigue. More severe adverse events are rare and easily mitigated by not exceeding a dose of 50 mg/kg. CONCLUSIONS: The administration of TXA as an adjunct to treat trauma saves lives. The ability of TXA to induce seizures is dose dependent with identifiable risk factors, making this serious adverse effect predictable. As for the potential for TXA to cause thrombotic events, uncertainty remains. If this association is proven to be real, the risk will likely be small, since the use of TXA is still advantageous in most situations because of its efficacy for a more common concern, bleeding.

From genome-wide associations to candidate causal variants by statistical fine-mapping.

Advancing from statistical associations of complex traits with genetic markers to understanding the functional genetic variants that influence traits is often a complex process. Fine-mapping can select and prioritize genetic variants for further study, yet the multitude of analytical strategies and study designs makes it challenging to choose an optimal approach. We review the strengths and weaknesses of different fine-mapping approaches, emphasizing the main factors that affect performance. Topics include interpreting results from genome-wide association studies (GWAS), the role of linkage disequilibrium, statistical fine-mapping approaches, trans-ethnic studies, genomic annotation and data integration, and other analysis and design issues.

A Guide to the Use of Vasopressors and Inotropes for Patients in Shock.

Shock is a life-threatening circulatory failure that results in inadequate tissue perfusion and oxygenation. Vasopressors and inotropes are vasoactive medications that are vital in increasing systemic vascular resistance and cardiac contractility, respectively, in patients presenting with shock. To be well versed in using these agents is an important skill to have in the critical care setting where patients can frequently exhibit symptoms of shock. In this review, we will discuss the pathophysiological mechanisms of shock and evaluate the current evidence behind the management of shock with an emphasis on vasopressors and inotropes.

The clinical impact of estimating low-density lipoprotein cholesterol (LDL-C) using different equations in the general population.

BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) is associated with atherosclerotic cardiovascular disease (ASCVD). Friedewald, Sampson, and Martin-Hopkins equations are used to calculate LDL-C. This study compares the impact of switching between these equations in a large geographically defined population. MATERIALS AND METHODS: Data for individuals who had a lipid panel ordered clinically between 2010 and 2019 were included. Comparisons were made across groups using the two-sample t-test or chi-square test as appropriate. Discordances between LDL measures based on clinically actionable thresholds were summarized using contingency tables. RESULTS: The cohort included 198,166 patients (mean age 54 years, 54% female). The equations perform similarly at the lower range of triglycerides but began to diverge at a triglyceride level of 125 mg/dL. However, at triglycerides of 175 mg/dL and higher, the Martin-Hopkins equation estimated higher LDL-C values than the Samson equation. This discordance was further exasperated at triglyceride values of 400 to 800 mg/dL. When comparing the Sampson and Friedewald equations, at triglycerides are below 175 mg/dL, 9% of patients were discordant at the 70 mg/dL cutpoint, whereas 42.4% were discordant when triglycerides are between 175 and 400 mg/dL. Discordance was observed at the clinically actionable LDL-C cutpoint of 190 mg/dL with the Friedewald equation estimating lower LDL-C than the other equations. In a high-risk subgroup (ASCVD risk score > 20%), 16.3% of patients were discordant at the clinical cutpoint of LDL-C < 70 mg/dL between the Sampson and Friedewald equations. CONCLUSIONS: Discordance at clinically significant LDL-C cutpoints in both the general population and high-risk subgroups were observed across the three equations. These results show that using different methods of LDL-C calculation or switching between different methods could have clinical implications for many patients.

So You Want to Do Trauma Research? A Practical Guide to Creating a Research Program at Your Home Institution.

BACKGROUND: There are 3 pillars upon which the foundation of a teaching program in health care is founded: research, education, and clinical care. However, in a busy academic trauma practice, the unfortunate reality is that research is often a low priority in the frenzy of mandates for clinical productivity. OBJECTIVE: The purpose of this report is to advise hospitals on how to create a modest trauma research program that supports research interests without significantly impacting the overall clinical productivity of the department. METHODS: Relevant literature related to the development of an academic trauma research department was reviewed. Relevant articles were then compared to this manuscript to assess the novelty of the topic. RESULTS: There are 4 essential components of a trauma research program: (1) a zealot, (2) institutional commitment and support, (3) a statistician, and (4) registry data access. CONCLUSION: The creation of a trauma research program may seem like a herculean effort, but this work is necessary for institutions hoping to achieve status as a Level I/II trauma center. Following the steps outlined in this report, trauma providers can create a robust research program at their institution without sacrificing clinical productivity.

Noninvasive prediction of axillary lymph node breast cancer metastasis using morphometric analysis of nodal tumor microvessels in a contrast-free ultrasound approach.

PURPOSE: Changes in microcirculation of axillary lymph nodes (ALNs) may indicate metastasis. Reliable noninvasive imaging technique to quantify such variations is lacking. We aim to develop and investigate a contrast-free ultrasound quantitative microvasculature imaging technique for detection of metastatic ALN in vivo. EXPERIMENTAL DESIGN: The proposed ultrasound-based technique, high-definition microvasculature imaging (HDMI) provides superb images of tumor microvasculature at sub-millimeter size scales and enables quantitative analysis of microvessels structures. We evaluated the new HDMI technique on 68 breast cancer patients with ultrasound-identified suspicious ipsilateral axillary lymph nodes recommended for fine needle aspiration biopsy (FNAB). HDMI was conducted before the FNAB and vessel morphological features were extracted, analyzed, and the results were correlated with the histopathology. RESULTS: Out of 15 evaluated quantitative HDMI biomarkers, 11 were significantly different in metastatic and reactive ALNs (10 with P << 0.01 and one with 0.01 < P < 0.05). We further showed that through analysis of these biomarkers, a predictive model trained on HDMI biomarkers combined with clinical information (i.e., age, node size, cortical thickness, and BI-RADS score) could identify metastatic lymph nodes with an area under the curve of 0.9 (95% CI [0.82,0.98]), sensitivity of 90%, and specificity of 88%. CONCLUSIONS: The promising results of our morphometric analysis of HDMI on ALNs offer a new means of detecting lymph node metastasis when used as a complementary imaging tool to conventional ultrasound. The fact that it does not require injection of contrast agents simplifies its use in routine clinical practice.

Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis.

BACKGROUND & AIMS: Our purpose was to detect pancreatic ductal adenocarcinoma (PDAC) at the prediagnostic stage (3-36 months before clinical diagnosis) using radiomics-based machine-learning (ML) models, and to compare performance against radiologists in a case-control study. METHODS: Volumetric pancreas segmentation was performed on prediagnostic computed tomography scans (CTs) (median interval between CT and PDAC diagnosis: 398 days) of 155 patients and an age-matched cohort of 265 subjects with normal pancreas. A total of 88 first-order and gray-level radiomic features were extracted and 34 features were selected through the least absolute shrinkage and selection operator-based feature selection method. The dataset was randomly divided into training (292 CTs: 110 prediagnostic and 182 controls) and test subsets (128 CTs: 45 prediagnostic and 83 controls). Four ML classifiers, k-nearest neighbor (KNN), support vector machine (SVM), random forest (RM), and extreme gradient boosting (XGBoost), were evaluated. Specificity of model with highest accuracy was further validated on an independent internal dataset (n = 176) and the public National Institutes of Health dataset (n = 80). Two radiologists (R4 and R5) independently evaluated the pancreas on a 5-point diagnostic scale. RESULTS: Median (range) time between prediagnostic CTs of the test subset and PDAC diagnosis was 386 (97-1092) days. SVM had the highest sensitivity (mean; 95% confidence interval) (95.5; 85.5-100.0), specificity (90.3; 84.3-91.5), F1-score (89.5; 82.3-91.7), area under the curve (AUC) (0.98; 0.94-0.98), and accuracy (92.2%; 86.7-93.7) for classification of CTs into prediagnostic versus normal. All 3 other ML models, KNN, RF, and XGBoost, had comparable AUCs (0.95, 0.95, and 0.96, respectively). The high specificity of SVM was generalizable to both the independent internal (92.6%) and the National Institutes of Health dataset (96.2%). In contrast, interreader radiologist agreement was only fair (Cohen's kappa 0.3) and their mean AUC (0.66; 0.46-0.86) was lower than each of the 4 ML models (AUCs: 0.95-0.98) (P < .001). Radiologists also recorded false positive indirect findings of PDAC in control subjects (n = 83) (7% R4, 18% R5). CONCLUSIONS: Radiomics-based ML models can detect PDAC from normal pancreas when it is beyond human interrogation capability at a substantial lead time before clinical diagnosis. Prospective validation and integration of such models with complementary fluid-based biomarkers has the potential for PDAC detection at a stage when surgical cure is a possibility.

Increasing the Resolution of Field-Flow Fractionation with Increasing Crossflow Gradients.

The resolution of flow field-flow fractionation (flow FFF) depends primarily on the crossflow rate and its change over time. In this work, we demonstrate a method for modulation of the crossflow rate during separation that increases the peak-to-peak resolution of the resulting fractograms. In classical FFF methods, the crossflow rate is either maintained constant or decreased during the separation of the different species. In this work, higher resolution between peaks was achieved by a novel gradient method in which the crossflow is increased briefly during separation to allow stronger retention of the later eluting peaks. We first outline the theoretical basis by which improved separation is achieved. We confirm our hypothesis by quantifying the impact of increasing crossflow on the resolution between a monoclonal antibody monomer and its high-molecular-weight aggregate. We then demonstrate that this method is applicable to two different FFF methods (AF4 and HF5) and various pharmaceutically relevant samples (monoclonal antibodies and adeno-associated viruses). Finally, we hypothesize that increasing the force perpendicular to the laminar flow as described here is broadly applicable to all FFF methods and improves the quality of FFF-based separations.

Photon-counting Detector CT with Deep Learning Noise Reduction to Detect Multiple Myeloma.

Background Photon-counting detector (PCD) CT and deep learning noise reduction may improve spatial resolution at lower radiation doses compared with energy-integrating detector (EID) CT. Purpose To demonstrate the diagnostic impact of improved spatial resolution in whole-body low-dose CT scans for viewing multiple myeloma by using PCD CT with deep learning denoising compared with conventional EID CT. Materials and Methods Between April and July 2021, adult participants who underwent a whole-body EID CT scan were prospectively enrolled and scanned with a PCD CT system in ultra-high-resolution mode at matched radiation dose (8 mSv for an average adult) at an academic medical center. EID CT and PCD CT images were reconstructed with Br44 and Br64 kernels at 2-mm section thickness. PCD CT images were also reconstructed with Br44 and Br76 kernels at 0.6-mm section thickness. The thinner PCD CT images were denoised by using a convolutional neural network. Image quality was objectively quantified in two phantoms and a randomly selected subset of participants (10 participants; median age, 63.5 years; five men). Two radiologists scored PCD CT images relative to EID CT by using a five-point Likert scale to detect findings reflecting multiple myeloma. The scoring for the matched reconstruction series was blinded to scanner type. Reader-averaged scores were tested with the null hypothesis of equivalent visualization between EID and PCD. Results Twenty-seven participants (median age, 68 years; IQR, 61-72 years; 16 men) were included. The blinded assessment of 2-mm images demonstrated improvement in viewing lytic lesions, intramedullary lesions, fatty metamorphosis, and pathologic fractures for PCD CT versus EID CT (P < .05 for all comparisons). The 0.6-mm PCD CT images with convolutional neural network denoising also demonstrated improvement in viewing all four pathologic abnormalities and detected one or more lytic lesions in 21 of 27 participants compared with the 2-mm EID CT images (P < .001). Conclusion Ultra-high-resolution photon-counting detector CT improved the visibility of multiple myeloma lesions relative to energy-integrating detector CT. © RSNA, 2022 Online supplemental material is available for this article.

Missense Genetic Variation of ICAM1 and Incident Heart Failure.

BACKGROUND: Intercellular adhesion molecule-1 (ICAM-1) is a cell surface protein that participates in endothelial activation and is hypothesized to play a central role in heart failure (HF). We evaluated associations of ICAM1 missense genetic variants with circulating ICAM-1 levels and with incident HF. METHODS AND RESULTS: We identified 3 missense variants within ICAM1 (rs5491, rs5498 and rs1799969) and evaluated their associations with ICAM-1 levels in the Coronary Artery Risk Development in Young Adults Study and the Multi-Ethnic Study of Atherosclerosis (MESA). We determined the association among these 3 variants and incident HF in MESA. We separately evaluated significant associations in the Atherosclerosis Risk in Communities (ARIC) study. Of the 3 missense variants, rs5491 was common in Black participants (minor allele frequency [MAF] > 20%) and rare in other race/ethnic groups (MAF < 5%). In Black participants, the presence of rs5491 was associated with higher levels of circulating ICAM-1 at 2 timepoints separated by 8 years. Among Black participants in MESA (n = 1600), the presence of rs5491 was associated with an increased risk of incident HF with preserved ejection fraction (HFpEF; HR = 2.30; [95% CI 1.25-4.21; P = 0.007]). The other ICAM1 missense variants (rs5498 and rs1799969) were associated with ICAM-1 levels, but there were no associations with HF. In ARIC, rs5491 was significantly associated with incident HF (HR = 1.24 [95% CI 1.02 - 1.51]; P = 0.03), with a similar direction of effect for HFpEF that was not statistically significant. CONCLUSIONS: A common ICAM1 missense variant among Black individuals may be associated with increased risk of HF, which may be HFpEF-specific.

Establishing stereochemical comparability in phosphorothioate oligonucleotides with nuclease P1 digestion coupled with LCMS analysis.

Stereochemical comparability is critical for ensuring manufacturing consistency in therapeutic phosphorothioate oligonucleotides. Currently, analytical methods for this assessment are limited. We hereby report on a novel protocol capable of detecting a stereochemistry change in a single phosphorothioate linkage by employing nuclease P1 digestion of the oligonucleotide with subsequent LCMS analysis of the resulting fragments. The method proves valuable for establishing stereochemical comparability and for ensuring manufacturing consistency of oligonucleotide therapeutics.

Factors Associated With Ultrasound Color Doppler Twinkling by Breast Biopsy Markers: In Vitro and Ex Vivo Evaluation of 35 Commercially Available Markers.

BACKGROUND. Targeted axillary lymph node dissection after neoadjuvant systemic therapy (NST) for breast cancer depends on identifying marked metastatic lymph nodes. However, ultrasound visualization of biopsy markers is challenging. OBJECTIVE. The purpose of our study was to identify biopsy markers that show actionable twinkling in cadaveric breast and to assess the association of actionable twinkling with markers' surface roughness. METHODS. Commercial breast biopsy markers were evaluated for twinkling artifact in various experimental conditions relating to scanning medium (solid gel phantom, ultrasound coupling gel, cadaveric breast), transducer (ML6-15, 9L, C1-6), and embedding material (present vs absent). Markers were assigned twinkling scores from 0 (confident in no twinkling) to 4 (confident in exuberant twinkling); a score of 3 or greater represented actionable twinkling (sufficient confidence to rely solely on twinkling for target localization). Markers were hierarchically advanced to evaluation with increasingly complex media if showing at least minimal twinkling for a given medium. A 3D coherence optical profiler measured marker surface roughness. Mixed-effects proportional odds regression models assessed associations between twinkling scores and transducer and embedding material; Wilcoxon rank sum test evaluated associations between actionable twinkling and surface roughness. RESULTS. Thirty-five markers (21 with embedding material) were evaluated. Ten markers without embedding material advanced to evaluation in cadaveric breast. Higher twinkling scores were associated with presence of embedding material (odds ratio [OR] = 5.05 in solid gel phantom, 9.84 in coupling gel) and transducer (using the C1-6 transducer as reference; 9L transducer: OR = 0.36, 0.83, and 0.04 in solid gel phantom, ultrasound coupling gel, and cadaveric breast; ML6-15 transducer: OR = 0.07, 0.18, and 0.00 respectively; post hoc p between 9L and ML6-15: p < .001, p = .02, and p = .04). In cadaveric breast, three markers (Cork, Professional Q, MRI [Flex]) exhibited actionable twinkling for two or more transducers; surface roughness was significantly higher for markers with than without actionable twinkling for C1-6 (median values: 0.97 vs 0.35, p = .02) and 9L (1.75 vs 0.36; p = .002) transducers. CONCLUSION. Certain breast biopsy markers exhibited actionable twinkling in cadaveric breast. Twinkling was observed with greater confidence for the C1-6 and 9L transducers than the ML6-15 transducer. Actionable twinkling was associated with higher marker surface roughness. CLINICAL IMPACT. Use of twinkling for marker detection could impact preoperative or intraoperative localization after NST.

Comprehensive Review of Current Pain Management in Rib Fractures With Practical Guidelines for Clinicians.

Rib fractures are present in 15% of all traumas and 60% of patients with chest traumas. Rib fractures are not life-threatening in isolation, but they can be quite painful which leads to splinting and compromise of respiratory function. Splinting limits the ability of a patient to take a deep breath, which leads to atelectasis, atelectasis to poor secretion removal, and poor secretion removal leads to pneumonia. Pneumonia is the common pathway to respiratory failure in patients with rib fractures. It is noted that in the elderly, each rib fracture increases developing pneumonia by 27% and the risk of dying by 19%. From a public health perspective, rib fractures have long-term implications with only 59% of patients returning to work at 6 months. In this review we will examine the state of art as it currently exists with regard to the management of pain associated with rib fractures. Included in this overview will be a brief review of the anatomy of the thorax and some important physiologic concepts, the latest trends in pharmacologic and noninvasive means of managing rib pain, a special section on epidural anesthesia, some other alternative invasive methods of pain control, and a review of the recent literature on rib plating. Finally, a practical, easy to follow guideline, to manage the patient with pain from rib fractures will be presented.