RNASeq Analysis for Accurate Identification of Fusion Partners in Tumor Specific Translocations Detected by Standard FISH Probes in Hematologic Malignancies.

Background: Fluorescence labeled DNA probes and in situ hybridization methods had shorter turn round time for results revolutionized their clinical application. Signals obtained from these probes are highly specific, yet they can produce fusion signals not necessarily representing fusion of actual genes due to other genes included in the probe design. In this study we evaluated discordance between cytogenetic, FISH and RNAseq results in 3 different patients with hematologic malignancies and illustrated the need to perform next generation sequencing (NGS) or RNASeq to accurately interpret FISH results. Methods: Bone marrow or peripheral blood karyotypes and FISH were performed to detect recurring translocations associated with hematologic malignancies in clinical samples routinely referred to our clinical cytogenetics laboratory. When required, NGS was performed on DNA and RNA libraries to detect somatic alterations and gene fusions in some of these specimens. Discordance in results between these methods is further evaluated. Results: For a patient with plasma cell leukemia standard FGFR3 / IGH dual fusion FISH assay detected fusion that was interpreted as FGFR3-positive leukemia, whereas NGS/RNASeq detected NSD2::IGH. For a pediatric acute lymphoblastic leukemia patient, a genetic diagnosis of PDGFRB-positive ALL was rendered because the PDGFRB break-apart probe detected clonal rearrangement, whereas NGS detected MEF2D::CSF1R. A MYC-positive B-prolymphocytic leukemia was rendered for another patient with a cytogenetically identified t(8;14) and MYC::IGH by FISH, whereas NGS detected a novel PVT1::RCOR1 not previously reported. Conclusions: These are 3 cases in a series of several other concordant results, nevertheless, elucidate limitations when interpreting FISH results in clinical applications, particularly when other genes are included in probe design. In addition, when the observed FISH signals are atypical, this study illustrates the necessity to perform complementary laboratory assays, such as NGS and/or RNASeq, to accurately identify fusion genes in tumorigenic translocations.

Automated prediction of acute promyelocytic leukemia from flow cytometry data using a graph neural network pipeline.

OBJECTIVES: Our study aimed to develop a machine learning (ML) model to accurately classify acute promyelocytic leukemia (APL) from other types of acute myeloid leukemia (other AML) using multicolor flow cytometry (MFC) data. Multicolor flow cytometry is used to determine immunophenotypes that serve as disease signatures for diagnosis. METHODS: We used a data set of MFC files from 27 patients with APL and 41 patients with other AML, including those with uncommon immunophenotypes. Our ML pipeline involved training a graph neural network (GNN) to output graph-level labels and identifying the most crucial MFC parameters and cells for predictions using an input perturbation method. RESULTS: The top-performing GNN achieved 100% accuracy on the training/validation and test sets on classifying APL from other AML and used MFC parameters similarly to expert pathologists. Pipeline performance is amenable to use in a clinical decision support system, and our deep learning architecture readily enables prediction explanations. CONCLUSIONS: Our ML pipeline shows robust performance on predicting APL and could be used to screen for APL using MFC data. It also allowed for intuitive interrogation of the model's predictions by clinicians.

Evaluation of metric and representation learning approaches: Effects of representations driven by relative distance on the performance.

Several deep neural network architectures have emerged recently for metric learning. We asked which architecture is the most effective in measuring the similarity or dissimilarity among images. To this end, we evaluated six networks on a standard image set. We evaluated variational autoencoders, Siamese networks, triplet networks, and variational auto-encoders combined with Siamese or triplet networks. These networks were compared to a baseline network consisting of multiple separable convolutional layers. Our study revealed the following: (i) the triplet architecture proved the most effective one due to learning a relative distance - not an absolute distance; (ii) combining auto-encoders with networks that learn metrics (e.g., Siamese or triplet networks) is unwarranted; and (iii) an architecture based on separable convolutional layers is a reasonable simple alternative to triplet networks. These results can potentially impact our field by encouraging architects to develop advanced networks that take advantage of separable convolution and relative distance.

Rhabdomyosarcoma With Epithelioid Features And NSD3::FOXO1 Fusion: Evidence For Reconsideration Of Previously Reported FOXO1::FGFR1 Fusion.

Epithelioid rhabdomyosarcoma is a rare rhabdomyosarcoma variant for which no diagnostic recurrent driver genetic events have been identified. Here we report a rapidly progressive and widely metastatic rhabdomyosarcoma with epithelioid features that arose in the thigh of a male infant. Conventional cytogenetics revealed a t(8;13)(p11.2;q14) translocation. Fluorescence in situ hybridization studies showed rearrangement of FOXO1 and amplification of its 3" end, and rearrangement of NSD3 and amplification of its 5` end. Next generation sequencing identified a NSD3::FOXO1 fusion, which is a previously unreported gene fusion. We also review the historic report of a FOXO1::FGFR1 fusion in a solid variant of alveolar rhabdomyosarcoma and propose that NSD3::FOXO1 fusion may have been the more appropriate interpretation of the data presented in that report.

EnhancerTracker: Comparing cell-type-specific enhancer activity of DNA sequence triplets via an ensemble of deep convolutional neural networks.

Motivation: Transcriptional enhancers - unlike promoters - are unrestrained by distance or strand orientation with respect to their target genes, making their computational identification a challenge. Further, there are insufficient numbers of confirmed enhancers for many cell types, preventing robust training of machine-learning-based models for enhancer prediction for such cell types. Results: We present EnhancerTracker , a novel tool that leverages an ensemble of deep separable convolutional neural networks to identify cell-type-specific enhancers with the need of only two confirmed enhancers. EnhancerTracker is trained, validated, and tested on 52,789 putative enhancers obtained from the FANTOM5 Project and control sequences derived from the human genome. Unlike available tools, which accept one sequence at a time, the input to our tool is three sequences; the first two are enhancers active in the same cell type. EnhancerTracker outputs 1 if the third sequence is an enhancer active in the same cell type(s) where the first two enhancers are active. It outputs 0 otherwise. On a held-out set (15%), EnhancerTracker achieved an accuracy of 64%, a specificity of 93%, a recall of 35%, a precision of 84%, and an F1 score of 49%. Availability and implementation: https://github.com/BioinformaticsToolsmith/EnhancerTracker. Contact: hani.girgis@tamuk.edu.

Cooling and Contraction of the Mesosphere and Lower Thermosphere From 2002 to 2021.

We examine the thermal structure of the mesosphere and lower thermosphere (MLT) using observations from 2002 through 2021 from the SABER instrument on the NASA TIMED satellite. These observations show that the MLT has significantly cooled and contracted between the years 2002 and 2019 (the year of the most recent solar minimum) due to a combination of a decline in the intensity of the 11-year solar cycle and increasing carbon dioxide (CO2.) During this time the thickness of atmosphere between the 1  and 10-4 hPa pressure surfaces (approximately 48 and 105 km) has contracted by 1,333 m, of which 342 m is attributed to increasing CO2. All other pressure surfaces in the MLT have similarly contracted. We further postulate that the MLT in the two most recent solar minima (2008-2009 and 2019-2020) was very likely the coldest and thinnest since the beginning of the Industrial Age. The sensitivity of the MLT to a doubling of CO2 is shown to be -7.5 K based on observed trends in temperature and growth rates of CO2. Colder temperatures observed at 10-4 hPa in 2019 than in the prior solar minimum in 2009 may be due to a decrease of 5% in solar irradiance in the Schumann-Runge band spectral region (175-200 nm).

A t(11;14)(q13;q32)/CCND1::IGH carrying progenitor germinal B-cell with subsequent cytogenetic aberrations contributes to the development of classic Hodgkin lymphoma.

Classic Hodgkin lymphoma (cHL) is characterized by the presence of Hodgkin Reed-Sternberg (HRS) cells. Although HRS cells express PAX5, cHL frequently lacks other B-cell markers. There is now evidence that HRS cells are monoclonal and are derived from germinal center B-cells. In terms of genetic aberrations, cHL frequently exhibit activated NF-kB signaling pathway. In this study, we present a case of cHL harboring a t(11;14) (q13;q32)/CCND1::IGH, identified by chromosome and fluorescence in situ hybridization analysis and with CCND1 expression in HRS cells. We also analyzed recurrent cytogenetic aberrations in t(11;14) positive mantle cell lymphoma (MCL) and those found in cHL from the literature to assess genetic overlap, clonal evolution, and to identify potential signaling pathways in cHL with CCND1::IGH. This analysis suggests the development of t(11;14)+ cHL and MCL from a transformed precursor cell with t(11;14) through genetic evolution and consequent deregulated pathways, including the NF-κB and NOTCH1 signaling.

An artificial intelligence system applied to recurrent cytogenetic aberrations and genetic progression scores predicts MYC rearrangements in large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL), the most common type of non-Hodgkin lymphoma, is characterized by MYC rearrangements (MYC R) in up to 15% of cases, and these have unfavorable prognosis. Due to cryptic rearrangements and variations in MYC breakpoints, MYC R may be undetectable by conventional methods in up to 10%-15% of cases. In this study, a retrospective proof of concept study, we sought to identify recurrent cytogenetic aberrations (RCAs), generate genetic progression scores (GP) from RCAs and apply these to an artificial intelligence (AI) algorithm to predict MYC status in the karyotypes of published cases. The developed AI algorithm is validated for its performance on our institutional cases. In addition, cytogenetic evolution pattern and clinical impact of RCAs was performed. Chromosome losses were associated with MYC-, while partial gain of chromosome 1 was significant in MYC R tumors. MYC R was the sole driver alteration in MYC-rearranged tumors, and evolution patterns revealed RCAs associated with gene expression signatures. A higher GPS value was associated with MYC R tumors. A subsequent AI algorithm (composed of RCAs + GPS) obtained a sensitivity of 91.4 and specificity of 93.8 at predicting MYC R. Analysis of an additional 59 institutional cases with the AI algorithm showed a sensitivity and specificity of 100% and 87% each with positive predictive value of 92%, and a negative predictive value of 100%. Cases with a MYC R showed a shorter survival.

Role of tropical lower stratosphere winds in quasi-biennial oscillation disruptions.

In 2016, the westerly quasi-biennial oscillation (WQBO) in the equatorial stratosphere was unprecedentedly disrupted by westward forcing near 40 hPa; this was followed by another disruption in 2020. Strong extratropical Rossby waves propagating toward the tropics were considered the main cause of the disruptions, but why the zonal wind is reversed only in the middle of the WQBO remains unclear. Here, we show that strong westerly winds in the equatorial lower stratosphere (70 to 100 hPa) help to disrupt the WQBO by hindering the wind reversal at its base. They also help equatorial westward waves propagate further upward, increasing the negative forcing at around 40 hPa that drives the QBO disruptions. Tropical westerly winds have been increasing in the past and are projected to increase in a warmer climate. These background wind changes may allow more frequent QBO disruptions in the future, leading to less predictability in atmospheric weather and climate systems.

A Combined Biomarker of Bright CD38 and MYC ≥55% Is Highly Predictive of Double-/Triple-Hit High-Grade B-Cell Lymphoma.

OBJECTIVES: Diagnosis of high-grade B-cell lymphoma with MYC and BCL2 or BCL6 rearrangements (double-/triple-hit lymphoma [DTHL]) appears to mandate fluorescence in situ hybridization (FISH) testing for all large B-cell lymphoma (LBCL). Given the low incidence of DTHL, we aimed to identify flow cytometry (FC) and immunohistochemistry (IHC) features of DTHL that could be used to develop an optimal screening strategy. This combined FC-IHC approach has not yet been studied. METHODS: We compared features of 40 cases of DTHL and 39 cases of diffuse LBCL (DLBCL) without MYC rearrangement. RESULTS: Bright CD38 expression (CD38bright) by FC, high MYC expression (≥55%), and double-expressor phenotype by IHC were significantly associated with DTHL. The biomarker combining FC and IHC, CD38bright and/or MYC ≥55%, was superior to FC and IHC markers alone in predicting DTHL. Restricting FISH testing to approximately 25% of LBCL based on CD38brightand/or MYC ≥55% would detect approximately 95% of DTHL-BCL2 and approximately 75% of DHL-BCL6. CONCLUSIONS: Our study demonstrated that the novel biomarker of CD38bright and/or MYC ≥55% is highly predictive of DTHL. Awareness of the advantages and limitations of this screening strategy would facilitate development of a rational diagnostic workflow to provide high-quality patient care.

Automated classification of cytogenetic abnormalities in hematolymphoid neoplasms.

MOTIVATION: Algorithms for classifying chromosomes, like convolutional deep neural networks (CNNs), show promise to augment cytogeneticists' workflows; however, a critical limitation is their inability to accurately classify various structural chromosomal abnormalities. In hematopathology, recurrent structural cytogenetic abnormalities herald diagnostic, prognostic and therapeutic implications, but are laborious for expert cytogeneticists to identify. Non-recurrent cytogenetic abnormalities also occur frequently cancerous cells. Here, we demonstrate the feasibility of using CNNs to accurately classify many recurrent cytogenetic abnormalities while being able to reliably detect non-recurrent, spurious abnormal chromosomes, as well as provide insights into dataset assembly, model selection and training methodology that improve overall generalizability and performance for chromosome classification. RESULTS: Our top-performing model achieved a mean weighted F1 score of 96.86% on the validation set and 94.03% on the test set. Gradient class activation maps indicated that our model learned biologically meaningful feature maps, reinforcing the clinical utility of our proposed approach. Altogether, this work: proposes a new dataset framework for training chromosome classifiers for use in a clinical environment, reveals that residual CNNs and cyclical learning rates confer superior performance, and demonstrates the feasibility of using this approach to automatically screen for many recurrent cytogenetic abnormalities while adeptly classifying non-recurrent abnormal chromosomes. AVAILABILITY AND IMPLEMENTATION: Software is freely available at https://github.com/DaehwanKimLab/Chromosome-ReAd. The data underlying this article cannot be shared publicly due to it being protected patient information. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Evaluation of the N2O Rate of Change to Understand the Stratospheric Brewer-Dobson Circulation in a Chemistry-Climate Model.

The Brewer-Dobson Circulation (BDC) determines the distribution of long-lived tracers in the stratosphere; therefore, their changes can be used to diagnose changes in the BDC. We evaluate decadal (2005-2018) trends of nitrous oxide (N2O) in two versions of the Whole Atmosphere Chemistry-Climate Model (WACCM) by comparing them with measurements from four Fourier transform infrared (FTIR) ground-based instruments, the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and with a chemistry-transport model (CTM) driven by four different reanalyses. The limited sensitivity of the FTIR instruments can hide negative N2O trends in the mid-stratosphere because of the large increase in the lowermost stratosphere. When applying ACE-FTS measurement sampling on model datasets, the reanalyses from the European Center for Medium Range Weather Forecast (ECMWF) compare best with ACE-FTS, but the N2O trends are consistently exaggerated. The N2O trends obtained with WACCM disagree with those obtained from ACE-FTS, but the new WACCM version performs better than the previous above the Southern Hemisphere in the stratosphere. Model sensitivity tests show that the decadal N2O trends reflect changes in the stratospheric transport. We further investigate the N2O Transformed Eulerian Mean (TEM) budget in WACCM and in the CTM simulation driven by the latest ECMWF reanalysis. The TEM analysis shows that enhanced advection affects the stratospheric N2O trends in the Tropics. While no ideal observational dataset currently exists, this model study of N2O trends still provides new insights about the BDC and its changes because of the contribution from relevant sensitivity tests and the TEM analysis.

The Montreal Protocol protects the terrestrial carbon sink.

The control of the production of ozone-depleting substances through the Montreal Protocol means that the stratospheric ozone layer is recovering1 and that consequent increases in harmful surface ultraviolet radiation are being avoided2,3. The Montreal Protocol has co-benefits for climate change mitigation, because ozone-depleting substances are potent greenhouse gases4-7. The avoided ultraviolet radiation and climate change also have co-benefits for plants and their capacity to store carbon through photosynthesis8, but this has not previously been investigated. Here, using a modelling framework that couples ozone depletion, climate change, damage to plants by ultraviolet radiation and the carbon cycle, we explore the benefits of avoided increases in ultraviolet radiation and changes in climate on the terrestrial biosphere and its capacity as a carbon sink. Considering a range of strengths for the effect of ultraviolet radiation on plant growth8-12, we estimate that there could have been 325-690 billion tonnes less carbon held in plants and soils by the end of this century (2080-2099) without the Montreal Protocol (as compared to climate projections with controls on ozone-depleting substances). This change could have resulted in an additional 115-235 parts per million of atmospheric carbon dioxide, which might have led to additional warming of global-mean surface temperature by 0.50-1.0 degrees. Our findings suggest that the Montreal Protocol may also be helping to mitigate climate change through avoided decreases in the land carbon sink.

Final Long-Term Reporting from a Randomized Controlled IDE Trial for Lumbar Artificial Discs in Single-Level Degenerative Disc Disease: 7-Year Results.

BACKGROUND: This study compared 7-year safety and efficacy outcomes of activL and ProDisc-L lumbar total disc replacements in patients with symptomatic, single-level lumbar degenerative disc disease (DDD). The objectives are to report 7-year outcomes of the trial, evaluate the outcomes for patients lost to follow-up, and determine whether early outcomes predict long-term outcomes. METHODS: This was a prospective, multicenter, randomized, controlled investigational device exemption study. Eligible patients with symptomatic, single-level lumbar DDD had failed ≥6 months of nonsurgical management. Patients (N = 283) were randomized to receive activL (n = 218) or ProDisc-L (n = 65). At 7 years, data were available from 206 patients (activL, 160; ProDisc-L, 46). Logistic regression models were fit to predict 7-year outcomes for patients lost to follow-up after 2 years. RESULTS: At 7 years, the activL group was noninferior to the ProDisc-L group on the primary composite endpoint (P = .0369). Both groups showed significant reductions in back/leg pain severity and improvements in disability index and quality-of-life relative to baseline (P < .0001). In both groups, opioid use was significantly reduced at 7 years (0%) relative to baseline (P < .01), and the overall reoperation rates were low (4.6%). activL patients showed a significantly better range of motion (ROM) for flexion-extension rotation than ProDisc-L patients (P = .0334). A significantly higher proportion of activL patients did not report serious adverse events (activL, 62%; ProDisc-L, 43%; P = .011). Predictive modeling indicated that >70% of patients (depending on outcome) lost to follow-up after 2 years would show clinically significant improvement at 7 years if improvements were achieved at 2 years. CONCLUSIONS: The benefits of activL and ProDisc-L are maintained after 7 years, with significant improvements from baseline observed in pain, function, and opioid use. activL is more effective at preserving ROM than ProDisc-L and has a more favorable safety profile. Improvements in other primary and secondary outcomes were similar between both disc designs. LEVEL OF EVIDENCE: 1.

On the response of the middle atmosphere to anthropogenic forcing.

Anthropogenic forcing of the atmosphere by greenhouse gases (GHG) and ozone-depleting substances has provided an unintended test of the robustness of current understanding of the physics and chemistry of the middle atmosphere, that is, the stratosphere and mesosphere. We explore this topic by examining how well anthropogenic changes can be simulated by modern, comprehensive numerical models. Specifically, we discuss the simulations of trends in global mean temperature; the development of the ozone hole and its impact on the dynamics of the Southern Hemisphere, both in the stratosphere and troposphere; trends in the stratospheric Brewer-Dobson circulation; and the response of the quasi-biennial oscillation (QBO) to increasing burdens of CO2 . We find that, in most of these cases, numerical simulation is able to reproduce observed changes and provide physical insights into the relevant mechanisms. Simulation of the QBO is on a less firm footing. Although many numerical models can now generate realistic QBOs, future projections of its behavior under the increasing burdens of GHG are inconsistent and even contradictory.

Identification of potential antiviral compounds against SARS-CoV-2 structural and non structural protein targets: A pharmacoinformatics study of the CAS COVID-19 dataset.

SARS-CoV-2 is a newly discovered virus which causes COVID-19 (coronavirus disease of 2019), initially documented as a human pathogen in 2019 in the city of Wuhan China, has now quickly spread across the globe with an urgency to develop effective treatments for the virus and emerging variants. Therefore, to identify potential therapeutics, an antiviral catalogue of compounds from the CAS registry, a division of the American Chemical Society was evaluated using a pharmacoinformatics approach. A total of 49,431 compounds were initially recovered. After a biological and chemical curation, only 23,575 remained. A machine learning approach was then used to identify potential compounds as inhibitors of SARS-CoV-2 based on a training dataset of molecular descriptors and fingerprints of known reported compounds to have favorable interactions with SARS-CoV-2. This approach identified 178 compounds, however, a molecular docking analysis revealed only 39 compounds with strong binding to active sites. Downstream molecular analysis of four of these compounds revealed various non-covalent interactions along with simultaneous modulation between ligand and protein active site pockets. The pharmacological profiles of these compounds showed potential drug-likeness properties. Our work provides a list of candidate anti-viral compounds that may be used as a guide for further investigation and therapeutic development against SARS-CoV-2.

Long-Term Clinical Outcomes With the Activ-L Lumbar Arthroplasty System.

BACKGROUND: Low back pain (LBP) due to degenerative disc disease (DDD) is the most common occupational disorder worldwide. Lumbar total disc replacement (LTDR) has provided an alternative to rigid fusion to relieve pain with less motion restriction. We present clinical results with long-term follow-up from a single-center, single-surgeon series of patients treated with the Activ-L artificial disc. METHODS: Thirty-three patients with symptomatic single-level DDD who failed nonsurgical therapy for a minimum of 6 months underwent single-level arthroplasty with the Activ-L system between 2007 and 2012. Demographic, preoperative, and postoperative data were collected prospectively. Clinical factors reviewed included occupational status, sensory deficits, functional status determined by Oswestry Disability Index (ODI), back pain, leg pain, pain medication consumption, and radiographic imaging. RESULTS: Average age at surgery was 38.0 ± 7.8 years, and the majority of patients were male (60.6%). Average follow-up was 2.7 ± 1.7 years. Average ODI at preoperative baseline was 54.6 ± 13.5, with scores significantly improved at 6 weeks (28.6 ± 17.4, P < .0001), 3 months (24.1 ± 16.8, P < .0001), 6 months (22.3 ± 16.3, P < .0001), 1 year (18.8 ± 15.3, P < .0001), and final follow-up (15.6 ± 16.4, P < .0001). Most patients (87.8%) reported pain medication usage within 14 days of baseline evaluation, with consumption decreasing significantly at 1-year (34.5%, P < .0001) and long-term follow-up (21.2%, P < .0001). One patient experienced mild unilateral graft subsidence at 1 year, which remained stable on radiographs at 5 years. None of the prostheses required revision surgery. CONCLUSIONS: The Activ-L disc replacement system is safe and effective for treating single-level lumbar DDD. Patients reported significant improvement in functional outcomes and decreases in pain medication consumption. Further investigation of the Activ-L system in larger populations is warranted. CLINICAL RELEVANCE: LBP is a common cause of disability worldwide, and better treatment options are needed to improve outcomes, including pain and mobility. Spine surgeons may choose the Activ-L disc replacement as a safe and effective treatment for LBP caused by single-level lumbar DDD.

Development and Clinical Validation of a Multiplex Gene Fusion Assay.

OBJECTIVE: The detection of gene fusion events is important for the diagnosis and management of malignancies. In this study, we describe the validation of a next-generation sequencing assay for multiplex detection of gene fusions. METHODS: Based on previously described gene fusion events that occur in pediatric oncology, a custom anchored multiplex next-generation sequencing assay was designed to target 93 genes. RESULTS: A total of 24 previously characterized specimens were examined. Twenty specimens had 1 or more previously described fusion events, and 4 specimens were negative for fusion events. The accuracy across specimens was 100% (20 of 20 specimens). The analytical sensitivity and specificity were both 100%. Interday reproducibility for fusion events was 94%; in comparison, intraday reproducibility was 90%. CONCLUSION: This multiple-gene fusion assay demonstrated appropriate sensitivity, specificity, and accuracy for clinical use. We anticipate that this assay will improve the diagnosis and management of patients with pediatric solid tumors.

Five-year Results of a Randomized Controlled Trial for Lumbar Artificial Discs in Single-level Degenerative Disc Disease.

STUDY DESIGN: A prospective, multicenter, randomized, controlled, investigational device exemption (IDE) noninferiority trial. OBJECTIVE: The aim of this study was to compare the 5-year safety and effectiveness of the activL Artificial Disc with Control Total Disc Replacement (TDR) systems (ProDisc-L or Charité) in the treatment of patients with symptomatic single-level lumbar degenerative disc disease (DDD). SUMMARY OF BACKGROUND DATA: The activL Artificial Disc received Food and Drug Administration approval in 2015 based on 2-year follow-up data. METHODS: Eligible patients presented with symptomatic, single-level, lumbar DDD who failed ≥6 months of nonsurgical management. At entry, 324 patients were randomly allocated (2 : 1) to treatment with activL (n = 218) or Control (n = 106, including n = 65 ProDisc-L and n = 41 Charité) TDR. At 5-year follow up, a total of 261 patients (176 activL patients and 85 Control patients) were available for analysis. RESULTS: The primary composite endpoint at 5 years for activL patients was noninferior to Control TDR. Relative to baseline, reductions in back pain severity and improvements in Oswestry Disability Index (ODI) were maintained for both the activL and Control TDR groups through 5 years. The activL group showed significantly better range of motion for flexion-extension rotation, flexion-extension translation, and disc angle, compared with Control TDR. Freedom from a serious adverse event through 5 years was 64% in activL patients, 47% in Control patients (log-rank P = 0.0068). Freedom from index-level and adjacent-level reoperation was high for TDR patients, ranging between 94% and 99%, respectively. CONCLUSION: Long-term evidence supports lumbar total disc replacement as safe. The next-generation activL Artificial Disc is more effective at preserving range of motion than first-generation lumbar TDRs (ProDisc-L and Charité) and offers a higher safety profile. Other primary and secondary outcomes are similar between disc designs. LEVEL OF EVIDENCE: 2.

Bright CD38 Expression by Flow Cytometric Analysis Is a Biomarker for Double/Triple Hit Lymphomas with a Moderate Sensitivity and High Specificity.

BACKGROUND: High-grade B-cell lymphomas (HGBCL) with MYC and BCL2 or/and BCL6 rearrangements (R), so-called double/triple-hit lymphomas (DH/THL), are uncommon, clinically aggressive lymphomas that require a prompt diagnosis. We aim to identify flow cytometric immunophenotypic (IP) features of DH/THL that may aid in triaging these cases followed by a timely confirmatory cytogenetic study. METHODS: We compared the IP features of 43 cases of DH/THL to those of 55 cases of single-hit lymphoma (SHL) and 59 cases of diffuse large B-cell lymphoma (DLBCL) without MYC-R (MYCneg DLBCL). We analyzed the expression patterns of CD10, CD19, CD20, CD38, and surface immunoglobulin light chain in lymphoma cells. RESULTS: Bright CD38 expression (CD38bright ) analyzed either qualitatively or semi-quantitatively was more common in DH/THL (56%) than in MYCneg DLBCL (17%) but less common compared to SHL (82%), indicating that CD38bright can serve as a biomarker for DH/THL. Additionally, CD38bright may be a better indicator for predicting DH/THL-BCL2 than DHL-BCL6, and very bright CD38 expression was exclusive to MYC rearranged lymphomas. The expression patterns of other markers were similar among these lymphoma groups. CONCLUSIONS: CD38bright is a biomarker associated with DH/THL with a moderate sensitivity (~50%) and high specificity (~90%). While this marker cannot be used as a screening tool, awareness of this correlation may aid in expediting the diagnosis and prioritizing FISH testing in resource limited settings or situations when samples are limited. Future studies to combine immunohistochemical markers are needed to further enhance the predictive power of CD38bright in diagnosing DH/THL. © 2019 International Clinical Cytometry Society.