Identification Of Subset Research Articles

Multicolor flow cytometry-based immunophenotyping for preclinical characterization of nanotechnology-based formulations: an insight into structure activity relationship and nanoparticle biocompatibility profiles.

Immunophenotyping, which is the identification of immune cell subsets based on antigen expression, is an integral technique used to determine changes of cell composition and activation in various disease states or as a response to different stimuli. As nanoparticles are increasingly utilized for diagnostic and therapeutic applications, it is important to develop methodology that allows for the evaluation of their immunological impact. Therefore, the development of techniques such as immunophenotyping are desirable. Currently, the most common technique used to perform immunophenotyping is multicolor flow cytometry. We developed two distinct multicolor flow cytometry immunophenotyping panels which allow for the evaluation of the effects of nanoparticles on the composition and activation status of treated human peripheral blood mononuclear cells. These two panels assess the presence of various lymphoid and myeloid-derived cell populations as well as aspects of their activation statuses-including proliferation, adhesion, co-stimulation/presentation, and early activation-after treatment with controls or nanoparticles. To conduct assay performance qualification and determine the applicability of this method to preclinical characterization of nanoparticles, we used clinical-grade nanoformulations (AmBisome, Doxil and Feraheme) and research-grade PAMAM dendrimers of different sizes (G3, G4 and G5) and surface functionalities (amine-, carboxy- and hydroxy-). We found that formulations possessing intrinsic fluorescent properties (e.g., Doxil and AmBisome) interfere with accurate immunophenotyping; such interference may be partially overcome by dilution. In the absence of interference (e.g., in the case of dendrimers), nanoparticle size and surface functionalities determine their effects on the cells with large amine-terminated dendrimers being the most reactive.

The role of physiotherapy in the treatment of chronic muscle pain: a review

Chronic muscle pain is a common and often debilitating condition that affects a large proportion of the population. It can be caused by a variety of factors, including injury, overuse, or underlying medical conditions, and can significantly impact a person's quality of life. The pathophysiology is complex and its understanding evolving, and clinical management is difficult, with heterogeneous intervention employed. While physiotherapy has emerged as a promising treatment option due to its non-invasive nature and potential to improve function and reduce pain. However, there is a need for further research to better understand the role of physiotherapy in treating chronic muscle pain and to provide evidence-based recommendations for its use in clinical practice. This paper aims to review the current literature on the role of physiotherapy in the treatment of chronic muscle pain and to provide an evidence-based summary of its effectiveness, optimal type and duration, and factors that may influence its effectiveness. The findings of this Research can be used to inform clinical practice and improve the management of chronic muscle pain. there is also some evidence for the use of intervention such as cognitive-behavioural therapy (CBT) approaches. Evidence for other interventions is more equivocal. In conclusion, identification of subsets of chronic muscle pain patients may be an important factor in selection an appropriate intervention approaches

To Test or Not? Xpert MTB/RIF as an Alternative to Smear Microscopy to Guide Line Probe Assay Testing for Drug-Resistant Tuberculosis.

Xpert MTB/RIF (Xpert) revolutionized tuberculosis (TB) diagnosis. Laboratory decision making on whether widely-used reflex drug susceptibility assays (MTBDRplus, first-line resistance; MTBDRsl, second-line) are conducted is based on smear status, with smear-negative specimens often excluded. We performed receiver operator characteristic (ROC) curve analyses using bacterial load information (smear microscopy grade, Xpert-generated semi-quantitation categories and minimum cycle threshold [CTmin] values) from Xpert rifampicin-resistant sputum for the prediction of downstream line probe assay results as "likely non-actionable" (no resistance or susceptible results generated). We evaluated actionable-to-non-actionable result ratios and pay-offs with missed resistance versus LPAs done universally. Smear-negatives were more likely than smear-positive specimens to generate a non-actionable MTBDRplus (23% [133/559] versus 4% [15/381]) or MTBDRsl (39% [220/559] versus 12% [47/381]) result. However, excluding smear-negatives would result in missed rapid diagnoses (e.g., only 49% [264/537] of LPA-diagnosable isoniazid resistance would be detected if smear-negatives were omitted). Testing smear-negatives with a semi-quantitation category ≥ "medium" had a high ratio of actionable-to-non-actionable results (12.8 or a 4-fold improvement versus testing all using MTBDRplus, 4.5 or 3-fold improvement for MTBDRsl), which would still capture 64% (168/264) and 77% (34/44) of LPA-detectable smear-negative resistance, respectively. Use of CTmins permitted optimization of this ratio with higher specificity for non-actionable results but decreased resistance detected. Xpert quantitative information permits identification of a smear-negative subset in whom the payoffs of the ratio of actionable-to-non-actionable LPA results with missed resistance may prove acceptable to laboratories, depending on context. Our findings permit the rational expansion of direct DST to certain smear-negative sputum specimens.

17th International Conference on Malignant Lymphoma, Palazzo dei Congressi, Lugano, Switzerland, 13 - 17 June, 2023.

Introduction: FL is characterized by a heterogeneous clinical course. The biologic importance of the tumour microenvironment in FL pathogenesis is well established. However, detailed information on the immune profile in PB has not been previously investigated, which becomes very relevant in the current era of the immunotherapy. The aim of this study was to characterise the PB immune profile of FL patients at diagnosis, first relapse (R1) and subsequent relapses (>R2) and compare them with healthy controls. Moreover, R1 was also analysed according to histological transformation (HT) and POD24 status. Methods: We collected PB samples of FL patients at diagnosis (n = 42), R1 (n = 22) and >R2 (n = 16) from April 2019 to August 2022 (median age at diagnosis: 65 years [30–82]; 22M/20F). 15 PB samples from healthy donors were also obtained (median age: 31 years [28–65]; 5M/10F). All individuals signed informed consent. The identification of major subsets of T-cells, B-cells, NK cells, monocytes, neutrophils, eosinophils, basophils, dendritic cells (DC) and myeloid suppressor cells (MSC) was performed by multiparameter flow cytometry. Euroflow methodology was used to set up the Omnicyt™ flow cytometer and acquired at least 150.000 events. All data were analysed using Infinicyt™ software version 2.0 (Cytognos, Salamanca, Spain). Results: Compared with healthy controls, FL patients showed a lower CD4+/CD8+ ratio due to an increase in CD8+ lymphocytes and a decrease in total CD4+ lymphocytes. In addition, FL patients had a significantly lower percentage of naïve T lymphocytes, a higher percentage of effector memory and effector lymphocytes, both CD4+ and CD8+. Of note, regulatory T lymphocytes (Treg) and Th1 cells were increased in FL patients, while NK-cells were diminished. Interestingly, differences in DC and MSC were also found between healthy controls and FL patients (Figure). These differences remained when comparing the immune populations between diagnosis and relapse and deepened with each relapse. No differences were observed between groups in the percentage of neutrophils, monocytes, eosinophils, or total B lymphocytes. A subanalysis performed in R1 samples according to HT and POD24 status revealed that HT-R1 presented significantly a smaller CD8+ central memory population compared with non HT-R1. POD24 patients displayed a lower CD4+/CD8+ ratio and a higher proportion of Th1 cells (p < 0.05). In both adverse prognostic groups, the percentage of myeloid DC and neutrophils was significantly lower. The research was funded by: This study has been funded by Instituto de Salud Carlos III (ISCIII) through the projects PI19/00887 to A.L.-G. and E.G., and PI19/00925 to L.M. Andrea Rivero was supported by a grant from Hospital Clinic de Barcelona during the conduct of the study. Keywords: indolent non-Hodgkin lymphoma, microenvironment No conflicts of interests pertinent to the abstract.

Use of immune checkpoint gene (ICG) signatures to identify selective enrichment of FGL1 and CEACAM1 in histologic subtypes of lung cancer.

e20527 Background: Immune checkpoint blockade has changed the management paradigm for lung cancer. Identification of vulnerable subsets using reliable predictive biomarkers is an area of unmet need. We systematically compared the pattern of expression of validated mediators of adaptive and innate immune response in clinical and histologic subsets of lung cancer using publicly available datasets. Methods: Gene expression data for lung adenocarcinoma (LUAD, N = 501) and and lung squamous cell carcinoma (LUSC, N = 491) was obtained from The Cancer Genome Atlas. We compared the expression of ICGs between LUSC and LUAD using DESeq2 and estimated the proportion of different immune cells in the tumor microenvironment by CIBERSORT. An expanded panel of ICG signatures from MSigDB was compared between LUSC and LUAD using gene set variation analysis (GSVA). Weighted gene co-expression network analysis (WGCNA) identified modules of immune checkpoint inhibitor genes with significant correlation with histology, which were further investigated for biologic pathway involvement and survival analysis using Ingenuity Pathway Analysis and Gene Expression Profiling Interactive Analysis (GEPIA2), respectively. Results: Majority of the ICGs had a higher expression in LUAD than LUSC with the strongest differential expression recorded for FGL1 (LogFC = 6.2, FDR = 1.2E-239) and CEACAM1 (LogFC = 1.4, FDR = 2E-71). Treg cells and monocytes were higher in LUAD while NK cells and macrophages were higher in LUSC. There was no difference in CD8(+) T cell population by histology. Genesets related to PD1 signaling from MSigDB had significantly higher GSVA scores in LUAD than LUSC. WGCNA identified 2 modules containing immune checkpoint genes – one module containing 15 of the 23 ICGs involved in allograft rejection, interferon gamma response, interferon alpha response, IL6-signaling, IL2-signaling and TNF-alpha signaling showed moderate correlation with LUAD (module-trait correlation = 0.3, P = 8e-26). A second module with 4 ICGs ( FGL1, LGALS3, CEACAM1, PVRL2) enriched in pathways related to carbohydrate and lipid metabolism (galactose degradation, gamma-linolenate biosynthesis) showed very strong correlation with LUAD (module-trait correlation = 0.85, P = 5e-278). Additional comparison by gender and smoking status along with external validation using independent dataset is ongoing. Conclusions: ICG expression profile differs between LUAD and LUSC with a stronger expression profile in LUAD than LUSC.

Biological risk factors for dementia in India

AbstractBackgroundMany clinical biomarkers have been associated with dementia. This paper uses a novel data set from an understudied population – a national sample of older Indians ‐ to assess the relative importance of 41 biomarkers using a variety of approaches. The value of these data is the extensiveness of the biomarker collection, the validated classification of dementia, and the uniqueness of the population with low average education. Many approaches to both summarizing and reducing data complexity have been suggested. Some of these are based on theory about biological mechanisms and some are agnostic and based on machine‐learning approaches. The results are informative for others collecting and analyzing biomarker data in population samples.MethodWe use 6 approaches to assessing the value of the biomarkers in explaining variance in dementia diagnosis and cognitive functioning – some traditional social science approaches and some based on machine learning. The aim of the different approaches is to determine how to best characterize the influence of biology as well as how to trim and combine the data. The five approaches to measuring biological risk: 41 individual biomarkers; identification of subsets of biomarkers with elastic net; support vector machine learning; factors developed with factor analysis; a principal components approach; and a factor classification based on a theoretical approach.ResultsResults indicate if the aim is explain variance in dementia, all the biomarkers or a reduced set of biomarkers identified by elastic net do the best job at explaining variability. However, biological markers chosen as most important do not fit well our understanding of biological mechanisms.ConclusionIf the aim is understanding the relative importance of biological systems, traditional social science approaches, e.g. the factor analysis and principal components approach, allow better understanding and interpretation of the biomarkers associated with cognitive performance.

Expanding panel size in spectral flow cytometry with StarBright Dyes excitable by the ultraviolet (355 nm), violet (405 nm), blue (488 nm) and yellow (561 nm) lasers.

Abstract The recently launched fluorescent dyes from Bio-Rad, StarBright Dyes, deliver tunable brightness and spectral properties, greater stability, improved lot-to-lot reproducibility, and spectral consistency. Specifically designed for multicolor flow cytometry with researchers needs in mind, StarBright Dyes address the common pain points in flow such as brightness, broad emission spectra, staining consistency, and ease-of-use, solving issues of signal resolution when constructing complex panels. These bright dyes have the additional benefit of a unique full spectral profile, making them ideal for inclusion in spectral flow cytometry, when creating multicolor panels. Here we present data of our newest additions to the StarBright range, the StarBright Blue and StarBright Yellow Dyes on a five-laser spectral cell analyzer. Both dye series are bright and allow expansion across the 488 and 561 lasers giving more dye choice for all panel sizes but are particularly useful when large panel design is required. In this study we show, when StarBright Blue and StarBright Yellow Dyes are combined with other members of the StarBright Dye range, polymer dyes and traditional fluorescent dyes, very large immunophenotyping panels can be constructed allowing identification of many peripheral blood subsets. In addition, novel dye combinations can be identified increasing the numbers of dyes and therefore markers identified from one sample. When combined with their ability to be fixed in both PFA based and alcohol-based fixatives, with minimal spectral changes, and to be pre-mixed for up to 33 days, the flexibility of StarBright Dyes means they are ideal for new and expanding existing panels regardless of the type of flow cytometer being used.

1455 Identification and characterization of specific subsets in systemic sclerosis fibroblast cultures

1455 Identification and characterization of specific subsets in systemic sclerosis fibroblast cultures

1568 Identification of fibroinflammatory and fibrotic transcriptomic subsets of human sclerotic cutaneous chronic graft-versus-host disease

1568 Identification of fibroinflammatory and fibrotic transcriptomic subsets of human sclerotic cutaneous chronic graft-versus-host disease

Revisiting the critical roles of reactive astrocytes in neurodegeneration.

Astrocytes, an integral component of the central nervous system (CNS), contribute to the maintenance of physiological homeostasis through their roles in synaptic function, K+ buffering, blood-brain barrier (BBB) maintenance, and neuronal metabolism. Reactive astrocytes refer to astrocytes undergoing morphological, molecular and functional remodelling in response to pathological stimuli. The activation and differentiation of astrocytes are implicated in the pathogenesis of multiple neurodegenerative diseases. However, there are still controversies regarding their subset identification, function and nomenclature in neurodegeneration. In this review, we revisit the multidimensional roles of reactive astrocytes in Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), multiple sclerosis (MS) and amyotrophic lateral sclerosis (ALS). Furthermore, we propose a precise linkage between astrocyte subsets and their functions based on single-cell sequencing analyses.

Abstract 5762: New perspective on racial disparities in prostate cancer: identification of new molecular subsets using whole-mount radical prostatectomy

Abstract Introduction: Prostate cancer is a heterogenous multifocal disease. We hypothesize that different tumor foci may harbor distinct driver molecular aberrations, making it a more complex disease and difficult to manage. To avoid overlooking smaller tumor foci with clinical and biological significance, we used an innovative approach to understand the genetic underpinnings of each tumor foci based on the molecular analysis of whole-mount radical prostatectomy specimens rather than a systematic sampling of dominant nodules alone. Our study aimed to identify distinct molecular subsets of prostate cancer, if any, and correlate them with clinical outcomes in Caucasians (CA) and African Americans (AA). Method: We randomly selected 834 whole-mount radical prostatectomy tissues including 463 (56%) CA and 371 (44%) AA. We used combined dual immunohistochemistry (IHC) for ERG and SPINK1 and dual RNA in-situ hybridization (ISH) for ETV1 and ETV4. The racial disparity in aberrant oncogene expression was analyzed by the Chi-squared test. The recurrence-free survival (RFS) of patients with distinct molecular subsets of prostate cancer was examined by the Kaplan-Meier method and cox-ph models. The Gleason’s grades of prostate biopsies were summarized by spaghetti plot and compared by linear mixed models. Results: Patients with localized prostate cancer expressing none, one, two, and three of four oncogenes were 16.4%, 58.4%, 21.7%, and 3.5%, respectively. The expression of ERG and SPINK1 was negatively correlated (odds ratio (OR)=0.38, 95% CI 0.29-0.51, p&amp;lt;.001). Compared with CA, AA had a lower incidence of ERG (38.8% vs 60.3%), a higher incidence of SPINK1 (63.3% vs 35.6%), and similar incidences of ETV1 (9.4% vs 9.3%) and ETV4 (4.6% vs 3.9%). Importantly, ETV1 expression was associated with a worse RFS in CAs (hazard ratio (HR)=2.49, 95% CI 1.15-5.38, p=.02). ETV4 expression was associated with a worse RFS in AA (HR=3.11, 95% CI 1.32-8.04, p=.01). In addition, ETV4 expression was associated with lymph node metastasis in AA (OR=4.0, 95% CI 1.06-12.44, p=.02) but not in CA (OR=0.56, 95% CI 0.03-2.85, p=.57). For those who had multiple biopsies before radical prostatectomy, Gleason’s grade increased with time in AA (0.23 per year, p&amp;lt;.001) but was unchanged in CA. ERG expression was associated with a lower Gleason grade (-0.20, p=.03). ETV4 was associated with a higher Gleason grade (0.50, p=.02). Conclusion: Our findings showed the molecular heterogeneity between CA and AA who had localized prostate cancer, and supported ETV1 and ETV4 as prognostic markers that can be incorporated into clinical practice to better predict prostate cancer recurrence after radical prostatectomy in CA and AA, respectively. Citation Format: Wei Zhao, Pin Li, Shannon Carskadon, Craig Rogers, James Peabody, Mani Menon, Dhananjay Chitale, Sean Williamson, Nilesh Gupta, Nallasivam Palanisamy. New perspective on racial disparities in prostate cancer: identification of new molecular subsets using whole-mount radical prostatectomy. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5762.

Abstract 6548: Bioinformatic characterization of dendritic and T cell subpopulations in the tumor microenvironment across different cancer types by single-cell RNA-Seq analysis

Abstract Although the development of single-cell RNAseq (scRNAseq) has improved the knowledge of the tumor microenvironment (TME), there is not a clear understanding of specific cell subtypes, markers that define these cell populations, nor the interaction between them. Previously, we showed that inflammasome activation is correlated with antitumor responses triggered by immune checkpoint blockade (ICB). This highlights a central role for TMEM176B, mostly expressed in myeloid cells, that impairs the recruitment of cytotoxic immune cells in the TME by inhibiting NLRP3 inflammasome activation. Still, the roles of the different subsets of myeloid and T cells in the TME and to what extent they are connected remain controversial. Here, we used scRNAseq data from human tumors to identify and characterize cDC2, Th17 and exhausted CD8+ T cell subpopulations in cancer. Five scRNAseq data sets of melanoma, basal cell carcinoma, breast, lung, colorectal, and ovary cancer patients were integrated, accounting for 382,019 immune cells in total. We applied and compared different bioinformatic tools for scRNASeq data normalization and data sets integration to find conserved immune cell populations across samples, data sets, and cancer types. Then, we evaluated different parameters using well-established methods for clustering and cell type classification to identify subtypes of DCs and T cells in the integrated data. We combined automatic methods with manual analysis of cluster markers to improve robustness and confidence in the cell populations identified. Three clusters of cDC2 were defined and characterized using different scRNAseq analysis tools for pathway enrichment analysis and transcription factors (TF) activation prediction. We found a subset of inflammatory cDC2 with high gene expression of IL1B and NLRP3, in contrast with another cluster characterized by high expression of TMEM176B and CD14. A third cluster showed an intermediate transcriptomic profile. The TMEM176B+ CD14+ cluster was characterized by the activation of JAK-STAT and hypoxia pathways, and the TF FOXL2, ETS2, and ESR2. The NLRP3+ IL1B+ cluster showed more activation of MAPK, Trail, and PI3K pathways, and the TF CEBPE. Moreover, the activation of TNFα and NFkB signaling pathways was found in both clusters. In addition, a conserved population of Th17 cells in the integrated data was observed. Th17 cells were heterogeneous, making the subpopulations and transcriptome signature difficult to define. Further analysis is being performed to identify Th17 subsets and their potential interactions with the cDC2 subclusters. A robust identification and characterization of these immune cell subsets will build towards our understanding of the interactions between these subpopulations triggered by inflammasome activation within the TME and the mechanisms behind ICB response. Citation Format: Yamil D. Mahmoud, Natalia Rego, Marcela Vilarino, Florencia Veigas, Maria R. Girotti, Juan M. Perez Saez, Gabriel A. Rabinovich, Marcelo Hill. Bioinformatic characterization of dendritic and T cell subpopulations in the tumor microenvironment across different cancer types by single-cell RNA-Seq analysis. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6548.

Abstract 4867: Effect of FGFR3 activity on Nectin-4 expression in urothelial carcinoma

Abstract Bladder cancer is a common malignancy in the U.S. and cause of significant morbidity and mortality. Combination platinum-based chemotherapy has long been the mainstay in the treatment of metastatic urothelial carcinoma (mUC); however, over the last decade there have been significant advances in systemic therapy, which includes the FDA approval of the pan-FGFR inhibitor erdafitinib (approved for tumors with FGFR2/3 alterations) and the antibody drug conjugate (ADC) enfortumab vedotin (which targets the cell surface protein Nectin-4). Despite these advances, most patients with mUC will progress and succumb from their disease, highlighting the need for further therapeutic development. In parallel to therapeutic advances, there have been significant advances in the molecular characterization of UC, including identification of luminal and basal subsets. NECTIN4 and FGFR3 alterations are known to be enriched in luminal subtypes and we have found, via query of the TCGA data, that NECTIN4 expression was significantly higher in FGFR3 altered tumors. Given this association we sought to investigate the effect of FGFR3 activity on Nectin-4 expression. Using erdafitinib, in select luminal UC cell lines (RT112, RT4, SW780) with FGFR3 fusion proteins, we found, much to our surprise, that FGFR inhibition increased Nectin-4 expression. Western blots, probing for Nectin-4, following 24H, 48H, and 72H of treatment with erdafitinib (50 nM) showed a significant increase in protein expression in all three cell lines. Importantly, we consistently saw increased expression of what we believe corresponds to the membrane bound form of Nectin-4 and have now confirm such by flow cytometry and immunofluorescence probing for Nectin-4 in the RT112 cell line. We have also seen statistically significant increases in NECTIN4 on RT-PCR following treatment with erdafitinib; however, we believe that Nectin-4 regulation by FGFR inhibition is not merely transcriptional because the induction of Nectin-4 protein appears significantly greater than the fold increase in mRNA. Notably, in two additional UC cell lines (HT1376 - a luminal cell line with high Nectin-4 expression &amp; UMUC3 - a basal cell line with low Nectin-4 expression), with no alterations in FGFR3, we did not see a significant change in Nectin-4 expression following treatment with erdafitinib. Based on our above results, we hypothesize that FGFR3 inhibition, in tumors harboring FGFR3 alterations, may act as a sensitize agent to Nectin-4 ADC targeted therapy; however, our results are preliminary and further investigation, particularly with in vivo models, is warranted. Citation Format: Sean Clark-Garvey, Mi Zhou, Andrew Truong, Wolfgang Beckabir, Michael Sturdivant, William Kim. Effect of FGFR3 activity on Nectin-4 expression in urothelial carcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4867.

Uncertainty Estimation for Heatmap-Based Landmark Localization.

Automatic anatomical landmark localization has made great strides by leveraging deep learning methods in recent years. The ability to quantify the uncertainty of these predictions is a vital component needed for these methods to be adopted in clinical settings, where it is imperative that erroneous predictions are caught and corrected. We propose Quantile Binning, a data-driven method to categorize predictions by uncertainty with estimated error bounds. Our framework can be applied to any continuous uncertainty measure, allowing straightforward identification of the best subset of predictions with accompanying estimated error bounds. We facilitate easy comparison between uncertainty measures by constructing two evaluation metrics derived from Quantile Binning. We compare and contrast three epistemic uncertainty measures (two baselines, and a proposed method combining aspects of the two), derived from two heatmap-based landmark localization model paradigms (U-Net and patch-based). We show results across three datasets, including a publicly available Cephalometric dataset. We illustrate how filtering out gross mispredictions caught in our Quantile Bins significantly improves the proportion of predictions under an acceptable error threshold. Finally, we demonstrate that Quantile Binning remains effective on landmarks with high aleatoric uncertainty caused by inherent landmark ambiguity, and offer recommendations on which uncertainty measure to use and how to use it. The code and data are available at https://github.com/schobs/qbin.

D-Transposition of the great arteries with restrictive foramen ovale in the fetus: the dilemma of predicting the need for postnatal urgent balloon atrial septostomy

ObjectiveRestrictive foramen ovale (FO) in dextro-transposition of the great arteries (d-TGA) with intact ventricular septum may lead to severe life-threatening hypoxia within the first hours of life, making urgent balloon atrial septostomy (BAS) inevitable. Reliable prenatal prediction of restrictive FO is crucial in these cases. However, current prenatal echocardiographic markers show low predictive value, and prenatal prediction often fails with fatal consequences for a subset of newborns. In this study, we described our experience and aimed to identify reliable predictive markers for BAS.MethodsWe included 45 fetuses with isolated d-TGA that were diagnosed and delivered between 2010 and 2022 in two large German tertiary referral centers. Inclusion criteria were the availability of former prenatal ultrasound reports, of stored echocardiographic videos and still images, which had to be obtained within the last 14 days prior to delivery and that were of sufficient quality for retrospective re-analysis. Cardiac parameters were retrospectively assessed and their predictive value was evaluated.ResultsAmong the 45 included fetuses with d-TGA, 22 neonates had restrictive FO postnatally and required urgent BAS within the first 24 h of life. In contrast, 23 neonates had normal FO anatomy, but 4 of them unexpectedly showed inadequate interatrial mixing despite their normal FO anatomy, rapidly developed hypoxia and also required urgent BAS (‘bad mixer’). Overall, 26 (58%) neonates required urgent BAS, whereas 19 (42%) achieved good O2 saturation and did not undergo urgent BAS. In the former prenatal ultrasound reports, restrictive FO with subsequent urgent BAS was correctly predicted in 11 of 22 cases (50% sensitivity), whereas a normal FO anatomy was correctly predicted in 19 of 23 cases (83% specificity). After current re-analysis of the stored videos and images, we identified three highly significant markers for restrictive FO: a FO diameter < 7 mm (p < 0.01), a fixed (p = 0.035) and a hypermobile (p = 0.014) FO flap. The maximum systolic flow velocities in the pulmonary veins were also significantly increased in restrictive FO (p = 0.021), but no cut-off value to reliably predict restrictive FO could be identified. If the above markers are applied, all 22 cases with restrictive FO and all 23 cases with normal FO anatomy could correctly be predicted (100% positive predictive value). Correct prediction of urgent BAS also succeeded in all 22 cases with restrictive FO (100% PPV), but naturally failed in 4 of the 23 cases with correctly predicted normal FO (‘bad mixer’) (82.6% negative predictive value).ConclusionPrecise assessment of FO size and FO flap motility allows a reliable prenatal prediction of both restrictive and normal FO anatomy postnatally. Prediction of likelihood of urgent BAS also succeeds reliably in all fetuses with restrictive FO, but identification of the small subset of fetuses that also requires urgent BAS despite their normal FO anatomy fails, because the ability of sufficient postnatal interatrial mixing cannot be predicted prenatally. Therefore, all fetuses with prenatally diagnosed d-TGA should always be delivered in a tertiary center with cardiac catheter stand-by, allowing BAS within the first 24 h after birth, regardless of their predicted FO anatomy.

Pretransplant systemic metabolic profiles in allogeneic hematopoietic stem cell transplant recipients - identification of patient subsets with increased transplant-related mortality

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is used in the treatment of high-risk acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS), however, the treatment has high risk of severe transplant-related mortality (TRM). In this study, we examined pretransplant serum samples derived from 92 consecutive allotransplant recipients with AML or MDS. Using non-targeted metabolomics, we identified 1274 metabolites including 968 of known identity (named biochemicals). We further investigated metabolites that differed significantly when comparing patients with and without early extensive fluid retention, pretransplant inflammation (both being associated with increased risk of acute graft-versus-host disease (GVHD)/nonrelapse mortality) and development of systemic steroid-requiring acute GVHD (aGVHD). All three factors are associated with TRM and were also associated with significantly altered amino acid metabolism, though there was only a minor overlap between these three factors with regard to significantly altered individual metabolites. Furthermore, steroid-requiring aGVHD was especially associated with altered taurine/hypotaurine, tryptophan, biotin, and phenylacetate metabolism together with altered malate-aspartate shuttle and urea cycle regulation. In contrast, pretransplant inflammation was associated with a weaker modulation of many different metabolic pathways, whereas extensive fluid retention was associated with a weaker modulation of taurine/hypotaurine metabolism. An unsupervised hierarchical cluster analysis based on the 13 most significantly identified metabolites associated with aGVHD identified a patient subset with high metabolite levels and increased frequencies of MDS/MDS-AML, steroid-requiring aGVHD and early TRM. On the other hand, a clustering analysis based on metabolites that were significantly altered for aGVHD, inflammation and fluid retention comparison groups identified a patient subset with a highly significant association with TRM. Our study suggests that the systemic pretransplant metabolic profiles can be used to identify patient subsets with an increased frequency of TRM.

A Single-Cell RNA-Sequencing Analysis of Distinct Subsets of Synovial Macrophages in Rheumatoid Arthritis

The polarization states and molecular signatures of macrophages in the synovium of patients with rheumatoid arthritis (RA) are not well understood. We aimed to identify specific subpopulations of macrophages and their features in RA synovium thereby providing a theoretical basis for treatment of RA. Single-cell RNA sequencing (scRNA-seq) was used to identify cell subsets and their gene signatures in synovial cells of patients with RA and osteoarthritis (OA). Spatial distribution of macrophages was visualized by deconvolving spatial transcriptomic data with scRNA-seq data. Flow cytometry and immunofluorescence were applied to investigate the expression of macrophage polarization indicators CD86 and CD206. Trajectory analysis was used to determine differentiation relationships. Transcription factor (TF) analysis was performed to find specific TFs. scRNA-seq identified three cell clusters of macrophages: M0-like MARCO+ Mϕ1, M2-like CSF1R+ Mϕ2, and M1-like PLAUR+ Mϕ3. Mϕ1 distributed widely in the synovium, whereas Mϕ2 and Mϕ3 distributed sparsely. CD86 and CD206 were both upregulated in macrophages of RA synovium, especially in lining layer. Trajectory analysis showed that Mϕ1 existed at the start of the differentiation trajectory. HOXB6, STAT1, and NFKB2 were TFs specific to Mϕ1, Mϕ2, and Mϕ3 under RA condition, respectively. Compared with in OA condition, three macrophage clusters upregulated CXCL2, CXCL1, IL1B, TNFAIP3, ICAM1, CXCL3, PLAU, CCL4L2, CCL4, and TNF in NF-kappa B signaling pathway. The identification of macrophage subsets with different polarized states and their molecular signatures provided a more precise understanding of macrophages, which may contribute to the development of novel therapeutic strategy for RA.

Calcium imaging and analysis of the jugular-nodose ganglia enables identification of distinct vagal sensory neuron subsets

Objective. Sensory nerves of the peripheral nervous system (PNS) transmit afferent signals from the body to the brain. These peripheral nerves are composed of distinct subsets of fibers and associated cell bodies, which reside in peripheral ganglia distributed throughout the viscera and along the spinal cord. The vagus nerve (cranial nerve X) is a complex polymodal nerve that transmits a wide array of sensory information, including signals related to mechanical, chemical, and noxious stimuli. To understand how stimuli applied to the vagus nerve are encoded by vagal sensory neurons in the jugular-nodose ganglia, we developed a framework for micro-endoscopic calcium imaging and analysis. Approach. We developed novel methods for in vivo imaging of the intact jugular-nodose ganglion using a miniature microscope (Miniscope) in transgenic mice with the genetically-encoded calcium indicator GCaMP6f. We adapted the Python-based analysis package Calcium Imaging Analysis (CaImAn) to process the resulting one-photon fluorescence data into calcium transients for subsequent analysis. Random forest classification was then used to identify specific types of neuronal responders. Results. We demonstrate that recordings from the jugular-nodose ganglia can be accomplished through careful surgical dissection and ganglia stabilization. Using a customized acquisition and analysis pipeline, we show that subsets of vagal sensory neurons respond to different chemical stimuli applied to the vagus nerve. Successful classification of the responses with a random forest model indicates that certain calcium transient features, such as amplitude and duration, are important for encoding these stimuli by sensory neurons. Significance. This experimental approach presents a new framework for investigating how individual vagal sensory neurons encode various stimuli on the vagus nerve. Our surgical and analytical approach can be applied to other PNS ganglia in rodents and other small animal species to elucidate previously unexplored roles for peripheral neurons in a diverse set of physiological functions.

4P Optimizing utilization of antibody-drug conjugates in NSCLC by identification of subsets using RNA sequencing

4P Optimizing utilization of antibody-drug conjugates in NSCLC by identification of subsets using RNA sequencing

A proficient two stage model for identification of promising gene subset and accurate cancer classification

A proficient two stage model for identification of promising gene subset and accurate cancer classification