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End-stage renal disease has traditionally been noted to disproportionately affect patients with fewer resources. Our goal was to assess practice patterns and outcomes in patients with unstable housing undergoing permanent hemodialysis access creation.A retrospective, single-center review of patients with unstable housing was conducted. Perioperative and long-term outcomes were assessed. Univariable and multivariable analysis as well as Kaplan-Meier analysis were performed.There were 144 patients (63% male) identified with a mean age of 57 years. Thirty-three percent of patients had no current permanent residence, and 81% had at least 3 addresses the year before operation. Access type included brachiocephalic (48%), brachiobasilic (19%), radiocephalic fistulas (11%), and prosthetic grafts (19%). Thirty-day readmission was seen in 27.8% of patients. Kaplan-Meier analysis showed that 1-year and 4-year patient survival were 94.4% and 80.6%, respectively. Multivariable analysis demonstrated that newly formed access (odds ratio [OR] 3.66, 95% CI 1.02 to 13.16, p = 0.05), absence of a permanent residence (OR 2.92, 95% CI 1.15 to 7.44, p = 0.03), and female gender (OR 2.86, 95% CI, 1.18 to 7.14, p = 0.02) were associated with 90-day readmission. Multivariable analysis of mortality revealed that previous stroke (hazard ratio [HR] 7.15, 95% CI 1.93 to 26.5, p = 0.003), history of alcohol use disorder (HR 4.55, 95% CI 1.22 to 16.99, p = 0.024), and age (HR 1.10, 95% CI, 1.02 to 1.18, p = 0.017) were associated with 4-year mortality; housing instability was not associated with decreased survival. Preoperative tunneled dialysis catheter (HR 1.63, 95% CI 1.02 to 2.61, p = 0.04) was associated with 4-year reintervention and frequent address change (HR 0.47, 95% CI 0.27 to 0.81, p = 0.01) was found to be a protective factor against long-term reintervention.Poor outcomes in patients with unstable housing were primarily driven by comorbidities. Lack of permanent residence was significantly associated with readmission.

Supplementary Methods and Figure legends

MetaCoreTM schematic of the TGF-β signaling pathway showing genes regulated by miR-17 TuD in Hep3B (1) and HepG2 (2).

The PI3K/AKT/mTOR pathway is often activated in lymphoma through alterations in PI3K, PTEN, and B-cell receptor signaling, leading to dysregulation of eIF4A (through its regulators, eIF4B, eIF4G, and PDCD4) and the eIF4F complex. Activation of eIF4F has a direct role in tumorigenesis due to increased synthesis of oncogenes that are dependent on enhanced eIF4A RNA helicase activity for translation. eFT226, which inhibits translation of specific mRNAs by promoting eIF4A1 binding to 5′-untranslated regions (UTR) containing polypurine and/or G-quadruplex recognition motifs, shows potent antiproliferative activity and significant in vivo efficacy against a panel of diffuse large B-cell lymphoma (DLBCL), and Burkitt lymphoma models with ≤1 mg/kg/week intravenous administration. Evaluation of predictive markers of sensitivity or resistance has shown that activation of eIF4A, mediated by mTOR signaling, correlated with eFT226 sensitivity in in vivo xenograft models. Mutation of PTEN is associated with reduced apoptosis in vitro and diminished efficacy in vivo in response to eFT226. In models evaluated with PTEN loss, AKT was stimulated without a corresponding increase in mTOR activation. AKT activation leads to the degradation of PDCD4, which can alter eIF4F complex formation. The association of eFT226 activity with PTEN/PI3K/mTOR pathway regulation of mRNA translation provides a means to identify patient subsets during clinical development.

Expression levels of miR-17 TuD. The data are expressed as delta CT value normalized to GAPDH.

Inhibition of miR-17, 20a, 20b, 93 and 106b activity by miR-17 TuD in HeLa cells as determined by luciferase reporter assays.

Tables S1-S3, Figures S1-S5

Inhibition of miR-17 family by miR-17 TuD had no effect on caspase 3/7 activity. Caspase 3/7 activity was represented as relative activity compared to NC TuD expression cells.

Neurotrauma, especially repetitive neurotrauma, is associated with the development of progressive neurodegeneration leading to chronic traumatic encephalopathy (CTE). Exposure to neurotrauma regularly occurs during sports and military service, often not requiring medical care. However, exposure to severe and/or repeated sub-clinical neurotrauma has been shown cause physical and psychological disability, leading to reduce life expectancy. Misfolding of proteins, or proteinopathy, is a pathological hallmark of CTE, in which chronic injury leads to local and diffuse protein aggregates. These aggregates are an overlapping feature of many neurodegenerative diseases such as CTE, Alzheimer’s Disease, Parkinsons disease. Neurotrauma is also a significant risk factor for the development of these diseases, however the mechanism’s underlying this association are not well understood. While phosphorylated tau aggregates are the primary feature of CTE, amyloid-beta, Transactive response DNA-binding protein 43 (TDP-43), and alpha-synuclein (αSyn) are also well documented. Aberrant misfolding of these proteins has been shown to disrupt brain homeostasis leading to neurodegeneration in a disease dependent manor. In CTE, the interaction between proteinopathies and their associated neurodegeneration is a current area of study. Here we provide an update on current literature surrounding the prevalence, characteristics, and pathogenesis of proteinopathies in CTE.

Ovarian cancer is one of the leading causes of cancer-related deaths among women in the United States. Metastasis to the central nervous system has become more frequent in the previous decades, however, treatment options remain limited. In this review, we discuss the pathophysiology of ovarian cancer and how metastasis to the central nervous system typically occurs. We then discuss cases of metastasis presented in the literature to evaluate current treatment regimens and protocols. Finally, we highlight emerging treatment options that are being utilized in clinics to provide personalized treatment therapy for a patient’s unique diagnosis. This review aims to further the understanding of pathophysiology, stimulate further innovative treatments, and present accessible resources through tables and figures.

Gray zone, a measure of tissue heterogeneity on late gadolinium enhanced-cardiac magnetic resonance (LGE-CMR) imaging, has been shown to predict ventricular arrhythmias (VAs) in ischemic cardiomyopathy (ICM) patients. However, no studies have described whether left ventricular (LV) tissue heterogeneity and intramyocardial fat mass on contrast-enhanced computed tomography (CE-CT), which provides greater spatial resolution, is useful for assessing the risk of VAs in ICM patients with LV systolic dysfunction and no previous VAs.The purpose of this proof-of-concept study was to determine the feasibility of measuring global LV tissue heterogeneity and intramyocardial fat mass by CE-CT for predicting the risk of VAs in ICM patients with LV systolic dysfunction and no previous history of VAs.Patients with left ventricular ejection fraction ≤35% and no previous VAs were enrolled in a prospective, observational registry and underwent LGE-CMR. From this cohort, patients with ICM who additionally received CE-CT were included in the present analysis. Gray zone on LGE-CMR was defined as myocardium with signal intensity (SI)peak SI of healthy myocardium but50% maximal SI. Tissue heterogeneity on CE-CT was defined as the standard deviation of the Hounsfield unit image gradients (HU/mm) within the myocardium. Intramyocardial fat on CE-CT was identified as regions of image pixels between -180 and -5 HU. The primary outcome was VAs, defined as appropriate implantable cardioverter-defibrillator shock or sudden arrhythmic death.The study consisted of 47 ICM patients, 13 (27.7%) of whom experienced VA events during mean follow-up of 5.6 ± 3.4 years. Increasing tissue heterogeneity (per HU/mm) was significantly associated with VAs after multivariable adjustment, including for gray zone (odds ratio [OR] 1.22;In ICM patients, CE-CT-derived LV tissue heterogeneity was independently associated with VAs and may represent a novel marker useful for risk stratification.

Aims Multiple wavefront pacing (MWP) and decremental pacing (DP) are two electroanatomic mapping (EAM) strategies that have emerged to better characterize the ventricular tachycardia (VT) substrate. The aim of this study was to assess how well MWP, DP, and their combination improve identification of electrophysiological abnormalities on EAM that reflect infarct remodelling and critical VT sites. Methods and results Forty-eight personalized computational heart models were reconstructed using images from post-infarct patients undergoing VT ablation. Paced rhythms were simulated by delivering an initial (S1) and an extra-stimulus (S2) from one of 100 locations throughout each heart model. For each pacing, unipolar signals were computed along the myocardial surface to simulate substrate EAM. Six EAM features were extracted and compared with the infarct remodelling and critical VT sites. Concordance of S1 EAM features between different maps was lower in hearts with smaller amounts of remodelling. Incorporating S1 EAM features from multiple maps greatly improved the detection of remodelling, especially in hearts with less remodelling. Adding S2 EAM features from multiple maps decreased the number of maps required to achieve the same detection accuracy. S1 EAM features from multiple maps poorly identified critical VT sites. However, combining S1 and S2 EAM features from multiple maps paced near VT circuits greatly improved identification of critical VT sites. Conclusion Electroanatomic mapping with MWP is more advantageous for characterization of substrate in hearts with less remodelling. During substrate EAM, MWP and DP should be combined and delivered from locations proximal to a suspected VT circuit to optimize identification of the critical VT site.

The image is from “Monuments of Memories for Our Times” series which is made with a dedicated consideration to the complexities inherent to the “monument.” In “public Library,” Sung explores documenting vacant community infrastructure as monument of current times to archive the impact of Covid-19.

Background: We developed a novel RIVAL system that consists of a CT-based computational simulation to identify VT circuits and an ECG-based automated approach to localize VT exit sites. Objective: Prospectively assess the ability of the RIVAL system to localize VT circuits and exits. Methods: Patients presenting for VT ablation were enrolled into the study. Pre-procedural cardiac CT was performed and used to conduct heart simulations for predicting VT circuits. The patient’s CT geometry with the predicted VT circuits was registered to the electroanatomic shell created during the procedure and imported into the RIVAL program. During the procedure, exit sites of induced VTs are localized in real-time using the 12-lead ECG onto the patient-specific CT surface. Predicted ablation regions obtained by combining RIVAL-predicted VT circuits with exit sites were analyzed offline to assess localization accuracy to the invasive VT ablation procedure. Results: Four patients with ischemic cardiomyopathy undergoing VT ablation had preprocedural cardiac CT. In P1, two VTs were induced during the procedure. The RIVAL predicted 2 VT circuits and achieved a mean localization error of 7.0mm for VT exit site prediction (Fig1). There was a spatial concordance between the predicted ablation areas and the clinical ablation regions. For P2, three VTs were induced during the VT ablation. A large area of scar was associated with 6 RIVAL-predicted VT circuits. The exit site localization accuracy could not be precisely quantitated because the VTs terminated with ablation at a mid-diastolic site. For P3, no VTs were inducible, however substrate modification (SM) was performed in the anterior-apical LV. The RIVAL predicted only one VT circuit located in the area where SM was performed. No VT was induced for P4 and the RIVAL did not predict any VT circuits. Conclusions: The RIVAL predicts the VT circuit and exit accurately, which may improve the precision of ablation therapies and procedure outcomes.

Immune cell therapies derived from induced pluripotent stem cells (iPSC) provide a novel opportunity for the treatment of multiple cancer types. Assessment of the persistence and biodistribution of these product candidates requires specific and sensitive methods to detect engineered cells in both liquid and solid biopsies. Here, we present the development and validation of two complimentary nucleic acid-based detection assays for iPSC-derived natural killer (iNK) cell product candidates containing Fate’s proprietary high-affinity, non-cleavable CD16 transgene (hnCD16). The first assay is a droplet digital PCR (ddPCR) method to detect and quantify hnCD16 transgene copies present in a pool of genomic DNA (gDNA). The primers and probe were designed to recognize the optimized codons of hnCD16. Assay linearity and accuracy were assessed through titration studies using 0.024 to 1 ng of hnCD16-containing DNA spiked into different amounts of hnCD16-negative gDNA. Precision was determined through multiple assay runs by different operators on two instruments. The second assay is an in situ hybridization based method utilizing RNAscope࣪ technology to detect cells expressing hnCD16 in fixed tissue. Probes targeting hnCD16 were used to optimize signal specificity. Cells expressing hnCD16 and tissues from in vivo studies treated with iNK products served as positive controls. For the ddPCR assay, absolute limit of detection (aLoD) was determined to be 4.9 copies of hnCD16 per 20 µL reaction, regardless of total genomic mass input. Absolute limit of quantification (aLoQ) was 12 copies per 20 µL reaction with a %CV ≤30. Relative limit of quantification (rLoQ), assessing transgene to total DNA ratio, is affected by the background gDNA input and is less sensitive with lower input mass. rLoQ for total mass of 70 - 250 ng was 97 - 22 copies/µg gDNA (0.064% - 0.015%) with a %CV ≤30. The sensitivity of this input range allows evaluation of clinical samples with low cellularity. While ddPCR provides robust quantification of the hnCD16 transcript, the RNAscope࣪ assay informs localization of the iNK product. Specificity of the probe was established by confirming its lack of affinity for endogenous CD16 using a variety of human normal and tumor tissues and by staining hnCD16-positive fixed cell pellets and tissues from in vivo studies. In cell pellets, positive RNAscope࣪ signal correlated with the known ratio of transgene positive cells. In murine tissues previously confirmed to contain iNK cell product, the RNAscope࣪ positive staining correlated with NKG2A immunohistochemistry staining, confirming the presence of product NK cells. The combined use of both the ddPCR and RNAscope࣪ assays targeted to hnCD16 allows for detection and quantification of transgene-bearing iNK cells in a wide variety of patient samples including tumor biopsies. Both assays are being utilized for cell detection and quantification in our ongoing clinical trials. Citation Format: Cara E. Bickers, Judy L. Martin, Steven Castro, Jason Zhang, Thomas Dailey, Eric Sung, Suzanna Gasparian, Jason O'Rourke, Moyar Ge, Tom T. Lee, Janel Huffman, Jode Goodridge, Ryan Bjordahl, Bahram Valamehr, Peter M. Szabo, Lilly Wong, Sarah Cooley. Detection of genetically engineered iPSC-derived natural killer cells in blood and tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1138.

COVID-19 infection carries significant morbidity and mortality. Current risk prediction for complications in COVID-19 is limited, and existing approaches fail to account for the dynamic course of the disease.The purpose of this study was to develop and validate the COVID-HEART predictor, a novel continuously updating risk-prediction technology to forecast adverse events in hospitalized patients with COVID-19.Retrospective registry data from patients with severe acute respiratory syndrome coronavirus 2 infection admitted to 5 hospitals were used to train COVID-HEART to predict all-cause mortality/cardiac arrest (AM/CA) and imaging-confirmed thromboembolic events (TEs) (n = 2,550 and n = 1,854, respectively). To assess COVID-HEART's performance in the face of rapidly changing clinical treatment guidelines, an additional 1,100 and 796 patients, admitted after the completion of development data collection, were used for testing. Leave-hospital-out validation was performed.Over 20 iterations of temporally divided testing, the mean area under the receiver operating characteristic curve were 0.917 (95% confidence interval [CI]: 0.916-0.919) and 0.757 (95% CI: 0.751-0.763) for prediction of AM/CA and TE, respectively. The interquartile ranges of median early warning times were 14 to 21 hours for AM/CA and 12 to 60 hours for TE. The mean area under the receiver operating characteristic curve for the left-out hospitals were 0.956 (95% CI: 0.936-0.976) and 0.781 (95% CI: 0.642-0.919) for prediction of AM/CA and TE, respectively.The continuously updating, fully interpretable COVID-HEART predictor accurately predicts AM/CA and TE within multiple time windows in hospitalized COVID-19 patients. In its current implementation, the predictor can facilitate practical, meaningful changes in patient triage and resource allocation by providing real-time risk scores for these outcomes. The potential utility of the predictor extends to COVID-19 patients after hospitalization and beyond COVID-19.

There is an unmet need for timely and reliable prediction of post-cardiac arrest (CA) clinical trajectories. We hypothesized that physiological time series (PTS) data recorded on the first day of intensive care would contribute significantly to discrimination of outcomes at discharge.Adult patients in the multicenter eICU database who were mechanically ventilated after resuscitation from out-of-hospital CA were included. Outcomes of interest were survival, neurological status based on Glasgow motor subscore (mGCS) and surrogate functional status based on discharge location (DL), at hospital discharge. Three machine learning predictive models were trained, one with features from the electronic health records (EHR), the second using features derived from PTS collected in the first 24 h after ICU admission (PTSData from 2216 admissions were included in the analysis. Discrimination of prediction models combining EHR and PTSThese results indicate that physiological data recorded in the early phase after CA resuscitation contain signatures that are linked to post-CA outcome. Additionally, they attest to the effectiveness of ML for post-CA predictive modeling.

FT819 is a first-of-kind, allogeneic, off-the-shelf CAR T-cell therapy derived from a clonal master induced pluripotent stem cell (iPSC) line precisely engineered to insert a novel 1XX anti-CD19 chimeric antigen receptor (CAR) under the regulation of the T-cell receptor alpha constant (TRAC) locus for optimized control of anti-tumor activity and to completely delete T-cell receptor (TCR) expression to eliminate the potential of graft-versus-host disease (GvHD). Unlike conventional allogeneic CAR T-cell therapies which require repeatedly sourcing of T cells from various donors as the starting material, the use of a clonal master engineered iPSC line serves as a renewable starting cell source and ensures routine mass production of a uniformly engineered, homogenous CAR T-cell product for broad patient access. T cell-derived iPSCs were generated using a proprietary non-integrating cellular reprogramming system and genetically modified to integrate a novel anti-CD19 1XX CAR into both alleles of the TRAC gene. After single cell subcloning, each engineered iPSC clone was screened for multiple critical quality attributes including pluripotency, identity, genomic stability, cassette integration, on/off-target integration, T-cell differentiation propensity, and CAR T-cell function. Accordingly, the ideal single cell-derived engineered iPSC clone was selected as the clonal master iPSC line for FT819 and was converted into a master cell bank (MCB). The iPSC MCB serves as a renewable source for the routine GMP manufacture of FT819 drug product. The FT819 production process consists of three stages: 1) generation of CD34-expressing hematopoietic progenitor cells from iPSCs (>90% CD34+ cells post enrichment); 2) lineage-specification to T cells followed by T-cell expansion (>5e5 fold expansion); and 3) fill/finish and cryopreservation of the drug product. As an example, in an initial small-scale manufacturing campaign, a total of 2.5 × 10 10 FT819 CAR T-cells were generated and filled and finished starting from one vial of the MCB. The FT819 drug product was tested on safety, identity, purity, and potency. The final product was comprised of CD45+CD7+ lymphocytes (>99%), with homogeneous CAR expression (>99% CAR+) and lacking expression of TCRαβ (not detected) on the cell surface. Importantly, there were no residual iPSCs detected in the FT819 drug product. The FT819 drug product exhibited potent and consistent effector function against NALM6 leukemia cells. The FT819 drug product is currently being used in a landmark Phase I study (NCT04629729), the first-ever iPSC-derived T-cell therapy to undergo clinical investigation, for the treatment of patients with relapsed/refractory B-cell lymphoma, chronic lymphocytic leukemia and precursor B-cell acute lymphoblastic leukemia. In summary, FT819 is a first-of-kind, off-the-shelf, CAR T-cell therapy uniquely derived from a clonal multiplexed-engineered master iPSC line. The novel manufacturing paradigm enables mass production of a uniformly engineered, homogenous cell therapy product that is available on-demand for broad patient access. A multi-center Phase 1 study of FT819 is currently ongoing for the treatment of B-cell malignancies. Key Words: cancer immunotherapy, cell therapy, CAR-T, CD19, allogeneic, induced pluripotent stem cell, iPSC, clonal master iPSC line, engineered, off-the-shelf, cGMP, production, manufacturing, FT819 Disclosures Yuan: Fate Therapeutics, Inc.: Current Employment. Clarke: Fate Therapeutics, Inc.: Current Employment. Lai: Fate Therapeutics, Inc.: Current Employment. Chang: Fate Therapeutics, Inc.: Current Employment. Yang: Fate Therapeutics, Inc.: Current Employment. Hsia: Fate Therapeutics, Inc.: Current Employment. Abujarour: Fate Therapeutics, Inc.: Current Employment. Lee: Fate Therapeutics, Inc.: Current Employment. van der Stegen: Fate Therapeutics, Inc.: Current Employment. Shaked: Fate Therapeutics, Inc.: Current Employment. Jalloh: Fate Therapeutics, Inc.: Current Employment. Moreno: Fate Therapeutics, Inc.: Current Employment. ORourke: Fate Therapeutics, Inc.: Current Employment. Sung: Fate Therapeutics, Inc.: Current Employment. Gutierrez: Fate Therapeutics, Inc.: Current Employment. Rezner: Fate Therapeutics, Inc.: Current Employment. Eberhart: Fate Therapeutics, Inc.: Current Employment. Magdaleno: Fate Therapeutics, Inc.: Current Employment. Farnan: Fate Therapeutics, Inc.: Current Employment. Plavsic: Fate Therapeutics, Inc.: Current Employment. Bressi: Fate Therapeutics, Inc.: Current Employment. Rivière: Centre for Commercialization of Cancer Immunotherapy: Other: Provision of Services; Fate Therapeutics: Other: Provision of Services, Patents & Royalties; The Georgia Tech Research Corporation (GTRC): Other: Provision of Services (uncompensated); FloDesign Sonics: Other: Provision of Services; Juno Therapeutics: Patents & Royalties. Valamehr: Fate Therapeutics, Inc.: Current Employment.