Human Clinical Data Research Articles

Application of robust regression in translational neuroscience studies with non-Gaussian outcome data.

Linear regression is one of the most used statistical techniques in neuroscience, including the study of the neuropathology of Alzheimer's disease (AD) dementia. However, the practical utility of this approach is often limited because dependent variables are often highly skewed and fail to meet the assumption of normality. Applying linear regression analyses to highly skewed datasets can generate imprecise results, which lead to erroneous estimates derived from statistical models. Furthermore, the presence of outliers can introduce unwanted bias, which affect estimates derived from linear regression models. Although a variety of data transformations can be utilized to mitigate these problems, these approaches are also associated with various caveats. By contrast, a robust regression approach does not impose distributional assumptions on data allowing for results to be interpreted in a similar manner to that derived using a linear regression analysis. Here, we demonstrate the utility of applying robust regression to the analysis of data derived from studies of human brain neurodegeneration where the error distribution of a dependent variable does not meet the assumption of normality. We show that the application of a robust regression approach to two independent published human clinical neuropathologic data sets provides reliable estimates of associations. We also demonstrate that results from a linear regression analysis can be biased if the dependent variable is significantly skewed, further indicating robust regression as a suitable alternate approach.

Molecular Pathways and Animal Models of Arrhythmias.

Arrhythmias account for over 300,000 annual deaths in the United States, and approximately half of all deaths are associated with heart disease. Mechanisms underlying arrhythmia risk are complex; however, work in humans and animal models over the past 25 years has identified a host of molecular pathways linked with both arrhythmia substrates and triggers. This chapter will focus on select arrhythmia pathways solved by linking human clinical and genetic data with animal models.

Commitment Complex Splicing Factors in Cancers of the Gastrointestinal Tract-An In Silico Study.

The initial step in pre-mRNA splicing involves formation of a spliceosome commitment complex (CC) or E-complex by factors that serve to bind and mark the exon-intron boundaries that will undergo splicing. The CC component U1 snRNP assembles at the 5'-splice site (ss), whereas SF1, U2AF2, and U2AF1 define the 3'-ss of the intron. A PRP40 protein bridges U1 snRNP with factors at the 3'-ss. To determine how defects in CC components impact cancers, we analyzed human gastrointestinal (GI) cancer patient tissue and clinical data from cBioPortal. cBioPortal datasets were analyzed for CC factor alterations and patient outcomes in GI cancers (bowel, stomach, esophagus, pancreas, and liver). In addition, co-expression datasets were used to determine the splicing targets of the CC. Our analysis found that frequency of genetic changes was low (1%-13%), but when combined with changes in expression levels, there was an overall surprisingly high incidence of CC component (>30%) alterations in GI cancers. Colon cancer patients carrying BRAF driver gene mutations had high incidences of CC alterations (19%-61%), whereas patients with APC, KRAS, or TP53 gene mutations had low (<5%) incidences of CC alterations. Most significantly, patients with mutations in CC genes exhibited a consistent trend of favorable survival rates, indicating that mutations that impair or lower CC component expression favor patient survival. Conversely, patients with high CC expression had worse survival. Pathway analysis indicates that the CC regulates specific metabolic and tumor suppressor pathways. Metabolic pathways involved in cell survival, nutrition, biosynthesis, autophagy, cellular movement (invasion), or immune surveillance pathways correlated with CC factor upregulation, whereas tumor suppressor pathways, which regulate cell proliferation and apoptosis, were inversely correlated with CC factor upregulation. This study demonstrates the versatility of in silico analysis to determine molecular function of large macromolecular complexes such as the spliceosome CC. Furthermore, our analysis indicates that therapeutic lowering of CC levels in colon cancer patients may enhance patient survival.

A latent code based multi-variable modulation network for susceptibility mapping.

Quantitative susceptibility mapping (QSM) is a technique for obtaining quantitative information on tissue susceptibility and has shown promising potential for clinical applications, in which the magnetic susceptibility is calculated by solving an ill-posed inverse problem. Recently, deep learning-based methods are proposed to address this issue, but the diversity of data distribution was not well considered, and thus the model generalization is limited in clinical applications. In this paper, we propose a Latent Code based Multi-Variable modulation network for QSM reconstruction (LCMnet). Particularly, a specific modulation module is exploited to incorporate three variables, i.e., field map, magnitude image, and initial susceptibility. The latent code in the modulated convolution is learned from feature maps of the field data using the encoder-decoder framework. The susceptibility map pre-estimated from simple thresholding is the constant input of the module, thereby enhancing the network stability and accelerating training convergence. As another input, multi-level features generated by a cross-fusion block integrate the information of field and magnitude data effectively. Experimental results on in vivo human brain data, challenge data, clinical data and synthetic data demonstrate that the proposed method LCMnet can achieve outstanding performance on accurate susceptibility measurement and also excellent generalization.

A botanical reference set illustrating a weight of evidence approach for skin sensitization risk assessment

Recent years have seen an increase in the use of botanicals and natural substances (BNS) in consumer products such as cosmetics and household care products. Most work conducted to date to assess botanicals for human safety has focused their use as dietary supplements and thus on systemic toxicity. However, the induction of skin sensitization is a possible adverse effect of natural products in particular those that come into skin contact, especially for cosmetics that remain on the skin and are not rinsed off following use. Assessments of BNS ingredients are often challenging for a number of reasons: the BNS are complex mixtures that can be of mostly unknown composition; the composition can be highly variable even within the same plant species and dependent on how processed; the physical form of the BNS raw material can vary from a highly concentrated powdered extract to a liquid extract containing only a small percentage of the BNS; testing of the BNS raw materials in New Approach Methods (NAM) has uncertainty as these methods are often not developed or validated for complex mixtures. In this study, a reference set of 14 selected BNS which span the range of skin sensitization potential was complied. These data were used in a Weight of Evidence (WoE) approach to evaluate their skin sensitization potential with each of the data rich BNS being classified as either having strong evidence of inducing skin sensitization based on human topical use history, animal data, clinical data, composition data and NAM data, or having some but more limited (weak) evidence of inducing skin sensitization, or having strong evidence of no skin sensitization potential. When available data have sufficient potency related information, sensitization potency assessment is also provided based on WoE, classifying these BNS as either strong, moderate, or weak sensitizers, or non-sensitizers. An outline for a BNS skin sensitization risk assessment framework is proposed starting with exposure-based waiving and WoE assessment for higher exposures. In addition to demonstrating the application of the WoE approach, the reference set presented here provides a set of ‘data rich’ botanicals which cover a range of sensitization potencies that could be used for evaluating existing test methods or aid in the development of new predictive models for skin sensitization.

The Emerging Role of MicroRNAs in Female Reproductive Diseases

Female infertility represents a significant global medical concern, attributable to a spectrum of disorders affecting the reproductive system, which encompasses premature ovarian insufficiency (POI), polycystic ovary syndrome (PCOS), Asherman syndrome (AS), endometriosis, preeclampsia, ovarian cancer, and endometrial cancer. It exerts a pervasive impact on women's reproductive well-being on a global scale. Recent years have witnessed a mounting body of evidence, drawing from investigations employing murine models and human clinical data, which elucidates the dysfunction of microRNAs (miRNAs) in various reproductive pathologies. This dysfunction, it appears, plays a pivotal role in the context of female gametogenesis and fertility. Nonetheless, the precise mechanistic links between miRNA dysfunction and the pathogenesis of these disorders remain, in many cases, inadequately understood. This comprehensive review endeavors to shed light on recent advancements in research pertaining to the regulatory functions of miRNAs in the etiology of diverse reproductive disorders that culminate in infertility. Furthermore, it addresses the potential utility of miRNAs as diagnostic biomarkers and therapeutic targets for these conditions. The paper also examines the existing limitations and challenges inherent to the clinical application of miRNAs in this context.

Towards system genetics analysis of head and neck squamous cell carcinoma using the mouse model, cellular platform, and clinical human data.

Head and neck squamous cell cancer (HNSCC) is a leading global malignancy. Every year, More than 830 000 people are diagnosed with HNSCC globally, with more than 430 000 fatalities. HNSCC is a deadly diverse malignancy with many tumor locations and biological characteristics. It originates from the squamous epithelium of the oral cavity, oropharynx, nasopharynx, larynx, and hypopharynx. The most frequently impacted regions are the tongue and larynx. Previous investigations have demonstrated the critical role of host genetic susceptibility in the progression of HNSCC. Despite the advances in our knowledge, the improved survival rate of HNSCC patients over the last 40 years has been limited. Failure to identify the molecular origins of development of HNSCC and the genetic basis of the disease and its biological heterogeneity impedes the development of new therapeutic methods. These results indicate a need to identify more genetic factors underlying this complex disease, which can be better used in early detection and prevention strategies. The lack of reliable animal models to investigate the underlying molecular processes is one of the most significant barriers to understanding HNSCC tumors. In this report, we explore and discuss potential research prospects utilizing the Collaborative Cross mouse model and crossing it to mice carrying single or double knockout genes (e.g. Smad4 and P53 genes) to identify genetic factors affecting the development of this complex disease using genome-wide association studies, epigenetics, microRNA, long noncoding RNA, lncRNA, histone modifications, methylation, phosphorylation, and proteomics.

Human Error and Clinical Data Sharing

Computer security issues have a widespread impact across all sectors and are increasingly influencing the healthcare industry. Since 2019, several reported attacks have been specifically aimed at exploiting vulnerabilities in medical network protocols like 'DICOM' and 'HL7,' as well as file formats, particularly those related to digital imaging and medical communications. While numerous articles delve into subjects such as security and blockchain, they often disregard the significant role that human errors play in compromising security. Human errors within hospital computer systems can lead to substantial implications for both patient care and data security. This article delves into the various forms of human errors that can occur within such systems and assesses their potential consequences on the overall effectiveness and security of healthcare information management. The study underscores the necessity of effective mitigation strategies to reduce the associated risks of these errors and enhance the dependability of hospital computer systems

The 2023 Walter B. Cannon Award Lecture: Mechanisms Regulating Vascular Function and Blood Pressure by the PPARγ-RhoBTB1-CUL3 Pathway.

Human genetic and clinical trial data suggest that peroxisome proliferator activated receptor γ (PPARγ), a nuclear receptor transcription factor plays an important role in the regulation of arterial blood pressure. The examination of a series of novel animal models, coupled with transcriptomic and proteomic analysis, has revealed that PPARγ and its target genes employ diverse pathways to regulate vascular function and blood pressure. In endothelium, PPARγ target genes promote an antioxidant state, stimulating both nitric oxide (NO) synthesis and bioavailability, essential components of endothelial-smooth muscle communication. In vascular smooth muscle, PPARγ induces the expression of a number of genes that promote an antiinflammatory state and tightly control the level of cGMP, thus promoting responsiveness to endothelial-derived NO. One of the PPARγ targets in smooth muscle, Rho related BTB domain containing 1 (RhoBTB1) acts as a substrate adaptor for proteins to be ubiquitinated by the E3 ubiquitin ligase Cullin-3 and targeted for proteasomal degradation. One of these proteins, phosphodiesterase 5 (PDE5) is a target of the Cullin-3/RhoBTB1 pathway. Phosphodiesterase 5 degrades cGMP to GMP and thus regulates the smooth muscle response to NO. Moreover, expression of RhoBTB1 under condition of RhoBTB1 deficiency reverses established arterial stiffness. In conclusion, the coordinated action of PPARγ in endothelium and smooth muscle is needed to maintain NO bioavailability and activity, is an essential regulator of vasodilator/vasoconstrictor balance, and regulates blood vessel structure and stiffness.

Differences and Similarities of the Intravenously Administered Lipid Nanoparticles in Three Clinical Trials: Potential Linkage between Lipid Nanoparticles and Extracellular Vesicles.

Lipid nanoparticles (LNPs) are clinically validated drug-delivery carriers. However, clinical data on intravenously administered LNPs are limited compared with those on intramuscularly administered LNPs (mRNA vaccines against COVID-19). Here, we reviewed three clinically tested intravenously administered LNPs (patisiran, mRNA-1944, and NTLA-2001). We summarize the differences and similarities in their formulations, mechanisms of action, and pharmacokinetics profiles. In humans, patisiran and mRNA-1944 exhibited similar multiphasic pharmacokinetic profiles with a secondary peak in the RNA concentration. siRNA (patisiran) and mRNA (mRNA-1944) exhibited prolonged blood circulation and were detectable for more than 28 days after a single administration. We further summarize the basics of extracellular vesicles (EVs) and discuss the potential linkages between LNPs and EVs. This Review provides an understanding of the human clinical data of intravenous LNP formulations, which can be potentially explored to develop next-generation LNP-and EV-based drug delivery carriers.

CBX4 deletion promotes tumorigenesis under KrasG12D background by inducing genomic instability

Chromobox protein homolog 4 (CBX4) is a component of the Polycomb group (PcG) multiprotein Polycomb repressive complexes 1 (PRC1), which is participated in several processes including growth, senescence, immunity, and tissue repair. CBX4 has been shown to have diverse, even opposite functions in different types of tissue and malignancy in previous studies. In this study, we found that CBX4 deletion promoted lung adenocarcinoma (LUAD) proliferation and progression in KrasG12D mutated background. In vitro, over 50% Cbx4L/L, KrasG12D mouse embryonic fibroblasts (MEFs) underwent apoptosis in the initial period after Adeno-Cre virus treatment, while a small portion of survival cells got increased proliferation and transformation abilities, which we called selected Cbx4−/−, KrasG12D cells. Karyotype analysis and RNA-seq data revealed chromosome instability and genome changes in selected Cbx4−/−, KrasG12D cells compared with KrasG12D cells. Further study showed that P15, P16 and other apoptosis-related genes were upregulated in the primary Cbx4−/−, KrasG12D cells due to chromosome instability, which led to the large population of cell apoptosis. In addition, multiple pathways including Hippo pathway and basal cell cancer-related signatures were altered in selected Cbx4−/−, KrasG12D cells, ultimately leading to cancer. We also found that low expression of CBX4 in LUAD was associated with poorer prognosis under Kras mutation background from the human clinical data. To sum up, CBX4 deletion causes genomic instability to induce tumorigenesis under KrasG12D background. Our study demonstrates that CBX4 plays an emerging role in tumorigenesis, which is of great importance in guiding the clinical treatment of lung adenocarcinoma.

Amiodarone prevents wave front-tail interactions in patients with heart failure: an in silico study.

Amiodarone (AM) is an antiarrhythmic drug whose chronic use has proved effective in preventing ventricular arrhythmias in a variety of patient populations, including those with heart failure (HF). AM has both class III [i.e., it prolongs the action potential duration (APD) via blocking potassium channels) and class I (i.e., it affects the rapid sodium channel) properties; however, the specific mechanism(s) by which it prevents reentry formation in patients with HF remains unknown. We tested the hypothesis that AM prevents reentry induction in HF during programmed electrical stimulation (PES) via its ability to induce postrepolarization refractoriness (PRR) via its class I effects on sodium channels. Here we extend our previous human action potential model to represent the effects of both HF and AM separately by calibrating to human tissue and clinical PES data, respectively. We then combine these models (HF + AM) to test our hypothesis. Results from simulations in cells and cables suggest that AM acts to increase PRR and decrease the elevation of takeoff potential. The ability of AM to prevent reentry was studied in silico in two-dimensional sheets in which a variety of APD gradients (ΔAPD) were imposed. Reentrant activity was induced in all HF simulations but was prevented in 23 of 24 HF + AM models. Eliminating the AM-induced slowing of the recovery of inactivation of the sodium channel restored the ability to induce reentry. In conclusion, in silico testing suggests that chronic AM treatment prevents reentry induction in patients with HF during PES via its class I effect to induce PRR.NEW & NOTEWORTHY This work presents a new model of the action potential of the human, which reproduces the complex dynamics during premature stimulation in heart failure patients with and without amiodarone. A specific mechanism of the ability of amiodarone to prevent reentrant arrhythmias is presented.

Computational mechanobiology model evaluating healing of postoperative cavities following breast-conserving surgery

Breast cancer is the most commonly diagnosed cancer type worldwide. Given high survivorship, increased focus has been placed on long-term treatment outcomes and patient quality of life. While breast-conserving surgery (BCS) is the preferred treatment strategy for early-stage breast cancer, anticipated healing and breast deformation (cosmetic) outcomes weigh heavily on surgeon and patient selection between BCS and more aggressive mastectomy procedures. Unfortunately, surgical outcomes following BCS are difficult to predict, owing to the complexity of the tissue repair process and significant patient-to-patient variability. To overcome this challenge, we developed a predictive computational mechanobiological model that simulates breast healing and deformation following BCS. The coupled biochemical-biomechanical model incorporates multi-scale cell and tissue mechanics, including collagen deposition and remodeling, collagen-dependent cell migration and contractility, and tissue plastic deformation. Available human clinical data evaluating cavity contraction and histopathological data from an experimental porcine lumpectomy study were used for model calibration. The computational model was successfully fit to data by optimizing biochemical and mechanobiological parameters through Gaussian process surrogates. The calibrated model was then applied to define key mechanobiological parameters and relationships influencing healing and breast deformation outcomes. Variability in patient characteristics including cavity-to-breast volume percentage and breast composition were further evaluated to determine effects on cavity contraction and breast cosmetic outcomes, with simulation outcomes aligning well with previously reported human studies. The proposed model has the potential to assist surgeons and their patients in developing and discussing individualized treatment plans that lead to more satisfying post-surgical outcomes and improved quality of life.

Amplifying the Effects of Contrast Agents on Magnetic Resonance Images Using a Deep Learning Method Trained on Synthetic Data.

Artificial intelligence (AI) methods can be applied to enhance contrast in diagnostic images beyond that attainable with the standard doses of contrast agents (CAs) normally used in the clinic, thus potentially increasing diagnostic power and sensitivity. Deep learning-based AI relies on training data sets, which should be sufficiently large and diverse to effectively adjust network parameters, avoid biases, and enable generalization of the outcome. However, large sets of diagnostic images acquired at doses of CA outside the standard-of-care are not commonly available. Here, we propose a method to generate synthetic data sets to train an "AI agent" designed to amplify the effects of CAs in magnetic resonance (MR) images. The method was fine-tuned and validated in a preclinical study in a murine model of brain glioma, and extended to a large, retrospective clinical human data set. A physical model was applied to simulate different levels of MR contrast from a gadolinium-based CA. The simulated data were used to train a neural network that predicts image contrast at higher doses. A preclinical MR study at multiple CA doses in a rat model of glioma was performed to tune model parameters and to assess fidelity of the virtual contrast images against ground-truth MR and histological data. Two different scanners (3 T and 7 T, respectively) were used to assess the effects of field strength. The approach was then applied to a retrospective clinical study comprising 1990 examinations in patients affected by a variety of brain diseases, including glioma, multiple sclerosis, and metastatic cancer. Images were evaluated in terms of contrast-to-noise ratio and lesion-to-brain ratio, and qualitative scores. In the preclinical study, virtual double-dose images showed high degrees of similarity to experimental double-dose images for both peak signal-to-noise ratio and structural similarity index (29.49 dB and 0.914 dB at 7 T, respectively, and 31.32 dB and 0.942 dB at 3 T) and significant improvement over standard contrast dose (ie, 0.1 mmol Gd/kg) images at both field strengths. In the clinical study, contrast-to-noise ratio and lesion-to-brain ratio increased by an average 155% and 34% in virtual contrast images compared with standard-dose images. Blind scoring of AI-enhanced images by 2 neuroradiologists showed significantly better sensitivity to small brain lesions compared with standard-dose images (4.46/5 vs 3.51/5). Synthetic data generated by a physical model of contrast enhancement provided effective training for a deep learning model for contrast amplification. Contrast above that attainable at standard doses of gadolinium-based CA can be generated through this approach, with significant advantages in the detection of small low-enhancing brain lesions.

Acrolein adducts and responding autoantibodies correlate with metabolic disturbance in Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is caused by many intertwining pathologies involving metabolic aberrations. Patients with metabolic syndrome (MetS) generally show hyperglycemia and dyslipidemia, which can lead to the formation of aldehydic adducts such as acrolein on peptides in the brain and blood. However, the pathogenesis from MetS to AD remains elusive.MethodsAn AD cell model expressing Swedish and Indiana amyloid precursor protein (APP-Swe/Ind) in neuro-2a cells and a 3xTg-AD mouse model were used. Human serum samples (142 control and 117 AD) and related clinical data were collected. Due to the involvement of MetS in AD, human samples were grouped into healthy control (HC), MetS-like, AD with normal metabolism (AD-N), and AD with metabolic disturbance (AD-M). APP, amyloid-beta (Aß), and acrolein adducts in the samples were analyzed using immunofluorescent microscopy, histochemistry, immunoprecipitation, immunoblotting, and/or ELISA. Synthetic Aß1-16 and Aß17-28 peptides were modified with acrolein in vitro and verified using LC–MS/MS. Native and acrolein-modified Aß peptides were used to measure the levels of specific autoantibodies IgG and IgM in the serum. The correlations and diagnostic power of potential biomarkers were evaluated.ResultsAn increased level of acrolein adducts was detected in the AD model cells. Furthermore, acrolein adducts were observed on APP C-terminal fragments (APP-CTFs) containing Aß in 3xTg-AD mouse serum, brain lysates, and human serum. The level of acrolein adducts was correlated positively with fasting glucose and triglycerides and negatively with high-density lipoprotein-cholesterol, which correspond with MetS conditions. Among the four groups of human samples, the level of acrolein adducts was largely increased only in AD-M compared to all other groups. Notably, anti-acrolein-Aß autoantibodies, especially IgM, were largely reduced in AD-M compared to the MetS group, suggesting that the specific antibodies against acrolein adducts may be depleted during pathogenesis from MetS to AD.ConclusionsMetabolic disturbance may induce acrolein adduction, however, neutralized by responding autoantibodies. AD may be developed from MetS when these autoantibodies are depleted. Acrolein adducts and the responding autoantibodies may be potential biomarkers for not only diagnosis but also immunotherapy of AD, especially in complication with MetS.

Using molecular dynamics simulations to show differences of movement over time in the CCR5 variants of genetically edited children

In 2018 He Jiankui presented a study where he claimed he successfully used CRISPR to genetically modify a set of twins, intending to provide them with resistance against HIV. Dr. He modified CCR5, C-C chemokine receptor type 5, in two patients which have been given the names “Lulu” and “Nana”. It has not been clinically confirmed that the variants introduced provide a protective effect. Because of the barriers to collecting human clinical data, here we use homology modeling to predict the effects of these proteins. Molecular dynamics simulations are used to compare these new variants to known variants using 3D protein models produced from predicted translations. This allows us to follow and compare the individual amino acid movement of the variants within a simulated aqueous environment over time. The simulations of the novel variants in twins Lulu and Nana showed differences in the amino acid residue movement of the protein over a 20-nanosecond interval when compared with known variants. This allows us to determine the stability of the protein by following the way the amino acids within the protein move in the simulated aqueous environment. Stability and amino acid movement affects the regulation and expression of the protein and can be altered when specific amino acids are targeted. The differences in the model simulations presented here suggest potential changes in functionality or stability.

A Pan-Cancer Analysis of Prognostic and Immunological Roles for Cell Death Genes.

The dysregulation of cell death is closely associated with the development, progression, tumor microenvironment (TME), and prognosis of cancer. However, there is no study that comprehensively explores the prognostic and immunological role of cell death in human pan-cancer. We used published human pan-cancer RNA-sequencing and clinical data to explore the prognostic and immunological roles of programmed cell death, which included apoptosis, autophagy, ferroptosis, necroptosis, and pyroptosis. A total of 9925 patients were included for bioinformatic analysis, with 6949 and 2976 patients in the training cohort and validation cohort, respectively. Five-hundred and ninety-nine genes were defined as programmed-cell-death-related genes. In the training cohort, 75 genes were identified to define PAGscore by survival analysis. According to the median value of PAGscore, patients were divided into high- and low-risk groups, and subsequent analyses demonstrated that the high-risk group had a higher level of genomic mutation frequency, hypoxia score, immuneScore, expression of immune genes, activity of malignant signaling pathways, and cancer immunity cycle. Most anti-tumor and pro-tumor components of the TME showed greater activity in high-risk patients. Scores of malignant cell properties were also higher in high-risk patients. These findings were confirmed in the validation cohort and external cohort. Our study constructed a reliable gene signature to distinguish prognosis-favorable and prognosis-unfavorable patients and demonstrated that cell death was significantly associated with cancer prognosis and the TME.

C72 POSTERIOR WALL CHARACTERIZATION IN PATIENTS AFFECTED BY ATRIAL FIBRILLATION

Abstract Background Several clinical data in humans demonstrate that atrial fibrillation (AF) dominant frequencies and rotors are mostly localized on the posterior wall (PW), but the correlation among these phenomena and abnormal conduction properties during sinus (SR) and paced rhythm (PR) has never been analyzed. Aims. To provide a characterization of the left atrial PW in patients affected by persistent AF. In particular, the purpose is to describe the electrophysiological properties in terms of rotational and focal activities during AF, propagation uniformity during SR and functional sites definition during PR. Methods Six patients from two EP centers have been selected for this analysis. The clinical procedures have been performed with CARTO3 mapping system. All EGMs have been collected with Pentaray and Octaray catheters. For each patient, the module CARTOFINDER has been used during AF to identify areas with shorter and longer cycle length (site of conduction jump), rotational and focal activities; at least 15 areas have been collected in the PW. SR and PR map were performed after electrical cardioversion to exploit the functional phenomena. The paced map has been created by setting an extra beat from the coronary sinus every three sinus beats (pacing interval=local effective refractory period +40ms). Rotational and focal activities during AF have been identified and associated with signals collected during SR and PR. EGMs have been characterized in terms of voltage amplitude (mV), signal duration (ms) and fractionation. Results Abnormal areas of conduction recorded during AF were 33; at least one site of conduction jump was found in every patient, in most of the cases (77%, 10 out of 13) it was localized on the PW. 10 areas of focal activities have been found of which 7 (70%) were localized on the PW. Rotational activity has been found in 2 patients (in one on the PW). During SR and paced rhythm, at sites of interest, we found lower voltages (SR 1.9 ± 1,3mV, PR 1,7 ± 1,15mV), signal fragmentation and longer signal duration (SR 52,7 ± 8,85ms, PR 51,3 ± 11,04ms) compared to healthy tissue. Conclusion There is a strong correlation between sites of interest during AF and signal abnormalities recorded during SR and PR. This research work may pave the way to the study of abnormal conduction sites during SR which represent a relevant element for AF maintenance, providing a further step towards substrate characterization in patients affected by AF.

Abstract LB349: The use of PBMC humanized mice to test the efficacy and safety of antibody and cell-based cancer immunotherapeutics

Abstract In the fight against cancer, immunotherapies are one of the largest growing therapeutics in development. Immunotherapeutics are designed to boost or harness the power of the immune system to prevent, control, or eliminate cancer; while many immune therapies have been found to be safe others have induced severe toxicities. For instance, even compounds that target the same molecule/antigen can have dramatically differing safety profiles. Current preclinical models evaluating these therapies are underequipped to assess the safety of these compounds: in vitro assays fail to predict systemic responses and traditional animal models often fail to correlate with human responses. To better meet the needs of assessing preclinical toxicity we developed a PBMC-humanized mouse model to test a variety of therapeutics, including both monoclonal and bispecific antibodies and induce human cytokine release responses which can manifest within hours or days later resulting in tissue damage and lethality of the mice. To date we have tested a variety of therapeutics, including Blinatumomab, Rituximab, EGFRxCD3 BiTE, CAR-T, and others in our platform while evaluating the ability of the therapeutic to induce human cytokines, bodyweight loss, clinical symptom assessment, and survival in the context of toxicity alone or along with the evaluation with efficacy. We found that many of the therapeutics tested in our platform showed similarities to clinical data in humans. For example, urelumab and utomilumab are both fully humanized monoclonal antibodies against 4-1BB (CD137). However, during clinical trials, urelumab was shown to induce severe liver toxicities while utomilumab was well tolerated. In our huPBMC mouse model, we likewise showed that huPBMC mice dosed with 10 mpk of urelumab experienced body weight loss, showed liver necrosis, and met the clinical criteria for early euthanasia compared to mice treated with 10 mpk utomilumab and PBS treated controls. Serum levels of enzymes associated with liver damage: AST, ALT and GLDH were significantly higher in urelumab treated mice and terminal serum cytokine analysis revealed similarities with those found to be increased in urelumab clinical trials, including elevated IFNγ, IP-10, MIG, and MIP-1α and MIP-1β. Further, HuPBMC mice are also capable of detecting variability among donors. We have screened well over 60 human PBMC donors in huPBMC mice treated with OKT3 and αCD28 and while we always see an increase in cytokines such as IFNγ - the range of induction varies greatly among donors. Further, we see PBMC-donor variability in body weight loss and survival rate after OKT3 and αCD28 treatments. We demonstrate that the PBMC humanized mouse model shows clinical relevance. The use of these models for preclinical safety assessments has the potential to become an important part of novel immunotherapeutic development for patient safety and reducing drug development costs. Citation Format: Destanie Rose, Won Lee, Guoxiang Yang, Jiwon Yang, Mingshan Cheng, Wenqian He, Bernard Buetow, Allison Vitsky, Maggie Liu, Bart Jessen, James Keck. The use of PBMC humanized mice to test the efficacy and safety of antibody and cell-based cancer immunotherapeutics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB349.

Pericytes: The lung-forgotten cell type.

Pericytes are a heterogeneous population of mesenchymal cells located on the abluminal surface of microvessels, where they provide structural and biochemical support. Pericytes have been implicated in numerous lung diseases including pulmonary arterial hypertension (PAH) and allergic asthma due to their ability to differentiate into scar-forming myofibroblasts, leading to collagen deposition and matrix remodelling and thus driving tissue fibrosis. Pericyte-extracellular matrix interactions as well as other biochemical cues play crucial roles in these processes. In this review, we give an overview of lung pericytes, the key pro-fibrotic mediators they interact with, and detail recent advances in preclinical studies on how pericytes are disrupted and contribute to lung diseases including PAH, allergic asthma, and chronic obstructive pulmonary disease (COPD). Several recent studies using mouse models of PAH have demonstrated that pericytes contribute to these pathological events; efforts are currently underway to mitigate pericyte dysfunction in PAH by targeting the TGF-β, CXCR7, and CXCR4 signalling pathways. In allergic asthma, the dissociation of pericytes from the endothelium of blood vessels and their migration towards inflamed areas of the airway contribute to the characteristic airway remodelling observed in allergic asthma. Although several factors have been suggested to influence this migration such as TGF-β, IL-4, IL-13, and periostin, recent evidence points to the CXCL12/CXCR4 pathway as a potential therapeutic target. Pericytes might also play an essential role in lung dysfunction in response to ageing, as they are responsive to environmental risk factors such as cigarette smoke and air pollutants, which are the main drivers of COPD. However, there is currently no direct evidence delineating the contribution of pericytes to COPD pathology. Although there is a lack of human clinical data, the recent available evidence derived from in vitro and animal-based models shows that pericytes play important roles in the initiation and maintenance of chronic lung diseases and are amenable to pharmacological interventions. Therefore, further studies in this field are required to elucidate if targeting pericytes can treat lung diseases.