Harnessing Artificial Intelligence for Enhanced Renal Analysis: Automated Detection of Hydronephrosis and Precise Kidney Segmentation.

Background and objective: Hydronephrosis is essential in the diagnosis of renal colic. We automated the detection of hydronephrosis from ultrasound images to standardize the therapy and reduce the misdiagnosis of renal colic. Methods: Anonymously collected ultrasound images of human kidneys, both normal and hydronephrotic, were preprocessed for neural networks. Six "state of the art" models were trained and cross-validated for the detection of hydronephrosis, and two convolutional networks were used for kidney segmentation. In the testing phase, performance metrics included true positives, true negatives, false positives, false negatives, accuracy, and F1 score, while the evaluation of the segmentation task involved accuracy, precision, dice, jaccard, recall, and ASSD. Key findings and limitations: A total of 523 sonographic kidney images (423 nonhydronephrotic and 100 hydronephrotic) were collected from three different ultrasound devices. After training on this dataset, all models were used to evaluate 200 new ultrasound kidney images (142 nonhydronephrotic and 58 hydronephrotic kidneys). The highest validation accuracy (98.5%) was achieved by the AlexNet model (GoogLeNet 97%, AlexNet_v2 96%, ResNet50 96%, ResNet101 97.5%, and ResNet152 95%). The deeplabv3_resnet50 and deeplabv3_resnet101 reached a dice coefficient of 94.74% and 94.48%, respectively, on the task of automated kidney segmentation. The study is limited by analyzing only hydronephrosis, but this specific focus enabled high detection accuracy. Conclusions and clinical implications: We show that our automated ultrasound deep learning model can be trained and used to interpret and segmentate ultrasound images from different sources with high accuracy. This method will serve as an automated tool in the diagnostic algorithm of acute renal failure in the future. Patient summary: Hydronephrosis is crucial in the diagnosis of renal colic. Recent advances in artificial intelligence allow automated detection of hydronephrosis in ultrasound images with high accuracy. These methods will help standardize the diagnosis and treatment renal colic.

Discovery of YAP1/TAZ pathway inhibitors through phenotypic screening with potent anti-tumor activity via blockade of Rho-GTPase signaling.

This study describes the identification and target deconvolution of small molecule inhibitors of oncogenic Yes-associated protein (YAP1)/TAZ activity with potent anti-tumor activity in vivo. A high-throughput screen (HTS) of 3.8 million compounds was conducted using a cellular YAP1/TAZ reporter assay. Target deconvolution studies identified the geranylgeranyltransferase-I (GGTase-I) complex as the direct target of YAP1/TAZ pathway inhibitors. The small molecule inhibitors block the activation of Rho-GTPases, leading to subsequent inactivation of YAP1/TAZ and inhibition of cancer cell proliferation in vitro. Multi-parameter optimization resulted in BAY-593, an in vivo probe with favorable PK properties, which demonstrated anti-tumor activity and blockade of YAP1/TAZ signaling in vivo.

The role of desmoglein-2 in kidney disease.

Desmosomes are multi-protein cell-cell adhesion structures supporting cell stability and mechanical stress resilience of tissues, best described in skin and heart. The kidney is exposed to various mechanical stimuli and stress, yet little is known about kidney desmosomes. In healthy kidneys, we found desmosomal proteins located at the apical-junctional complex in tubular epithelial cells. In four different animal models and patient biopsies with various kidney diseases, desmosomal components were significantly upregulated and partly miss-localized outside of the apical-junctional complexes along the whole lateral tubular epithelial cell membrane. The most upregulated component was desmoglein-2 (Dsg2). Mice with constitutive tubular epithelial cell-specific deletion of Dsg2 developed normally, and other desmosomal components were not altered in these mice. When challenged with different types of tubular epithelial cell injury (unilateral ureteral obstruction, ischemia-reperfusion, and 2,8-dihydroxyadenine crystal nephropathy), we found increased tubular epithelial cell apoptosis, proliferation, tubular atrophy, and inflammation compared to wild-type mice in all models and time points. In vitro, silencing DSG2 via siRNA weakened cell-cell adhesion in HK-2 cells and increased cell death. Thus, our data show a prominent upregulation of desmosomal components in tubular cells across species and diseases and suggest a protective role of Dsg2 against various injurious stimuli.

Matrix Metalloproteinase-7 in Urinary Extracellular Vesicles Identifies Rapid Disease Progression in Autosomal Dominant Polycystic Kidney Disease.

SIGNIFICANCE STATEMENT: There is an unmet need for biomarkers of disease progression in autosomal dominant polycystic kidney disease (ADPKD). This study investigated urinary extracellular vesicles (uEVs) as a source of such biomarkers. Proteomic analysis of uEVs identified matrix metalloproteinase 7 (MMP-7) as a biomarker predictive of rapid disease progression. In validation studies, MMP-7 was predictive in uEVs but not in whole urine, possibly because uEVs are primarily secreted by tubular epithelial cells. Indeed, single-nucleus RNA sequencing showed that MMP-7 was especially increased in proximal tubule and thick ascending limb cells, which were further characterized by a profibrotic phenotype. Together, these data suggest that MMP-7 is a biologically plausible and promising uEV biomarker for rapid disease progression in ADPKD. BACKGROUND: In ADPKD, there is an unmet need for early markers of rapid disease progression to facilitate counseling and selection for kidney-protective therapy. Our aim was to identify markers for rapid disease progression in uEVs. METHODS: Six paired case-control groups ( n =10-59/group) of cases with rapid disease progression and controls with stable disease were formed from two independent ADPKD cohorts, with matching by age, sex, total kidney volume, and genetic variant. Candidate uEV biomarkers were identified by mass spectrometry and further analyzed using immunoblotting and an ELISA. Single-nucleus RNA sequencing of healthy and ADPKD tissue was used to identify the cellular origin of the uEV biomarker. RESULTS: In the discovery proteomics experiments, the protein abundance of MMP-7 was significantly higher in uEVs of patients with rapid disease progression compared with stable disease. In the validation groups, a significant >2-fold increase in uEV-MMP-7 in patients with rapid disease progression was confirmed using immunoblotting. By contrast, no significant difference in MMP-7 was found in whole urine using ELISA. Compared with healthy kidney tissue, ADPKD tissue had significantly higher MMP-7 expression in proximal tubule and thick ascending limb cells with a profibrotic phenotype. CONCLUSIONS: Among patients with ADPKD, rapid disease progressors have higher uEV-associated MMP-7. Our findings also suggest that MMP-7 is a biologically plausible biomarker for more rapid disease progression.

Sublethal necroptosis signaling promotes inflammation and liver cancer.

It is currently not well known how necroptosis and necroptosis responses manifest in vivo. Here, we uncovered a molecular switch facilitating reprogramming between two alternative modes of necroptosis signaling in hepatocytes, fundamentally affecting immune responses and hepatocarcinogenesis. Concomitant necrosome and NF-κB activation in hepatocytes, which physiologically express low concentrations of receptor-interacting kinase 3 (RIPK3), did not lead to immediate cell death but forced them into a prolonged "sublethal" state with leaky membranes, functioning as secretory cells that released specific chemokines including CCL20 and MCP-1. This triggered hepatic cell proliferation as well as activation of procarcinogenic monocyte-derived macrophage cell clusters, contributing to hepatocarcinogenesis. In contrast, necrosome activation in hepatocytes with inactive NF-κB-signaling caused an accelerated execution of necroptosis, limiting alarmin release, and thereby preventing inflammation and hepatocarcinogenesis. Consistently, intratumoral NF-κB-necroptosis signatures were associated with poor prognosis in human hepatocarcinogenesis. Therefore, pharmacological reprogramming between these distinct forms of necroptosis may represent a promising strategy against hepatocellular carcinoma.

MASI enables fast model-free standardization and integration of single-cell transcriptomics data.

Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However, fast and computationally inexpensive tools for standardization of cell-type annotation and data integration are still needed in order to increase research inclusivity. To standardize cell-type annotation and integrate single-cell transcriptomics datasets, we have built a fast model-free integration method, named MASI (Marker-Assisted Standardization and Integration). We benchmark MASI with other well-established methods and demonstrate that MASI outperforms other methods, in terms of integration, annotation, and speed. To harness knowledge from single-cell atlases, we demonstrate three case studies that cover integration across biological conditions, surveyed participants, and research groups, respectively. Finally, we show MASI can annotate approximately one million cells on a personal laptop, making large-scale single-cell data integration more accessible. We envision that MASI can serve as a cheap computational alternative for the single-cell research community.

IL-6 in the infarcted heart is preferentially formed by fibroblasts and modulated by purinergic signaling.

Plasma IL-6 is elevated after myocardial infarction (MI) and is associated with increased morbidity and mortality. Which cardiac cell type preferentially contributes to IL-6 expression and how its production is regulated are largely unknown. Here, we studied the cellular source and purinergic regulation of IL-6 formation in a murine MI model. We found that IL-6, measured in various cell types in post-MI hearts at the protein level and by quantitative PCR and RNAscope, was preferentially formed by cardiac fibroblasts (CFs). Single-cell RNA-Seq (scRNA-Seq) in infarcted mouse and human hearts confirmed this finding. We found that adenosine stimulated fibroblast IL-6 formation via the adenosine receptor A2bR in a Gq-dependent manner. CFs highly expressed Adora2b and rapidly degraded extracellular ATP to AMP but lacked CD73. In mice and humans, scRNA-Seq revealed that Adora2B was also mainly expressed by fibroblasts. We assessed global IL-6 production in isolated hearts from mice lacking CD73 on T cells (CD4-CD73-/-), a condition known to be associated with adverse cardiac remodeling. The ischemia-induced release of IL-6 was strongly attenuated in CD4-CD73-/- mice, suggesting adenosine-mediated modulation. Together, these findings demonstrate that post-MI IL-6 was mainly derived from activated CFs and was controlled by T cell-derived adenosine. We show that purinergic metabolic cooperation between CFs and T cells is a mechanism that modulates IL-6 formation by the heart and has therapeutic potential.

[Artificial intelligence in urology-opportunities and possibilities]. / Künstliche Intelligenz in der Urologie ­ Chancen und Möglichkeiten.

The use of artificial intelligence (AI) in urology can contribute to a significant improvement with regard to individualization of diagnostics and therapy as well as healthcare cost reduction. The potential applications and advantages of AI in medicine are often underestimated or incompletely understood. This makes it difficult to conceptually solve relevant medical problems using AI. With current advances in computer science, multiple, highly complex nonmedical processes have already been studied and optimized in an automated fashion. The development of AI models, if applied correctly, can lead to more effective processing and analysis of patient-related data and correspondingly optimized diagnosis and therapy of urological patients. In this review, the current status on the application of AI in medicine and its opportunities and possibilities in urology are presented from a conceptual perspective using practical examples.

Platelet-instructed SPP1+ macrophages drive myofibroblast activation in fibrosis in a CXCL4-dependent manner.

Fibrosis represents the common end stage of chronic organ injury independent of the initial insult, destroying tissue architecture and driving organ failure. Here we discover a population of profibrotic macrophages marked by expression of Spp1, Fn1, and Arg1 (termed Spp1 macrophages), which expands after organ injury. Using an unbiased approach, we identify the chemokine (C-X-C motif) ligand 4 (CXCL4) to be among the top upregulated genes during profibrotic Spp1 macrophage differentiation. In vitro and in vivo studies show that loss of Cxcl4 abrogates profibrotic Spp1 macrophage differentiation and ameliorates fibrosis after both heart and kidney injury. Moreover, we find that platelets, the most abundant source of CXCL4 in vivo, drive profibrotic Spp1 macrophage differentiation. Single nuclear RNA sequencing with ligand-receptor interaction analysis reveals that macrophages orchestrate fibroblast activation via Spp1, Fn1, and Sema3 crosstalk. Finally, we confirm that Spp1 macrophages expand in both human chronic kidney disease and heart failure.

Single-nucleus RNA sequencing in ischemic cardiomyopathy reveals common transcriptional profile underlying end-stage heart failure.

Ischemic cardiomyopathy (ICM) is the leading cause of heart failure worldwide, yet the cellular and molecular signature of this disease is largely unclear. Using single-nucleus RNA sequencing (snRNA-seq) and integrated computational analyses, we profile the transcriptomes of over 99,000 human cardiac nuclei from the non-infarct region of the left ventricle of 7 ICM transplant recipients and 8 non-failing (NF) controls. We find the cellular composition of the ischemic heart is significantly altered, with decreased cardiomyocytes and increased proportions of lymphatic, angiogenic, and arterial endothelial cells in patients with ICM. We show that there is increased LAMININ signaling from endothelial cells to other cell types in ICM compared with NF. Finally, we find that the transcriptional changes that occur in ICM are similar to those in hypertrophic and dilated cardiomyopathies and that the mining of these combined datasets can identify druggable genes that could be used to target end-stage heart failure.

Fast model-free standardization and integration of single-cell transcriptomics data.

Single-cell transcriptomics datasets from the same anatomical sites generated by different research labs are becoming increasingly common. However, fast and computationally inexpensive tools for standardization of cell-type annotation and data integration are still needed in order to increase research inclusivity. To standardize cell-type annotation and integrate single-cell transcriptomics datasets, we have built a fast model-free integration method, named MASI (Marker-Assisted Standardization and Integration). MASI first identifies putative cell-type markers from reference data through an ensemble approach. Then, it converts gene expression matrix to cell-type score matrix with the identified putative cell-type markers for the purpose of cell-type annotation and data integration. Because of integration through cell-type markers instead of model inference, MASI can annotate approximately one million cells on a personal laptop, which provides a cheap computational alternative for the single-cell community. We benchmark MASI with other well-established methods and demonstrate that MASI outperforms other methods based on speed. Its performance for both tasks of data integration and cell-type annotation are comparable or even superior to these existing methods. To harness knowledge from single-cell atlases, we demonstrate three case studies that cover integration across biological conditions, surveyed participants, and research groups, respectively.

Targeting Immune-Fibroblast Crosstalk in Myocardial Infarction and Cardiac Fibrosis.

Inflammation and tissue fibrosis co-exist and are causally linked to organ dysfunction. However, the molecular mechanisms driving immune-fibroblast crosstalk in human cardiac disease remains unexplored and there are currently no therapeutics to target fibrosis. Here, we performed multi-omic single-cell gene expression, epitope mapping, and chromatin accessibility profiling in 38 donors, acutely infarcted, and chronically failing human hearts. We identified a disease-associated fibroblast trajectory marked by cell surface expression of fibroblast activator protein (FAP), which diverged into distinct myofibroblasts and pro-fibrotic fibroblast populations, the latter resembling matrifibrocytes. Pro-fibrotic fibroblasts were transcriptionally similar to cancer associated fibroblasts and expressed high levels of collagens and periostin (POSTN), thymocyte differentiation antigen 1 (THY-1), and endothelin receptor A (EDNRA) predicted to be driven by a RUNX1 gene regulatory network. We assessed the applicability of experimental systems to model tissue fibrosis and demonstrated that 3 different in vivo mouse models of cardiac injury were superior compared to cultured human heart and dermal fibroblasts in recapitulating the human disease phenotype. Ligand-receptor analysis and spatial transcriptomics predicted that interactions between C-C chemokine receptor type 2 (CCR2) macrophages and fibroblasts mediated by interleukin 1 beta (IL-1ß) signaling drove the emergence of pro-fibrotic fibroblasts within spatially defined niches. This concept was validated through in silico transcription factor perturbation and in vivo inhibition of IL-1ß signaling in fibroblasts where we observed reduced pro-fibrotic fibroblasts, preferential differentiation of fibroblasts towards myofibroblasts, and reduced cardiac fibrosis. Herein, we show a subset of macrophages signal to fibroblasts via IL-1ß and rewire their gene regulatory network and differentiation trajectory towards a pro-fibrotic fibroblast phenotype. These findings highlight the broader therapeutic potential of targeting inflammation to treat tissue fibrosis and restore organ function.

Adult human kidney organoids originate from CD24+ cells and represent an advanced model for adult polycystic kidney disease.

Adult kidney organoids have been described as strictly tubular epithelia and termed tubuloids. While the cellular origin of tubuloids has remained elusive, here we report that they originate from a distinct CD24+ epithelial subpopulation. Long-term-cultured CD24+ cell-derived tubuloids represent a functional human kidney tubule. We show that kidney tubuloids can be used to model the most common inherited kidney disease, namely autosomal dominant polycystic kidney disease (ADPKD), reconstituting the phenotypic hallmark of this disease with cyst formation. Single-cell RNA sequencing of CRISPR-Cas9 gene-edited PKD1- and PKD2-knockout tubuloids and human ADPKD and control tissue shows similarities in upregulation of disease-driving genes. Furthermore, in a proof of concept, we demonstrate that tolvaptan, the only approved drug for ADPKD, has a significant effect on cyst size in tubuloids but no effect on a pluripotent stem cell-derived model. Thus, tubuloids are derived from a tubular epithelial subpopulation and represent an advanced system for ADPKD disease modeling.

Spatial multi-omic map of human myocardial infarction.

Myocardial infarction is a leading cause of death worldwide1. Although advances have been made in acute treatment, an incomplete understanding of remodelling processes has limited the effectiveness of therapies to reduce late-stage mortality2. Here we generate an integrative high-resolution map of human cardiac remodelling after myocardial infarction using single-cell gene expression, chromatin accessibility and spatial transcriptomic profiling of multiple physiological zones at distinct time points in myocardium from patients with myocardial infarction and controls. Multi-modal data integration enabled us to evaluate cardiac cell-type compositions at increased resolution, yielding insights into changes of the cardiac transcriptome and epigenome through the identification of distinct tissue structures of injury, repair and remodelling. We identified and validated disease-specific cardiac cell states of major cell types and analysed them in their spatial context, evaluating their dependency on other cell types. Our data elucidate the molecular principles of human myocardial tissue organization, recapitulating a gradual cardiomyocyte and myeloid continuum following ischaemic injury. In sum, our study provides an integrative molecular map of human myocardial infarction, represents an essential reference for the field and paves the way for advanced mechanistic and therapeutic studies of cardiac disease.

Dosimetric properties of thermoluminescent NaCl pellets from Khewra Salt Mines, Pakistan.

Thermoluminescence (TL) and extended dosimetric characteristics of naturally occurring sodium chloride (NaCl) salt were studied. Pellets were prepared from mined crystalline salt obtained from Khewra Salt Mines, Pakistan and irradiated from 1 mGy to 10,000 mGy using cobalt-60 gamma source. The TL response showed two dominant peaks around 125°C and 230°C, respectively, at low doses, with an additional peak in between at doses beyond 300 mGy. A linear and supra-linear TL response was observed between 1 mGy-100 mGy and 100 mGy-10 Gy dose ranges, respectively. During the first 24 h post-irradiation, the TL intensity dropped by 20%. A maximum angular dependence of up to 50% was observed between 0° to 360°. For photon energies between 33 keV and 1.25 MeV significant energy dependence was observed for photons < 100 keV only. Sample sensitivity increased with dose a qualitatively similar behaviour to TLD-200. Effective atomic number (Zeff ) of the sample (14.6) was comparable to TLD-200 (16.3). No significant dose rate effects (deviation for a cobalt-60 source within 3.5%) on the TL sensitivity of the sample were found. The lowest detectable dose limit (LDDL) for salt sample was found to be 0.8 mGy whereas the sample reproducibility test showed a maximum of ±11% deviation from the first value.

Thermoluminescence (TL), kinetic parameters and dosimetric features of Pakistani limestone.

Thermoluminescence (TL), kinetic parameters and dosimetric features of Pakistani limestone (CaCO3) is reported in this study. Both compositional and structural analyses reveal that the material has a crystalline nature with rhombohedral structure and non-uniform crystallite size having major content of CaCO3. A powdered limestone sample of 30 mg is found to be the optimized weight for TL and other dosimetric studies. After irradiating the samples with a test dose of 100 Gy using a ß source three composite glow peaks termed as P1, P2 and P3 are visible at 100, 230 and 330 °C respectively using a linear heating rate of 1 °C/s during the TL readout. The Coefficient of Variation (COV) is found to be about 4%. Kinetic parameters (i.e., frequency factor (f), activation energy (E), and the kinetic order (b)) are estimated using both first and second Order of kinetics using an in-house Computerized Glow Curve Deconvolution (GCD) software. The figure-of-merit (FOM) is found to be 2.12%. The distribution of continuum traps with activation energy in the range of 0.77-2.59 eV is observed in the kinetic parameter analysis of the glow peaks of the sample. The TL response in the dose range of 1-5 Gy (not reported previously) and linearity in the dose response in the dose range of 1-10 Gy is observed in samples of Pakistani limestone. The Minimum Detectable Dose (MDD) is 1.01 Gy clearly resembling the experimentally linear fitted results. After a fading study for a period of thirty days, only the first peak i.e., P1 majorly fades while no major change is observed in the amplitude of peaks P2 and P3. In addition, P1 is the main contributor fading by 92% within the first 24 h of irradiation while P2 fades by 30 %. However, P3 shows stability with a very minor fading of 0.05% within 24 h of irradiation. This study concludes that Pakistani limestone can be further assessed as a potential radiation dosimeter for various applications.

Single-nucleus profiling of human dilated and hypertrophic cardiomyopathy.

Heart failure encompasses a heterogeneous set of clinical features that converge on impaired cardiac contractile function1,2 and presents a growing public health concern. Previous work has highlighted changes in both transcription and protein expression in failing hearts3,4, but may overlook molecular changes in less prevalent cell types. Here we identify extensive molecular alterations in failing hearts at single-cell resolution by performing single-nucleus RNA sequencing of nearly 600,000 nuclei in left ventricle samples from 11 hearts with dilated cardiomyopathy and 15 hearts with hypertrophic cardiomyopathy as well as 16 non-failing hearts. The transcriptional profiles of dilated or hypertrophic cardiomyopathy hearts broadly converged at the tissue and cell-type level. Further, a subset of hearts from patients with cardiomyopathy harbour a unique population of activated fibroblasts that is almost entirely absent from non-failing samples. We performed a CRISPR-knockout screen in primary human cardiac fibroblasts to evaluate this fibrotic cell state transition; knockout of genes associated with fibroblast transition resulted in a reduction of myofibroblast cell-state transition upon TGFß1 stimulation for a subset of genes. Our results provide insights into the transcriptional diversity of the human heart in health and disease as well as new potential therapeutic targets and biomarkers for heart failure.

Characteristics, reasons and patterns of Road Traffic Injuries presenting in emergency department of a tertiary care public hospital in Karachi.

Objectives: To determine the main characteristics, reasons and patterns of road traffic injuries (RTIs) in a tertiary care public hospital of Karachi. Methods: It was a hospital based cross sectional study conducted in a public tertiary care hospital emergency department with a sample size 425 selected conveniently. Participants included the consenting victims or caretaking attendants of road traffic injuries (RTIs) from 25th May to 28th June in 2019. A structured questionnaire was developed after literature review and was translated into "Urdu" language. The questionnaire collected detailed information on socio-demographic characteristics, possible reasons of RTI's such as condition of vehicle, over speeding and breaking traffic rules. Data was analyzed by using software SPSS version 20. Results: Almost half of RTI victims (43.1%) belonged to the age group 18-29. Majority of the victims were males (86.6%). The most common vehicle involved was motorbike (87.50%) followed by Rickshaw (6.8%) and Car (2.4%). Majority of RTIs occurred on main road (75.30%). The most common sites of injuries were lower limb (64%), upper limb (37.60%) and head (32.2%). The severe injuries were significantly more likely to happen in events in which direct collision with other vehicle/thing was involved, road conditions were wet and pedestrian were crossing the road. Conclusion: Motorbikes were involved in majority of RTIs. Main reasons of RTIs included irresponsible road behaviors including over-speeding, careless road crossing, breaking the signal and riding on wet roads which lead to moderate to severe injuries in almost two thirds of participants.

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling.

Introduction: SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants. Methods: We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8+ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19. Results: We observed increased CD8+ T cell exhaustion in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8+ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8+ T cells revealed heterogeneity among CD16+ NK-like CD8+ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions. Discussion: We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8+ effector T cells, ultimately resulting in the appearance of NK-like CD8+ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8+ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8+ T cells in COVID-19 severity.