Chloroxine inhibits pancreatic cancer progression through targeted antagonization of the PI3K/AKT/mTOR signaling pathway / La cloroxina inhibe la progresión del cáncer de páncreas mediante la antagonización dirigida de la vía de señalización PI3K/AKT/mTOR

Background: Patients with pancreatic cancer have a dismal prognosis due to tumor cell infiltration and metastasis. Many reports have documented that EMT and PI3K–AKT–mTOR axis control pancreatic cancer cell infiltration and metastasis. Chloroxine is an artificially synthesized antibacterial compound that demonstrated anti-pancreatic cancer effects in our previous drug-screening trial. We have explored the impact of chloroxine on pancreatic cancer growth, infiltration, migration, and apoptosis. Methods: The proliferation of pancreatic cancer cell lines (PCCs) treated with chloroxine was assessed through real-time cell analysis (RTCA), colony formation assay, CCK-8 assay, as well as immunofluorescence. Chloroxine effects on the infiltrative and migratory capacities of PCCs were assessed via Transwell invasion and scratch experiments. To assess the contents of EMT- and apoptosis-associated proteins in tumor cells, we adopted Western immunoblotting as well as immunofluorescence assays, and flow cytometry to determine chloroxine effects on PCCs apoptosis. The in vivo chloroxine antineoplastic effects were explored in nude mice xenografts. Results: Chloroxine repressed pancreatic cancer cell growth, migration, and infiltration in vitro, as well as in vivo, and stimulated apoptosis of the PCCs. Chloroxine appeared to inhibit PCC growth by Ki67 downregulation; this targeted and inhibited aberrant stimulation of the PI3K–AKT–mTOR signaling cascade, triggered apoptosis in PCC via mitochondria-dependent apoptosis, and modulated the EMT to inhibit PCC infiltration and migration. Conclusions: Chloroxine targeted and inhibited the PI3K–AKT–mTOR cascade to repress PCCs growth, migration, as well as invasion, and triggered cellular apoptosis. Therefore, chloroxine may constitute a potential antineoplastic drug for the treatment of pancreatic cancer.(AU)

A host-microbiota interactome reveals extensive transkingdom connectivity.

The myriad microorganisms that live in close association with humans have diverse effects on physiology, yet the molecular bases for these impacts remain mostly unknown1-3. Classical pathogens often invade host tissues and modulate immune responses through interactions with human extracellular and secreted proteins (the 'exoproteome'). Commensal microorganisms may also facilitate niche colonization and shape host biology by engaging host exoproteins; however, direct exoproteome-microbiota interactions remain largely unexplored. Here we developed and validated a novel technology, BASEHIT, that enables proteome-scale assessment of human exoproteome-microbiome interactions. Using BASEHIT, we interrogated more than 1.7 million potential interactions between 519 human-associated bacterial strains from diverse phylogenies and tissues of origin and 3,324 human exoproteins. The resulting interactome revealed an extensive network of transkingdom connectivity consisting of thousands of previously undescribed host-microorganism interactions involving 383 strains and 651 host proteins. Specific binding patterns within this network implied underlying biological logic; for example, conspecific strains exhibited shared exoprotein-binding patterns, and individual tissue isolates uniquely bound tissue-specific exoproteins. Furthermore, we observed dozens of unique and often strain-specific interactions with potential roles in niche colonization, tissue remodelling and immunomodulation, and found that strains with differing host interaction profiles had divergent interactions with host cells in vitro and effects on the host immune system in vivo. Overall, these studies expose a previously unexplored landscape of molecular-level host-microbiota interactions that may underlie causal effects of indigenous microorganisms on human health and disease.

Machine learning models and nomogram based on clinical, laboratory profiles and skeletal muscle index to predict pancreatic fistula after pancreatoduodenectomy.

Background: Postoperative pancreatic fistula (POPF) is a perilous complication that may arise subsequent to pancreaticoduodenectomy (PD). In recent times, there has been an escalating interest in employing machine learning (ML) techniques to aid in treatment decision-making. The purpose of this research is to assess the effectiveness of ML in comparison to conventional models, while also conducting an initial evaluation of the predictive capability of skeletal muscle index (SMI) concerning POPF. Methods: This retrospective observational study was carried out at The First Affiliated Hospital of Wenzhou Medical University from January 2012 to January 2021, encompassing data from 269 patients who underwent PD. After identifying independent factors associated with the condition, a logistic regression model was employed to construct a nomogram, alongside the establishment of five ML models. To assess their effectiveness, the best-performing ML model and nomogram were evaluated on a separate test group comprising 77 additional patients. The evaluation involved comparing the area under the curve (AUC) and Brier score. Results: Among the 269 patients studied, the incidence of POPF was found to be 56.9%, with 106 patients (69.3%) experiencing clinically-relevant POPF. We identified six independent factors associated with POPF, including body mass index (BMI), SMI, pancreatic duct dilatation, tumor size, triglyceride levels, and the ratio of aspartate aminotransferase to alanine aminotransferase (AST/ALT) on the first postoperative day. When evaluated on the test set, the Gaussian Naive Bayes (GNB) model, which was the best-performing ML model, achieved an AUC of 0.824 and a Brier score of 0.175. The corresponding performance indicators for the nomogram were 0.844 for AUC and 0.165 for the Brier score. Conclusions: This study found that there is minimal difference between ML and the nomogram based on logistic regression in predicting POPF. Additionally, SMI shows promise as a potential and practical tool for assessing the risk of POPF.

Improved Performance of QDSSCs Can Be Achieved by Constructing a Transparent Anatase TiO2@MWCNT Photoanode Based on the Bionic Mountain Lotus.

In this research, the structural characteristics of the mountain holly leaf were emulated. It was observed that after the initially uneven surface of the petals is filled with infiltrated water, it exhibits a distinctive transparent beauty after rainfall. Furthermore, the presence of leaf veins enhances the structural strength of the petals and facilitates nutrient transport. Inspired by previous studies on double-layer spin-coated films, we further developed and designed the TA TiO2@MWCNT photocathode thin film. This innovative film incorporates multiwalled carbon nanotubes (MWCNT) into a previously established TA TiO2 photocathode thin film. The inclusion of MWCNT results in the formation of a three-dimensional highway structure, where MWCNT intertwines within the TA TiO2 film. Under the operational state of immersion in the electrolyte, it maintains a level of transparency similar to that of the TA TiO2 photoanode thin film. The high-temperature sintering process results in the oxidation and depletion of MWCNTs on the surface of the film, leaving behind uniformly dispersed concave defects, thereby greatly enhancing the specific surface area. The findings demonstrate that the optoelectrode of high transparency and high specific surface area, TA TiO2@MWCNT, comprehensively enhances the performance of the solar cells. The transparent QDSSC surpasses its counterparts for the first time, achieving a power conversion efficiency (PCE) of 6.335%. This sets the stage for new materials and innovative approaches in the field of solar cells and other titanium dioxide film-related areas.

Decoding the autoantibody reactome.

Autoantibodies influence a wide range of conditions beyond autoimmune diseases.

Chloroxine inhibits pancreatic cancer progression through targeted antagonization of the PI3K/AKT/mTOR signaling pathway.

BACKGROUND: Patients with pancreatic cancer have a dismal prognosis due to tumor cell infiltration and metastasis. Many reports have documented that EMT and PI3K-AKT-mTOR axis control pancreatic cancer cell infiltration and metastasis. Chloroxine is an artificially synthesized antibacterial compound that demonstrated anti-pancreatic cancer effects in our previous drug-screening trial. We have explored the impact of chloroxine on pancreatic cancer growth, infiltration, migration, and apoptosis. METHODS: The proliferation of pancreatic cancer cell lines (PCCs) treated with chloroxine was assessed through real-time cell analysis (RTCA), colony formation assay, CCK-8 assay, as well as immunofluorescence. Chloroxine effects on the infiltrative and migratory capacities of PCCs were assessed via Transwell invasion and scratch experiments. To assess the contents of EMT- and apoptosis-associated proteins in tumor cells, we adopted Western immunoblotting as well as immunofluorescence assays, and flow cytometry to determine chloroxine effects on PCCs apoptosis. The in vivo chloroxine antineoplastic effects were explored in nude mice xenografts. RESULTS: Chloroxine repressed pancreatic cancer cell growth, migration, and infiltration in vitro, as well as in vivo, and stimulated apoptosis of the PCCs. Chloroxine appeared to inhibit PCC growth by Ki67 downregulation; this targeted and inhibited aberrant stimulation of the PI3K-AKT-mTOR signaling cascade, triggered apoptosis in PCC via mitochondria-dependent apoptosis, and modulated the EMT to inhibit PCC infiltration and migration. CONCLUSIONS: Chloroxine targeted and inhibited the PI3K-AKT-mTOR cascade to repress PCCs growth, migration, as well as invasion, and triggered cellular apoptosis. Therefore, chloroxine may constitute a potential antineoplastic drug for the treatment of pancreatic cancer.

Distinguishing features of long COVID identified through immune profiling.

Post-acute infection syndromes may develop after acute viral disease1. Infection with SARS-CoV-2 can result in the development of a post-acute infection syndrome known as long COVID. Individuals with long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions2-4. However, the biological processes that are associated with the development and persistence of these symptoms are unclear. Here 275 individuals with or without long COVID were enrolled in a cross-sectional study that included multidimensional immune phenotyping and unbiased machine learning methods to identify biological features associated with long COVID. Marked differences were noted in circulating myeloid and lymphocyte populations relative to the matched controls, as well as evidence of exaggerated humoral responses directed against SARS-CoV-2 among participants with long COVID. Furthermore, higher antibody responses directed against non-SARS-CoV-2 viral pathogens were observed among individuals with long COVID, particularly Epstein-Barr virus. Levels of soluble immune mediators and hormones varied among groups, with cortisol levels being lower among participants with long COVID. Integration of immune phenotyping data into unbiased machine learning models identified the key features that are most strongly associated with long COVID status. Collectively, these findings may help to guide future studies into the pathobiology of long COVID and help with developing relevant biomarkers.

Dihydrotanshinone I Inhibits Pancreatic Cancer Progression via Hedgehog/ Gli Signal Pathway.

INTRODUCTION: Pancreatic cancer is highly fatal and its incidence is rising worldwide. Its poor prognosis is attributed to a lack of effective diagnostic and therapeutic strategies. Dihydrotanshinone I (DHT), a phenanthrene quinone liposoluble compound from Salvia miltiorrhiza Bunge (Danshen), exerts anti-tumor effects by inhibiting cell proliferation, enhancing apoptosis, and inducing cell differentiation. However, its effects on pancreatic cancer are unclear. > Methods: The role of DHT in the growth of tumor cells was explored using real-time cell analysis (RTCA), colony formation assay, and CCK-8. The effects of DHT on tumor cells invasion as well as migration were assessed by Transwell and migration assays. Expressions of pro-apoptosis and metastasis factors in tumor cells were examined using western blot. Tumor apoptosis rates were studied using flow cytometry. The anticancer effect of DHT in vivo was assessed by tumor transplantation into nude mice. RESULTS: Our analyses show that DHT has a suppressive role in epithelial-mesenchymal transition (EMT), invasiveness, proliferation, as well as migratory ability of Patu8988 and PANC-1 cells via Hedgehog/Gli signaling. Moreover, it drives apoptosis via caspases/BCL2/BAX signaling. Experiments in nude mice transplanted with tumors have shown DHT to have anticancer effects in vivo. > Conclusion: Our data show that DHT effectively suppresses pancreatic cancer cell proliferation as well as metastasis, and induces apoptosis via Hedgehog/Gli signaling. These effects have been reported to be dose- and time-dependent. Therefore, DHT can be exploited as a potential treatment for pancreatic cancer.>.

SARS-CoV-2 mRNA vaccines decouple anti-viral immunity from humoral autoimmunity.

mRNA-based vaccines dramatically reduce the occurrence and severity of COVID-19, but are associated with rare vaccine-related adverse effects. These toxicities, coupled with observations that SARS-CoV-2 infection is associated with autoantibody development, raise questions whether COVID-19 vaccines may also promote the development of autoantibodies, particularly in autoimmune patients. Here we used Rapid Extracellular Antigen Profiling to characterize self- and viral-directed humoral responses after SARS-CoV-2 mRNA vaccination in 145 healthy individuals, 38 patients with autoimmune diseases, and 8 patients with mRNA vaccine-associated myocarditis. We confirm that most individuals generated robust virus-specific antibody responses post vaccination, but that the quality of this response is impaired in autoimmune patients on certain modes of immunosuppression. Autoantibody dynamics are remarkably stable in all vaccinated patients compared to COVID-19 patients that exhibit an increased prevalence of new autoantibody reactivities. Patients with vaccine-associated myocarditis do not have increased autoantibody reactivities relative to controls. In summary, our findings indicate that mRNA vaccines decouple SARS-CoV-2 immunity from autoantibody responses observed during acute COVID-19.

Plasmodium infection is associated with cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein.

Sero-surveillance can monitor and project disease burden and risk. However, SARS-CoV-2 antibody test results can produce false positive results, limiting their efficacy as a sero-surveillance tool. False positive SARS-CoV-2 antibody results are associated with malaria exposure, and understanding this association is essential to interpret sero-surveillance results from malaria-endemic countries. Here, pre-pandemic samples from eight malaria endemic and non-endemic countries and four continents were tested by ELISA to measure SARS-CoV-2 Spike S1 subunit reactivity. Individuals with acute malaria infection generated substantial SARS-CoV-2 reactivity. Cross-reactivity was not associated with reactivity to other human coronaviruses or other SARS-CoV-2 proteins, as measured by peptide and protein arrays. ELISAs with deglycosylated and desialated Spike S1 subunits revealed that cross-reactive antibodies target sialic acid on N-linked glycans of the Spike protein. The functional activity of cross-reactive antibodies measured by neutralization assays showed that cross-reactive antibodies did not neutralize SARS-CoV-2 in vitro. Since routine use of glycosylated or sialated assays could result in false positive SARS-CoV-2 antibody results in malaria endemic regions, which could overestimate exposure and population-level immunity, we explored methods to increase specificity by reducing cross-reactivity. Overestimating population-level exposure to SARS-CoV-2 could lead to underestimates of risk of continued COVID-19 transmission in sub-Saharan Africa.

Distinguishing features of Long COVID identified through immune profiling.

SARS-CoV-2 infection can result in the development of a constellation of persistent sequelae following acute disease called post-acute sequelae of COVID-19 (PASC) or Long COVID 1-3 . Individuals diagnosed with Long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions 1-3 ; however, the basic biological mechanisms responsible for these debilitating symptoms are unclear. Here, 215 individuals were included in an exploratory, cross-sectional study to perform multi-dimensional immune phenotyping in conjunction with machine learning methods to identify key immunological features distinguishing Long COVID. Marked differences were noted in specific circulating myeloid and lymphocyte populations relative to matched control groups, as well as evidence of elevated humoral responses directed against SARS-CoV-2 among participants with Long COVID. Further, unexpected increases were observed in antibody responses directed against non-SARS-CoV-2 viral pathogens, particularly Epstein-Barr virus. Analysis of circulating immune mediators and various hormones also revealed pronounced differences, with levels of cortisol being uniformly lower among participants with Long COVID relative to matched control groups. Integration of immune phenotyping data into unbiased machine learning models identified significant distinguishing features critical in accurate classification of Long COVID, with decreased levels of cortisol being the most significant individual predictor. These findings will help guide additional studies into the pathobiology of Long COVID and may aid in the future development of objective biomarkers for Long COVID.

High-throughput identification of autoantibodies that target the human exoproteome.

Autoantibodies that recognize extracellular proteins (the exoproteome) exert potent biological effects but are challenging to detect. Here, we developed rapid extracellular antigen profiling (REAP), a high-throughput technique for the comprehensive discovery of exoproteome-targeting autoantibodies. Patient samples are applied to a genetically barcoded yeast surface display library containing 2,688 human extracellular proteins. Antibody-coated yeast are isolated, and sequencing of barcodes is used to identify displayed antigens. To benchmark REAP's performance, we screened 77 patients with autoimmune polyglandular syndrome type 1 (APS-1). REAP sensitively and specifically detected both known and previously unidentified autoantibodies in APS-1. We further screened 106 patients with systemic lupus erythematosus (SLE) and identified numerous autoantibodies, several of which were associated with disease severity or specific clinical manifestations and exerted functional effects on cell signaling ex vivo. These findings demonstrate the utility of REAP to atlas the expansive landscape of exoproteome-targeting autoantibodies and their impacts on patient health outcomes.

Plasmodium infection induces cross-reactive antibodies to carbohydrate epitopes on the SARS-CoV-2 Spike protein.

Individuals with acute malaria infection generated high levels of antibodies that cross-react with the SARS-CoV-2 Spike protein. Cross-reactive antibodies specifically recognized the sialic acid moiety on N-linked glycans of the Spike protein and do not neutralize in vitro SARS-CoV-2. Sero-surveillance is critical for monitoring and projecting disease burden and risk during the pandemic; however, routine use of Spike protein-based assays may overestimate SARS-CoV-2 exposure and population-level immunity in malaria-endemic countries.

Divergent and self-reactive immune responses in the CNS of COVID-19 patients with neurological symptoms.

Individuals with coronavirus disease 2019 (COVID-19) frequently develop neurological symptoms, but the biological underpinnings of these phenomena are unknown. Through single-cell RNA sequencing (scRNA-seq) and cytokine analyses of cerebrospinal fluid (CSF) and blood from individuals with COVID-19 with neurological symptoms, we find compartmentalized, CNS-specific T cell activation and B cell responses. All affected individuals had CSF anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies whose target epitopes diverged from serum antibodies. In an animal model, we find that intrathecal SARS-CoV-2 antibodies are present only during brain infection and not elicited by pulmonary infection. We produced CSF-derived monoclonal antibodies from an individual with COVID-19 and found that these monoclonal antibodies (mAbs) target antiviral and antineural antigens, including one mAb that reacted to spike protein and neural tissue. CSF immunoglobulin G (IgG) from 5 of 7 patients showed antineural reactivity. This immune survey reveals evidence of a compartmentalized immune response in the CNS of individuals with COVID-19 and suggests a role of autoimmunity in neurologic sequelae of COVID-19.

Diverse functional autoantibodies in patients with COVID-19.

COVID-19 manifests with a wide spectrum of clinical phenotypes that are characterized by exaggerated and misdirected host immune responses1-6. Although pathological innate immune activation is well-documented in severe disease1, the effect of autoantibodies on disease progression is less well-defined. Here we use a high-throughput autoantibody discovery technique known as rapid extracellular antigen profiling7 to screen a cohort of 194 individuals infected with SARS-CoV-2, comprising 172 patients with COVID-19 and 22 healthcare workers with mild disease or asymptomatic infection, for autoantibodies against 2,770 extracellular and secreted proteins (members of the exoproteome). We found that patients with COVID-19 exhibit marked increases in autoantibody reactivities as compared to uninfected individuals, and show a high prevalence of autoantibodies against immunomodulatory proteins (including cytokines, chemokines, complement components and cell-surface proteins). We established that these autoantibodies perturb immune function and impair virological control by inhibiting immunoreceptor signalling and by altering peripheral immune cell composition, and found that mouse surrogates of these autoantibodies increase disease severity in a mouse model of SARS-CoV-2 infection. Our analysis of autoantibodies against tissue-associated antigens revealed associations with specific clinical characteristics. Our findings suggest a pathological role for exoproteome-directed autoantibodies in COVID-19, with diverse effects on immune functionality and associations with clinical outcomes.

Neuroinvasion of SARS-CoV-2 in human and mouse brain.

Although COVID-19 is considered to be primarily a respiratory disease, SARS-CoV-2 affects multiple organ systems including the central nervous system (CNS). Yet, there is no consensus on the consequences of CNS infections. Here, we used three independent approaches to probe the capacity of SARS-CoV-2 to infect the brain. First, using human brain organoids, we observed clear evidence of infection with accompanying metabolic changes in infected and neighboring neurons. However, no evidence for type I interferon responses was detected. We demonstrate that neuronal infection can be prevented by blocking ACE2 with antibodies or by administering cerebrospinal fluid from a COVID-19 patient. Second, using mice overexpressing human ACE2, we demonstrate SARS-CoV-2 neuroinvasion in vivo. Finally, in autopsies from patients who died of COVID-19, we detect SARS-CoV-2 in cortical neurons and note pathological features associated with infection with minimal immune cell infiltrates. These results provide evidence for the neuroinvasive capacity of SARS-CoV-2 and an unexpected consequence of direct infection of neurons by SARS-CoV-2.

Diverse Functional Autoantibodies in Patients with COVID-19.

COVID-19 manifests with a wide spectrum of clinical phenotypes that are characterized by exaggerated and misdirected host immune responses1-8. While pathological innate immune activation is well documented in severe disease1, the impact of autoantibodies on disease progression is less defined. Here, we used a high-throughput autoantibody discovery technique called Rapid Extracellular Antigen Profiling (REAP) to screen a cohort of 194 SARS-CoV-2 infected COVID-19 patients and healthcare workers for autoantibodies against 2,770 extracellular and secreted proteins (the "exoproteome"). We found that COVID-19 patients exhibit dramatic increases in autoantibody reactivities compared to uninfected controls, with a high prevalence of autoantibodies against immunomodulatory proteins including cytokines, chemokines, complement components, and cell surface proteins. We established that these autoantibodies perturb immune function and impair virological control by inhibiting immunoreceptor signaling and by altering peripheral immune cell composition, and found that murine surrogates of these autoantibodies exacerbate disease severity in a mouse model of SARS-CoV-2 infection. Analysis of autoantibodies against tissue-associated antigens revealed associations with specific clinical characteristics and disease severity. In summary, these findings implicate a pathological role for exoproteome-directed autoantibodies in COVID-19 with diverse impacts on immune functionality and associations with clinical outcomes.

Newborn Dried Blood Spots for Serologic Surveys of COVID-19.

There is an urgent need for inexpensive, population-wide surveillance testing for COVID-19. We tested newborn dried blood spot (DBS) anti-SARS-CoV-2 antibodies for all infants born at Yale from March to May 2020, and found that newborn DBS serologies reflect maternal and population-wide infection rates during the study period. This suggests a role for DBS in COVID-19 surveillance in areas where viral testing is limited.

Exploratory neuroimmune profiling identifies CNS-specific alterations in COVID-19 patients with neurological involvement.

One third of COVID-19 patients develop significant neurological symptoms, yet SARS-CoV-2 is rarely detected in central nervous system (CNS) tissue, suggesting a potential role for parainfectious processes, including neuroimmune responses. We therefore examined immune parameters in cerebrospinal fluid (CSF) and blood samples from a cohort of patients with COVID-19 and significant neurological complications. We found divergent immunological responses in the CNS compartment, including increased levels of IL-12 and IL-12-associated innate and adaptive immune cell activation. Moreover, we found increased proportions of B cells in the CSF relative to the periphery and evidence of clonal expansion of CSF B cells, suggesting a divergent intrathecal humoral response to SARS-CoV-2. Indeed, all COVID-19 cases examined had anti-SARS-CoV-2 IgG antibodies in the CSF whose target epitopes diverged from serum antibodies. We directly examined whether CSF resident antibodies target self-antigens and found a significant burden of CNS autoimmunity, with the CSF from most patients recognizing neural self-antigens. Finally, we produced a panel of monoclonal antibodies from patients' CSF and show that these target both anti-viral and anti-neural antigens-including one mAb specific for the spike protein that also recognizes neural tissue. This exploratory immune survey reveals evidence of a compartmentalized and self-reactive immune response in the CNS meriting a more systematic evaluation of neurologically impaired COVID-19 patients.

Neuroinvasion of SARS-CoV-2 in human and mouse brain.

Although COVID-19 is considered to be primarily a respiratory disease, SARS-CoV-2 affects multiple organ systems including the central nervous system (CNS). Yet, there is no consensus whether the virus can infect the brain, or what the consequences of CNS infection are. Here, we used three independent approaches to probe the capacity of SARS-CoV-2 to infect the brain. First, using human brain organoids, we observed clear evidence of infection with accompanying metabolic changes in the infected and neighboring neurons. However, no evidence for the type I interferon responses was detected. We demonstrate that neuronal infection can be prevented either by blocking ACE2 with antibodies or by administering cerebrospinal fluid from a COVID-19 patient. Second, using mice overexpressing human ACE2, we demonstrate in vivo that SARS-CoV-2 neuroinvasion, but not respiratory infection, is associated with mortality. Finally, in brain autopsy from patients who died of COVID-19, we detect SARS-CoV-2 in the cortical neurons, and note pathologic features associated with infection with minimal immune cell infiltrates. These results provide evidence for the neuroinvasive capacity of SARS-CoV2, and an unexpected consequence of direct infection of neurons by SARS-CoV-2.