Most downloaded biology preprints, all time
in category pathology
686 results found. For more information, click each entry to expand.
1,094 downloads bioRxiv pathology
Ferenc Tajti, Christoph Kuppe, Asier Antoranz, Mahmoud M Ibrahim, Hyojin Kim, Francesco Ceccarelli, Christian Holland, Hannes Olauson, Jürgen Floege, Leonidas G Alexopoulos, Rafael Kramann, Julio Saez-Rodriguez
To develop efficient therapies and identify novel early biomarkers for chronic kidney disease an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in CKD origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for nine kidney disease entities that account for a majority of CKD worldwide. We included data from five distinct studies and compared glomerular gene expression profiles to that of non-tumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms and conditions, that we mitigated with a bespoke stringent procedure. This allowed us to perform a global transcriptome-based delineation of different kidney disease entities, obtaining a landscape of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. Furthermore, we derived functional insights by inferring activity of signaling pathways and transcription factors from the collected gene expression data, and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating e.g. that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in RPGN whereas not expressed in control kidney tissue. These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities, that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate this, we provide our results as a free interactive web application: https://saezlab.shinyapps.io/ckd_landscape/.
1,080 downloads bioRxiv pathology
Background: Anosmia is a frequent symptom in coronavirus disease 2019 (COVID-19) patients that generally resolves within weeks. In contrast, the anosmia caused by other upper respiratory infections affects a small proportion of patients and may take months to resolve or never resolve. The mechanisms behind COVID-19-induced olfactory dysfunction remain unknown. Here, we address the unique pathophysiology of COVID-19-associated olfactory dysfunction. Methods: The expression of ACE2 (virus binding receptor) and TMPRSS2 and Furin (host cell proteases facilitating virus entry) was examined in the nasal mucosa, composed of respiratory mucosa (RM), olfactory mucosa (OM), and olfactory bulb (OB) of mouse and human tissues using immunohistochemistry and gene analyses. Results: Co-expression of ACE2, TMPRSS2, and Furin was observed in the RM and in the OM, especially in the supporting cells of the olfactory epithelium and the Bowman glands. Notably, the olfactory receptor neurons (ORNs) in the OM were positive for ACE2 but almost negative for TMPRSS2 and Furin. Cells in the OB expressed ACE2 strongly and Furin weakly, and did not express TMPRSS2. All three gene expressions were confirmed in the nasal mucosa and OB. Conclusions: ACE2 was widely expressed in all tissues, whereas TMPRSS2 and Furin were expressed only in certain types of cells and were absent in the ORNs. These findings, together with clinical reports, suggest that COVID-19-related anosmia occurs mainly through sensorineural and central dysfunction and, to some extent, conductive olfactory dysfunction. The expression of ACE2, but not TMPRSS2 or Furin, in ORNs may explain the early recovery from anosmia. ### Competing Interest Statement The authors have declared no competing interest.
1,046 downloads bioRxiv pathology
Joel J Credle, Matthew L Robinson, Jonathan Gunn, Daniel Monaco, Brandon Sie, Alexandra Tchir, Justin Hardick, Xuwen Zheng, Kathryn Shaw-Saliba, Richard E. Rothman, Susan H. Eshleman, Andrew Pekosz, Kasper Hansen, Heba Mostafa, Martin Steinegger, H. Benjamin Larman
The emergence of SARS-CoV-2 has caused the current COVID-19 pandemic with catastrophic societal impact. Because many individuals shed virus for days before symptom onset, and many show mild or no symptoms, an emergent and unprecedented need exists for development and deployment of sensitive and high throughput molecular diagnostic tests. RNA-mediated oligonucleotide Annealing Selection and Ligation with next generation DNA sequencing (RASL-seq) is a highly multiplexed technology for targeted analysis of polyadenylated mRNA, which incorporates sample barcoding for massively parallel analyses. Here we present a more generalized method, capture RASL-seq ("cRASL-seq"), which enables analysis of any targeted pathogen- (and/or host-) associated RNA molecules. cRASL-seq enables highly sensitive (down to ~1-100 pfu/ml or cfu/ml) and highly multiplexed (up to ~10,000 target sequences) detection of pathogens. Importantly, cRASL-seq analysis of COVID-19 patient nasopharyngeal (NP) swab specimens does not involve nucleic acid extraction or reverse transcription, steps that have caused testing bottlenecks associated with other assays. Our simplified workflow additionally enables the direct and efficient genotyping of selected, informative SARS-CoV-2 polymorphisms across the entire genome, which can be used for enhanced characterization of transmission chains at population scale and detection of viral clades with higher or lower virulence. Given its extremely low per-sample cost, simple and automatable protocol and analytics, probe panel modularity, and massive scalability, we propose that cRASL-seq testing is a powerful new surveillance technology with the potential to help mitigate the current pandemic and prevent similar public health crises. ### Competing Interest Statement J.J.C. and H.B.L. are listed as inventors on a patent describing the cRASL-seq method. H.B.L. has founded a company to license and commercialize oligonucleotide probe ligation related technologies.
1,037 downloads bioRxiv pathology
OBJECTIVE: Urothelial carcinoma of the urinary bladder is the fourth most common cancer in males in the United States. In addition to mutations in FGFR3, TP53, AKT1, TSC1, and PTEN genes, mutations in PIK3CA have been also described in urothelial carcinomas, preferentially in low-grade tumors. Mutations in PIK3CA also has been shown to have implications for prognosis, surveillance and therapeutic response. Thus, determining the PIK3CA status in urothelial carcinomas could potentially improved the clinical management of patients with bladder cancer. Herein, we evaluated the presence of PIK3CA mutations in exons 1, 9, and 20 in 21 urothelial carcinomas of the urinary bladder. METHODS: Patients were treated by radical cystectomy without neoadjuvant chemotherapy. Representative tissue blocks (1 for each case) were selected. We used a pinpoint DNA extraction technique from formalin-fixed, paraffin-embedded and mutational analysis using the polymerase chain reaction (PCR) assay coupled with sequencing of targeted exons. Patients included 15 men and 6 women, with a median age of 68 years (range, 42 to 76 years), with 3 noninvasive and 18 invasive urothelial carcinomas. Noninvasive carcinomas included 1 case each of low-grade papillary urothelial carcinoma, high-grade papillary urothelial carcinoma, and urothelial carcinoma in situ (CIS). Invasive tumors included 3 pT1, 5 pT2, 6 pT3, and 4 pT4 urothelial carcinomas. RESULTS: We did not find mutations in the analyzed exons of the PIK3CA gene, in any of the 21 urothelial carcinomas. The preponderance of invasive high-grade and high-stage tumors could explain the absence of identifiable mutations in our cohort. CONCLUSIONS: PIK3CA mutations as prognosticators of outcome or predictors of therapeutic response await further evaluation.
1,031 downloads medRxiv pathology
There is an exponential growth of COVID-19. The adaptation of preventive measures to limit the spread of infection among the people is the best solution to this health issue. The identification of infected cases and their isolation from healthy people is one of the most important preventive measures. In this regard, screening of the samples from a large number of people is needed which requires a lot of reagent kits for the detection of SARS-CoV-2. The use of smart pooled sample testing with the help of algorithms may be a quite useful strategy in the current prevailing scenario of the COVID-19 pandemic. With the help of this strategy, the optimum number of samples to be pooled for a single test may be determined based on the total positivity rate of the particular community.
1,025 downloads medRxiv pathology
Introduction The coronavirus disease 2019(COVID-19) is caused by the virus SARS-CoV-2 and is declared as a global pandemic by the World Health Organization (WHO). Various hematological parameters alteration has been documented in the Chinese literature in SARS-Cov-2 infection. However, there is a need for research to evaluate the pattern of the hematological parameters of COVID-19 patients in the Indian population. Aims & Objectives: The objective of the study is to see the Neutrophil-Lymphocyte Ratio (NLR), Platelet Lymphocyte Ratio (PLR), and other hematological parameters alteration of COVID-19 patients along with their clinical course in the Indian scenario. Methods: A single-center prospective study of 32 patients with laboratory-confirmed COVID-19 admitted to Super Speciality Pediatric Hospital & Post Graduate Teaching Institute NOIDA, from March to April, were enrolled for the study. The demographic data, the clinical status of the patients during admission and follow up, baseline, and follow up hematological findings were recorded. Statistical analysis of the data was carried out, and relevant findings were presented. Results: Demographic characterization shows a mean age of 37.7 years, male (41.9%), female (58.1%)with the majority of patients are mildly symptomatic to asymptomatic(93%). The CBC values and NLR, PLR at baseline between the male and the female patients, are not showing any statistically significant difference as the 95% C.I. A statistically significant increment in the lab parameters is observed in follow-up visits. Conclusion: The majority of the patients are younger and have mild clinical presentation with female predominance. Pediatric cases have mild symptomology. Baseline CBC findings show mild neutrophilia, lymphopenia, eosinopenia, and normal to mild thrombocytopenia. An increase in CBC parameters, NLR was noted in follow up cases. Anemia was not noted in baseline CBC and in the follow-up group. A onetime PLR is not indicative of disease progression. Key words: Corona virus,COVID-19,CBC,NLR,PLR
1,008 downloads bioRxiv pathology
A Statistical Analysis was performed to probe the correlation between the Zika Virus (ZIKV) and its possibility to induce Microcephaly in infants. It was found that without considering a false positive on tests for ZIKV on mothers there seems to be a statistical significance on ZIKV to cause Microcephaly in infants with a probability of q=0.092 ±15%. It was also shown that without knowing the confidence of the false positive tests of ZIKV it is not possible to statistically assert that this significance is true. It is proposed that to be able to discard the hypothesis of ZIKV not to cause the disease it is necessary to have a 30% of confidence in the ZIKV test.
989 downloads bioRxiv pathology
Since the early 1990s, ash dieback due to the invasive ascomycete Hymenoscyphus fraxineus is threatening Fraxinus excelsior in most of its natural range. Previous studies reported significant levels of genetic variability for susceptibility in F. excelsior either in field or inoculation experiments. The present study was based on a field experiment planted in 1995, fifteen years before onset of the disease. Crown and collar status were monitored on 788 trees from 23 open-pollinated progenies originating from 3 French provenances. Susceptibility was modeled using a Bayesian approach where spatio-temporal effects were explicitly taken into account. Moderate narrow-sense heritability was found for Crown Dieback (CD, h2 = 0.42). This study is first to show that Collar Lesions are also heritable (h2 = 0.49 for prevalence and h2 = 0.42 for severity) and that there is significant genetic correlation (r=0.40) between the severities of both symptoms. There was no evidence for differences between Provenances. Family effects were detected, but computing Individual Breeding Values (IBV) showed that most of the genetic variation lies within families. In agreement with previous reports, early flushing correlates with better crown status. Consequences of these results in terms of management and breeding are discussed.
985 downloads bioRxiv pathology
Patients with Alzheimer’s disease (AD) frequently suffer from spatial memory impairment and wandering behavior, but brain circuits causing such symptoms remain largely unclear. In healthy brains, spatially-tuned hippocampal place cells and entorhinal grid cells represent distinct spike patterns in different environments, a circuit function called “remapping” that underlies pattern separation of spatial memory. We investigated whether knock-in expression of mutated amyloid precursor protein deteriorates the remapping of place cells and grid cells. We found that the remapping of CA1 place cells was disrupted although their spatial tuning was only mildly diminished. Grid cells in the medial entorhinal cortex (MEC) were impaired, sending severely disrupted remapping signals to the hippocampus. Furthermore, fast gamma oscillations were disrupted in both CA1 and MEC, resulting in impaired fast gamma coupling in the MEC→CA1 circuit. These results point to the link between grid cell impairment and remapping disruption as a circuit mechanism causing spatial memory impairment in AD.
981 downloads bioRxiv pathology
Visual analysis of solid tissue mounted on glass slides is currently the primary method used by pathologists for determining the stage, type and subtypes of cancer. Although whole slide images are usually large (10s to 100s thousands pixels wide), an exhaustive though time-consuming assessment is necessary to reduce the risk of misdiagnosis. In an effort to address the many diagnostic challenges faced by trained experts, recent research has been focused on developing automatic prediction systems for this multi-class classification problem. Typically, complex convolutional neural network (CNN) architectures, such as Google's Inception, are used to tackle this problem. Here, we introduce a greatly simplified CNN architecture, PathCNN, which allows for more efficient use of computational resources and better classification performance. Using this improved architecture, we trained simultaneously on whole-slide images from multiple tumor sites and corresponding non-neoplastic tissue. Dimensionality reduction analysis of the weights of the last layer of the network capture groups of images that faithfully represent the different types of cancer, highlighting at the same time differences in staining and capturing outliers, artifacts and misclassification errors. Our code is available online at: https://github.com/sedab/PathCNN.
966 downloads bioRxiv pathology
Robert V. Blair, Monica Vaccari, Lara A Doyle-Meyers, Chad J. Roy, Kasi Russell-Lodrigue, Marissa Fahlberg, Chris J Monjure, Brandon Beddingfield, Kenneth S Plante, Jessica A. Plante, Scott C. Weaver, Xuebin Qin, Cecily C Midkiff, Gabrielle Lehmicke, Nadia Golden, Breanna Threeton, Toni Penney, Carolina Allers, Mary B Barnes, Melissa Pattison, Prasun K Datta, Nicholas J Maness, Angela Birnbaum, Tracy Fischer, Rudolf P. Bohm, Jay Rappaport
SARS-CoV-2 induces a wide range of disease severity ranging from asymptomatic infection, to a life-threating illness, particularly in the elderly and persons with comorbid conditions. Among those persons with serious COVID-19 disease, acute respiratory distress syndrome (ARDS) is a common and often fatal presentation. Animal models of SARS-CoV-2 infection that manifest severe disease are needed to investigate the pathogenesis of COVID-19 induced ARDS and evaluate therapeutic strategies. Here we report ARDS in two aged African green monkeys (AGMs) infected with SARS-CoV-2 that demonstrated pathological lesions and disease similar to severe COVID-19 in humans. We also report a comparatively mild COVID-19 phenotype characterized by minor clinical, radiographic and histopathologic changes in the two surviving, aged AGMs and four rhesus macaques (RMs) infected with SARS-CoV-2. We found dramatic increases in circulating cytokines in three of four infected, aged AGMs but not in infected RMs. All of the AGMs showed increased levels of plasma IL-6 compared to baseline, a predictive marker and presumptive therapeutic target in humans infected with SARS-CoV-2 infection. Together, our results show that both RM and AGM are capable of modeling SARS-CoV-2 infection and suggest that aged AGMs may be useful for modeling severe disease manifestations including ARDS. ### Competing Interest Statement The authors have declared no competing interest.
963 downloads bioRxiv pathology
In 2013, two new avian influenza viruses (AIVs) H7N9 and H10N8 emerged in China caused worldwide concerns. Previous studies have studied their originations independently; this study is the first time to investigate their co-originating characteristics. Gene segments of assorted subtype influenza A viruses, as well as H10N8 and H7N9, were collected from public database. With the help of series software, small and large-scale phylogenetic trees, mean evolutionary rates, and divergence years were obtained successionally. The results demonstrated the two AIVs co-originated from H9N2, and shared a spectrum of mutations in common on many key sites related to pathogenic, tropism and epidemiological characteristics. For a long time, H9N2 viruses had been circulated in eastern and southern China; poultry was the stable and lasting maintenance reservoir. High carrying rate of AIVs H9N2 in poultry had an extremely high risk of co-infections with other influenza viruses, which increased the risk of virus reassortment. It implied that novel AIVs reassortants based on H9N2 might appear and prevail at any time in China; therefore, surveillance of H9N2 AIVs should be given a high priority.
960 downloads bioRxiv pathology
Cancer is the second leading cause of death in United States. Early diagnosis of this disease is essential for many types of treatment. Cancer is most accurately observed by pathologists using tissue biopsy. In the past, evaluation of tissue samples was done manually, but to improve effciency and ensure consistent quality, there has been a push to evaluate these algorithmically. One important task in histological analysis is the segmentation and evaluation of nuclei. Nuclear morphology is important to understand the grade and progression of cancer. Convolutional neural networks (CNN) were trained to perform nuclei segmentation. Stains are used to highlight cellular features. However, there is signifcant variability in imaging of stained slides due to differences in stain, slide preparation and slide storage. This make automated methods challenging to implement across different datasets. This paper evaluates four stain normalization methods to reduce the variability between slides. Nuclear segmentation accuracy was evaluated for each normalized method. Baseline segmentation accuracy was improved by more than 50% of its base value as measured by the AUC and Recall. We believe this is the first study to look at the impact of four stain normalization approaches (histogram equalization, Reinhart, Macenko, Khan) on segmentation accuracy.
955 downloads medRxiv pathology
BackgroundMetagenomic next-generation sequencing (mNGS) of plasma cell-free DNA has emerged as an attractive diagnostic modality allowing broad-range pathogen detection, noninvasive sampling, and earlier diagnosis. However, little is known about its real-world clinical impact as used in routine practice. MethodsWe performed a retrospective cohort study of all patients for whom plasma mNGS (Karius test) was performed for all indications at 5 U.S. institutions over 1.5 years. Comprehensive chart review was performed, and standardized assessment of clinical impact of the mNGS based on the treating teams interpretation of Karius results and patient management was established. ResultsA total of 82 Karius tests were evaluated, from 39 (47.6%) adults and 43 (52.4%) children and a total of 53 (64.6%) immunocompromised patients. Karius positivity rate was 50/82 (61.0%), with 24 (48.0%) showing two or more organisms (range, 2-8). The Karius test results led to positive impact in 6 (7.3%), negative impact in 3 (3.7%), no impact in 70 (85.4%), and was indeterminate in 3 (3.7%). Cases with positive Karius result and clinical impact involved bacteria and/or fungi but not DNA viruses or parasites. In 10 patients who underwent 16 additional repeated tests, only one was associated with clinical impact. ConclusionsThe real-world impact of the Karius test as currently used in routine clinical practice is limited. Further studies are needed to identify high-yield patient populations, define the complementary role of mNGS to conventional microbiological methods, and how best to integrate mNGS into current testing algorithms. SummaryIn a multicenter retrospective cohort study, we show that the real-world clinical impact of plasma metagenomic next-generation sequencing (mNGS) for the noninvasive diagnosis of infections is limited (positive impact 7.3%). Further studies are needed to optimize the impact of mNGS.
955 downloads bioRxiv pathology
Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. However, complex morphological information remains unutilized in unaided approach to histopathology. In this study, we demonstrate how deep learning framework can be used for an automatic classification of Renal Cell Carcinoma (RCC) subtypes, and for identification of features that predict survival outcome from digital histopathological images. Convolutional neural networks (CNN's) trained on whole-slide images distinguish clear cell and chromophobe RCC from normal tissue with a classification accuracy of 93.39 % and 87.34 %, respectively. Further, a CNN trained to distinguish clear cell, chromophobe and papillary RCC achieves a classification accuracy of 92.61 %. Here, we introduced a novel support vector machine based method to deal with data imbalance in multi-class classification to improve the accuracy. Finally, we extracted the morphological features from high probability tumor regions identified by the CNN to predict patient survival outcome of most common clear cell RCC. The generated risk index based on both tumor shape and nuclei features are significantly associated with patient survival outcome. These results highlight that deep learning can play a role in both cancer diagnosis and prognosis.
942 downloads bioRxiv pathology
Edward J. Sanderlin, Nancy R Leffler, Kvin Lertpiriyapong, Qi Cai, Heng Hong, Vasudevan Bakthavatchalu, James G Fox, Joani Zary Oswald, Calvin R. Justus, Elizabeth A Krewson, Elizabeth A. O’Rourke, Li V. Yang
GPR4 is a proton-sensing G protein-coupled receptor that can be activated by extracellular acidosis. It has recently been demonstrated that activation of GPR4 by acidosis increases the expression of numerous inflammatory and stress response genes in vascular endothelial cells (ECs) and also augments EC-leukocyte adhesion. Inhibition of GPR4 by siRNA or small molecule inhibitors reduces endothelial cell inflammation. As acidotic tissue microenvironments exist in many types of inflammatory disorders, including inflammatory bowel disease (IBD), we examined the role of GPR4 in IBD using a dextran sulfate sodium (DSS)-induced colitis mouse model. We observed that GPR4 mRNA expression was increased in mouse and human IBD tissues when compared to control intestinal tissues. To determine the function of GPR4 in IBD, wild-type and GPR4-deficient mice were treated with 3% DSS for 7 days to induce acute colitis. Our results showed that the severity of colitis was decreased in GPR4-deficient DSS-treated mice in comparison to wild-type DSS-treated mice. Clinical parameters, macroscopic disease indicators, and histopathological features were less severe in the DSS-treated GPR4-deficient mice than the DSS-treated wild-type mice. Inflammatory gene expression, leukocyte infiltration, and isolated lymphoid follicle (ILF) formation were reduced in intestinal tissues of DSS-treated GPR4-null mice. Collectively, our results suggest GPR4 provides a pro-inflammatory role in IBD as the absence of GPR4 ameliorates intestinal inflammation in the acute DSS-induced IBD mouse model.
941 downloads bioRxiv pathology
Purpose: To use T1-, T2-weighted and diffusion tensor MR images to portray glioma grade by employing a voxel-wise supervised machine learning approach, and to assess the feasibility of this tool in preoperative tumor characterization. Materials and Methods: Conventional MRI, DTI datasets and histopathological evaluations of 40 patients with WHO grade II-IV gliomas were retrospectively analyzed. Databases were construed incorporating preoperative images, tumor delineation and grades. This data was used to train a multilayer perceptron based artificial neural network that performed voxel-by-voxel correlation of tumor grade and the feature vector. Results were mapped to grayscale images, whereas grade map was defined as a composite image that depicts grade assignments for intra-tumoral regions. The voxel-wise probability for high grade tumor classification was calculated for the entire tumor volumes, defined as the grade index. Results: The color hue on glioma grade maps allowed the discrimination of low and high grade cases. This method revealed connection between the heterogeneous appearance of tumors and the histopathological findings. Classification by the grade index had 92.31% specificity, 85.71% sensitivity. Conclusion: Glioma grade maps are advantageous in the visualization of the heterogeneous nature of intra-tumoral diffusion and relaxivity and can further enhance the characterization of tumors by providing a preoperative modality that expands information available for clinicians.
922 downloads medRxiv pathology
Seigo Nagashima, Monalisa Castilho Mendes, Ana Paula Camargo Martins, Nicolas Henrique Borges, Thiago Mateus Godoy, Anna Flavia Ribeiro dos Santos Miggiolaro, Felipe da Silva Deziderio, Lucia de Noronha, Cleber Machado-Souza
Objective: Endothelial cells that are close to the alveolar-capillary exchange membranes can be activated by SARS-CoV-2 infection leading to cytokine release and macrophage activation syndrome. This could trigger endothelial dysfunction, pyroptosis, and immunothrombosis, which are the vascular changes commonly referred to as COVID-19 endotheliopathy. Thus, this study aimed to identify tissue biomarkers associated with endothelial activation/dysfunction and the pyroptosis pathway in the lung and myocardial samples of COVID-19 patients and to compare them to pandemic Influenza A virus H1N1 subtype 2009 and Control cases. Approach and Results: Post-mortem lung (COVID-19 group=6 cases; H1N1 group=10 cases, and Control group=11 cases) and myocardial samples (COVID-19=2 cases and control=1 case) were analyzed using immunohistochemistry and the following monoclonal primary antibodies: anti-CD163, anti-interleukin-6 (IL-6), anti-tumor necrosis factor-alpha (TNF-alpha), anti-intercellular adhesion molecule-1 (ICAM-1), and anti-caspase-1. From the result, IL-6, TNF-alpha, ICAM-1, and caspase-1 showed higher tissue expression in the COVID-19 group than in the H1N1 and control groups. Conclusion: Our results demonstrated the presence of endotheliopathy and suggest the participation of the pyroptosis pathway in both the pulmonary and myocardial samples. These conditions might lead to systemic immunothrombotic events that could impair the efforts of clinical staff to avoid fatal outcomes. One of the goals of health professionals should be to identify the high-risk of immunothrombosis patients early to block endotheliopathy and its consequences.
916 downloads bioRxiv pathology
Background: An interaction of the food types with the gut microbiota changes is deeply implicated in human health and disease. To verify whether animal-based diets would lead to gut dysbiosis, systemic inflammation and inflammatory pathogenesis, we fed mice with chondroitin sulfate (CS), a sulfate-containing O-glycan naturally occurring in livestock and poultry products, and monitored the dynamic changes of microbial flores, inflammatory signatures, and pathogenic hallmarks. Results: A metagenomic gut microbiota analysis revealed the overgrowth of sulfatase-secreting bacteria and sulfate-reducing bacteria in the gastrointestinal tracts of mice upon daily CS feeding. Sulfatase-secreting bacteria compromise gut integrity through prompting mucin degradation and mucus lesions, which were evident from the upregulation of secretary leukocyte protease inhibitor (SLPI) and mucin 1/4 (MUC-1/4). A synchronous elevation of lipopolysaccharide (LPS) and tumor necrosis factor α (TNF-α) levels in the serum as well as cerebral, hepatic, cardiac and muscular tissues suggests bacterial endotoxinemia, chronic low-grade inflammation and mitochondrial dysfunction, eventually leading to the onset of global inflammatory pathogenesis towards arthritis, dementia, tumor, and fatty liver. Conclusions: CS triggers the early-phase and multi-systemic pathogenesis like arthritis, dementia, tumor, and fatty liver by enhancing gut opportunistic infection and evoking low-grade inflammation in mice. A plausible reason for the inconsistency of CS in treatment of osteoarthritis (OA) was also discussed.
908 downloads medRxiv pathology
Myriam Remmelink, Ricardo De Mendoca, Nicky D'Haene, Sarah De Clercq, Camille Verocq, Laetitia Lebrun, Philomene Lavis, Marie Lucie Racu, Anne Laure Trepant, Calliope Maris, Sandrine Rorive, Jean Christophe Goffard, Olivier De Witte, Lorenzo Peluso, Jean Louis Vincent, Christine Decaestecker, Fabio Silvio Taccone, Isabelle Salmon
Background Post-mortem studies can provide important information for understanding new diseases and small autopsy case series have already reported different findings in COVID-19 patients. Methods We evaluated whether some specific post-mortem features are observed in these patients and if these changes are related to the presence of the virus in different organs. Complete macroscopic and microscopic autopsies were performed on different organs in 17 COVID-19 non-survivors. Presence of SARS-CoV-2 was evaluated with immunohistochemistry (IHC) in lung samples and with real-time reverse-transcription polymerase chain reaction (RT-PCR) test in lung and other organs. Results Pulmonary findings revealed early-stage diffuse alveolar damage (DAD) in 15 out of 17 patients and microthrombi in small lung arteries in 11 patients. Late-stage DAD, atypical pneumocytes and/or acute pneumonia were also observed. Four lung infarcts, two acute myocardial infarctions and one ischemic enteritis were observed. There was no evidence of myocarditis, hepatitis or encephalitis. Kidney evaluation revealed the presence of hemosiderin in tubules or pigmented casts in most patients. Spongiosis and vascular congestion were the most frequently encountered brain lesions. No specific SARS-CoV-2 lesions were observed in any organ. IHC revealed positive cells with a heterogeneous distribution in the lungs of 11 of the 17 (65%) patients; RT-PCR yielded a wide distribution of SARS-CoV-2 in different tissues, with 8 patients showing viral presence in all tested organs (i.e. lung, heart, spleen, liver, colon, kidney and brain). Conclusions In conclusion, autopsies revealed a great heterogeneity of COVID-19-related organ injury and the remarkable absence of any specific viral lesions, even when RT-PCR identified the presence of the virus in many organs.
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