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At present, COVID-19 remains a public health concern due to the ongoing evolution of SARS-CoV-2 and its prevalence in particular countries. This paper provides an updated overview of the epidemiology and pathogenesis of COVID-19, with a focus on the emergence of SARS-CoV-2 variants and the phenomenon known as 'long COVID'. Meanwhile, diagnostic and detection advances will be mentioned. Though many inventions have been made to combat the COVID-19 pandemic, some outstanding ones include multiplex RT-PCR, which can be used for accurate diagnosis of SARS-CoV-2 infection. ELISA-based antigen tests also appear to be potential diagnostic tools to be available in the future. This paper also discusses current treatments, vaccination strategies, as well as emerging cell-based therapies for SARS-CoV-2 infection. The ongoing evolution of SARS-CoV-2 underscores the necessity for us to continuously update scientific understanding and treatments for it.

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Liquid biopsy, a noninvasive diagnosis that examines circulating tumor components in body fluids, is increasingly used in cancer management. An overview of relevant literature emphasizes the current state of liquid biopsy applications in cancer care. Biomarkers in liquid biopsy, particularly circulating tumor DNA (ctDNA), circulating tumor RNAs (ctRNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), and other components, offer promising opportunities for early cancer diagnosis, treatment selection, monitoring, and disease assessment. The implementation of liquid biopsy in precision medicine has shown significant potential in various cancer types, including lung cancer, colorectal cancer, breast cancer, and prostate cancer. Advances in genomic and molecular technologies such as next-generation sequencing (NGS) and digital polymerase chain reaction (dPCR) have expanded the utility of liquid biopsy, enabling the detection of somatic variants and actionable genomic alterations in tumors. Liquid biopsy has also demonstrated utility in predicting treatment responses, monitoring minimal residual disease (MRD), and assessing tumor heterogeneity. Nevertheless, standardizing liquid biopsy techniques, interpreting results, and integrating them into the clinical routine remain as challenges. Despite these challenges, liquid biopsy has significant clinical implications in cancer management, offering a dynamic and noninvasive approach to understanding tumor biology and guiding personalized treatment strategies.

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BACKGROUND: Menstrual blood (MB) is a convenient specimen type that can be self-collected easily and non-invasively by women. This study assessed the potential application of MB as a diagnostic specimen to detect genital tract infections (GTIs) and human papillomavirus (HPV) infections in women. METHOD: Genomic DNA was extracted from MB samples. Pacific Bioscience (Pacbio) 16S ribosomal DNA (rDNA) high-fidelity (HiFi) long-read sequencing and HPV PCR were performed. RESULTS: MB samples were collected from women with a pathological diagnosis of CIN1, CIN2, CIN3 or HPV infection. The sensitivity and positive predictive value (PPV) of high-risk HPV detection using MB were found to be 66.7%. A shift in vaginal flora and a significant depletion in Lactobacillus spp. in the vaginal microbiota communities were observed in the MB samples using 16S rDNA sequencing. CONCLUSIONS: In this study, we demonstrated that MB is a proper diagnostic specimen of consideration for non-invasive detection of HPV DNA and genotyping using PCR and the diagnosis of GTIs using metagenomic next-generation sequencing (mNGS). MB testing is suitable for all women who menstruate and this study has opened up the possibility of the use of MB as a diagnostic specimen to maintain women's health.

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Colorectal cancer (CRC) is one of the most prevalent cancers and the second leading cause of cancer deaths in developed countries. Early CRC may have no symptoms and symptoms usually appear with more advanced diseases. Regular screening can identify people who are at increased risk of CRC in order to offer earlier treatment. A cost-effective non-invasive platform for the screening and monitoring of CRC patients allows early detection and appropriate treatment of the disease, and the timely application of adjuvant therapy after surgical operation is needed. In this study, a cohort of 71 plasma samples that include 48 colonoscopy- and histopathology-confirmed CRC patients with TNM stages I to IV were recruited between 2017 and 2019. Plasma mRNA profiling was performed in CRC patients using NanoString nCounter. Normalized data were analyzed using a Mann-Whitney U test to determine statistically significant differences between samples from CRC patients and healthy subjects. A multiple-group comparison of clinical phenotypes was performed using the Kruskal-Wallis H test for statistically significant differences between multiple groups. Among the 27 selected circulating mRNA markers, all of them were found to be overexpressed (gene expression fold change > 2) in the plasma of patients from two or more CRC stages. In conclusion, NanoString-based targeted plasma CRC-associated mRNAs circulating the marker panel that can significantly distinguish CRC patients from a healthy population were developed for the non-invasive diagnosis of CRC using peripheral blood samples.

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Metagenomic sequencing has emerged as a transformative tool in infectious disease diagnosis, offering a comprehensive and unbiased approach to pathogen detection. Leveraging international standards and guidelines is essential for ensuring the quality and reliability of metagenomic sequencing in clinical practice. This review explores the implications of international standards and guidelines for the application of metagenomic sequencing in infectious disease diagnosis. By adhering to established standards, such as those outlined by regulatory bodies and expert consensus, healthcare providers can enhance the accuracy and clinical utility of metagenomic sequencing. The integration of international standards and guidelines into metagenomic sequencing workflows can streamline diagnostic processes, improve pathogen identification, and optimize patient care. Strategies in implementing these standards for infectious disease diagnosis using metagenomic sequencing are discussed, highlighting the importance of standardized approaches in advancing precision infectious disease diagnosis initiatives.

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Programmed cell death (PCD) is a fundamental biological process that plays a critical role in cell development, differentiation, and homeostasis. The secretion and uptake of extracellular vesicles (EVs) is one of the important regulatory mechanisms for PCD. EVs are natural membrane structures secreted by cells that contain a variety of proteins, lipids, nucleic acids, and other bioactive molecules. Due to their important roles in intercellular communication and disease progression, there is great interest in studying EVs and their cargo. Different protein components are sorted and packaged in EVs, allowing EVs to perform their functions. The study of EV proteomics helps us understand the role of PCD in the development of diseases. Meanwhile, proteomics is a powerful tool for studying the composition and function of EVs, which assists in the identification, quantification, and profiling of protein components of EVs, and provides insight into the molecular mechanisms involved in PCD and related diseases. In this review, we summarize the characteristics of EV proteomics in different types of PCD, compare different proteomic profiling strategies for EVs, and discuss the impact of EV proteomics on cell function and regulation during PCD, to understand its role in the pathogenesis of related diseases.

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Circulating tumor RNA (ctRNA) has recently emerged as a novel and attractive liquid biomarker. CtRNA is capable of providing important information about the expression of a variety of target genes noninvasively, without the need for biopsies, through the use of circulating RNA sequencing. The overexpression of cancer-specific transcripts increases the tumor-derived RNA signal, which overcomes limitations due to low quantities of circulating tumor DNA (ctDNA). The purpose of this work is to present an up-to-date review of current knowledge regarding ctRNAs and their status as biomarkers to address the diagnosis, prognosis, prediction, and drug resistance of colorectal cancer. The final section of the article discusses the practical aspects involved in analyzing plasma ctRNA, including storage and isolation, detection technologies, and their limitations in clinical applications.

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BACKGROUND: Next-generation sequencing comprehensive genomic panels (NGS CGPs) have enabled the delivery of tailor-made therapeutic approaches to improve survival outcomes in patients with cancer. Within the China Greater Bay Area (GBA), territorial differences in clinical practices and health care systems and strengthening collaboration warrant a regional consensus to consolidate the development and integration of precision oncology (PO). Therefore, the Precision Oncology Working Group (POWG) formulated standardized principles for the clinical application of molecular profiling, interpretation of genomic alterations, and alignment of actionable mutations with sequence-directed therapy to deliver clinical services of excellence and evidence-based care to patients with cancer in the China GBA. METHODS: Thirty experts used a modified Delphi method. The evidence extracted to support the statements was graded according to the GRADE system and reported according to the Revised Standards for Quality Improvement Reporting Excellence guidelines, version 2.0. RESULTS: The POWG reached consensus in six key statements: harmonization of reporting and quality assurance of NGS; molecular tumor board and clinical decision support systems for PO; education and training; research and real-world data collection, patient engagement, regulations, and financial reimbursement of PO treatment strategies; and clinical recommendations and implementation of PO in clinical practice. CONCLUSION: POWG consensus statements standardize the clinical application of NGS CGPs, streamline the interpretation of clinically significant genomic alterations, and align actionable mutations with sequence-directed therapies. The POWG consensus statements may harmonize the utility and delivery of PO in China's GBA.

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The combination of a PD-L1 inhibitor and an anti-angiogenic agent has become the new reference standard in the first-line treatment of non-excisable hepatocellular carcinoma (HCC) due to the survival advantage, but its objective response rate remains low at 36%. Evidence shows that PD-L1 inhibitor resistance is attributed to hypoxic tumor microenvironment. In this study, we performed bioinformatics analysis to identify genes and the underlying mechanisms that improve the efficacy of PD-L1 inhibition. Two public datasets of gene expression profiles, (1) HCC tumor versus adjacent normal tissue (N = 214) and (2) normoxia versus anoxia of HepG2 cells (N = 6), were collected from Gene Expression Omnibus (GEO) database. We identified HCC-signature and hypoxia-related genes, using differential expression analysis, and their 52 overlapping genes. Of these 52 genes, 14 PD-L1 regulator genes were further identified through the multiple regression analysis of TCGA-LIHC dataset (N = 371), and 10 hub genes were indicated in the protein-protein interaction (PPI) network. It was found that POLE2, GABARAPL1, PIK3R1, NDC80, and TPX2 play critical roles in the response and overall survival in cancer patients under PD-L1 inhibitor treatment. Our study provides new insights and potential biomarkers to enhance the immunotherapeutic role of PD-L1 inhibitors in HCC, which can help in exploring new therapeutic strategies.

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INTRODUCTION: COVID-19 pandemic is one of the most serious public health events of this century. There have been more than 670 million confirmed cases and more than 6 million deaths worldwide. From the emergence of the Alpha variant to the later rampant Omicron variant, the high transmissibility and pathogenicity of SARS-CoV-2 accelerate the research and development of effective vaccines. Against this background, mRNA vaccines stepped onto the historical stage and became an important tool for COVID-19 prevention. AREAS COVERED: This article introduces the characteristics of different mRNA vaccines in the prevention of COVID-19, including antigen selection, therapeutic mRNA design and modification, and different delivery systems of mRNA molecules. It also summarizes and discusses the mechanisms, safety, effectiveness, side effects, and limitations of current COVID-19 mRNA vaccines. EXPERT OPINION: Therapeutic mRNA molecules have plenty of advantages, including flexible design, rapid production, sufficient immune activation, safety without the risk of genome insertion in the host cells, and no viral vectors or particles involved, making them an important tool to fight diseases in the future. However, the application of COVID-19 mRNA vaccines also faces many challenges, such as storage and transportation, mass production, and nonspecific immunity.

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Background: Cell free RNA (cfRNA) contains transcript fragments from multiple cell types, making it useful for cancer detection in clinical settings. However, the pathophysiological origins of cfRNAs in plasma from colorectal cancer (CRC) patients remain unclear. Methods: To identify the tissue-specific contributions of cfRNAs transcriptomic profile, we used a published single-cell transcriptomics profile to deconvolute cell type abundance among paired plasma samples from CRC patients who underwent tumor-ablative surgery. We further validated the differentially expressed cfRNAs in 5 pairs of CRC tumor samples and adjacent tissue samples as well as 3 additional CRC tumor samples using RNA-sequencing. Results: The transcriptomic component from intestinal secretory cells was significantly decreased in the in-house post-surgical cfRNA. The HPGD, PACS1, and TDP2 expression was consistent across cfRNA and tissue samples. Using the Cancer Genome Atlas (TCGA) CRC datasets, we were able to classify the patients into two groups with significantly different survival outcomes. Conclusions: The three-gene signature holds promise in applying minimal residual disease (MRD) testing, which involves profiling remnants of cancer cells after or during treatment. Biomarkers identified in the present study need to be validated in a larger cohort of samples in order to ascertain their possible use in early diagnosis of CRC.

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Pediatric population was generally less affected clinically by SARS-CoV-2 infection. Few pediatric cases of COVID-19 have been reported compared to those reported in infected adults. However, a rapid increase in the hospitalization rate of SARS-CoV-2 infected pediatric patients was observed during Omicron variant dominated COVID-19 outbreak. In this study, we analyzed the B.1.1.529 (Omicron) genome sequences collected from pediatric patients by whole viral genome amplicon sequencing using Illumina next generation sequencing platform, followed by phylogenetic analysis. The demographic, epidemiologic and clinical data of these pediatric patients are also reported in this study. Fever, cough, running nose, sore throat and vomiting were the more commonly reported symptoms in children infected by Omicron variant. A novel frameshift mutation was found in the ORF1b region (NSP12) of the genome of Omicron variant. Seven mutations were identified in the target regions of the WHO listed SARS-CoV-2 primers and probes. On protein level, eighty-three amino acid substitutions and fifteen amino acid deletions were identified. Our results indicate that asymptomatic infection and transmission among children infected by Omicron subvariants BA.2.2 and BA.2.10.1 are not common. Omicron may have different pathogenesis in pediatric population.

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BACKGROUND: Colorectal cancer (CRC) is the second leading cause of cancer deaths in Hong Kong. We tested the hypothesis that circulating tumor cell (CTC) analysis by ARB101 antibody could be used as a tool for CRC detection, progression, and therapy response. RESEARCH METHODS: ARB101 antibody was used for investigation of CDH17 expression in formalin-fixed, paraffin-embedded (FFPE) tissue sections and circulating tumor cells (CTCs) of CRC patients. RESULTS: Using ARB101, highest sensitivity was observed in 98/100 (98%) colorectal cancer tissue compared to 72/100 gastric cancer (72%) and 27/32 pancreatic cancer (84%). Immunoreactivity of CDH17 was significantly higher in distant metastatic (tumor-node-metastasis [TNM] stage IV) than non-distant metastatic (TNM stage I to III) CRC. ARB101 antibody also manifested the higher sensitivity than c-erbB2 (8%) and epidermal growth factor receptor (EGFR)-targeting antibodies (37%) with the significance (p < 0.0001). ARB101 positive CTCs were detected in 64/83 (77%) TNM stage I to IV CRC patients. Furthermore, ARB101 positive CTCs detected in TNM stage I to III CRC patients before and after surgical operation are statistically significant (p < 0.0001). CONCLUSIONS: CTC detection by ARB101 antibody could serve as a potential non-invasive approach for CRC detection, progression, and monitoring of treatment response.

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The outbreak of COVID-19 has positively impacted the NGS market recently. Targeted sequencing (TS) has become an important routine technique in both clinical and research settings, with advantages including high confidence and accuracy, a reasonable turnaround time, relatively low cost, and fewer data burdens with the level of bioinformatics or computational demand. Since there are no clear consensus guidelines on the wide range of next-generation sequencing (NGS) platforms and techniques, there is a vital need for researchers and clinicians to develop efficient approaches, especially for the molecular diagnosis of diseases in the emergency of the disease and the global pandemic outbreak of COVID-19. In this review, we aim to summarize different methods of TS, demonstrate parameters for TS assay designs, illustrate different TS panels, discuss their limitations, and present the challenges of TS concerning their clinical application for the molecular diagnosis of human diseases.

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Colorectal cancer (CRC) threatens human health seriously. Early diagnosis of CRC is critical to improving patient survival. Meanwhile, non-invasive detection through tumor-circulating markers can be an important auxiliary diagnosis. In this study, we performed targeted RNA sequencing in paired tumor and adjacent normal fresh frozen tissues from 68 patients, and we also measured circulating mRNA levels in 4 time-point plasma samples collected before and after operation or chemotherapy. Our results showed that SOX9 (6.73-fold with adjusted p value < 1 × 10-45), MYC (20.59-fold with adjusted p value < 1 × 10-57), and MMP7 (131.94-fold with adjusted p value < 1 × 10-78) highly expressed in tumor compared with adjacent normal tissues. Besides, the circulating mRNA of SOX9 (41.14-fold with adjusted p value < 1 × 10-13) in CRC was significantly higher than in the normal control as well. Moreover, a SOX9-based 9-gene panel (SOX9, GSK3A, FZD4, LEF1, DVL1, FZD7, NFATC1, KRT19, and RUVBL1) showed the non-invasive diagnostic value of CRC (AUC: 0.863 (0.766-0.960), TPR: 0.92, TNR: 0.87). In summary, SOX9 expression consistently increases in tumor and plasma samples from CRC patients, which indicates the important role of SOX9 in CRC progression and its potential in non-invasive diagnosis of CRC.

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The implementation of DP will revolutionize current practice by providing pathologists with additional tools and algorithms to improve workflow. Furthermore, DP will open up opportunities for development of AI-based tools for more precise and reproducible diagnosis through computational pathology. One of the key features of AI is its capability to generate perceptions and recognize patterns beyond the human senses. Thus, the incorporation of AI into DP can reveal additional morphological features and information. At the current rate of AI development and adoption of DP, the interest in computational pathology is expected to rise in tandem. There have already been promising developments related to AI-based solutions in prostate cancer detection; however, in the GI tract, development of more sophisticated algorithms is required to facilitate histological assessment of GI specimens for early and accurate diagnosis. In this review, we aim to provide an overview of the current histological practices in AP laboratories with respect to challenges faced in image preprocessing, present the existing AI-based algorithms, discuss their limitations and present clinical insight with respect to the application of AI in early detection and diagnosis of GI cancer.

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INTRODUCTION: Clinical metagenomic next-generation sequencing (mNGS) allows a comprehensive genetic analysis of microbial materials. Different from other traditional target-driven molecular diagnostic tests, such as PCR, mNGS is a hypothesis-free diagnostic approach that allows a comprehensive genetic analysis of the clinical specimens that cover nearly any common, rare, and new pathogens ranging broadly from viruses, bacteria, fungi to parasites. AREAS COVERED: In this article, we discussed the clinical application of the mNGS using two clinical cases as examples and described the use of mNGS to assist the diagnosis of parasitic pulmonary infection. The advantages and challenges in implementing mNGS in clinical microbiology are also discussed. EXPERT OPINION: mNGS is a promising technology that allows quick diagnosis of infectious diseases. Currently, a plethora of sequencing and analysis methods exists for mNGS, each with individual merits and pitfalls. While standards and best practices were proposed by various metagenomics working groups, they are yet to be widely adopted in the community. The development of a consensus set of guidelines is necessary to guide the usage of this new technology and the interpretation of NGS results before clinical adoption of mNGS testing.

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BACKGROUND: Owing to the cytotoxic effect, it is challenging for clinicians to decide whether post-operative adjuvant therapy is appropriate for a non-small cell lung cancer (NSCLC) patient. Radiomics has proven its promising ability in predicting survival but research on its actionable model, particularly for supporting the decision of adjuvant therapy, is limited. METHODS: Pre-operative contrast-enhanced CT images of 123 NSCLC cases were collected, including 76, 13, 16, and 18 cases from R01 and AMC cohorts of The Cancer Imaging Archive (TCIA), Jiangxi Cancer Hospital and Guangdong Provincial People's Hospital respectively. From each tumor region, 851 radiomic features were extracted and two augmented features were derived therewith to estimate the likelihood of adjuvant therapy. Both Cox regression and machine learning models with the selected main and interaction effects of 853 features were trained using 76 cases from R01 cohort, and their test performances on survival prediction were compared using 47 cases from the AMC cohort and two hospitals. For those cases where adjuvant therapy was unnecessary, recommendations on adjuvant therapy were made again by the outperforming model and compared with those by IBM Watson for Oncology (WFO). RESULTS: The Cox model outperformed the machine learning model in predicting survival on the test set (C-Index: 0.765 vs. 0.675). The Cox model consists of 5 predictors, interestingly 4 of which are interactions with augmented features facilitating the modulation of adjuvant therapy option. While WFO recommended no adjuvant therapy for only 13.6% of cases that received unnecessary adjuvant therapy, the same recommendations by the identified Cox model were extended to 54.5% of cases (McNemar's test p = 0.0003). CONCLUSIONS: A Cox model with radiomic and augmented features could predict survival accurately and support the decision of adjuvant therapy for bettering the benefit of NSCLC patients.

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This study aimed to identify radiomic features of primary tumor and develop a model for indicating extrahepatic metastasis of hepatocellular carcinoma (HCC). Contrast-enhanced computed tomographic (CT) images of 177 HCC cases, including 26 metastatic (MET) and 151 non-metastatic (non-MET), were retrospectively collected and analyzed. For each case, 851 radiomic features, which quantify shape, intensity, texture, and heterogeneity within the segmented volume of the largest HCC tumor in arterial phase, were extracted using Pyradiomics. The dataset was randomly split into training and test sets. Synthetic Minority Oversampling Technique (SMOTE) was performed to augment the training set to 145 MET and 145 non-MET cases. The test set consists of six MET and six non-MET cases. The external validation set is comprised of 20 MET and 25 non-MET cases collected from an independent clinical unit. Logistic regression and support vector machine (SVM) models were identified based on the features selected using the stepwise forward method while the deep convolution neural network, visual geometry group 16 (VGG16), was trained using CT images directly. Grey-level size zone matrix (GLSZM) features constitute four of eight selected predictors of metastasis due to their perceptiveness to the tumor heterogeneity. The radiomic logistic regression model yielded an area under receiver operating characteristic curve (AUROC) of 0.944 on the test set and an AUROC of 0.744 on the external validation set. Logistic regression revealed no significant difference with SVM in the performance and outperformed VGG16 significantly. As extrahepatic metastasis workups, such as chest CT and bone scintigraphy, are standard but exhaustive, radiomic model facilitates a cost-effective method for stratifying HCC patients into eligibility groups of these workups.

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BACKGROUND: The import of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.36.27 has sparked the fourth wave of COVID-19 outbreak in Hong Kong. This strain has been circulating in Hong Kong since September 2020 but rarely found in other countries (<1%). RESEARCH DESIGN AND METHODS: A total of 14 SARS-CoV-2 genome sequences collected from patients in Hong Kong between July 2020 and March 2021 were determined by whole viral genome sequencing using Illumina next-generation sequencing platform, followed by phylogenetic analysis. RESULTS: Of the 14 SARS-CoV-2 genome sequences analyzed, 9 strains belonged to the PANGO lineage B.1.36.27, GISAID clade GH, and Nextclade clade 20A. Compared to the reference genome, 31 nucleotide differences and 11 amino acid differences were identified in the genome of the SARS-CoV-2 from PANGO lineage B.1.36.27. CONCLUSIONS: We reported the nucleotides and amino acids mutations identified in the SARS-CoV-2 from PANGO lineage B.1.36.27. Our viral genome sequences enriched the understanding of SARS-CoV-2 mutational landscape and improved the repertoire of known SARS-CoV-2 variants for tracking and tracing. From this study, we found no evidence to show that SARS-CoV-2 from lineage B.1.36.27 can compromise existing vaccines and antibody therapies.

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