We describe the Harder--Narasimhan filtration of the Hodge bundle for Teichm\"uller curves in the non-varying strata of quadratic differentials appearing in [CM2]. Moreover, we show that the Hodge bundle on the non-varying strata away from the irregular components can split as a direct sum of line bundles. As applications, we determine all individual Lyapunov exponents of algebraically primitive Teichm\"uller curves in the non-varying strata and derive new results regarding the asymptotic behavior of Lyapunov exponents.

Purpose:Self-collected specimens are increasingly being used as alternatives to swab-based methods for the detection of respiratory viruses. While saliva is well accepted, gargle specimens are a potential alternative with characteristics that are more favorable for laboratory handling. This study assessed the performance of gargle specimens in the detection of influenza A viruses (IAVs).Patients and Methods:We performed a prospective head-to-head comparison between combined nasopharyngeal and oropharyngeal swabs (NPS&OPS) and purified water gargle (PWG) among adult outpatients with febrile respiratory symptoms to detect IAVs using real-time RT-PCR during two influenza seasons.Results:During study periods 1 (July 13 to 26, 2022, H3N2 predominated) and 2 (February 25 to March 10, 2023, H1N1 pdm09 predominated), a total of 459 patients were recruited. The overall agreement between the NPS&OPS and PWG was 85.0% (390/459, κ = 0.697), with 88.0% in period 1 and 82.6% in period 2. The detection rate of IAVs in PWG (51.6%, 237/459) was lower than that in NPS&OPS (62.3%, 286/459) (p < 0.0001). The overall sensitivity and specificity were 96.6% (93.7-98.3%) and 100% (97.1-100%) in NPS&OPS and were 80.1% (75.0-84.4%) and 100% (97.1-100%) in PWG, respectively. Among the 227 pairs of concordant positive specimens, cycle threshold (Ct) values were significantly lower in NPS&OPS than in PWG (median Ct values: 24.2, 28.2, p < 0.0001).Conclusion:Although self-collected PWG specimens offer acceptable performance for IAVs molecular testing, NPS&OPS remain a reliable option. Given the convenience of collection, nonviscous gargles are recommended for viral detection during emergencies or under specific conditions.

Abstract Recent advances in unbiased metagenomic next-generation sequencing (mNGS) have enabled the simultaneous examination of both microbial and host genetic material in a single test. This study harnesses cost-effective bronchoalveolar lavage fluid (BALF) mNGS data from patients with lung cancer (n=123) and pulmonary infections (n=279). We developed a machine learning-based diagnostic approach to differentiate between these two conditions, which are often misdiagnosed in clinical settings. To ensure independence between model construction and validation, we divided the cohorts based on the collection dates of the samples. The training cohort (lung cancer, n=87; pulmonary infection, n=197) revealed distinct differences in DNA/RNA microbial composition, bacteriophage abundances, and host responses, including gene expression, transposable element levels, immune cell composition, and tumor fraction determined by copy number variation (CNV). These features, blinded to the validation cohort, were integrated into a host/microbe metagenomics-driven machine learning model (Model VI). The model demonstrated an Area Under the Curve (AUC) of 0.87 (95% CI = 0.857-0.883) in the training cohort and 0.831 (95% CI = 0.819-0.843) in the validation cohort for differentiating between patients with lung cancer and pulmonary infections. Applying a composite predictive model based on a rule-in and rule-out strategy significantly increased accuracy in distinguishing lung cancer from tuberculosis (ACC=0.913), fungal infection (ACC=0.955), and bacterial infection (ACC=0.836). These results underscore the potential of mNGS-based analysis as a valuable, cost-effective tool for the early differentiation of lung cancer from pulmonary infections, offering a comprehensive testing solution in a clinical context.

Ecological studies suggested a link between air pollution and severe COVID-19 outcomes, while studies accounting for individual-level characteristics are limited. In the present study, we aimed to investigate the impact of short-term ambient air pollution exposure on disease severity among a cohort of 569 laboratory confirmed COVID-19 patients admitted to designated hospitals in Zhejiang province, China, from January 17 to March 3, 2020, and elucidate the possible biological processes involved using transcriptomics. Compared with mild cases, severe cases had higher proportion of medical conditions as well as unfavorable results in most of the laboratory tests, and manifested higher air pollution exposure levels. Higher exposure to air pollutants was associated with increased risk of severe COVID-19 with odds ratio (OR) of 1.89 (95% confidence interval (CI): 1.01, 3.53), 2.35 (95% CI: 1.20, 4.61), 2.87 (95% CI: 1.68, 4.91), and 2.01 (95% CI: 1.10, 3.69) for PM2.5, PM10, NO2 and CO, respectively. OR for NO2 remained significant in two-pollutant models after adjusting for other pollutants. Transcriptional analysis showed 884 differentially expressed genes which mainly were enriched in virus clearance related biological processes between patients with high and low NO2 exposure levels, indicating that compromised immune response might be a potential underlying mechanistic pathway. These findings highlight the impact of short-term air pollution exposure, particularly for NO2, on COVID-19 severity, and emphasize the significance in mitigating the COVID-19 burden of commitments to improve air quality.

Idiopathic pulmonary fibrosis (IPF) is a group of chronic interstitial pulmonary diseases characterized by myofibroblast proliferation and extracellular matrix (ECM) deposition. However, current treatments are not satisfactory. Therefore, more effective therapies need to be explored. Cepharanthine (CEP) is a naturally occurring alkaloid that has recently been reported to have multiple pharmacological effects, particularly in chronic inflammation. For in vivo experiments, first, a pulmonary fibrosis murine model was generated via tracheal injection of bleomycin (BLM). Second, the clinical manifestations and histopathological changes of the mice were used to verify that treatment with CEP might significantly reduce BLM-induced fibrosis. Furthermore, flow cytometric analysis was used to analyze the changes in the number of M2 macrophages in the lung tissues before and after treatment with CEP to explore the relationship between macrophage M2 polarization and pulmonary fibrosis. In vitro, we constructed two co-culture systems (THP-1 and MRC5 cells, RAW264.7 and NIH 3T3 cells), and measured the expression of fibrosis-related proteins to explore whether CEP could reduce pulmonary fibrosis by regulating macrophage M2 polarization and fibroblast activation. The results showed that the intranasal treatment of CEP significantly attenuated the symptoms of pulmonary fibrosis induced by BLM in a murine model. Our findings also indicated that CEP treatment markedly reduced the expression of fibrosis markers, including TGF-β1, collagen I, fibronectin and α-SMA, in the mouse lung. Furthermore, in vitro studies demonstrated that CEP attenuated pulmonary fibrosis by inhibiting fibroblast activation through modulating macrophage M2 polarization and reducing TGF-β1 expression. This study demonstrated the potential and efficacy of CEP in the treatment of pulmonary fibrosis. In particular, this study revealed a novel mechanism of CEP in inhibiting fibroblast activation by regulating macrophage M2 polarization and reducing the expression of fibrosis-associated factors. Our findings open a new direction for future research into the treatment of pulmonary fibrosis.

AbstractHyperglycemia and diabetes are common metabolic disorders. It is considered a safe and effective strategy to screen active ingredients from food and herbs for controlling blood sugar levels. Quinic acid (QA) is a natural polyphenolic acid with various health‐promoting properties. In this study, QA was found to exhibit a potent inhibitory effect on α‐glucosidase activity, with a half maximal inhibitory concentration (IC50) of 5.46 mM. This inhibitory property surpassed that of three common organic acids including gallic acid, malic acid, and citric acid. A combination of 25% acarbose (0.5 mM) and 75% QA (5 mM) (v/v) exhibited synergistic inhibition of α‐glucosidase activity. Enzyme kinetics, fluorescence spectra, and molecular docking analyses indicated that QA acted as an uncompetitive inhibitor of α‐glucosidase, with hydrogen bonds playing a key role in the intermolecular interactions. Moreover, QA was found to effectively inhibit three major nonenzymatic glycation products including advanced glycosylation end products (AGEs), fructosamine, and α‐dicarbonyl in a dose‐dependent manner, outperforming the positive control aminoguanidine (AG) within the tested concentration range. Utilizing a Caco‐2 cell model, QA demonstrated the ability to inhibit the transmembrane absorption of glucose. This study highlighted QA as a promising food functional factor that had been overlooked in the past, offering potential benefits in improving hyperglycemia, diabetes, and associated complications through the inhibition of α‐glucosidase, nonenzymatic glycosylation, and glucose uptake.

Babesiosis, as a vector-borne infectious disease, remains relatively rare and is prone to being overlooked and misdiagnosed. Therefore, understanding the epidemiological characteristics and clinical manifestations of babesiosis is crucial for the prompt detection and treatment of the disease. We reported a 63-year-old male patient presenting with spontaneous fever and chills. Laboratory investigations revealed erythrocytopenia, reduced hemoglobin levels, and increased reticulocytes and total bilirubin. Bone marrow examination indicated vigorous cell proliferation, a decreased granulocyte to red cell ratio, and predominant erythroid cell proliferation, with a higher prevalence of intermediate and late-stage juvenile granulocyte and erythroid cells. Initial treatment focused on hemophagocytic syndrome triggered by Epstein-Barr virus infection yielded unsatisfactory results, leading to secondary multiple pulmonary infections. Metagenomic next-generation sequencing (mNGS) of sputum samples pointed to hemolytic anemia induced by Babesia infection, which was subsequently confirmed through peripheral blood smear analysis. The patient responded well to prompt administration of atovaquone and azithromycin, with symptoms resolving and laboratory parameters normalizing. Hemolytic anemia resulting from babesiosis should be distinguished from hemophagocytic syndrome caused by Epstein-Barr virus and other hematologic conditions. mNGS represents an efficient technique for Babesia detection.

The antibiotic resistome is the collection of all antibiotic resistance genes (ARGs) present in an individual. Whether an individual's susceptibility to infection and the eventual severity of coronavirus disease 2019 (COVID-19) is influenced by their respiratory tract antibiotic resistome is unknown. Additionally, whether a relationship exists between the respiratory tract and gut ARGs composition has not been fully explored. We recruited 66 patients with COVID-19 at three disease stages (admission, progression, and recovery) and conducted a metagenome sequencing analysis of 143 sputum and 97 fecal samples obtained from them. Respiratory tract, gut metagenomes, and peripheral blood mononuclear cell (PBMC) transcriptomes are analyzed to compare the gut and respiratory tract ARGs of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between ARGs and immune response. Among the respiratory tract ARGs, we found that Aminoglycoside, Multidrug, and Vancomycin are increased in ICU patients compared with nICU patients. In the gut, we found that Multidrug, Vancomycin, and Fosmidomycin were increased in ICU patients. We discovered that the relative abundances of Multidrug were significantly correlated with clinical indices, and there was a significantly positive correlation between ARGs and microbiota in the respiratory tract and gut. We found that immune-related pathways in PBMC were enhanced, and they were correlated with Multidrug, Vancomycin, and Tetracycline ARGs. Based on the ARG types, we built a respiratory tract-gut ARG combined random-forest classifier to distinguish ICU COVID-19 patients from nICU patients with an AUC of 0.969. Cumulatively, our findings provide some of the first insights into the dynamic alterations of respiratory tract and gut antibiotic resistome in the progression of COVID-19 and disease severity. They also provide a better understanding of how this disease affects different cohorts of patients. As such, these findings should contribute to better diagnosis and treatment scenarios.

Background Metagenomic next-generation sequencing (mNGS) provides innovative solutions for predicting complex infections. A comprehensive understanding of its strengths and limitations in real-world clinical settings is necessary to ensure that it is not overused or misinterpreted. Methods Two hundred nine cases with suspected pneumonia were recruited to compare the capabilities of 2 available mNGS assays (bronchoalveolar lavage fluid [BALF] mNGS and plasma mNGS) to identify pneumonia-associated DNA/RNA pathogens and predict antibiotic resistance. Results Compared to clinical diagnosis, BALF mNGS demonstrated a high positive percent agreement (95.3%) but a low negative percent agreement (63.1%). Plasma mNGS revealed a low proportion of true negatives (30%) in predicting pulmonary infection. BALF mNGS independently diagnosed 65.6% (61/93) of coinfections and had a remarkable advantage in detecting caustic, rare, or atypical pathogens. Pathogens susceptible to invasive infection or bloodstream transmission, such as Aspergillus spp, Rhizopus spp, Chlamydia psittaci, and human herpesviruses, are prone to be detected by plasma mNGS. BALF mNGS tests provided a positive impact on the diagnosis and treatment of 128 (61.2%) patients. Plasma mNGS, on the other hand, turned out to be more suitable for diagnosing patients who received mechanical ventilation, developed severe pneumonia, or developed sepsis (all P < .01). BALF mNGS was able to identify resistance genes that matched the phenotypic resistance of 69.4% (25/36) of multidrug-resistant pathogens. Conclusions Our data reveal new insights into the advantages and disadvantages of 2 different sequencing modalities in pathogen identification and antibiotic resistance prediction for patients with suspected pneumonia.

Background:Metagenomic next-generation sequencing (mNGS) is a promising tool for improving antimicrobial therapy and infection control decision-making in complex infections. Secondary infection surveillance using mNGS in COVID-19 patients has rarely been reported.Methods:Respiratory pathogen and antibiotic resistance prediction were evaluated by BALF mNGS for 192 hospitalized COVID-19 patients between December 2022 and February 2023.Results:Secondary infection was confirmed in 83.3% (160/192) of the COVID-19 patients, with bacterial infections (45%, 72/160) predominating, followed by mixed bacterial and fungal infections (20%, 32/160), and fungal infections (17.5%, 28/160). The incidence of bacterial or viral secondary infection was significantly higher in patients who were admitted to the ICU, received mechanical ventilation, or developed severe pneumonia (all p<0.05). Klebsiella pneumoniae (n=30, 8.4%) was the most prevalent pathogen associated with secondary infection followed by Acinetobacter baumannii (n=29, 8.1%), Candida albicans (n=29, 8.1%), Aspergillus fumigatus (n=27, 7.6%), human herpes simplex virus type 1 (n=23, 6.4%), Staphylococcus aureus (n=20, 5.6%) and Pneumocystis jiroveci (n=14, 3.9%). The overall concordance between the resistance genes detected by mNGS and the reported phenotypic resistance in 69 samples containing five clinically important pathogens (ie, K. pneumoniae, A. baumannii, S. aureus, P. aeruginosa and E. coli) that caused secondary infection was 85.5% (59/69).Conclusion:mNGS can detect pathogens causing secondary infection and predict antimicrobial resistance for COVID19 patients. This is crucial for initiating targeted treatment and rapidly detect unsuspected spread of multidrug-resistant pathogens.

Triterpene saponins exhibit various biological and pharmacological activities. However, the knowledge on saponin biosynthesis in tea plants (Camellia sinensis L.) is still limited. In this work, tea flower and seed samples at different developmental stages and leaves were collected and analyzed with UPLC-PDA-MS and RNA sequencing for saponin determination and transcriptome comparison. The saponin content reached around 19% in the freshly mature seeds and 7% in the green flower buds, and decreased with the fruit ripeness and flower blooming. Almost no saponins were detected in leaf samples. PCA and KEGG analysis suggested that the gene expression pattern and secondary metabolism in TF1 and TS2 vs. leaf samples were significantly different. Weighted gene coexpression network analysis (WGCNA) uncovered two modules related to saponin content. The mevalonate (MVA) instead of 2-C-methyl-d-erythritol-4-phospate (MEP) pathway was responsible for saponin accumulation in tea plants, and 3-hydroxy-3-methylglutaryl-CoA synthase (HMGS), diphosphomevalonate decarboxylase (MVD) and isopentenyl diphosphate isomerase (IDI) may be the key enzymes involved in saponin biosynthesis in tea seeds and flowers. Moreover, ten transcription factors (TFs) were predicted to regulate saponin biosynthesis in the tea plant. Taken together, our study provides a global insight into the saponin biosynthesis and accumulation in the tea plant.

Two major green leaf volatiles (GLVs) in tea that contribute greatly to tea aroma, particularly the green odor, are (E)-2-hexenal and (Z)-3-hexenal. Until now, their formation and related mechanisms during tea manufacture have remained unclear. Our data showed that the contents of (E)-2-hexenal and (Z)-3-hexenal increased more than 1000-fold after live tea leaves were torn. Subsequently, a new (Z)-3:(E)-2-hexenal isomerase (CsHI) was identified in Camellia sinensis. CsHI irreversibly catalyzed the conversion of (Z)-3-hexenal to (E)-2-hexenal. Abiotic stresses including low temperature, dehydration, and mechanical wounding, did not influence the (E)-2-hexenal content in intact tea leaves during withering, but regulated the proportions of (Z)-3-hexenal and (E)-2-hexenal in torn leaves by modulating CsHI at the transcript level. For the first time, this work reveals the formation of (E)-2-hexenal during tea processing and suggests that CsHI may play a pivotal role in tea flavor development as well as in plant defense against abiotic stresses.

The role of respiratory tract microbes and the relationship between respiratory tract and gut microbiomes in coronavirus disease 2019 (COVID-19) remain uncertain. Here, the metagenomes of sputum and fecal samples from 66 patients with COVID-19 at three stages of disease progression are sequenced. Respiratory tract, gut microbiome, and peripheral blood mononuclear cell (PBMC) samples are analyzed to compare the gut and respiratory tract microbiota of intensive care unit (ICU) and non-ICU (nICU) patients and determine relationships between respiratory tract microbiome and immune response. In the respiratory tract, significantly fewer Streptococcus, Actinomyces, Atopobium, and Bacteroides are found in ICU than in nICU patients, while Enterococcus and Candida increase. In the gut, significantly fewer Bacteroides are found in ICU patients, while Enterococcus increases. Significant positive correlations exist between relative microbiota abundances in the respiratory tract and gut. Defensin-related pathways in PBMCs are enhanced, and respiratory tract Streptococcus is reduced in patients with COVID-19. A respiratory tract-gut microbiota model identifies respiratory tract Streptococcus and Atopobium as the most prominent biomarkers distinguishing between ICU and nICU patients. The findings provide insight into the respiratory tract and gut microbial dynamics during COVID-19 progression, considering disease severity, potentially contributing to diagnosis, and treatment strategies.

COVID-19 The study presented in article number 2200956 by Shufa Zheng, Yu Chen, and co-workers, shows that dynamic changes occur in the respiratory tract and gut microbial communities of COVID-19 patients with different disease severity and that significant changes in the composition of the respiratory tract and gut microbiomes can be found between intensive care unit (ICU) and non-ICU patients.

Background: Severe disease of COVID-19 and mortality occur more frequently in male patients than that in female patients may be related to testosterone level. However, the diagnostic value of changes in the level of testosterone in predicting severe disease of male COVID-19 patients has not been determined yet.Methods: Sixty-one male COVID-19 patients admitted to the First Affiliated Hospital of Zhejiang University School of Medicine were enrolled. Serum samples at different stages of the patients after admission were collected and testosterone levels were detected to analyze the correlation between testosterone level and disease severity. Transcriptome analysis of PBMC was performed in 34 patients.Results: Testosterone levels at admission in male non-ICU COVID-19 patients (3.7 nmol/L, IQR: 1.5 -4.7) were significantly lower than those in male ICU COVID-19 patients (6.7 nmol/L, IQR: 4.2 -8.7). Testosterone levels in the non-ICU group increased gradually during the progression of the disease, while those in the ICU group remained low. In addition, testosterone level of enrolled patients in the second week after onset was significantly correlated with the severity of pneumonia, and ROC curve showed that testosterone level in the second week after onset was highly effective in predicting the severity of COVID-19. Transcriptome studies have found that testosterone levels of COVID-19 patients were associated with immune response, including T cell activation and regulation of lymphocyte activation. In addition, CD28 and Inositol Polyphosphate-4-Phosphatase Type II B (INPP4B) were found positively correlated with testosterone.Conclusions: Serum testosterone is an independent risk factor for predicting the severity of COVID-19 in male patients, and the level of serum testosterone in the second week after onset is valuable for evaluating the severity of COVID-19. Testosterone level is associated with T cell immune activation. The monitoring of serum testosterone should be highlighted in clinical treatment and the related mechanism should be further studied.

Sourness usually reduces the sensory quality of black tea, and organic acids are considered as one of major contributors. A UPLC-MRM-MS method was successfully developed to analyze organic acids during the processing of black tea made of "Yingshuang" tea variety. The contents of quinic acid and citric acid increased first and then decreased during withering, but didn't significantly changed after the whole processing. Malic acid content obviously dropped in early withering, and then stayed at low level. These three acids at withering stage were regulated by quinate dehydrogenase (QDH), citrate synthase (CS), phosphoenolpyruvate carboxylase (PEPC) and malic enzyme (ME). Gallic acid sharply increased after rolling, resulted from the hydrolysis of epigallocatechin gallate (EGCG) by endogenous tannase. This work revealed the dynamic changes and regulatory mechanisms of organic acids during the black tea manufacturing process, which is helpful to improve the processing technology and quality of black tea.

Understanding the transmission mechanism of SARS-CoV-2 is a prerequisite to effective control measures. To investigate the potential modes of SARS-CoV-2 transmission, 21 COVID-19 patients from 12-47 days after symptom onset were recruited. We monitored the release of SARS-CoV-2 from the patients' exhaled breath and systematically investigated environmental contamination of air, public surfaces, personal necessities, and the drainage system. SARS-CoV-2 RNA was detected in 0 of 9 exhaled breath samples, 2 of 8 exhaled breath condensate samples, 1 of 12 bedside air samples, 4 of 132 samples from private surfaces, 0 of 70 samples from frequently touched public surfaces in isolation rooms, and 7 of 23 feces-related air/surface/water samples. The maximum viral RNA concentrations were 1857 copies/m3 in the air, 38 copies/cm2 in sampled surfaces and 3092 copies/mL in sewage/wastewater samples. Our results suggest that nosocomial transmission of SARS-CoV-2 can occur via multiple routes. However, the low detection frequency and limited quantity of viral RNA from the breath and environmental specimens may be related to the reduced viral load of the COVID-19 patients on later days after symptom onset. These findings suggest that the transmission dynamics of SARS-CoV-2 differ from those of SARS-CoV in healthcare settings.

Background:Viral nucleic acid detection is considered the gold standard for the diagnosis of coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2 infection. However, unsuitable sample types and laboratory detection kits/methods lead to misdiagnosis, which delays the prevention and control of the pandemic.Methods:We compared four nucleic acid detection methods [two kinds of reverse transcription polymerase chain reactions (RT-PCR A: ORF1ab and N testing; RT-PCRB: only ORF1ab testing), reverse transcription recombinase aided amplification (RT-RAA) and droplet digital RT-PCR (dd-RT-PCR)] using 404 samples of 72 hospitalized COVID-19 patients, including oropharyngeal swab (OPS), nasopharyngeal swabs (NPS) and saliva after deep cough, to evaluate the best sample type and method for SARS-CoV-2 detection.Results:Among the four methods, dd-RT-PCR exhibited the highest positivity rate (93.0%), followed by RT-PCR B (91.2%) and RT-RAA (91.2%), while the positivity rate of RT-PCR A was only 71.9%. The viral load in OPS [24.90 copies/test (IQR 15.58-129.85)] was significantly lower than that in saliva [292.30 copies/test (IQR 20.20-8628.55)] and NPS [274.40 copies/test (IQR 33.10-2836.45)]. In addition, if OPS samples were tested alone by RT-PCR A, only 21.4% of the COVID-19 patients would be considered positive. The accuracy of all methods reached nearly 100% when saliva and NPS samples from the same patient were tested simultaneously.Conclusions:SARS-CoV-2 nucleic acid detection methods should be fully evaluated before use. High-positivity rate methods such as RT-RAA and dd-RT-PCR should be considered when possible. Furthermore, saliva after deep cough and NPS can greatly improve the accuracy of the diagnosis, and testing OPS alone is not recommended.

BackgroundTimely diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a prerequisite for treatment and prevention. The serology characteristics and complement diagnosis value of the antibody test to RNA test need to be demonstrated.MethodSerial sera of 80 patients with PCR-confirmed coronavirus disease 2019 (COVID-19) were collected at the First Affiliated Hospital of Zhejiang University, Hangzhou, China. Total antibody (Ab), IgM and IgG antibodies against SARS-CoV-2 were detected, and the antibody dynamics during the infection were described.ResultsThe seroconversion rates for Ab, IgM and IgG were 98.8%, 93.8% and 93.8%, respectively. The first detectible serology marker was Ab, followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 days post exposure (d.p.e.) or 9, 10 and 12 days post onset (d.p.o.), respectively. The antibody levels increased rapidly beginning at 6 d.p.o. and were accompanied by a decline in viral load. For patients in the early stage of illness (0–7 d.p.o), Ab showed the highest sensitivity (64.1%) compared with IgM and IgG (33.3% for both; p<0.001). The sensitivities of Ab, IgM and IgG increased to 100%, 96.7% and 93.3%, respectively, 2 weeks later. When the same antibody type was detected, no significant difference was observed between enzyme-linked immunosorbent assays and other forms of immunoassays.ConclusionsA typical acute antibody response is induced during SARS-CoV-2 infection. Serology testing provides an important complement to RNA testing in the later stages of illness for pathogenic-specific diagnosis and helpful information to evaluate the adapted immunity status of patients.

Influenza remains one of the major epidemic diseases worldwide. Acute lung injury mainly caused by excessive pro-inflammatory host immune responses leads to high mortality rates in severe influenza patients. Galectin-1, an animal lectin ubiquitously expressed in mammalian tissues, is reported to play important roles in viral diseases. Here, we established murine and A549 cell models to explore the potential roles of galectin-1 treatment in H1N1pdm09-induced acute lung injury. We found that galectin-1 protein level was elevated in A549 cell culture supernatants and mouse BALF after H1N1pdm09 challenge. In vivo experiments showed recombinant galectin-1 treatment reduced wet/dry weight ratio, inflammatory cell infiltration in mouse lungs and mediated the expression of cytokines and chemokines including IL-1β, IL-6, IL-10, IL-12(p40), IL-12(p70), G-CSF, MCP-1, MIP-1α and RANTES in serum and BALF of infected mice. Reduced apoptosis and viral titers in mouse lungs were also found after galectin-1 treatment. As expected, galectin-1 treated mice performed reduced body weight loss and enhanced survival rate against H1N1pdm09 challenge. In addition, in vitro experiments showed that viral titers decreased in a dose-dependent manner and cell apoptosis in A549 cells reduced after recombinant galectin-1 treatment. Taken together, our findings indicate a potentially positive effect of Gal-1 treatment on ameliorating the progress of H1N1pdm09-induced acute lung injury and recombinant galectin-1 might serve as a new agent in treating influenza.