Lassa virus (LASV), a member of the Arenaviridae family, is the causative agent of Lassa fever (LF), an acute zoonotic hemorrhagic disease transmitted by rodents, characterized by high infectivity and mortality rates. Due to the nonspecific nature of early clinical symptoms, the development of rapid, sensitive, and specific diagnostic methods is critical for effective epidemic control. In this study, the Lassa virus glycoprotein complex (LASV-G) was selected as the target antigen. High-affinity rabbit monoclonal antibodies were generated using a single B-cell cloning approach, and an AlphaLISA (Amplified Luminescent Proximity Homogeneous Assay)-based homogeneous, no-wash detection system was established. Sixteen LASV-G-specific monoclonal antibodies were isolated through flow cytometric sorting, and the optimal antibody pair (56-24) was identified by AlphaLISA pairing and performance screening. The established AlphaLISA system exhibited a limit of detection (LOD) of 0.025 ng/mL, representing approximately a 30-fold increase in sensitivity compared with conventional Enzyme Linked Immunosorbent Assay (ELISA), while reducing the total assay time to less than 30 min. The coefficient of variation (CV) was below 8%, and no cross-reactivity was observed with Ebola, dengue, yellow fever, Zika, or influenza virus antigens. These findings demonstrate that the developed AlphaLISA assay possesses high sensitivity, rapid detection, and good tolerance to matrix effects, significantly improving the efficiency of early LASV antigen detection. This work provides a potential platform for the rapid on-site screening and epidemiological surveillance of highly pathogenic viruses.

Introduction:The optimization of neutralizing monoclonal antibodies (NMAbs) is crucial to counter viral evolution. The structural stability of the heavy-chain complementarity-determining region 3 (H3 CDR) significantly influences affinity maturation potential, yet its impact on computational optimization remains unclear. Methods:This study employed an artificial intelligence (AI) model to optimize two categories of SARS-CoV-2 NMAbs: one featuring a conformationally stabilized H3 CDR via a twin cysteine motif, and another with flexible H3 CDR loops. Optimized antibody derivatives were evaluated for binding affinity to the SARS-CoV-2 spike protein, pseudovirus and live virus neutralization, and in vivo efficacy in a murine infection model. Structural analyses were conducted to elucidate interaction mechanisms with the angiotensin-converting enzyme 2 (ACE2) receptor. Results:H3 CDR stabilization via twin cysteines markedly enhanced AI-driven optimization efficacy. Optimized derivatives from the stabilized antibody category exhibited improved binding affinity and superior neutralization potency against both pseudotyped and authentic SARS-CoV-2 viruses. Structural analyses revealed optimized antibodies formed tighter interactions with the ACE2 receptor, including enhanced binding between key residues and ACE2, which correlated with biological efficacy. In contrast, antibodies lacking H3 CDR stabilization showed no affinity improvement after the same optimization process. In vivo, optimized antibodies effectively suppressed viral replication and reduced viral loads in infected mice. Mechanistically, the twin cysteine stabilization minimized structural perturbations caused by affinity-enhancing mutations, unlocking the optimization potential of the H3 CDR. Discussion:These findings establish that conformational stabilization of the H3 CDR in seed antibodies is a critical determinant for successful AI-driven affinity maturation. The study proposes a strategic framework for antibody development that prioritizes structurally stabilized H3 CDR regions, offering a robust approach to generating high-potency therapeutics against rapidly evolving viral pathogens.

Capsular polysaccharides (CPSs) of encapsulated bacterial pathogens, such as Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, serve as potent antigens for eliciting protective immunity against invasive infections. Polysaccharide and protein-polysaccharide conjugate vaccines have significantly reduced the global burden of diseases caused by these pathogens through direct immune protection and herd immunity. While traditional polysaccharide vaccines induce T cell-independent responses, conjugate vaccines-comprising CPSs linked to carrier proteins, drive robust T cell-dependent immunity, offering enhanced and durable protection. This review examines the evolution of polysaccharide-based vaccines, focusing on antigen design, carrier protein selection, and conjugation strategies, while addressing current challenges and future prospects. Key hurdles include the expansion of vaccine valency to broaden coverage against non-vaccine serotypes to lower the risk of serotype replacement, managing manufacturing and quality control complexities in multivalent formulations, and mitigating interference between carrier proteins and CPSs during T cell activation. Emerging strategies propose leveraging bacterial surface immunogenic proteins as novel carriers, which could streamline vaccine valency, amplify antibody-mediated protection, and circumvent existing limitations. Such innovations hold promise for advancing next-generation conjugate vaccines, optimizing efficacy while addressing the dynamic challenges of bacterial pathogenicity and vaccine development.

Most human viral pandemics are caused by animal-originated viruses with human adaptation. It is challenging to infer adaptation from viral genes or their coded protein sequences, particularly when the data labels for modeling are inadequate or the input sequence to be predicted is incomplete. Here, we developed a semi-supervised General Intelligence framework to predict Virus Adaptation based on Language-model-embedded protein sequences (GIVAL) for blind input of virus sequences. The language model in GIVAL, named virus Bidirectional Encoder Representations from Transformers (vBERT), was pretrained for embedding using hidden Markov model-contextualized tokens of viral protein sequences. vBERT outperformed prevalent pretrained models like DNABERT-2, proteinBERT, ESM-2, Transformer, and Word2Vec on distinguishing viral proteins with various-grained labels, such as serotypes and single phenotype-altering mutation. The semi-supervised GIVAL obtained higher accuracy in virus adaptation prediction and better fault tolerance on raw labels in the training dataset, overcoming the obstacle of modeling with insufficient labels and predicting blind input. GIVAL was applicable to the adaptation prediction of diverse viruses. For influenza A viruses (IAVs), higher human adaptation was predicted for equine-origin H3N8 IAVs and bovine H5N1 IAVs with simulated mutations. For coronaviruses, GIVAL predicted an adaptation shift of receptor binding from Middle East respiratory syndrome-related coronavirus (MERS-CoV) receptor to severe acute respiratory syndrome coronavirus receptor of 2 recently reported MERS-CoV-like virus variants. For monkeypox viruses, GIVAL quantified an incremental adaptation shift of viral variants, matching the rise in human monkeypox cases. Summarily, GIVAL provides a generally intelligent framework for predicting virus adaptation based on its genotype, with the potential to extend to more genotype-to-phenotype prediction scenarios.

Staphylococcal enterotoxin B (SEB) holds critical importance in disease diagnosis, food safety, and public health due to its high toxicity and potent pathogenicity. Traditional immunoassay methods for detecting SEB often exhibit insufficient accuracy and robustness. This study leverages machine learning technology to integrate the quantitative measurement advantages of electrochemical methods with the strong specificity of immunoassays, achieving high-precision coupled electrochemical immunodetection of SEB. Firstly, an electrochemical immunosensing system was developed to capture the target analyte SEB by immobilizing specific antibodies on the electrode surface. Cyclic voltammetry (CV) was utilized to accurately characterize the immune response process. Secondly, feature selection methodologies within machine learning are utilized to identify eight key parameters from CV curves that are highly related to SEB concentration. This enhancement significantly improves both the accuracy and interpretability of SEB measurement data. Lastly, a multivariate linear regression algorithm is employed to effectively train and fit the extracted feature data. This approach successfully mitigates noise introduced by variations in electrode batches, experimental conditions, and operational techniques-thereby enabling robust quantitative measurements of SEB concentration with high precision. The entire detection process requires only 20 μL sample and is accomplished in just two minutes. This method can detect antigen concentrations at both ng/mL and μg/mL levels, with a detection limit of 1 ng/mL. The [Formula: see text] score for predicting SEB antigen concentration is approximately 0.999, accompanied by a mean absolute percentage error (MAPE) of 6.09% This approach achieves high precision, robustness, and specificity in SEB detection, offering extensive detection range, rapid response time, and cost-effectiveness, presenting new opportunities for identifying various pathogenic toxins.

While antibody responses to influenza viruses have been extensively studied, the immunogenicity of influenza vaccines remains highly variable among individuals. Growing evidence suggests that the gut microbiota (GM) and associated metabolites play a critical yet understudied role in shaping host immunity, including responses to vaccines. However, the mechanistic pathways linking microbial communities, blood metabolites, and influenza vaccine-induced antibody production remain poorly understood. This study investigates the GM-blood metabolite-antibody level axis to identify potential modulators of vaccine immunogenicity. In this study, 2-sample Mendelian randomization (MR) were conducted to identify causality. We performed 2-sample MR using genome-wide association study data from MiBioGen (GM, N = 14,306), Avon Longitudinal Study of Parents and Children (anti-influenza immunoglobulin G (IgG), N = 4735), and metabolite genome-wide association study (N = 7824). Instrumental variables (P < 5 × 10-⁵, r² < 0.01, F > 10) were analyzed via inverse-variance-weighted (IVW) regression with sensitivity analyses (MR-Egger, weighted median). Two-step MR assessed metabolite mediation effects. Our analysis revealed positive correlations between influenza virus subtype influenza A H1N1 virus IgG levels and the Escherichia Shigella genus, Ruminococcaceae UCG002, and Ruminococcaceae UCG003 genera. Conversely, negative correlations were observed with the Erysipelotrichaceae family, Rhodospirillaceae family, Barnesiella genus, and Eubacterium fissicatena group. For influenza virus subtype influenza A H3N2 virus IgG antibodies, positive associations were identified with the Bacteroidales S24-7*group, Defluviitaleaceae family, Adlercreutzia, Desulfovibrio, Eubacterium eligens group, Eubacterium rectale group, and Ruminococcaceae UCG014 genus, while negative associations were noted for the Negativicutes class and Selenomonadales order. Two-step MR analysis suggested mediation effects: the association between the Erysipelotrichaceae family and influenza A H1N1 virus IgG levels was partially mediated by bradykinin, des-Arg(9) (proportion mediated: 27.16%, P = .006). The link between Ruminococcaceae UCG014 and influenza A H3N2 virus IgG levels was partially mediated by alanine (proportion mediated: 26.86%, P = .002). This study demonstrates the potential role of blood metabolites as mediators in modulating the impact of the GM on immunity to influenza.

Human metapneumovirus (HMPV) is a leading cause of acute respiratory tract infections in infants and children. Currently, no approved HMPV vaccine is available. We developed a novel recombinant influenza virus, which carried partial HMPV F protein (HMPV-F) epitopes, utilizing reverse genetics. The novel single-stranded RNA virus, termed rFLU-HMPV/F-NA, was synthesized in the neuraminidase (NA) fragment of influenza virus A/PuertoRico/8/34 (PR8). The morphological characteristics of rFLU-HMPV/F-NA were consistent with the wild-type flu virus. The virus could passage in specific pathogen-free (SPF) chicken embryos for at least five consecutive generations with haemagglutinin (HA) titres of 28-9 or 8-9LogTCID50/mL. BALB/c mice were intranasally immunized at 21-day intervals with 104 TCID50 (low-dose group) or 106 TCID50 (high-dose group) rFLU-HMPV/F-NA, and PBS or PR8 vaccine was used for the control group. rFLU-HMPV/F-NA induced robust humoral, mucosal, and cellular immune responses in vivo in a dose-dependent manner. More importantly, wt clinical HMPV isolate challenge studies showed that rFLU-HMPV/F-NA provided significant immune protection against HMPV infection compared to the PBS or PR8 vaccine control group, as shown by improved histopathological changes and reduced viral titres in the lungs of immunized mice post-challenge. These findings demonstrate that rFLU-HMPV/F-NA has potential as a promising HMPV candidate vaccine and warrants further investigation into its control of HMPV infection.

Background: Acute lung injury (ALI) is a major cause of death in patients with various viral pneumonias. Our team previously identified four volatile compounds from aromatic Chinese medicines. Based on molecular compatibility theory, we defined their combination as aromatic molecular compatibility (AC), though its therapeutic effects and underlying mechanisms remain unclear. Methods: This study used influenza A virus (IAV) A/PR/8/34 to construct cell and mouse models of ALI to explore AC’s protective effects against viral infection. The therapeutic effect of AC was verified by evaluating the antiviral efficacy in the mouse models, including improvements in their lung and colon inflammation, oxidative stress, and the suppression of the NLRP3 inflammasome. In addition, 16S rDNA and lipid metabolomics were used to analyze the potential therapeutic mechanisms of AC. Results: Our in vitro and in vivo studies demonstrated that AC increased the survival of the IAV-infected cells and mice, inhibited influenza virus replication and the expression of proinflammatory factors in the lung tissues, and ameliorated barrier damage in the colonic tissues. In addition, AC inhibited the expression of ROS and the NLRP3 inflammasome and improved the inflammatory cell infiltration into the lung tissues. Finally, AC effectively regulated intestinal flora disorders and lipid metabolism in the model mice, significantly reduced cholesterol and triglyceride expression, and thus reduced the abnormal accumulation of lipid droplets (LDs) after IAV infection. Conclusions: In this study, we demonstrated that AC could treat IAV-induced ALIs through multiple pathways, including antiviral and anti-inflammatory pathways and modulation of the intestinal flora and the accumulation of LDs.

The viruses threats provoke concerns regarding their sustained epidemic transmission, making the development of vaccines particularly important. In the prolonged and costly process of vaccine development, the most important initial step is to identify protective immunogens. Machine learning (ML) approaches are productive in analyzing big data such as microbial proteomes, and can remarkably reduce the cost of experimental work in developing novel vaccine candidates. We intensively evaluated the B cell epitope immunogenicity prediction power of eight commonly-used ML methods by random sampling cross validation on a large dataset consisting of known viral immunogens and non-immunogens we manually curated from the public domain. Extreme Gradient Boosting, K Nearest Neighbours, and Random Forest) showed the strongest predictive power. We then proposed a novel soft-voting based ensemble approach (VirusImmu), which demonstrated a powerful and stable capability for viral immunogenicity prediction across the test set and external test set irrespective of protein sequence length. VirusImmu was successfully applied to facilitate identifying linear B cell epitopes against African Swine Fever Virus as confirmed by indirect ELISA in vitro. In short, VirusImmu exhibited tremendous potentials in predicting immunogenicity of viral protein segments. It is freely accessible at https://github.com/zhangjbig/VirusImmu.

With the widespread prevalence of pandemics such as influenza and SARS-CoV-2, there has been an explosive accumulation of viral variants, posing a huge challenge to monitoring virus mutation and other data processing. The present study aimed to develop a tool, named VirusVAR, to lightweight and customize virus genome sequences. The present study took SARS-CoV-2 genomes as an example to construct VirusVAR based on the variations (VAR) of the full-length genomes downloaded from public databases. All genome sequences were subjected to quality control, single nucleotide variants (SNVs) annotation, format conversion, and final compression before appending to BZ2 files, lightweight more than 12 million SARS-CoV-2 sequences with a size of more than 500 Giga Bytes (GB) into a set of storage files with a size of 941 Million Bytes (MB), with a compression ratio of 1: 594. VirusVAR is a tool to lightweight and customize virus genome sequences, capable of timely updating, quickly querying, and customizable outputting of virus sequences.

Staphylococcal enterotoxin B (SEB), an exotoxin produced by single- or multi-drug-resistant Staphylococcus aureus ( S. aureus ), can induce food poisoning and toxic shock syndrome. Because no treatment is available for SEB-poisoned patients, development of a safe and effective SEB antidote is urgently needed. First, SEB was prepared, and native SEB (nSEB) was used to construct lethal mouse and rhesus monkey models. Second, F(ab′) 2 fragments of IgG antibodies were cleaved with pepsin from horses inoculated with Freund’s adjuvant-purified nSEB. Finally, protective efficacy was evaluated in mouse and rhesus monkey models of lethal SEB intoxication. In mouse and monkey model studies, the purity of the prepared nSEB reached 90%, and that of the F(ab′) 2 fragments reached 83.09%. In mice and rhesus monkeys, the median lethal dose (LD 50 ) of staphylococcal enterotoxin B (SEB) was 21.87 μg/kg and 23.77 μg/kg, respectively. Additionally, administration of 6.25 mg/kg and 7.125 mg/kg of F(ab′) 2 fragments, respectively, effectively prevented SEB-induced lethality. Finally, single-cell sequencing of peripheral blood immune cells was used to detect the effects of the therapeutic antibody on peripheral blood immune cells. The underlying mechanism was found to involve inhibition of neutrophil activation, proliferation, and differentiation. Purified F(ab′) 2 fragments were an effective antidote to lethal SEB doses in mice and rhesus monkeys, and therefore might be a favorable candidate for treating patients with severe SEB intoxication.

Respiratory syncytial virus (RSV) remains the primary cause of lower respiratory tract infections, particularly in infants and the elderly. In this study, we employed reverse genetics to generate a chimeric influenza virus expressing neuraminidase-3F protein conjugate with three repeats of the RSV F protein protective epitope inserted into the NA gene of A/California/7/2009 ca (CA/AA ca), resulting in rFlu/RSV/NA-3F (hereafter, rFRN3). The expression of NA-3F protein was confirmed by Western blotting. The morphology and temperature-sensitive phenotype of rFRN3 were similar to CA/AA ca. Its immunogenicity and protective efficiency were evaluated in BALB/c mice and cotton rats. Intranasal administration of rFRN3 elicited robust humoral, cellular, and to some extent, mucosal immune responses. Compared to controls, rFRN3 protected animals from RSV infection, attenuated lung injury, and reduced viral titers in the nose and lungs post-RSV challenge. These results demonstrate that rFRN3 can trigger RSV-specific immune responses and thus exhibits potent protective efficacy. The "dual vaccine" approach of a cold-adapted influenza vector RSV vaccine will improve the prophylaxis of influenza and RSV infection. rFRN3 thus warrants further clinical investigations as a candidate RSV vaccine.

Severe fever with thrombocytopenia syndrome (SFTS) is caused by the SFTS virus (SFTSV) with high morbidity and mortality. The major immunodominant region of SFTSV surface glycoprotein (G) remains unclear. In this study, we constructed adenovirus type 5 (Ad5) vectored vaccine candidates expressing different regions of SFTSV G (Gn, Gc and Gn-Gc) and evaluated their immunogenicity and protective efficacy in mice. In wild-type mice, compared with Ad5-Gc or Ad5-Gn-Gc, Ad5-Gn recruited/activated more dendritic cells and B cells in lymph nodes or peripheral blood, causing Th1-/Th2-mediated responses in splenocytes and triggered a greater level of SFTSV-neutralizing antibodies. In IFNAR Ab-treated mice, immunization of Ad5-Gn exhibited better protection against SFTSV challenge than Ad5-Gc or Ad5-Gn-Gc. Furthermore, passive immunization revealed complete protective immunity of Gn-specific serum rather than Gc. Collectively, our data demonstrated that Gn is the immunodominant fragment of SFTSV G and could be a potential candidate for SFTSV vaccine development.

Respiratory syncytial virus is the major cause of respiratory viral infections, particularly in infants, immunocompromised populations, and the elderly (over 65 years old), the prevention of RSV infection has become a priority. In this study, we generated a chimeric influenza virus, termed LAIV/RSV/HA-3F, using reverse genetics technology which contained three repeats of the RSV fusion protein neutralizing epitope site II to the N terminal in the background of the hemagglutinin (HA) gene of cold adapted influenza vaccine A/California/7/2009 ca. LAIV/RSV/HA-3F exhibited cold-adapted (ca) and attenuated (att) phenotype. BALB/c mice immunized intranasally with LAIV/RSV/HA-3F showed robust immunogenicity, inducing viral-specific antibody responses against both influenza and RSV, eliciting RSV-specific humoral, cellular and mucosal immune responses. LAIV/RSV/HA-3F also conferred protection as indicated by reduced viral titers and improved lung histopathological alterations against live RSV virus challenge. Mechanismly, single-cell RNA sequencing (scRNA-seq) and single-cell T cell antigen receptor (TCR) sequencing were employed to characterize the immune responses triggered by chimeric RSV vaccine, displaying that LAIV/RSV/HA-3F provided protection mainly via interferon-γ (IFN-γ). Moreover, we found that LAIV/RSV/HA-3F significantly inhibited viral replication in the challenged lung and protected against subsequent RSV challenge in cotton rats without causing lung disease. Taken together, our findings demonstrated that LAIV/RSV/HA-3F has potential as a promising bivalent vaccine with dual purpose candidate for the prevention of influenza and RSV, and preclinical and clinical studies warrant further investigations.

为了给预防疫苗和治疗药物的有效性评价提供参考依据,该试验建立了稳定的乳房炎奶牛模型,可为广泛感染性疾病"人病兽防"理念的验证提供可靠途径.自全国不同地区取奶牛临床型乳房炎乳样,经细菌分离鉴定后,将大肠杆菌不同菌株感染6-8周龄Balb/c小鼠和2-6岁泌乳后期健康易感奶牛,通过测定不同菌株对小鼠、奶牛的感染力和致病力,筛选出对两者均具有较强致病性的强毒株;使用强毒株攻击易感奶牛,记录奶牛攻毒前后临床表现,及日产奶量、乳汁细菌数和体细胞数的变化情况;攻击小鼠,记录小鼠攻毒前后临床表现和死亡情况,以建立稳定的大肠杆菌感染致病实验动物模型.结果表明:筛选到3株不同血清型的强毒株大肠杆菌LZ06(O6)、ESH05(O8)、EHL11(O81),能够致死小鼠并导致奶牛乳房炎疾病;建立稳定的大肠杆菌乳房炎模型和小鼠致死性模型.该试验成功筛选到导致奶牛乳房炎的大肠杆菌强毒株,建立的实验动物模型可用于大肠杆菌疫苗和治疗药物的有效性评价,为大肠杆菌引起的人兽共患病"人病兽防"理念和策略提供新的评估途径.

以浓缩纯化的猫杯状病毒(feline calicivirus,FCV)免疫BALB/c小鼠,取其脾细胞与小鼠骨髓瘤细胞SP2/0融合,用间接ELISA试验检测细胞培养上清,获得5株阳性杂交瘤细胞克隆株,命名为1E2、4C3、5F11、6G9和7D2,分别制备腹水后进行纯化.以多克隆抗体为金标抗体,腹水ELISA和中和效价较高的单抗(4C3)作为检测线抗体,羊抗兔二抗为质检抗体,制备检测FCV病毒抗原的免疫胶体金快速诊断试纸条.在pH为7.4的条件下,金标抗体的最适质量浓度为0.1 g/L,检测线最佳包被质量浓度为1.0 g/L,质控线最终质量浓度为0.5 g/L.经检测该试纸条具有敏感性高,特异性强,稳定性好的特点,用制备的胶体金试纸条与RT-PCR方法同时对76份猫鼻咽拭子进行检测,比较两者的符合率,符合率在90％以上.结果表明,本试验研制的胶体金试纸条可以用于FCV的临床检测.

采用无针肌内注射流感疫苗免疫SD大鼠和巴马小型猪,用有针肌内注射免疫作为对照,通过观察评价局部接种效果,并采用血凝抑制试验测定疫苗免疫后的血抑抗体效价及鸡胚中和试验评价中和抗体效价.结果显示,无针肌内注射30 μg HA抗原量可达到免疫的最佳效果.与有针肌内注射相比,无针肌内注射能产生对各型别病毒的更好的血凝抑制抗体和中和性抗体.结果表明,无针肌内注射四价流感裂解疫苗安全、有效,将为流感疫苗快速大规模接种提供新的策略,为无针注射免疫疫苗临床试验研究提供依据.

Electrochemical Immunosensing (EI) combines electrochemical analysis and immunology principles and is characterized by its simplicity, rapid detection, high sensitivity, and specificity. EI has become an important approach in various fields, such as clinical diagnosis, disease prevention and treatment, environmental monitoring, and food safety. However, EI multi-component detection still faces two major bottlenecks: first, the lack of cost-effective and portable detection platforms; second, the difficulty in eliminating batch differences and accurately decoupling signals from multiple analytes. With the gradual maturation of biochip technology, high-throughput analysis and portable detection utilizing the advantages of miniaturized chips, high sensitivity, and low cost have become possible. Meanwhile, Artificial Intelligence (AI) enables accurate decoupling of signals and enhances the sensitivity and specificity of multi-component detection. We believe that by evaluating and analyzing the characteristics, benefits, and linkages of EI, biochip, and AI technologies, we may considerably accelerate the development of EI multi-component detection. Therefore, we propose three specific prospects: first, AI can enhance and optimize the performance of the EI biochips, addressing the issue of multi-component detection for portable platforms. Second, the AI-enhanced EI biochips can be widely applied in home care, medical healthcare, and other areas. Third, the cross-fusion and innovation of EI, biochip, and AI technologies will effectively solve key bottlenecks in biochip detection, promoting interdisciplinary development. However, challenges may arise from AI algorithms that are difficult to explain and limited data access. Nevertheless, we believe that with technological advances and further research, there will be more methods and technologies to overcome these challenges.

目的 本研究旨在建立新型布尼亚病毒抗体检测的高特异性、低成本间接ELISA方法.方法 通过优化抗原表达、纯化、包被、血清稀释、孵育时间等条件,以Gn的截短蛋白Gn2为包被抗原,开发了一种间接ELISA方法.检测该方法的稳定性、敏感性、特异性、符合率.结果 批内和批间变异系数均小于10％,阳性血清临床符合率达76.9％(10/13),阴性血清临床符合率达86.7％(26/30).结论 本研究所建立的间接ELISA方法可用于临床血清样品的检测,为发热伴血小板减少综合征的疾病诊断和监测提供了较为可靠和廉价的检测方法.