Fidelity Characterization of Highly Pathogenic Porcine Reproductive and Respiratory Syndrome Virus and NADC30-like Strain.

The porcine reproductive and respiratory syndrome virus (PRRSV) has significantly impacted the global pork industry for over three decades. Its high mutation rates and frequent recombination greatly intensifies its epidemic and threat. To explore the fidelity characterization of Chinese highly pathogenic PRRSV JXwn06 and the NADC30-like strain CHsx1401, self-recombination and mutation in PAMs, MARC-145 cells, and pigs were assessed. In vitro, CHsx1401 displayed a higher frequency of recombination junctions and a greater diversity of junction types than JXwn06. In vivo, CHsx1401 exhibited fewer junction types yet maintained a higher junction frequency. Notably, JXwn06 showed more accumulation of mutations. To pinpoint the genomic regions influencing their fidelity, chimeric viruses were constructed, with the exchanged nsp9-10 regions between JXwn06 and CHsx1401. The SJn9n10 strain, which incorporates JXwn06's nsp9-10 into the CHsx1401 genome, demonstrated reduced sensitivity to nucleotide analogs compared to CHsx1401. Conversely, compared with JXwn06, the JSn9n10 strain showed increased sensitivity to these inhibitors. The swapped nsp9-10 also influences the junction frequency and accumulated mutations as their donor strains. The results indicate a propensity for different types of genetic variations between these two strains and further highlight the nsp9-10 region as a critical determinant of their fidelity.

Metagenomic next-generation sequencing for the diagnosis of neurobrucellosis.

Objective: This study investigates the application of metagenomic next-generation sequencing (mNGS) in the diagnosis of neurobrucellosis (NB). Methods: We retrospectively analyzed patients diagnosed with NB who underwent cerebrospinal fluid (CSF) mNGS testing in Xijing Hospital from 2015 to 2021. Results: Among the 20 individuals included in the study, the serum rose bengal test was positive in 11 out of 16 cases, serum agglutination test was positive in 13 out of 16 cases, CSF culture was positive in 6 out of 11 cases, and CSF mNGS tests were positive in 18 out of 20 cases. Conclusion: CSF mNGS demonstrates superior sensitivity; therefore, it is recommended to collect CSF for mNGS testing prior to antibiotic therapy when NB is suspected.

Neurobrucellosis (NB) is a disease of the nervous system caused by a type of bacteria called Brucella. It is rare, serious and manifests inconsistently, making it hard to diagnose. Metagenomic next-generation sequencing (mNGS) is a new way to detect disease-causing bacteria by looking at their genetic material. mNGS is fast, accurate and covers a wide range of disease-causing bacteria. We looked back at patients diagnosed with NB at Xijing Hospital between 2015 and 2021 and tested samples of the fluid surrounding the brain and the spinal cord, called cerebrospinal fluid (CSF), by mNGS. A total of 20 patients were included in the study. Compared with the traditional methods, mNGS of CSF samples showed advantages in diagnosing NB. However, antibiotics may affect the results.

Hydration deactivation mechanism of the 〈100〉 oriented cuprous oxide photocathodes in solar water splitting and the regenerated three-dimensional structure.

Photocorrosion is the most ticklish problem of cuprous oxide (Cu2O), and it is widely assumed that the deactivation of Cu2O photocathodes in solar water splitting is caused by spontaneous oxidation-reduction (REDOX) reactions. However, this work shows that 〈100〉-oriented Cu2O photocathodes undergo a non-REDOX hydration deactivation mechanism. Briefly, water molecules are embedded in the Cu2O crystals at low potential under illumination and produce amorphous CuOH, which can be dehydrated at high potential to heal the Cu-O-Cu bonds and regenerate foamed Cu2O films with a three-dimensional skeleton structure. This study provides a new insight towards the protection and application of Cu2O photocathodes.

A Rift Valley fever mRNA vaccine elicits strong immune responses in mice and rhesus macaques.

Rift Valley fever virus (RVFV) is listed as a priority pathogen by the World Health Organization (WHO) because it causes serious and fatal disease in humans, and there are currently no effective countermeasures. Therefore, it is urgent to develop a safe and efficacious vaccine. Here, we developed six nucleotide-modified mRNA vaccines encoding different regions of the Gn and Gc proteins of RVFV encapsulated in lipid nanoparticles, compared their ability to induce immune responses in mice and found that mRNA vaccine encoding the full-length Gn and Gc proteins had the strongest ability to induce cellular and humoral immune responses. IFNAR(-/-) mice vaccinated with mRNA-GnGc were protected from lethal RVFV challenge. In addition, mRNA-GnGc induced high levels of neutralizing antibodies and cellular responses in rhesus macaques, as well as antigen-specific memory B cells. These data demonstrated that mRNA-GnGc is a potent and promising vaccine candidate for RVFV.

An adenovirus-vectored RVF vaccine confers complete protection against lethal RVFV challenge in A129 mice.

Instruction: Rift valley fever virus (RVFV) is a mosquito-transmitted bunyavirus that causes severe disease in animals and humans. Nevertheless, there are no vaccines applied to prevent RVFV infection for human at present. Therefore, it is necessary to develop a safe and effective RVFV vaccine. Methods: We generated Ad5-GnGcopt, a replication-deficient recombinant Ad5 vector (human adenovirus serotype 5) expressing codon-optimized RVFV glycoproteins Gn and Gc, and evaluated its immunogenicity and protective efficacy in mice. Results and Discussion: Intramuscular immunization of Ad5-GnGcopt in mice induces strong and durable antibody production and robust cellular immune responses. Additionally, a single vaccination with Ad5-GnGcopt vaccination can completely protect interferon-α/ß receptor-deficient A129 mice from lethal RVFV infection. Our work indicates that Ad5-GnGcopt might represent a potential vaccine candidate against RVFV. However, further research is needed, first to confirm its efficacy in a natural animal host, and ultimately escalate as a potential vaccine candidate for humans.

Structure analysis of multi-component pastes - The effect of water distribution on the rheological properties.

Techno-functional properties of multi-component blends and ingredients are determined by the contribution of each ingredient and the water distribution between those ingredients in the blends. However, ingredients can consist of multiple components, which should be considered to better understand the properties of ingredients and blends thereof. Recently, empirical models were used to describe the viscosity of mildly refined ingredient blends. While many compositions were described well by the empirical models, blends with high fiber contents were not predicted sufficiently well. Therefore, in this research, the multi-component blends of commercial pea protein, pea starch, and pea fiber isolates were investigated on their rheological properties as a function of dry matter content. The same properties were then measured for blends of two of these isolates mixed in different ratios. From the rheological experiments, estimations of the water distribution were made with the polymer blending law. The results were compared with CLSM images. A quantitative analysis of the CLSM images mostly confirmed the model outcomes. The isolate ratio could describe the isolate blends sufficiently well, meaning that it was not necessary to know the exact compositions of the ingredients. It was concluded that changes in meso-structure of the blends, for example a phase transition at high fiber contents, caused the lower predictability by the recently published empirical viscosity models. This study demonstrates that the water distribution in multi-component blends plays a crucial role for their viscoelastic properties and the contribution of the individual isolates and components. Moreover, these polymer blending laws that include water distribution provide extra mechanical insights into the fraction behavior in multi-component blends.

A new risk model for CSTA, FAM83A, and MYCT1 predicts poor prognosis and is related to immune infiltration in lung squamous cell carcinoma.

OBJECTIVES: To create a prognostic model based on differentially expressed genes (DEGs) in early lung squamous cell carcinoma (LUSC) and characterize the relationship between risk scores and tumor immune infiltration. METHODS: We identified DEGs in normal and tumor tissues that overlapped between LUSC-related data sets from the Gene Expression Omnibus and the Cancer Genome Atlas and evaluated their roles in the diagnosis and prognosis of LUSC by Kaplan-Meier survival analysis, receiver operating characteristic (ROC) analysis, meta-analysis and nomogram analysis. We then constructed a risk model based on Cox regression analysis and the Akaike information criterion and identified the relationship between LUSC risk scores and immune infiltration. RESULTS: Sixty-two overlapping DEGs were involved with keratinocyte differentiation, epidermal cell differentiation, neutrophil migration, granulocyte chemotaxis, granulocyte migration, leukocyte aggregation, and positive regulation of nuclear factor-κB (NF-κB) activity. Overexpression of family with sequence similarity 83 member A (FAM83A) and MYC target 1 (MYCT1), kallikrein related peptidase 8 (KLK8), and downregulation of ADP ribosylation factor like GTPase 14 (ARL14), caspase recruitment domain family member 14 (CARD14), cystatin A (CSTA), dickkopf WNT signaling pathway inhibitor 4 (DKK4), desmoglein 3 (DSG3), and keratin 6B (KRT6B) were associated with a poor prognosis in LUSC and had significant value for LUSC diagnosis. The expression of CSTA, FAM83A, and MYCT1 and high-risk scores were independent risk factors for a poor prognosis in LUSC. A risk nomogram revealed that risk scores could predict the prognosis of LUSC. The risk score was associated with neutrophils, naive B cells, helper follicular T cells, and activated dendritic cells. CONCLUSIONS: The expression levels of CSTA, FAM83A, and MYCT1 are related to the diagnosis and prognosis of LUSC and may have potential as therapeutic targets in LUSC. A risk model and nomogram based on CSTA, FAM83A, and MYCT1 can predict the prognosis of LUSC.

Single-dose of a replication-competent adenovirus-vectored vaccine provides sterilizing protection against Rift Valley fever virus challenge.

Rift Valley fever virus (RVFV) is one of the most important virulent pathogens causing severe disease in animals and humans. However, there is currently no approved vaccine to prevent RVFV infection in humans. The use of human adenovirus serotype 4 (Ad4) as a vector for an RVFV vaccine has not been reported. Here, we report the generation of a replication-competent recombinant Ad4 vector expressing codon-optimized forms of the RVFV glycoproteins Gn and Gc (named Ad4-GnGc). Intramuscular immunization with Ad4-GnGc elicited robust neutralizing antibodies against RVFV and cellular immune responses in mice. A single low-dose vaccination with Ad4-GnGc completely protected interferon-α/ß receptor-deficient A129 mice from lethal RVFV infection. More importantly, Ad4-GnGc efficacy was not affected by pre-existing immunity to adenovirus serotype 5, which currently exists widely in populations. These results suggest that Ad4-GnGc is a promising vaccine candidate against RVFV.

Co-analysis of cucumber rhizosphere metabolites and microbial PLFAs under excessive fertilization in solar greenhouse.

Fertilizer application is the most common measure in agricultural production, which can promote the productivity of crops such as cucumbers, but the problem of excessive fertilization occurs frequently in solar greenhouses. However, the effects of fertilization levels on cucumber rhizosphere soil microbes and metabolites and their relationships are still unclear. In order to determine how fertilization levels affect the rhizosphere microenvironment, we set up four treatments in the solar greenhouse: no-fertilization (N0P0K0), normal fertilization (N1P1K1), slight excessive fertilization (N2P2K2), and extreme excessive fertilization (N3P3K3). The results showed that fertilization treatments significantly increased cucumber yield compared to no-fertilization, but, the yield of N3P3K3 was significantly lower than that of N1P1K1 and N2P2K2. Fertilization levels had significant effects on rhizosphere microorganisms, and pH, NH4 +-N and AP were the main environmental factors that affected the changes in microbial communities. The total PLFAs, the percentages of fungi and arbuscular mycorrhizal fungi (AMF) were significantly reduced and bacteria percentage was significantly increased in N3P3K3 compared to other fertilization treatments. Differential metabolites under different fertilization levels were mainly organic acids, esters and sugars. Soil phenols with autotoxic effect under fertilization treatments were higher than that of N0P0K0. In addition, compared with soil organic acids and alkanes of N0P0K0, N2P2K2 was significantly increased, and N3P3K3 was not significantly different. This suggested that cucumber could maintain microbial communities by secreting beneficial metabolites under slight excessive fertilization (N2P2K2). But under extremely excessive fertilization (N3P3K3), the self-regulating ability of cucumber plants and rhizosphere soil was insufficient to cope with high salt stress. Furthermore, co-occurrence network showed that 16:1ω5c (AMF) was positively correlated with 2-palmitoylglycerol, hentriacontane, 11-octadecenoic acid, decane,4-methyl- and d-trehalose, and negatively correlated with 9-octadecenoic acid at different fertilization levels. This indicated that the beneficial microorganisms in the cucumber rhizosphere soil promoted with beneficial metabolites and antagonized with harmful metabolites. But with the deepening of overfertilization, the content of beneficial microorganisms and metabolites decreased. The study provided new insights into the interaction of plant rhizosphere soil metabolites and soil microbiomes under the different fertilization levels.

The economic impact of porcine reproductive and respiratory syndrome outbreak in four Chinese farms: Based on cost and revenue analysis.

The economic impact after the outbreak of porcine reproductive and respiratory syndrome (PRRS) has been proven to be tremendous for pig production worldwide. However, the economic impact of the disease is not well understood in China. In our previous study, we acquired and analyzed the main production data (the number of weaned piglets, health costs, delayed marketing age, etc.) from the management system before and after the PRRS outbreaks occurring in November 2014, March 2015, December 2016, and February 2017. This study aimed to analyze and quantify the economic losses of the four PRRS outbreaks in Chinese herds. A straightforward approach was used to calculate additional costs and decreased revenues based on the PRRS-induced production deficiencies by average cost-of-production indices calculated from annual estimates of costs between 2014 and 2017. The results showed that economic losses varied between ¥668.14 and ¥1004.43 per sow in breeding herds from the outbreaks to regain the basic performance, with an average of ¥822.75 per sow, and the mean costs in the fattening herds (including nursery pigs) were ¥601.62 per sow, ranging from ¥318.64 to ¥937.14. Overall, the economic impact of PRRS on the whole herd was ¥1424.37 per sow. The majority of the losses were due to the reduction in the number of weaned piglets for breeding herds, and the increased feed cost (occupying 44.88%) was the primary source of loss for fattening herds. Our study fills the gap in knowledge of PRRS economics in China, enriches the data for veterinary economics, and re-stresses the necessity for producers and veterinarians to control PRRS effectively.

[ST segment morphological classification based on support vector machine multi feature fusion].

ST segment morphology is closely related to cardiovascular disease. It is used not only for characterizing different diseases, but also for predicting the severity of the disease. However, the short duration, low energy, variable morphology and interference from various noises make ST segment morphology classification a difficult task. In this paper, we address the problems of single feature extraction and low classification accuracy of ST segment morphology classification, and use the gradient of ST surface to improve the accuracy of ST segment morphology multi-classification. In this paper, we identify five ST segment morphologies: normal, upward-sloping elevation, arch-back elevation, horizontal depression, and arch-back depression. Firstly, we select an ST segment candidate segment according to the QRS wave group location and medical statistical law. Secondly, we extract ST segment area, mean value, difference with reference baseline, slope, and mean squared error features. In addition, the ST segment is converted into a surface, the gradient features of the ST surface are extracted, and the morphological features are formed into a feature vector. Finally, the support vector machine is used to classify the ST segment, and then the ST segment morphology is multi-classified. The MIT-Beth Israel Hospital Database (MITDB) and the European ST-T database (EDB) were used as data sources to validate the algorithm in this paper, and the results showed that the algorithm in this paper achieved an average recognition rate of 97.79% and 95.60%, respectively, in the process of ST segment recognition. Based on the results of this paper, it is expected that this method can be introduced in the clinical setting in the future to provide morphological guidance for the diagnosis of cardiovascular diseases in the clinic and improve the diagnostic efficiency.

Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid.

Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope. Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage. Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly. Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists. Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer's primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.

The mechanism of N-acetyl-l-cysteine in improving the secretion of porcine follicle-stimulating hormone in Pichia pastoris.

Our previous study revealed that N-acetyl-l-cysteine (NAC) could enhance the secretion of recombinant proteins by Pichia pastoris, but the corresponding molecular mechanisms are still unclear. In the present study, we explored whether other thiols have a similar action on the secretion of recombinant human serum albumin and porcine follicle-stimulating hormone fusion protein (HSA-pFSHß), to reveal the mechanism of NAC on HSA-pFSHß secretion. Transcriptome analysis showed that genes involved in oxidoreductase activity and oxidation-reduction process were upregulated in cells supplemented with NAC. The other three thiol-reducing regents including dimercaptopropanol (DT), thioglycolic acid, and mercaptolactic acid could improve HSA-pFSHß production in the culture supernatant. Among them, only DT had similar effect as NAC on HSA-pFSHß secretion and the increase of GSH content. Moreover, 1-20 mM GSH, 1-10 mM cysteine, or 1-20 mM N-acetyl-d-cysteine supplementation could improve the secretion of HSA-pFSHß. Furthermore, 0.4-3.2 mM ethacrynic acid, rather than 1-16 mM BSO could inhibit the effect of NAC on the production of HSA-pFSHß. These results indicated that NAC improved the secretion of HSA-pFSHß by increasing the intracellular GSH content through its thiol activity rather than as a precursor for GSH synthesis. In conclusion, our results demonstrate, for the first time, that the secretion of recombinant HSA-pFSHß in Pichia pastoris could be improved through thiol-reducing agent supplementation, and the mechanism of the effect NAC has on HSA-pFSHß secretion is associated with improving the intracellular GSH content.

In situ confinement pyrolysis of ZIF-67 nanocrystals on hollow carbon spheres towards efficient electrocatalysts for oxygen reduction.

The design and preparation of metal-organic frameworks (MOFs) as self-sacrificed precursors/templates has been considered as a promising strategy in recent years for fabricating metal/carbon electrocatalysts with intriguing architectures and outstanding properties. However, the serious aggregation during the calcination and the poor electron conductivity are still obstacles for these electrocatalysts which need to be urgently solved. Herein, an in situ confinement pyrolysis protocol is reported to transform ZIF-67 nanocrystals on hollow carbon spheres (HCS) to cobalt and nitrogen-enriched carbon shell, resulting in the formation of hierarchical HCS@Co/NC. This is the first study of electrochemistry for HCS decorated with MOFs or MOFs derivatives. In the structure, metallic Co nanoparticles (NPs) and N species are strongly anchored and dispersed in the network of nanocarbon shell, which not only affords a boosting conductivity but also greatly alleviates the aggregation of active sites. Meanwhile, the unique structure with hollow feature provides an effective pathway for mass transport and shortens the transmission path of electrons. Thanks to the advantages of structure and composition, the HCS@Co/NC catalyst exhibits a superb performance of oxygen reduction reaction, which outperforms the commercial Pt/C benchmark.

Realizing Hydrogen De/Absorption Under Low Temperature for MgH2 by Doping Mn-Based Catalysts.

Magnesium hydride (MgH2) has been considered as a potential material for storing hydrogen, but its practical application is still hindered by the kinetic and thermodynamic obstacles. Herein, Mn-based catalysts (MnCl2 and Mn) are adopted and doped into MgH2 to improve its hydrogen storage performance. The onset dehydrogenation temperatures of MnCl2 and submicron-Mn-doped MgH2 are reduced to 225 °C and 183 °C, while the un-doped MgH2 starts to release hydrogen at 315 °C. Further study reveals that 10 wt% of Mn is the better doping amount and the MgH2 + 10 wt% submicron-Mn composite can quickly release 6.6 wt% hydrogen in 8 min at 300 °C. For hydrogenation, the completely dehydrogenated composite starts to absorb hydrogen even at room temperature and almost 3.0 wt% H2 can be rehydrogenated in 30 min under 3 MPa hydrogen at 100 °C. Additionally, the activation energy of hydrogenation reaction for the modified MgH2 composite significantly decreases to 17.3 ± 0.4 kJ/mol, which is much lower than that of the primitive MgH2. Furthermore, the submicron-Mn-doped sample presents favorable cycling stability in 20 cycles, providing a good reference for designing and constructing efficient solid-state hydrogen storage systems for future application.

Data relating to sequencing statistics and the reads and genomic coverage aligning to Taenia solium in the cerebrospinal fluid.

This data can serve as a reference for other next-generation sequencing (NGS) of the cerebrospinal fluid (CSF). In the related research article, entitled "Next-Generation Sequencing of Cerebrospinal Fluid for the Diagnosis of Neurocysticercosis", we reported NGS of the CSF might be an auxiliary method for neurocysticercosis (NCC) patients who have complicated manifestations and courses to receive early diagnosis and treatment. In this article, we retrieved the available data about the sequencing statistics of the CSF samples and the number of unique reads and genomic coverage aligning to microorganic sequences. The data were generated by the Illumina MiniSeq system for sequencing and computational subtraction of the human host sequences was performed. Finally, the remaining sequencing data were aligned to the Microbial Genome Databases. This data can serve as a reference for other NGS of the CSF.

Correction to: Evolutionary and recombination analysis of porcine reproductive and respiratory syndrome isolates in China.

The original version of this article unfortunately contained an error in GenBank Accession Number.

Evolutionary and recombination analysis of porcine reproductive and respiratory syndrome isolates in China.

Seven strains of porcine reproductive and respiratory syndrome virus (PRRSV) were isolated from 2014 to 2017 in the Shandong province of China and their genomes were sequenced and analyzed. Results showed that all seven of the isolates belong to PRRSV 2, and are clustered into four lineages (lineage 1, 3, 5 and 8) based on comparisons of the ORF5 gene. Comparative analysis of genomes and specific amino acid sites revealed that three of the strains (SDwh1402, SDwh1602 and SDwh1701) have evolved directly from modified live virus (MLV) JXA1-P80, TJM-F92 and IngelvacPRRS. Further recombination analysis revealed that two of the strains (SDyt1401 and SDwh1601) were the result of a recombination event between MLVs JXA1-P80 and NADC30 while two other strains (SDwh1403 and SDqd1501) were the result of recombination between MLVs IngelvacPRRS and NADC30 and HP-PRRSV and QYYZ, respectively. Our results add to the data on MLV evolution and PRRSV recombination and provide a better understanding of the epidemiology of PRRSV in China.

Next-generation sequencing of cerebrospinal fluid for the diagnosis of neurocysticercosis.

OBJECTIVE: Neurocysticercosis (NCC) is the most common parasitic disease of the human central nervous system (CNS). However, a diagnosis of NCC may be hard to make if the specific clinical and routine neuroimaging manifestations are lacking, which hinders physicians from considering further immunodiagnostic tests. PATIENTS AND METHODS: Seven patients presented with fever, headache, nausea, cognitive decline, confusion, or progressive leg weakness. There were no pathogens found in the cerebrospinal fluid (CSF); patients were clinically suspected of meningoencephalitis or cerebrovascular disease. To clearly determine the etiology, next generation sequencing (NGS) of the CSF was used to detect pathogens in these seven patients. RESULTS: Taenia solium DNA sequences were detected in the seven patients, but not in the non-template controls (NTCs) or the other patients with clinically suspected CNS infections. Based on the patients' medical data and the diagnostic criteria for NCC, seven patients were diagnosed with probable NCC. The unique reads aligning to Taenia solium ranged from 6 to 261064, with genomic coverage ranging from 0.0003% to 14.8079%. The number of unique reads and genomic coverage dropped in three of the seven patients after antiparasitic treatment, consistent with the relief of symptoms. CONCLUSION: This study showed that NGS of the CSF might be an auxiliary diagnostic method for NCC patients. Larger studies are required.