A highly efficient and accurate method of detecting and subtyping Influenza A pdm H1N1 and H3N2 viruses with newly emerging mutations in the matrix gene in Eastern Taiwan.

The rapid identification of Influenza A virus and its variants, which cause severe respiratory diseases, is imperative to providing timely treatment and improving patient outcomes. Conventionally, two separate assays (total test duration of up to 6 h) are required to initially differentiate Influenza A and B viruses and subsequently distinguish the pdm H1N1 and H3N2 serotypes of Influenza A virus. In this study, we developed a multiplex real-time RT-PCR method for simultaneously detecting Influenza A and B viruses and subtyping Influenza A virus, with a substantially reduced test duration. Clinical specimens from hospitalized patients and outpatients with influenza-like symptoms in Eastern Taiwan were collected between 2011 and 2015, transported to Hualien Tzu Chi Hospital, and analyzed. Conventional RT-PCR was used to subtype the isolated Influenza A viruses. Thereafter, for rapid identification, the multiplex real-time RT-PCR method was developed and applied to identify the conserved regions that aligned with the available primers and probes. Accordingly, a multiplex RT-PCR assay with three groups of primers and probes (MAF and MAR primers and MA probe; InfAF and InfAR primers and InfA probe; and MBF and MBR primers and MB probe) was established to distinguish these viruses in the same reaction. Thus, with this multiplex RT-PCR assay, Influenza B, Influenza A pdm H1N1, and Influenza A H3N2 viruses were accurately detected and differentiated within only 2.5 h. This multiplex RT-PCR assay showed similar analytical sensitivity to the conventional singleplex assay. Further, the phylogenetic analyses of our samples revealed that the characteristics of these viruses were different from those reported previously using samples collected during 2012-2013. In conclusion, we developed a multiplex real-time RT-PCR method for highly efficient and accurate detection and differentiation of Influenza A and B viruses and subtyping Influenza A virus with a substantially reduced test duration for diagnosis.

A Novel 3D Culture Scaffold to Shorten Development Time for Multicellular Tumor Spheroids.

Multicellular tumor spheroids and tumoroids are considered ideal in vitro models that reflect the features of the tumor microenvironment. Biomimetic components resembling the extracellular matrix form scaffolds to provide structure to 3-dimensional (3D) culture systems, supporting the growth of both spheroids and tumoroids. Although Matrigel has long been used to support 3D culture systems, batch variations, component complexity, and the use of components derived from tumors are complicating factors. To address these issues, we developed the ACD 3D culture system to provide better control and consistency. We evaluated spheroid and tumoroid formation using the ACD 3D culture system, including the assessment of cell viability and cancer marker expression. Under ACD 3D culture conditions, spheroids derived from cancer cell lines exhibited cancer stem cell characteristics, including a sphere-forming size and the expression of stem cell marker genes. The ACD 3D culture system was also able to support patient-derived primary cells and organoid cell cultures, displaying adequate cell growth, appropriate morphology, and resistance to oxaliplatin treatment. These spheroids could also be used for drug screening purposes. In conclusion, the ACD 3D culture system represents an efficient tool for basic cancer research and therapeutic development.

Preoptimized phage cocktail for use in aerosols against nosocomial transmission of carbapenem-resistant Acinetobacter baumannii: A 3-year prospective intervention study.

Using bacteriophages (phages) as environmental sanitizers has been recognized as a potential alternative method to remove bacterial contamination in vitro; however, very few studies are available on the application of phages for infection control in hospitals. Here, we performed a 3-year prospective intervention study using aerosolized phage cocktails as biocontrol agents against carbapenem-resistant Acinetobacter baumannii (CRAB) infection in the hospital. When a CRAB-infected patient was identified in an intensive care unit (ICU), their surrounding environment was chosen for phage aerosol decontamination. Before decontamination, 501 clinical specimens from the patients were subjected to antibiotic resistance analysis and phage typing. The optimal phage cocktails were a combination of different phage families or were constructed by next-evolutionary phage typing with the highest score for the host lysis zone to prevent the development of environmental CRAB phage resistance. The phage infection percentage of the antibiotic-resistant A. baumannii strains was 97.1%, whereas the infection percentage in the antibiotic-susceptible strains was 79.3%. During the phage decontamination periods from 2017 to 2019, the percentage of carbapenem-resistant A. baumannii in test ICUs decreased significantly from 65.3% to 55%. The rate of new acquisitions of CRAB infection over the three years was 4.4 per 1000 patient-days, which was significantly lower than that in the control wards (8.9 per 1000 patient-days) where phage decontamination had never been performed. In conclusion, our results support the potential of phage cocktails to decrease CRAB infection rates, and the aerosol generation process may make this approach more comprehensive and time-saving.

Mesenchymal stem cell-derived exosomes improve motor function and attenuate neuropathology in a mouse model of Machado-Joseph disease.

BACKGROUND: Machado-Joseph disease is the most common autosomal dominant hereditary ataxia worldwide without effective treatment. Mesenchymal stem cells (MSCs) could slow the disease progression, but side effects limited their clinical application. Besides, MSC-derived exosomes exerted similar efficacy and have many advantages over MSCs. The aim of this study was to examine the efficacy of MSC-derived exosomes in YACMJD84.2 mice. METHODS: Rotarod performance was evaluated every 2 weeks after a presymptomatic administration of intravenous MSC-derived exosomes twice in YACMJD84.2 mice. Loss of Purkinje cells, relative expression level of Bcl-2/Bax, cerebellar myelin loss, and neuroinflammation were assessed 8 weeks following treatment. RESULTS: MSC-derived exosomes were isolated and purified through anion exchange chromatography. Better coordination in rotarod performance was maintained for 6 weeks in YACMJD84.2 mice with exosomal treatment, compared with those without exosomal treatment. Neuropathological changes including loss of Purkinje cells, cerebellar myelin loss, and neuroinflammation were also attenuated 8 weeks after exosomal treatment. The higher relative ratio of Bcl-2/Bax was consistent with the attenuation of loss of Purkinje cells. CONCLUSIONS: MSC-derived exosomes could promote rotarod performance and attenuate neuropathology, including loss of Purkinje cells, cerebellar myelin loss, and neuroinflammation. Therefore, MSC-derived exosomes have a great potential in the treatment of Machado-Joseph disease.

[Drug Discrimination Method Based on Near Infrared Reflectance Spectrum and Balance Cascading Sparse Representation Based Classification].

The combination of near infrared spectrum and pattern recognition methods has a wide application prospect in rapid and nondestructive supervision and management of drugs. The traditional identification methods regard the smallest error rate as the goal while the imbalance of classes is ignored. This makes the positive class is overwhelming covered by the negative class and reduces its effect for the classifier, so that the classification results tend to recognize the negative class correctly, which severely affects the identification accuracy. In this paper, we mainly studied the class imbalance problems of true or false drugs via infrared spectral data of its, and then propose a balance cascading and sparse representation based classification method (BC-SRC) by combining the Balance Cascading with SRC. We sampling majority samples from the majority class for several times, which has the same size as minority samples and the majority samples we sampled can contain all the majority class samples entirely (sampling times is ceiling the result of majority samples number divide minority samples number). We can get sets of results, and then obtain the final predict labels form those results. Experiments of three databases achieved on Matlab2012a shows that the method is effective. From the experimental results, it can be seen that the method is superior to the commonly used Partial Least Squares (PLS), Extreme Learning Machine (ELM) and BP. Particularly, for the imbalanced databases, when the imbalance factor is greater than 10, the proposed method has more stable performance with higher classification accuracy than the existing ones mentioned above.

Human risk factors associated with pilots in runway excursions.

A breakdown analysis of civil aviation accidents worldwide indicates that the occurrence of runway excursions represents the largest portion among all aviation occurrence categories. This study examines the human risk factors associated with pilots in runway excursions, by applying a SHELLO model to categorize the human risk factors and to evaluate the importance based on the opinions of 145 airline pilots. This study integrates aviation management level expert opinions on relative weighting and improvement-achievability in order to develop four kinds of priority risk management strategies for airline pilots to reduce runway excursions. The empirical study based on experts' evaluation suggests that the most important dimension is the liveware/pilot's core ability. From the perspective of front-line pilots, the most important risk factors are the environment, wet/containment runways, and weather issues like rain/thunderstorms. Finally, this study develops practical strategies for helping management authorities to improve major operational and managerial weaknesses so as to reduce the human risks related to runway excursions.

[Sparse Denoising Autoencoder Application in Identification of Counterfeit Pharmaceutical].

Near-infrared(NIR)As a fast and non-destructive testing technology, spectroscopy techniques is very suitable for pharmaceutical discrimination. Autoencoder network, as a hot research topic, has drawn widespread attention in machine learning research in recent years. Compared with traditional surface learning algorithm models, Autoencoder network has more powerful modeling capability as a typical deep networks model. Based on the unsupervised greedy layer-wise pre-training, autoencoder trains the network layer by layer while minimizing the error in reconstructing. Each layer is pre-trained with an unsupervised learning algorithm, learning a nonlinear transformation of the input of each layer which is the output of the previous layer. Pre-whitening process could get the inner structural features of the data more effectively. The supervised fine-tuning is followed with the unsupervised pre-training which sets the stage for a final training phase. The deep architecture is fine-tuned with respect to a supervised training criterion with gradient-based optimization. In this paper, firstly, the preprocessing step and pre-whitening transformation were used to treat near-infrared spectroscopy data of erythromycin ethylsuccinate, The pre-whitening transformation would reduce the correlation of the features, which gave each feature the same variance. Experimental results showed that the pre-whitening process had improved the classification accuracy of Sparse Denoising Autoencoder (SDAE) effectively. The SDAE with two hidden layers combined with pre-whitening was used to build the classification model for the identification of counterfeit pharmaceutical. The BP neural networks was compared with SVM algorithm for the classification accuracy and mean absolute difference (MAD). SDAE algorithm had higher classification accuracy than BP neural networks which had the same network structure with the SDAE networks, and SDAE algorithm also performed better than the SVM algorithm when the train datasets achieved a certain amount. As to the generalization performances, SDAE algorithm had less mean absolute difference of classification accuracy than SVM and BP Neural Networks. This result showed that SDAE algorithm could be effectively used to discriminate the counterfeit pharmaceutical.

Human adenovirus type 8 epidemic keratoconjunctivitis with large corneal epithelial full-layer detachment: an endemic outbreak with uncommon manifestations.

Epidemic viral conjunctivitis is a highly contagious disease that is encountered year-round. The causative agents are mainly adenoviruses and enteroviruses. It occurs most commonly upon infection with subgroup D adenoviruses of types 8, 19, or 37. For common corneal involvement of human adenovirus type 8 epidemic keratoconjunctivitis, full-layer epithelial detachment is rarely seen. Herein, we report three cases of epidemic keratoconjunctivitis during an outbreak which manifested as large corneal epithelial full-layer detachment within a few days. The lesions healed without severe sequelae under proper treatment. The unique manifestation of this outbreak may indicate the evolution of human adenovirus type 8.

[Drug discrimination by near infrared spectroscopy based on summation wavelet extreme learning machine].

As an effective technique to identify counterfeit drugs, Near Infrared Spectroscopy has been successfully used in the drug management of grass-roots units, with classifier modeling of Pattern Recognition. Due to a major disadvantage of the characteristic overlap and complexity, the wide bandwidth and the weak absorption of the Spectroscopy signals, it seems difficult to give a satisfactory solutions for the modeling problem. To address those problems, in the present paper, a summation wavelet extreme learning machine algorithm (SWELM(CS)) combined with Cuckoo research was adopted for drug discrimination by NIRS. Specifically, Extreme Learning Machine (ELM) was selected as the classifier model because of its properties of fast learning and insensitivity, to improve the accuracy and generalization performances of the classifier model; An inverse hyperbolic sine and a Morlet-wavelet are used as dual activation functions to improve convergence speed, and a combination of activation functions makes the network more adequate to deal with dynamic systems; Due to ELM' s weights and hidden layer threshold generated randomly, it leads to network instability, so Cuckoo Search was adapted to optimize model parameters; SWELM(CS) improves stability of the classifier model. Besides, SWELM(CS) is based on the ELM algorithm for fast learning and insensitivity; the dual activation functions and proper choice of activation functions enhances the capability of the network to face low and high frequency signals simultaneously; it has high stability of classification by Cuckoo Research. This compact structure of the dual activation functions constitutes a kernel framework by extracting signal features and signal simultaneously, which can be generalized to other machine learning fields to obtain a good accuracy and generalization performances. Drug samples of near in- frared spectroscopy produced by Xian-Janssen Pharmaceutical Ltd were adopted as the main objects in this paper. Experiments for binary classification and multi-label classification were conducted, and the conclusion proved that the proposed method has more stable performance, higher classification accuracy and lower sensitivity to training samples than the existing ones, such as the BP neural network, ELM and-ELM by particle swarm optimization.

[Parallel PLS algorithm using MapReduce and its aplication in spectral modeling].

Partial least squares (PLS) has been widely used in spectral analysis and modeling, and it is computation-intensive and time-demanding when dealing with massive data To solve this problem effectively, a novel parallel PLS using MapReduce is proposed, which consists of two procedures, the parallelization of data standardizing and the parallelization of principal component computing. Using NIR spectral modeling as an example, experiments were conducted on a Hadoop cluster, which is a collection of ordinary computers. The experimental results demonstrate that the parallel PLS algorithm proposed can handle massive spectra, can significantly cut down the modeling time, and gains a basically linear speedup, and can be easily scaled up.

New genotypes of Orientia tsutsugamushi isolated from humans in Eastern Taiwan.

Scrub typhus, an acute febrile illness, is caused by the obligate intracellular bacterium Orientia tsutsugamushi. In our study, O. tsutsugamushi was rapidly detected and typed by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) analysis of the 56-kDa type-specific antigen (TSA) gene. To investigate the genotypes of clinical variants of O. tsutsugamushi, we collected 3223 blood samples from eastern Taiwanese patients with suspected scrub typhus from 2002 to 2008. In total, 505 samples were found to be positive for scrub typhus infection by PCR, and bacteria were isolated from 282 of them. Four prototype genotype strains (Karp, Kato, Kawasaki and Gilliam) and eleven different Taiwanese genotype isolates (Taiwan-A, -B, -C, -D, -E, -G, -H, -J, -N, -O and -P) were identified by RPLF analysis. Taiwan-H, the major genotype in eastern Taiwan, exhibited prevalence and isolation rates of 47.3% (239/505) and 42.6% (120/282), respectively. We also assessed the genetic relatedness of the 56-kDa TSA gene among eight Taiwan-H isolates, thirteen other Taiwanese isolates and 104 DNA sequences deposited in the GenBank database using MEGA version 5.0 and PHYLIP version 3.66. We found that the Taiwan-H isolates formed into a new cluster, which was designated the Taiwan Gilliam-variant (TG-v) cluster to distinguish it from the Japanese Gilliam-variant (JG-v) cluster. According to Simplot analysis, TG-v is a new recombinant strain among Gilliam, Ikeda and Kato. Moreover, the Gilliam-Kawasaki cluster had the highest percentage of RFLP cases and was the most frequently isolated type in eastern Taiwan (50.1%, 253/505; 44.0%, 124/282). These findings shed light on the genetic evolution of O. tsutsugamushi into different strains and may be useful in vaccine development and epidemic disease control in the future.

Involvement of extraneural tissues and upregulation of inducible nitric oxide synthase after experimental infection with rabies virus in BALB/c mice and LEW/SsN rats.

Rabies virus can cause fatal encephalomyelitis, but the involvement of extraneural organs has not been well characterized. In this study, we investigated the histopathological changes and the distribution of viral antigens in extraneural organs after pathogenic rabies virus infection in mouse and rat models. In histopathological examination, classical viral encephalitis and rabies-specific Negri body were observed in the brain. In addition to the central nervous system (CNS), inflammatory responses were found in other organs, such as the heart, kidney, liver, and lung. Similarly, immunohistochemical staining and reverse transcription-polymerase chain reaction revealed the presence of rabies virus in the CNS and extraneural tissues. Moreover, macrophages, especially in the lung and heart, were involved in the infection. Transcriptional analyses of the expression of inducible nitric oxide synthase (iNOS) demonstrated that rabies virus potentiated the gene expression of iNOS in the brain, lung, and heart. The immunoreactive iNOS-positive macrophages were detected adjacent to the infection. These results suggest that macrophages are involved in the extraneural infection and the expression of iNOS in macrophages contributes to the formation of tissue inflammation. Our study indicates the involvement of extraneural organs following rabies virus infection, which may aggravate the progression of this deadly disease.

[A novel online process monitoring method based on near infrared spectroscopy and its application to the column chromatographic separation for traditional Chinese medicine].

Near infrared spectroscopy (NIRS) is a process analysis and monitoring tool with many advantages, while it needs to set up quantitative or discriminative calibration models in advance, and needs to adjust these models when the process conditions are varied, which makes it difficult for ordinary user to take its full advantage of it. To tackle this problem, this paper presented a novel, simple and model-free methodology for online process monitoring based on two reciprocal viewpoints of measuring the variability of spectroscopy-both the similarity and dissimilarity of process spectrum, i.e., the adaptive moving window standard deviation function(AMWSW) and similarity function(S). The methodology was validated by a column chromatography process of traditional Chinese medicine using near infrared spectroscopy. The online trend curves of AMWSW and S obtained by proposed method were validated by a comparison with the content variation curves of multiple indicative components analyzed by high performance liquid chromatography (HPLC), and these trend curves demonstrated their potential for real-time process status monitoring, accurately determining the beginning point, the peak point, the end point of the elution, and the phase change from water solution to ethanol solution. The proposed methodology can also be used to other process analysis techniques, such as ultraviolet/visible, infrared, Raman, fluorescence, chromatograph and mass spectrum.

Sufficient virus-neutralizing antibody in the central nerve system improves the survival of rabid rats.

BACKGROUND: Rabies is known to be lethal in human. Treatment with passive immunity for the rabies is effective only when the patients have not shown the central nerve system (CNS) signs. The blood-brain barrier (BBB) is a complex functional barrier that may compromise the therapeutic development in neurological diseases. The goal of this study is to determine the change of BBB integrity and to assess the therapeutic possibility of enhancing BBB permeability combined with passive immunity in the late stage of rabies virus infection. METHODS: The integrity of BBB permeability in rats was measured by quantitative ELISA for total IgG and albumin levels in the cerebrospinal fluid (CSF) and by exogenously applying Evans blue as a tracer. Western blotting of occludin and ZO-1, two tight junction proteins, was used to assess the molecular change of BBB structure.The breakdown of BBB with hypertonic arabinose, recombinant tumor necrosis factor-alpha (rTNF-γ), and focused ultrasound (FUS) were used to compare the extent of BBB disruption with rabies virus infection. Specific humoral immunity was analyzed by immunofluorescent assay and rapid fluorescent focus inhibition test. Virus-neutralizing monoclonal antibody (mAb) 8-10E was administered to rats with hypertonic breakdown of BBB as a passive immunotherapy to prevent the death from rabies. RESULTS: The BBB permeability was altered on day 7 post-infection. Increased BBB permeability induced by rabies virus infection was observed primarily in the cerebellum and spinal cord. Occludin was significantly decreased in both the cerebral cortex and cerebellum. The rabies virus-specific antibody was not strongly elicited even in the presence of clinical signs. Disruption of BBB had no direct association with the lethal outcome of rabies. Passive immunotherapy with virus-neutralizing mAb 8-10E with the hypertonic breakdown of BBB prolonged the survival of rabies virus-infected rats. CONCLUSIONS: We demonstrated that the BBB permeability was altered in a rat model with rabies virus inoculation. Delivery of neutralizing mAb to the infected site in brain combined with effective breakdown of BBB could be an aggressive but feasible therapeutic mode in rabies when the CNS infection has been established.

Cabin safety and emergency evacuation: passenger experience of flight CI-120 accident.

Aircraft evacuation effectiveness is a critical but challenging issue in the civil aviation industry. This paper explores the cabin safety perceptions of passengers from their emergency evacuation experiences in an actual aviation accident. A questionnaire survey and in-depth interviews were conducted with China Airlines flight CI-120 passengers. The qualitative and quantitative results provide insights into passengers' views of cabin safety. The in-depth interview results show that passenger safety education requires more instructions about the use of emergency equipment. The data from the passenger perception questionnaire were analyzed using the factor analysis method; the findings indicate that crew assistance and emergency procedures are the most important factors. The results are likely to be of value to the aviation industry when taking into account passenger perceptions in implementing safety programs.

[Real-time monitoring of industrial acetic acid production process using a new type of online NIR analysis system].

The safe and real-time monitoring of the production process of acetic acid is always a key technical problem. The conventional online chromatographic analysis can't satisfy the requirements of real-time analysis for its inherent disadvantages. A new type of on-line near-infrared analysis system has been developed for real-time analysis of the concentration of each component in acetic acid reaction kettles instantly. Its features and configuration were described in detail. Both the laboratory modeling and field application results have confirmed that this system is of high stability and accuracy. The proposed system can effectively solve the key technical problems in the manufacture and ensure the safety and stability of production process of acetic acid.

Aviation occupant survival factors: an empirical study of the SQ006 accident.

We present an empirical study of Singapore Airline (SIA) flight SQ006 to illustrate the critical factors that influence airplane occupant survivability. The Fuzzy Delphi Method was used to identify and rank the survival factors that may reduce injury and fatality in potentially survivable accidents. This is the first attempt by a group from both the public and private sectors in Taiwan to focus on cabin-safety issues related to survival factors. We designed a comprehensive survey based on our discussions with aviation safety experts. We next designed an array of important cabin-safety dimensions and then investigated and selected the critical survival factors for each dimension. Our findings reveal important cabin safety and survivability information that should provide a valuable reference for developing and evaluating aviation safety programs. We also believe that the results will be practical for designing cabin-safety education material for air travelers. Finally, the major contribution of this research is that it has identified 47 critical factors that influence accident survivability; therefore, it may encourage improvements that will promote more successful cabin-safety management.

[Isomap-PLS nonlinear modeling method for near infrared spectroscopy].

For modeling the nonlinear relationship existing between samples' near infrared (NIR) spectra and their chemical or physical properties, a novel modeling method was put forward in the present paper, which builds model by combining Isomap and partial least squares (PLS). Isomap is a newly proposed nonlinear dimension reduction algorithm, and belongs to the algorithm family of manifold learning, which is a new branch of machine learning. Isomap is based on multidimensional scaling (MDS) algorithm; however, it replaces the Euclidean distance in MDS with an approximated geodesic distance, so it can effectively find out the intrinsic low dimensional structure from high dimensional data. By combining Isomap and PLS, refered to as Isomap-PLS, a novel nonlinear modeling method for NIR spectra analysis was proposed. In this method, Isomap was used to extract nonlinear information from high dimensional NIR spectra while keeping the invariance of geometric property, and then PLS was adopted to remove linear information redundancy and build a calibration model. The parameters of the Isomap, i.e. the number of the nearest neighbor k and output dimension d, can affect the performance of the method. In this paper, a grid search approach was used for parameter optimization. The Isomap-PLS modeling method was applied to two public benchmark NIR datasets, and the modeling results were compared with that of PLS. The results demonstrated that in both datasets, each model built with Isomap-PLS had a smaller rooted mean square error of cross-validation (RMSECV) than the corresponding model built with PLS. Moreover, for some properties, the RMSECV of Isomap-PLS was significantly reduced by a factor of 2-5 compared with that of PLS. It can be concluded that by taking the virtue that Isomap can reflect the intrinsic nonlinear structure of NIR spectra, Isomap-PLS can effectively model the nonlinear correlations between spectra and physicochemical properties of the samples, and so it gains more power in calibration and prediction than PLS.

An outbreak of human metapneumovirus infection in hospitalized psychiatric adult patients in Taiwan.

Human metapneumovirus (hMPV) is a paramyxovirus that is associated with respiratory tract infection (RTI) mostly in children, but these outbreaks have rarely been reported in adults. We encountered an outbreak of this disease involving 10 adults in a psychiatric ward in eastern Taiwan. The nasopharyngeal swab specimens from 13 patients with symptoms of RTI were obtained and analyzed. The RT-PCR tests were negative to influenza virus A/B, adenovirus, RSV, parainfluenza virus, coronavirus, Nipah virus and Legionella. The antigen tests were negative to Legionella, Chlamydia, and Mycoplasma. Blood culture was negative in all except patient no. 1, who was found positive for coagulase-negative staphylococci. The hMPV was identified in 10 of 13 adults (77%), but negative for the other virus. Cough was present in all (100%), fever in 90%, and X-ray evidence of pneumonia in 7 patients. One patient died of respiratory failure. We report this outbreak in a mental hospital to alert the medical profession that this unusual infection of hMPV can occur as an outbreak in an adult setting and is an occupational hazard for healthcare personnel.

Neural tube defects and disturbed maternal folate- and homocysteine-mediated one-carbon metabolism.

Disturbances in maternal folate and homocysteine metabolism are associated with neural tube defects (NTDs). However, the role played by specific components in the one-carbon metabolic pathways leading to NTDs remains unclear. Here, we conducted a case-control study to investigate the relationship between the disturbed one-carbon metabolism and the risk of NTD-affected pregnancies. Major components were examined in population-based samples of women who had NTD-affected pregnancies (case subjects, n=46) or unaffected by any birth defects (control subjects, n=44). We used the newly developed high-performance liquid chromatography tandem mass spectrometry along with a routine chemiluminescent assay, to measure serum concentrations of 5-methyltetrahydrofolate (5-MeTHF), 5-formyltetrahydrofolate (5-FoTHF), folic acid, serine, histidine, homocysteine, cystathionine, methionine, S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH), total folate and vitamin B12 in both groups adjusting for lifestyle and sociodemographic variables. We found significantly lower serum concentrations of 5-MeTHF (P<0.001), 5-FoTHF (P=0.004), total folate (P<0.001) and vitamin B12 (P=0.005) and remarkably higher concentrations of SAH (P=0.016) in cases than in controls. Therefore, these compounds could be identified as potential risk factors for NTD's early diagnosis. Further analysis of relevant genetic and epidemiologic investigations may provide more insights into the pathogenesis of NTDs and enhance current nutritional intervention strategies to reduce the risk of NTD-affected pregnancies.