Single-chromosome dynamics reveals locus-dependent dynamics and chromosome territory orientation.

Dynamic chromatin organization instantly influences DNA accessibility through modulating local macromolecular density and interactions, driving changes in transcription activities. Chromatin dynamics have been reported to be locally confined but contribute to coherent chromatin motion across the entire nucleus. However, the regulation of dynamics, nuclear orientation and compaction of subregions along a single chromosome are not well-understood. We used CRISPR-based real-time single-particle tracking and polymer models to characterize the dynamics of specific genomic loci and determine compaction levels of large human chromosomal domains. Our studies showed that chromosome compaction changed during interphase and that compactions of two arms on chromosome 19 were different. The dynamics of genomic loci were subdiffusive and dependent on chromosome regions and transcription states. Surprisingly, the correlation between locus-dependent nuclear localization and mobility was negligible. Strong tethering interactions detected at the pericentromeric region implies local condensation or associations with organelles within local nuclear microenvironments, such as chromatin-nuclear body association. Based on our findings, we propose a 'guided radial model' for the nuclear orientation of the long arm of chromosome 19.

Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women.

While FRAX with BMD could be more precise in estimating the fracture risk, DL-based models were validated to slightly reduce the number of under- and over-treated patients when no BMD measurements were available. The validated models could be used to screen for patients at a high risk of fracture and osteoporosis. PURPOSE: Fracture risk assessment tool (FRAX) is useful in classifying the fracture risk level, and precise prediction can be achieved by estimating both clinical risk factors and bone mineral density (BMD) using dual X-ray absorptiometry (DXA). However, DXA is not frequently feasible because of its cost and accessibility. This study aimed to establish the reliability of deep learning (DL)-based alternative tools for screening patients at a high risk of fracture and osteoporosis. METHODS: Participants were enrolled from the National Bone Health Screening Project of Taiwan in this cross-sectional study. First, DL-based models were built to predict the lowest T-score value in either the lumbar spine, total hip, or femoral neck and their respective BMD values. The Bland-Altman analysis was used to compare the agreement between the models and DXA. Second, the predictive model to classify patients with a high fracture risk was built according to the estimated BMD from the first step and the FRAX score without BMD. The performance of the model was compared with the classification based on FRAX with BMD. RESULTS: Approximately 10,827 women (mean age, 65.4 ± 9.4 years) were enrolled. In the prediction of the lumbar spine BMD, total hip BMD, femoral neck BMD, and lowest T-score, the root-mean-square error (RMSE) was 0.099, 0.089, 0.076, and 0.68, respectively. The Bland-Altman analysis revealed a nonsignificant difference between the predictive models and DXA. The FRAX score with femoral neck BMD for major osteoporotic fracture risk was 9.7% ± 6.7%, whereas the risk for hip fracture was 3.3% ± 4.6%. Comparison between the classification of FRAX with and without BMD revealed the accuracy rate, positive predictive value (PPV), and negative predictive value (NPV) of 78.8%, 64.6%, and 89.9%, respectively. The area under the receiver operating characteristic curve (AUROC), accuracy rate, PPV, and NPV of the classification model were 0.913 (95% confidence interval: 0.904-0.922), 83.5%, 71.2%, and 92.2%, respectively. CONCLUSION: While FRAX with BMD could be more precise in estimating the fracture risk, DL-based models were validated to slightly reduce the number of under- and over-treated patients when no BMD measurements were available. The validated models could be used to screen for patients at a high risk of fracture and osteoporosis.

Efficient photoanode with a MoS2/TiO2/Au nanoparticle heterostructure for ultraviolet-visible photoelectrocatalysis.

Green energy technology is generally becoming one of hot issues that need to be solved due to the adverse effects on the environment of fossil fuels. One of the strategies being studied and developed by theorists and experimentalists is the use of photoelectrochemical (PEC) cells, which are emerging as a candidate to produce hydrogen from water splitting. However, creating photoelectrodes that meet the requirements for PEC water splitting has emerged as the primary obstacle in bringing this technology to commercial fruition. Here, we construct a heterostructure, which consists of MoS2/TiO2/Au nanoparticles (NPs) to overcome the drawbacks of the photoanode. Owing to the dependence on charge transfer, the bandgap of MoS2/TiO2and the utilization the Au NPs as a stimulant for charges separation of TiO2by localized surface plasmon resonances effect as well as the increase of hot electron injection to cathode, leading to photocatalytic activities are improved. The results have recorded a significant increase in the photocurrent density from 2.3µAcm-2of TiO2to approximately 16.3µAcm-2of MoS2/TiO2/Au NPs. This work unveils a promising route to enhance the visible light adsorption and charge transfer in photo-electrode of the PEC cells by combining two-dimensional materials with metal NPs.

A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma.

BACKGROUND: Adenosine-to-inosine RNA editing (ATIRE) is characterized as non-mutational epigenetic reprogramming hallmark of cancer, while little is known about its predictive role in cancer survival. METHODS: To explore survival-related ATIRE events in lung squamous cell carcinoma (LUSC), ATIRE profile, gene expression data, and corresponding clinical information of LUSC patients were downloaded from the TCGA database. Patients were randomly divided into a training (n = 134) and validation cohort (n = 94). Cox proportional hazards regression followed by least absolute shrinkage and selection operator algorithm were performed to identify survival-related ATIRE sites and to generate ATIRE risk score. Then a nomogram was constructed to predict overall survival (OS) of LUSC patients. The correlation of ATIRE level and host gene expression and ATIREs' effect on transcriptome expression were analyzed. RESULTS: Seven ATIRE sites that were TMEM120B chr12:122215052A > I, HMOX2 chr16:4533713A > I, CALCOCO2 chr17:46941503A > I, LONP2 chr16:48388244A > I, ZNF440 chr19:11945758A > I, CLCC1 chr1:109474650A > I, and CHMP3 chr2:86754288A > I were identified to generate the risk score, of which high levers were significantly associated with worse OS and progression-free survival in both the training and validation sets. High risk-score was also associated with advanced T stages and worse clinical stages. The nomogram performed well in predicting OS probability of LUSC. Moreover, the editing of ATIRE sites exerted a significant association with expression of host genes and affected several cancer-related pathways. CONCLUSIONS: This is the first comprehensive study to analyze the role of ATIRE events in predicting LUSC survival. The AITRE-based model might serve as a novel tool for LUSC survival prediction.

[Seed morphology and germination characteristics of Tripterygium wilfordii].

The seeds of Tripterygium wilfordii are characterized by dormancy and a long germination cycle under natural sowing conditions. In this study, we developed a method for rapid germination of T. wilfordii seeds by analyzing the size, morphology, thousand-grain weight, viability, moisture content, physicochemical properties, and seed germination rates under different germination conditions. The seeds of T. wilfordii were fine columnar with a thick and hard outer seed coat. They had the length of 6.69 mm, the width of 2.14 mm, the thickness of 1.68 mm, the thousand-grain weight of 8.99 g, the moisture content of 8.86%, the soluble sugar content of 21.3 mg·g~(-1), the starch content of 28.9 mg·g~(-1), the soluble protein content of 44.2 mg·g~(-1), and the seed viability of only 54.0%. The seeds were respectively treated with distilled water, ultrasonication, low-temperature storage, 50 ℃ water, 100 mg·L~(-1) 6-BA, 0.6% KMnO_4, 1% KNO_3, 50 mg·L~(-1) NAA, and 100 mg·L~(-1) GA_3 solution. The results showed that soaking the seeds in 100 mg·L~(-1) GA_3 solution significantly promoted the germination. Further, the seeds were soaked in 50, 100, 250, 500, and 1 000 mg·L~(-1) GA_3 solutions, which demonstrated that high concentration(500 mg·L~(-1), 1 000 mg·L~(-1)) of GA_3 solutions increased the germination rate and speed and shortened the germination cycle from more than 3 months to less than 15 days. The findings of this study are of great significance to the breeding of T. wilfordii and lay a foundation for the large-scale propagation of T. wilfordii seeds and the excavation of T. wilfordii germplasm resources.

CRISPR-Sirius: RNA scaffolds for signal amplification in genome imaging.

Clustered regularly interspaced short palindromic repeats (CRISPR) guide RNA scaffolds have been adapted to carry multiple binding sites for fluorescent proteins to enhance brightness for live cell imaging of genomic loci. However, many of these modifications result in guide RNA instability and thus produce lower genome-labeling efficiency than anticipated. Here we introduce CRISPR-Sirius, based on octet arrays of aptamers conferring both enhanced guide RNA stability and brightness, and provide initial biological applications of this platform.

C-BERST: defining subnuclear proteomic landscapes at genomic elements with dCas9-APEX2.

Mapping proteomic composition at distinct genomic loci in living cells has been a long-standing challenge. Here we report that dCas9-APEX2 biotinylation at genomic elements by restricted spatial tagging (C-BERST) allows the rapid, unbiased mapping of proteomes near defined genomic loci, as demonstrated for telomeres and centromeres. C-BERST enables the high-throughput identification of proteins associated with specific sequences, thereby facilitating annotation of these factors and their roles.

Functional near-infrared spectroscopy (fNIRS) as a tool to assist the diagnosis of major psychiatric disorders in a Chinese population.

Advances in neuroimaging have promised the development of specific and objective biomarkers for the diagnosis and treatment of psychiatric disorders. Recently, functional near-infrared spectroscopy (fNIRS) has been used during cognitive tasks to measure cortical dysfunction associated with mental illnesses such as Schizophrenia (SCH), Major-Depressive disorder (MD) and Bipolar Disorder (BD). We investigated the ability of fNIRS as a clinically viable tool to successfully distinguish healthy individuals from those with major psychiatric disorders. 316 patients with major psychiatric disorders (198 SCH/54 MD/64 BP) and 101 healthy controls were included in this study. Changes in oxygenated-hemoglobin during a Chinese language verbal fluency test were measured using a 52-channel fNIRS machine over the bilateral temporal and frontal lobe areas. We evaluated the ability of two task-evoked features selected from prior studies the Integral and Centroid values, to identify individuals with major diagnoses. Both the integral value of frontal and centroid value of temporal showed sensitivity in classifying individuals with mental disorders from healthy controls. However, using a combined index featuring both the integral value and centroid value to differentiate psychiatric disorders from healthy controls with an AUC of 0.913, differentiate individuals with mood disorders from healthy controls showed an AUC of 0.899, while for schizophrenia the AUC was 0.737. Our data suggest that fNIRS can be used as a candidate biomarker during differential diagnosis individuals with mood or psychosis disorders and offer a step towards individualization of treatment.

Tongue image quality assessment based on a deep convolutional neural network.

BACKGROUND: Tongue diagnosis is an important research field of TCM diagnostic technology modernization. The quality of tongue images is the basis for constructing a standard dataset in the field of tongue diagnosis. To establish a standard tongue image database in the TCM industry, we need to evaluate the quality of a massive number of tongue images and add qualified images to the database. Therefore, an automatic, efficient and accurate quality control model is of significance to the development of intelligent tongue diagnosis technology for TCM. METHODS: Machine learning methods, including Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Adaptive Boosting Algorithm (Adaboost), Naïve Bayes, Decision Tree (DT), Residual Neural Network (ResNet), Convolution Neural Network developed by Visual Geometry Group at University of Oxford (VGG), and Densely Connected Convolutional Networks (DenseNet), were utilized to identify good-quality and poor-quality tongue images. Their performances were made comparisons by using metrics such as accuracy, precision, recall, and F1-Score. RESULTS: The experimental results showed that the accuracy of the three deep learning models was more than 96%, and the accuracy of ResNet-152 and DenseNet-169 was more than 98%. The model ResNet-152 obtained accuracy of 99.04%, precision of 99.05%, recall of 99.04%, and F1-score of 99.05%. The performances were better than performances of other eight models. The eight models are VGG-16, DenseNet-169, SVM, RF, GBDT, Adaboost, Naïve Bayes, and DT. ResNet-152 was selected as quality-screening model for tongue IQA. CONCLUSIONS: Our research findings demonstrate various CNN models in the decision-making process for the selection of tongue image quality assessment and indicate that applying deep learning methods, specifically deep CNNs, to evaluate poor-quality tongue images is feasible.

Lung CSC-derived exosomal miR-210-3p contributes to a pro-metastatic phenotype in lung cancer by targeting FGFRL1.

Lung cancer has the highest mortality rate among human cancers, and the majority of deaths can be attributed to metastatic spread. Lung cancer stem cells (CSCs) are a component of the tumour microenvironment that contributes to this process. Exosomes are small membrane vesicles secreted by all types of cells that mediate cell interactions, including cancer metastasis. Here, we show that lung CSC-derived exosomes promote the migration and invasion of lung cancer cells, up-regulate expression levels of N-cadherin, vimentin, MMP-9 and MMP-1, and down-regulate E-cadherin expression. Moreover, we verified that these exosomes contribute to a pro-metastatic phenotype in lung cancer cells via miR-210-3p transfer. The results of bioinformatics analysis and dual-luciferase reporter assays further indicated that miR-210-3p may bind to fibroblast growth factor receptor-like 1 (FGFRL1); silencing FGFRL1 enhanced the metastatic ability of lung cancer cells, whereas overexpressing FGFRL1 suppressed metastasis. Taken together, our results provide new insights into a potential molecular mechanism whereby lung CSC-derived exosomal miR-210-3p targets FGFRL1 to promote lung cancer metastasis. FGFRL1 may be a promising therapeutic target in lung cancer.

Isolation and characterization of a glycosyltransferase with specific catalytic activity towards flavonoids from Tripterygium wilfordii.

Flavonoids are important secondary metabolites that exist in many medicinal plants. Flavonoid glycosyltransferases can transfer sugar moieties to their parent rings, producing various flavonoid glycosides with significant pharmacological activities. Here, we report the molecular cloning of the O-glycosyltransferase TwUGT2 from Tripterygium wilfordii and its catalytic activity was explored by heterologous expression in E. coli. The results showed that TwUGT2 has specific glycosyltransferase activity towards C-3 and 7 hydroxyl groups of flavonoids, thereby converting quercetin and pinocembrin into isoquercitrin and pinocembrin 7-O-beta-D-glucoside, respectively. The identification of TwUGT2 will provide a useful molecular tool for synthetic biology and contribute to drug discovery.[Formula: see text].

Admission Serum Calcium Level as a Prognostic Marker for Intracerebral Hemorrhage.

BACKGROUND: Prognostic significance of serum calcium level in patients with intracerebral hemorrhage is not well studied. The aim of the study was to identify if a relationship between admission serum calcium level and prognosis exists in patients with intracerebral hemorrhage. METHODS: A total of 1262 confirmed intracerebral hemorrhage patients were included. Demographic data, medical history, medicine history, laboratory data, imaging data, clinical score, and progress note were collected from their medical records. All images of head computed tomography were reanalyzed. Ninety-day prognosis was recorded, and poor outcome was defined as death or major disability caused by intracerebral hemorrhage. RESULTS: During the 90-day follow-up period, 504 patients died and 226 patients suffered from major disability. Death and major disability were combined as poor prognosis. The remaining 532 patients showed good prognosis. Admission serum calcium level was lower in the patients with poor prognosis than in the patients with good prognosis (2.41 ± 0.23 mmol/l, 2.55 ± 0.26 mmol/l, P < 0.001). Admission INR and hematoma volume were higher in the patients with poor prognosis than in the patients with good prognosis (INR: 1.74 ± 0.29, 1.70 ± 0.29, P = 0.029; hematoma volume: 11.6 ± 4.4 ml, 10.7 ± 4.1 ml, P < 0.001). There was no difference in admission APTT level between the two prognosis groups (28.4 ± 5.6 s, 27.8 ± 5.4 s, P = 0.056). A multivariate COX regression analysis reported that admission serum calcium level ≤ 2.41 mmol/l was associated with the increased risk of poor prognosis (death or major disability) in the patients (HR 1.45, 95% CI 1.32-1.60). In addition, there was a significant linear association of serum calcium level with coagulation function markers and hematoma volume on admission (APTT: r = - 0.091, P = 0.001; INR: r = - 0.063, P = 0.025; hematoma volume: r = -0.108, P < 0.001). CONCLUSIONS: Admission serum calcium level might be a prognostic marker for intracerebral hemorrhage. Potential mechanism involved calcium-induced coagulation function abnormality.

[Effect of GR24 on accumulation of diterpenoids in Tripterygium wilfordii suspension cells].

Terpenoids are main bioactive components in Tripterygium wilfordii,but the contents of some terpenoids are relatively low. In order to provide scientific evidence for the regulation of terpenoids in T. wilfordii,this research explored the effect of GR24 on accumulations of four diterpenoids( triptolide,tripterifordin,triptophenolide,and triptinin B) in T. wilfordii suspension cells by biological technology and UPLC-QQQ-MS/MS. The results indicated that 100 µmol·L-1 GR24 inhibited the accumulations of triptolide,tripterifordin,triptophenolide,and triptinin B to different degrees. Compared with the control group,the contents of 4 diterpenoids( in the induced group) were down to 96.59%,63.80%,61.02% and 33.59% in 240 h,respectively. Among them,the accumulation of triptinin B iswas significantly inhibited. In addition,the key time point of inhibitory effect was 120 h after induction with GR24 in some diterpenoids. This is the first systematic study focusing on the effect of GR24 on the accumulations of diterpenoids in T. wilfordii suspension cells. The dynamic accumulation ruleregularity of four diterpenoids after induced by GR24 was summarized,which laid a foundation for further study on the chemical response mechanism of terpenoids to GR24.

Diagnostic Significance of Serum Levels of Nerve Growth Factor and Brain Derived Neurotrophic Factor in Diabetic Peripheral Neuropathy.

BACKGROUND Our study aimed to explore the levels of nerve growth factor (NGF) and brain derived neurotrophic factor (BDNF) in healthy participants, type 2 diabetes mellitus (T2DM) patients, and diabetic peripheral neuropathy (DPN) patients in order to find their effects on DPN. MATERIAL AND METHODS The clinical data of 110 healthy participants (age: 57.3±8.2 year, height: 165.4±5.5 cm, weight: 64.1±7.5 kg), 83 T2DM patients (age: 56.5±7.9 year, height: 164.8±6.2 cm, and weight: 63.6±6.6 kg), and 65 DPN patients (age: 58.2±7.3 year, height: 166.7±6.7 cm, weight: 63.1±5.8 kg) were observed. ELISA was applied to detect serum NGF and BDNF levels. Receiver operating characteristic (ROC) curve analysis was performed to evaluate diagnostic value of serum NGF and BDNF levels in DPN. Logistic regression analysis was performed to analyze risk factors for DPN. RESULTS Serum NGF and BDNF levels decreased most in DPN patients. Subsequently, we determined that serum NGF and BDNF levels were correlated with: the course of disease for patients, fasting C-peptide (FCP), 2-hour postprandial C-peptide level (2-h PCP), glycosylated hemoglobin level (HbAlc), and 24-hour urinary microalbumin excretion (24-h UME). ROC curve analysis identified high sensitivity, specificity, and accuracy of NGF and BDNF levels on DPN. Serum levels of NGF and BDNF, course of disease, 2-h PCP level, and postprandial blood glucose level were determined to be risk factors for DPN. CONCLUSIONS Our study highlights that serum levels of NGF and BDNF might be associated with the occurrence and development of DPN.

Large cargo transport by nuclear pores: implications for the spatial organization of FG-nucleoporins.

Nuclear pore complexes (NPCs) mediate cargo traffic between the nucleus and the cytoplasm of eukaryotic cells. Nuclear transport receptors (NTRs) carry cargos through NPCs by transiently binding to phenylalanine-glycine (FG) repeats on intrinsically disordered polypeptides decorating the NPCs. Major impediments to understand the transport mechanism are the thousands of FG binding sites on each NPC, whose spatial distribution is unknown, and multiple binding sites per NTR, which leads to multivalent interactions. Using single molecule fluorescence microscopy, we show that multiple NTR molecules are required for efficient transport of a large cargo, while a single NTR promotes binding to the NPC but not transport. Particle trajectories and theoretical modelling reveal a crucial role for multivalent NTR interactions with the FG network and indicate a non-uniform FG repeat distribution. A quantitative model is developed wherein the cytoplasmic side of the pore is characterized by a low effective concentration of free FG repeats and a weak FG-NTR affinity, and the centrally located dense permeability barrier is overcome by multivalent interactions, which provide the affinity necessary to permeate the barrier.

[Molecular authentication of Jinyinhua formula granule by using allele-specific PCR].

Traditional authentication method is hard to identify herb's authenticity of traditional Chinese medicine(TCM) formula granules because they have lost all their morphological characteristics. In this study, a new allele-specific PCR method was established for identifying the authentication of Jinyinhua formula granule (made from Lonicerae Japonicae Flos) based on an SNP site in trnL-trnF fragment. Genomic DNA was successfully extracted from Lonicerae Japonicae Flos and its formula granules by using an improved spin column method and then PCR was performed with the designed primer. Approximately 110 bp specific bands was obtained only in the authentic Lonicerae Japonicae Flos and its formula granules, while no bands were found in fake mixed products. In addition, the PCR product sequence was proved from Lonicerae Japonicae Flos trnL-trnF sequence by using BLAST method. Therefore, DNA molecular authentication method could make up the limitations of character identification method and microscopic identification, and quickly identify herb's authenticity of TCM formula granules, with enormous potential for market supervision and quality control.

[Cloning and protein expression analysis of geranyl diphosphate synthase genes in Tripterygium wilfordii].

Based on the transcriptome data, the study cloned full-length cDNA of TwGPPS1 and TwGPPS2 genes from Tripterygium wilfordii suspension cells and then analyzed the bioinformation of the sequence and protein expression. The cloned TwGPPS1 has a 1 278 bp open reading frame (ORF) encoding a polypeptide of 425 amino acids. The deduced isoelectric point (pI) was 6.68, a calculated molecular weight was about 47.189 kDa. The full-length cDNA of the TwGPPS2 contains a 1 269 bp open reading frame (ORF) encoding a polypeptide of 422 amino acids. The deduced isoelectric point (pI) was 6.71, a calculated molecular weight was about 46.774 kDa.The entire reading frame of TwGPPS1,2 was cloned into the pET-32a(+) vector and expressed in E. coli BL21 (DE3) cells to obtain the TwGPPS protein, which laid a basis for further study on the regulation of terpenoid secondary metabolism and biological synthesis.

Design and discovery of Novel Thiazole acetamide derivatives as anticholinesterase agent for possible role in the management of Alzheimer's.

A novel series of thiazole acetamides was synthesized in excellent yields and characterized with the aid of various spectroscopic and elemental analysis. These compounds were evaluated for in vitro acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activities for possible benefit in Alzheimers disease (AD). Among the synthesized compound, 6d was identified as the most potent compound of AChE (IC50=3.14±0.16 µM) with a selectivity index (SI) of 2.94 against BuChE. These compounds were further tested for inhibition of Aß aggregation and ß-secretase, where it showed potent inhibition which confirmed its multifactorial benefits in AD. The toxicity and docking study were also carried out to exemplify the pharmacological profile of compound 6d as prospective lead molecule against AD.

Protective efficacy of recombinant canine adenovirus type-2 expressing TgROP18 (CAV-2-ROP18) against acute and chronic Toxoplasma gondii infection in mice.

BACKGROUND: The use of recombinant viral vectors expressing T. gondii antigens is a safe and efficient approach to induce immune responses against the parasite, as well as a valuable tool for vaccine development. We have previously prolonged the survival time of mice challenged with the RH strain of T. gondii by immunizing the mice with a eukaryotic vector expressing the protein ROP18 of T. gondii. We are now looking for ways to improve this vaccination strategy and enhance protection. METHODS: In this study, we constructed and characterized a novel recombinant canine adenovirus type 2 expressing ROP18 (CAV-2-ROP18) of T. gondii by cytopathic effect (CPE) and indirect immunofluorescence assay (IFA) following transfection into MDCK cells. Intramuscular immunization of Kunming mice with CAV-2-ROP18 was carried out to evaluate humoral and cellular immune responses. RESULTS: The vaccination of experimental mice with CAV-2-ROP18 elicited antibody production against ROP18, including high levels of a mixed IgG1/IgG2a and significant production of IFN-γ or IL-2, and displayed a significant bias towards a helper T cell type 1 (Th1) profile. Furthermore, the presence of T. gondii-specific IFN-γ-production and TNF-α-production T cells was elicited in both CD4+ and CD8+ T cell compartments. Significantly higher survival rates (40%) occurred in the experimental group, and a reduction in brain cyst burden was detected in vaccinated mice. CONCLUSION: These results demonstrate the potential use of a CAV vector harboring the ROP18 gene in the development of a vaccine against acute and chronic toxoplasmosis.

Syndrome Differentiation Analysis on Mars500 Data of Traditional Chinese Medicine.

Mars500 study was a psychological and physiological isolation experiment conducted by Russia, the European Space Agency, and China, in preparation for an unspecified future manned spaceflight to the planet Mars. Its intention was to yield valuable psychological and medical data on the effects of the planned long-term deep space mission. In this paper, we present data mining methods to mine medical data collected from the crew consisting of six spaceman volunteers. The synthesis of the four diagnostic methods of TCM, inspection, listening, inquiry, and palpation, is used in our syndrome differentiation. We adopt statistics method to describe the syndrome factor regular pattern of spaceman volunteers. Hybrid optimization based multilabel (HOML) is used as feature selection method and multilabel k-nearest neighbors (ML-KNN) is applied. According to the syndrome factor statistical result, we find that qi deficiency is a base syndrome pattern throughout the entire experiment process and, at the same time, there are different associated syndromes such as liver depression, spleen deficiency, dampness stagnancy, and yin deficiency, due to differences of individual situation. With feature selection, we screen out ten key factors which are essential to syndrome differentiation in TCM. The average precision of multilabel classification model reaches 80%.