Antibiotic Resistance and Molecular Epidemiological Characteristics of Streptococcus agalactiae Isolated from Pregnant Women in Guangzhou, South China.

Streptococcus agalactiae colonization in pregnant women can cause postpartum intrauterine infections and life-threatening neonatal infections. To formulate strategies for the prevention and treatment of S. agalactiae infections, we performed a comprehensive analysis of antibiotic resistance and a molecular-based epidemiological investigation of S. agalactiae in this study. Seventy-two S. agalactiae strains, collected from pregnant women, were subjected to antibiotic susceptibility tests; then, the screened erythromycin and clindamycin nonsusceptible isolates were used for macrolides and clindamycin resistance genes detection, respectively. Detection of resistance genes, serotyping, and determination of virulence genes were performed by polymerase chain reaction. The clonal relationships among the colonized strains were evaluated by multilocus sequence typing. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) mass peak analysis was performed to discriminate the specific sequence types (STs). In our study, 69.4% and 47.2% of the strains were nonsusceptible to erythromycin and clindamycin, respectively; the multidrug resistance rate was 66.7%. All erythromycin nonsusceptible strains harbored resistance genes, whereas only 52.9% of the clindamycin nonsusceptible strains possessed the linB gene. Erythromycin resistance was mainly mediated by the ermB or mefA/E genes. Four serotypes were identified, and the most common serotype was serotype III (52.8%), followed by Ib (22.2%), Ia (18.0%), and II (4.2%). All the strains were divided into 18 STs that were assigned to nine clonal complexes. Most of the major STs were distributed into specific serotypes, including ST19/serotype III, ST17/serotype III, ST485/serotype Ia, ST862/serotype III, and ST651/serotype III. Analysis of virulence genes yielded seven clusters, of which bca-cfb-scpB-lmb (61.6%) was the predominant virulence gene cluster. Among all ST strains distributed in this region, only the ST17 strains had a mass peak at 7620 Da. The outcomes of this study are beneficial for the epidemiological comparison of colonized S. agalactiae in different regions and may be helpful for developing the strategies for the prevention of S. agalactiae infection in Guangzhou. Furthermore, our results show that MALDI-TOF MS can be used for the rapid identification of the ST17 strains.

DiffRecon: Diffusion-based CT reconstruction with cross-modal deformable fusion for DR-guided non-coplanar radiotherapy.

In non-coplanar radiotherapy, DR is commonly used for image guiding which needs to fuse intraoperative DR with preoperative CT. But this fusion task performs poorly, suffering from unaligned and dimensional differences between DR and CT. CT reconstruction estimated from DR could facilitate this challenge. Thus, We propose a unified generation and registration framework, named DiffRecon, for intraoperative CT reconstruction based on DR using the diffusion model. Specifically, we use the generation model for synthesizing intraoperative CTs to eliminate dimensional differences and the registration model for aligning synthetic CTs to improve reconstruction. To ensure clinical usability, CT is not only estimated from DR but the preoperative CT is also introduced as prior. We design a dual-encoder to learn prior knowledge and spatial deformation among pre- and intra-operative CT pairs and DR parallelly for 2D/3D feature deformable conversion. To calibrate the cross-modal fusion, we insert cross-attention modules to enhance the 2D/3D feature interaction between dual encoders. DiffRecon has been evaluated by both image quality metrics and dosimetric indicators. The high image synthesis metrics are with RMSE of 0.02±0.01, PSNR of 44.92±3.26, and SSIM of 0.994±0.003. The mean gamma passing rates between rCT and sCT for 1%/1 mm, 2%/2 mm and 3%/3 mm acceptance criteria are 95.2%, 99.4% and 99.9% respectively. The proposed DiffRecon can reconstruct CT accurately from a single DR projection with excellent image generation quality and dosimetric accuracy. These demonstrate that the method can be applied in non-coplanar adaptive radiotherapy workflows.

Uncertainty estimation- and attention-based semi-supervised models for automatically delineate clinical target volume in CBCT images of breast cancer.

OBJECTIVES: Accurate segmentation of the clinical target volume (CTV) of CBCT images can observe the changes of CTV during patients' radiotherapy, and lay a foundation for the subsequent implementation of adaptive radiotherapy (ART). However, segmentation is challenging due to the poor quality of CBCT images and difficulty in obtaining target volumes. An uncertainty estimation- and attention-based semi-supervised model called residual convolutional block attention-uncertainty aware mean teacher (RCBA-UAMT) was proposed to delineate the CTV in cone-beam computed tomography (CBCT) images of breast cancer automatically. METHODS: A total of 60 patients who undergone radiotherapy after breast-conserving surgery were enrolled in this study, which involved 60 planning CTs and 380 CBCTs. RCBA-UAMT was proposed by integrating residual and attention modules in the backbone network 3D UNet. The attention module can adjust channel and spatial weights of the extracted image features. The proposed design can train the model and segment CBCT images with a small amount of labeled data (5%, 10%, and 20%) and a large amount of unlabeled data. Four types of evaluation metrics, namely, dice similarity coefficient (DSC), Jaccard, average surface distance (ASD), and 95% Hausdorff distance (95HD), are used to assess the model segmentation performance quantitatively. RESULTS: The proposed method achieved average DSC, Jaccard, 95HD, and ASD of 82%, 70%, 8.93, and 1.49 mm for CTV delineation on CBCT images of breast cancer, respectively. Compared with the three classical methods of mean teacher, uncertainty-aware mean-teacher and uncertainty rectified pyramid consistency, DSC and Jaccard increased by 7.89-9.33% and 14.75-16.67%, respectively, while 95HD and ASD decreased by 33.16-67.81% and 36.05-75.57%, respectively. The comparative experiment results of the labeled data with different proportions (5%, 10% and 20%) showed significant differences in the DSC, Jaccard, and 95HD evaluation indexes in the labeled data with 5% versus 10% and 5% versus 20%. Moreover, no significant differences were observed in the labeled data with 10% versus 20% among all evaluation indexes. Therefore, we can use only 10% labeled data to achieve the experimental objective. CONCLUSIONS: Using the proposed RCBA-UAMT, the CTV of breast cancer CBCT images can be delineated reliably with a small amount of labeled data. These delineated images can be used to observe the changes in CTV and lay the foundation for the follow-up implementation of ART.

A 4D-CBCT correction network based on contrastive learning for dose calculation in lung cancer.

OBJECTIVE: This study aimed to present a deep-learning network called contrastive learning-based cycle generative adversarial networks (CLCGAN) to mitigate streak artifacts and correct the CT value in four-dimensional cone beam computed tomography (4D-CBCT) for dose calculation in lung cancer patients. METHODS: 4D-CBCT and 4D computed tomography (CT) of 20 patients with locally advanced non-small cell lung cancer were used to paired train the deep-learning model. The lung tumors were located in the right upper lobe, right lower lobe, left upper lobe, and left lower lobe, or in the mediastinum. Additionally, five patients to create 4D synthetic computed tomography (sCT) for test. Using the 4D-CT as the ground truth, the quality of the 4D-sCT images was evaluated by quantitative and qualitative assessment methods. The correction of CT values was evaluated holistically and locally. To further validate the accuracy of the dose calculations, we compared the dose distributions and calculations of 4D-CBCT and 4D-sCT with those of 4D-CT. RESULTS: The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) of the 4D-sCT increased from 87% and 22.31 dB to 98% and 29.15 dB, respectively. Compared with cycle consistent generative adversarial networks, CLCGAN enhanced SSIM and PSNR by 1.1% (p < 0.01) and 0.42% (p < 0.01). Furthermore, CLCGAN significantly decreased the absolute mean differences of CT value in lungs, bones, and soft tissues. The dose calculation results revealed a significant improvement in 4D-sCT compared to 4D-CBCT. CLCGAN was the most accurate in dose calculations for left lung (V5Gy), right lung (V5Gy), right lung (V20Gy), PTV (D98%), and spinal cord (D2%), with the relative dose difference were reduced by 6.84%, 3.84%, 1.46%, 0.86%, 3.32% compared to 4D-CBCT. CONCLUSIONS: Based on the satisfactory results obtained in terms of image quality, CT value measurement, it can be concluded that CLCGAN-based corrected 4D-CBCT can be utilized for dose calculation in lung cancer.

Development and validation of two redox-related genes associated with prognosis and immune microenvironment in endometrial carcinoma.

In recent studies, the tumourigenesis and development of endometrial carcinoma (EC) have been correlated significantly with redox. We aimed to develop and validate a redox-related prognostic model of patients with EC to predict the prognosis and the efficacy of immunotherapy. We downloaded gene expression profiles and clinical information of patients with EC from the Cancer Genome Atlas (TCGA) and the Gene Ontology (GO) dataset. We identified two key differentially expressed redox genes (CYBA and SMPD3) by univariate Cox regression and utilised them to calculate the risk score of all samples. Based on the median of risk scores, we composed low-and high-risk groups and performed correlation analysis with immune cell infiltration and immune checkpoints. Finally, we constructed a nomogram of the prognostic model based on clinical factors and the risk score. We verified the predictive performance using receiver operating characteristic (ROC) and calibration curves. CYBA and SMPD3 were significantly related to the prognosis of patients with EC and used to construct a risk model. There were significant differences in survival, immune cell infiltration and immune checkpoints between the low-and high-risk groups. The nomogram developed with clinical indicators and the risk scores was effective in predicting the prognosis of patients with EC. In this study, a prognostic model constructed based on two redox-related genes (CYBA and SMPD3) were proved to be independent prognostic factors of EC and associated with tumour immune microenvironment. The redox signature genes have the potential to predict the prognosis and the immunotherapy efficacy of patients with EC.

The Activated AMPK/mTORC2 Signaling Pathway Associated with Oxidative Stress in Seminal Plasma Contributes to Idiopathic Asthenozoospermia.

Asthenozoospermia is a common form of abnormal sperm quality in idiopathic male infertility. While most sperm-mediated causes have been investigated in detail, the significance of seminal plasma has been neglected. Herein, we aimed to investigate the possible pathogenic factors leading to decreased sperm motility based on seminal plasma. Semen was collected from normo- (NOR, n = 70), idiopathic oligo- (OLI, n = 57), and idiopathic asthenozoospermic (AST, n = 53) patients. Using attenuated total reflection-Fourier transform infrared coupled with chemometrics, distinct differences in the biochemical compositions of nucleic acids, protein structure (amides I, II, and III), lipids, and carbohydrates in seminal plasma of AST were observed when compared to NOR and OLI. Compared with NOR and OLI, the levels of peptide aggregation, protein phosphorylation, unsaturated fatty acid, and lipid to protein ratio were significantly increased in AST; however, the level of lipid saturation was significantly decreased in seminal plasma of AST. Compared with NOR, the levels of ROS, MDA, 8-iso-prostaglandin F2α (8-isoPGF2α), and the ratio of phospho-AMPKα/AMPKα1 were significantly increased in AST; however, the levels of SOD, glutathione S-transferase (GSTs), protein carbonyl derivative (PC), and the ratio of phospho-Rictor/Rictor were significantly decreased in seminal plasma of AST. Changes of the AMPK/mTORC2 signaling in the seminal microenvironment possibly induce abnormal glucose and lipid metabolism, which impairs energy production. Oxidative stress potentially damages seminal plasma lipids and proteins, which in turn leads to impaired sperm structure and function. These findings provide evidence that the changes in seminal plasma compositions, oxidative stress, and activation of the AMPK/mTORC2 signaling contribute to the development of asthenozoospermia.

An enzyme-activatable dual-readout probe for sensitive ß-galactosidase sensing and Escherichia coli analysis.

Rapid and accurate sensing of ß-galactosidase (ß-gal) activity is particularly critical for the early detection of many diseases and has become a topic of interest in recent years. However, most traditional probes for ß-gal sensing often suffer from the disadvantages of narrow dynamic range, low reaction efficiency and are only employed with either colorimetric or fluorescence sensing. Furthermore, ß-galactosidase sensing based assay for efficient detection and antibiotic resistance analysis of Escherichia coli (E.coli) is not available. Here, an enzyme-induced probe assay was reported for dual sensitive fluorescence and colorimetric measurement of ß-gal activity, and was further employed for detection of Escherichia coli and their antibiotic resistance analysis. The DCM-ßgal probe was virtually non-emissive in aqueous solution, while it could be activated by ß-gal to produce bright emission. Under optimized conditions, DCM-ßgal displayed high sensitivity, selectivity and rapid response to ß-gal with a low detection limit of 1.5 × 10-3 U ml-1. Importantly, this assay was successfully applied to sensitive detection of E. coli cells with a fast detection process within 5 h and a low detection concentration of 1 × 103 CFU ml-1. Furthermore, the enzyme-activatable assay was also successfully applied for high throughput E. coli antibiotic resistance analysis. The DCM-ßgal strategy is applied for the first time on the detection of E. coli cells and their antibiotic resistance analysis. It is provided with the advantages of high selectively, a simple operation, low cost and rapid detection. The detection platform can also be extended to analyze the level of ß-gal in other types of cells or biological samples. Overall, the simple, effective and dual-readout assay holds promise for efficient sensing of ß-gal activity and provides a potential tool for E. coli detection and their antibiotic resistance analysis.

Association between tea consumption and semen quality among 1385 healthy Chinese men.

Information on the association between tea drinking and semen quality is limited. Little is reported on whether tea drinking is benefit to sperm quality. This cross-sectional and longitudinal study was conducted between April 2017 and July 2018. Participants were healthy men who were screened as potential sperm donors recruited at the Hubei Province Human Sperm Bank of China. A structured questionnaires containing sociodemographic information, daily habits, sperm collection-related information was completed for each participant at interview. Repeated semen samples were taken to examine the sperm parameters, including sperm volume, sperm concentration, sperm count, progressive motility, and total motility. A total of 1385 men with 6466 sperm samples were included in this study. Two groups were compared: tea drinking men (389, 28.1%) and non-tea drinking men (996, 71.9%). Compared with subjects who never drink tea, the analyses showed that sperm concentration and total sperm count were higher in tea-consuming subjects. A 10-year period or more duration of tea drinking significantly increased semen concentrations by 16.27% (P < 0.05). Sperm concentration was increased in subjects with a frequency of tea drinking of 3 days or more per week (P < 0.05) or, among men who were occasional alcohol drinkers, when tea concentration was weak (P < 0.05). No evidence of trend effects (P for trend > 0.05) or interaction effects (P for interaction > 0.05) between tea consumption and sperm quality, respectively. Our findings provide evidence that tea drinking may improve male reproductive health. Long-term, frequent, weak tea drinking tends to increase sperm quality among men with low BMI or health-related behaviors like smoking or alcohol intake.

Rapid and high-throughput testing of antifungal susceptibility using an AIEgen-based analytical system.

The increasing resistance among fungi to antimicrobials are posing global threats to health. Early treatment with appropriate antifungal drugs guided by the antifungal susceptibility testing (AFST) can dramatically reduce the mortality of severe fungal infections. However, the long test time (24-48 h) of the standard AFSTs cannot provide timely results due to the slow growth of the pathogen. Herein, we report a new AFST that is independent of growth rate analysis using a luminogen with aggregation-induced emission characteristics (AIEgen) named DMASP. DMASP is a water-soluble small-molecule probe that can readily penetrate the dense fungal cell wall. Based on its mitochondria-targeting ability and AIE characteristics, fungal activity can be dynamically indicated via real-time fluorescence monitoring. This allows fungal susceptibility to various antimicrobials to be assessed within 12 h in a wash-free, one-step manner. This method may serve as a promising tool to rapidly detect possible drug-resistant fungal strain and guide the precise use of antimicrobial against fungal diseases.

Point-of-Care Urinalysis with One Drop of Sample Using an Aggregation-Induced Emission Luminogen under the Coffee-Ring Effect.

Development of a practical point-of-care test for urinalysis is crucial for early diagnosis and treatment of chronic kidney disease (CKD). However, the classical gold standard detection method depends on sophisticated instruments and complicated procedures, impeding them from being utilized in resource-limited settings and daily screening. Herein, we report a rapid point-of-care device for the simultaneous quantification of microalbuminuria and leukocyte using one drop of urine. A luminogen (TTVP) with an aggregation-induced emission property can selectively activate its near-infrared fluorescence in the presence of albumin and leukocyte via hydrophobic or electrostatic interactions. The fluorescence signals from urine albumin and leukocyte could be well-separated combined with the coffee-ring effect. Using a smartphone-based detection device, simultaneous quantification of urine albumin and leukocyte was successfully achieved, which only took 20 min and required one drop of urine. The performance of this system is also verified with 120 clinical samples, which might serve as a simple, low-cost, and rapid tool for CKD screening and disease monitoring at the point of care.

[Effects of simulated acid rain on soil N2O emission from typical forest in subtropical sou-thern China.] / æ¨¡æ‹Ÿé ¸é›¨å¯¹å—äºšçƒ­å¸¦å ¸åž‹æ£®æž—åœŸå£¤N2O排放的影响.

Based on a long-term simulated acid rain experiment, soil N2O emission fluxes were measured using static chambers and the gas chromatography method in a coniferous and broadleaved mixed forest and a monsoon evergreen broadleaved forest in southern China. During the five-year observation periods (2014-2018), soil N2O emission fluxes in the two forests showed obvious seasonal variation. The soil N2O emission fluxes in wet season were significantly higher than that in dry season, with a large annual variation. Due to the decreases of precipitation, soil N2O emission fluxes of the two forests in 2017 and 2018 were generally low. Soil N2O emission flux was positively correlated with soil temperature and soil moisture. In the monsoon evergreen broadleaved forest, soil N2O emission flux in the control plot was 12.6 µg N2O·m-2·h-1. Soil N2O emission fluxes under the pH 3.5 and pH 3.0 treatments increased by 42.9% and 61.1%, respectively. Soil N2O emission was significantly increased under simulated acid rain in the monsoon evergreen broadleaved forest. Acid rain promoted soil N2O emission in the coniferous and broadleaved mixed forest, but without significant difference among the treatments. Under the scenario of increasing acid rain, soil N2O emission fluxes in typical subtropical southern China forests would increase, and the magnitude of such increase was different among forest types.

A systematical rheological study of polysaccharide from Sophora alopecuroides L. seeds.

The rheological properties of polysaccharide (SAP) from Sophora alopecuroides L. seeds were systematically investigated by fitting different models. The steady flow testing indicated that SAP exhibited shear-thinning behaviors, which were enhanced with increasing concentration and decreasing temperature. This was demonstrated quantitatively by Williamson and Arrhenius models. According to the generalized Morris equation, SAP exhibited random coil conformation with the potential to form weak gel-like network. On the other hand, multiple results of dynamic tests confirmed the viscoelastic properties of SAP, showing oscillatory behaviors between a dilute solution and an elastic gel. Furthermore, SAP solutions were thermorheologically stable without remarkable energetic interactions or structural heterogeneity, since their rheological patterns were successfully applied to Time-temperature superposition (TTS) principle, modified Cole-Cole analysis and Cox-Merz rule.

PEDOT:PSS/graphene quantum dots films with enhanced thermoelectric properties via strong interfacial interaction and phase separation.

The typical conductive polymer of PEDOT:PSS has recently attracted intensive attention in thermoelectric conversion because of its low cost and low thermal conductivity as well as high electrical conductivity. However, compared to inorganic counterparts, the relatively poor thermoelectric performance of PEDOT:PSS has greatly limited its development and high-tech applications. Here, we report a dramatic enhancement in the thermoelectric performance of PEDOT:PSS by constructing unique composite films with graphene quantum dots (GQDs). At room temperature, the electrical conductivity and Seebeck coefficient of PEDOT:PSS/GQDs reached to 7172 S/m and 14.6 µV/K, respectively, which are 30.99% and 113.2% higher than those of pristine PEDOT:PSS. As a result, the power factor of the optimized PEDOT:PSS/GQDs composite is 550% higher than that of pristine PEDOT:PSS. These significant improvements are attributed to the ordered alignment of PEDOT chains on the surface of GQDs, originated from the strong interfacial interaction between PEDOT:PSS and GQDs and the separation of PEDOT and PSS phases. This study evidently provides a promising route for PEDOT:PSS applied in high-efficiency thermoelectric conversion.

Tumor localization using diffuse optical tomography and linearly constrained minimum variance beamforming.

We present a tumor localization method for diffuse optical tomography using linearly constrained minimum variance (LCMV) beamforming. Beamforming is a spatial filtering technique where signals from certain directions can be enhanced while noise and interference from other directions are suppressed. In our method, we tessellate the domain into small voxels and regard each voxel as a possible position of abnormality (e.g., tumor).We then design a spatial filter based on the linearly constrained minimum variance criterion and apply it to each voxel in the domain. The abnormality is localized by observing the peak in the filter output signals. We test our method using simulated 3D examples. We assume a cubic transmission geometry and consider different cases where the abnormality is an absorber, a scatterer, and both. We also give examples showing the resolution of our method and its performance under different perturbation levels and noise levels. Simulation results show that LCMV beamforming can localize the abnormality well with good computational efficiency. It can be used alone for tumor localization and also as an effective preprocessing tool for improving the image reconstruction performances of other inverse methods.

Image reconstruction for diffuse optical tomography using sparsity regularization and expectation-maximization algorithm.

We present an image reconstruction method for diffuse optical tomography (DOT) by using the sparsity regularization and expectation-maximization (EM) algorithm. Typical image reconstruction approaches in DOT employ Tikhonov-type regularization, which imposes restrictions on the L(2) norm of the optical properties (absorption/scattering coefficients). It tends to cause a blurring effect in the reconstructed image and works best when the unknown parameters follow a Gaussian distribution. In reality, the abnormality is often localized in space. Therefore, the vector corresponding to the change of the optical properties compared with the background would be sparse with only a few elements being nonzero. To incorporate this information and improve the performance, we propose an image reconstruction method by regularizing the L(1) norm of the unknown parameters and solve it iteratively using the expectation-maximization algorithm. We verify our method using simulated 3D examples and compare the reconstruction performance of our approach with the level-set algorithm, Tikhonov regularization, and simultaneous iterative reconstruction technique (SIRT). Numerical results show that our method provides better resolution than the Tikhonov-type regularization and is also efficient in estimating two closely spaced abnormalities.

Identification of key microRNAs and genes in preeclampsia by bioinformatics analysis.

Preeclampsia is a leading cause of perinatal maternal-foetal mortality and morbidity. The aim of this study is to identify the key microRNAs and genes in preeclampsia and uncover their potential functions. We downloaded the miRNA expression profile of GSE84260 and the gene expression profile of GSE73374 from the Gene Expression Omnibus database. Differentially expressed miRNAs and genes were identified and compared to miRNA-target information from MiRWalk 2.0, and a total of 65 differentially expressed miRNAs (DEMIs), including 32 up-regulated miRNAs and 33 down-regulated miRNAs, and 91 differentially expressed genes (DEGs), including 83 up-regulated genes and 8 down-regulated genes, were identified. The pathway enrichment analyses of the DEMIs showed that the up-regulated DEMIs were enriched in the Hippo signalling pathway and MAPK signalling pathway, and the down-regulated DEMIs were enriched in HTLV-I infection and miRNAs in cancers. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses of the DEGs were performed using Multifaceted Analysis Tool for Human Transcriptome. The up-regulated DEGs were enriched in biological processes (BPs), including the response to cAMP, response to hydrogen peroxide and cell-cell adhesion mediated by integrin; no enrichment of down-regulated DEGs was identified. KEGG analysis showed that the up-regulated DEGs were enriched in the Hippo signalling pathway and pathways in cancer. A PPI network of the DEGs was constructed by using Cytoscape software, and FOS, STAT1, MMP14, ITGB1, VCAN, DUSP1, LDHA, MCL1, MET, and ZFP36 were identified as the hub genes. The current study illustrates a characteristic microRNA profile and gene profile in preeclampsia, which may contribute to the interpretation of the progression of preeclampsia and provide novel biomarkers and therapeutic targets for preeclampsia.

Estimating parametric line-source models with electroencephalography.

We develop three parametric models for electroencephalography (EEG) to estimate current sources that are spatially distributed on a line. We assume a realistic head model and solve the EEG forward problem using the boundary element method (BEM). We present the models with increasing degrees of freedom, provide the forward solutions, and derive the maximum-likelihood estimates as well as Cramér-Rao bounds of the unknown source parameters. A series of experiments are conducted to evaluate the applicability of the proposed models. We use numerical examples to demonstrate the usefulness of our line-source models in estimating extended sources. We also apply our models to the real EEG data of N20 response that is known to have an extended source. We observe that the line-source models explain the N20 measurements better than the dipole model.

Parametric surface-source modeling and estimation with electroencephalography.

Electroencephalography (EEG) is an important tool for studying the brain functions and is becoming popular in clinical practice. In this paper, we develop four parametric EEG models to estimate current sources that are spatially distributed on a surface. Our models approximate the source shape and extent explicitly and can be applied to localize extended sources which are often encountered, e.g., in epilepsy diagnosis. We assume a realistic head model and solve the EEG forward problem using the boundary element method. We present the source models with increasing degrees of freedom, provide the forward solutions, and derive the maximum-likelihood estimates as well as Cramér-Rao bounds of the unknown source parameters. In order to evaluate the applicability of the proposed models, we first compare their estimation performances with the dipole model's using several known source distributions. We then discuss the conditions under which we can distinguish between the proposed extended sources and the focal dipole using the generalized likelihood ratio test. We also apply our models to the electric measurements obtained from a phantom body in which an extended electric source is imbedded. We observe that the proposed model can capture the source extent information satisfactorily and the localization accuracy is better than the dipole model.

Optimized extraction and molecular characterization of polysaccharides from Sophora alopecuroides L. seeds.

Optimized extraction of crude polysaccharides from Sophora alopecuroides L. seeds (CSAP) was firstly investigated, and the results were extraction time 4.15 h, extraction temperature 70.68°C and water/seed ratio 50.99:1 ml/g. At this proximal point, highest yield (10.88%) and relative viscosity (1.2952) were obtained for CSAP, which contained 78.40% sugar, 6.08% protein, 9.71% ash, 7.16% moisture and 1.88% uronic acid. Neutral fractions of F15, F25, F35 and F60 were further obtained via stepwise alcohol precipitation. Results of monosaccharide composition indicated that CSAP and its neutral fractions mainly consisted of mannose and galactose (79.45-97.52%) with M/G ratios of 0.94-1.48, typical for galactomannans, which were demonstrated by FT-IR. Weight-average molecular weight, radius of gyration and hydrodynamic radius were in the same order (F15>F25>F35>F60), whereas the highest intrinsic viscosity was observed for F25. Multiple analyses, including Mark-Houwink-Sakurada exponent (0.48-0.80), persistence length (1.45-3.93 nm), conformation zoning (random coil) and power-law exponent (b>1), showed flexible coils for all neutral fractions. Concerning viscometry, there were no aggregates (K″ 0.60) or coil overlaps ("master curve") of F25 in dilute solutions. Relatively weak surface activity of F25 was probably related to its particular chemical structure and proteinaceous moieties closely conjoined.

Physicochemical properties and structural characterization of a galactomannan from Sophora alopecuroides L. seeds.

A water-soluble neutral polysaccharide (F25) was fractionated from crude polysaccharides of Sophora alopecuroides L. seeds. Its physicochemical properties and structural characterization were investigated. The I2-KI and Congo red reactions showed F25 possessed many branches without triple-helical conformation, which coincided with methylation and NMR analyses, i.e., F25 was a galactomannan with 1,4-linked ß-d-Manp backbone distributed randomly (M/G 1.48-1.84) by major T-α-d-Galp (86.82%) or minor 1,4-linked α-d-Galp (13.18%) at O-6. Compared with [η] of deionized water (2.98dL/g), it was indicated that NaCl (2.89-2.90dL/g) and NaOH (2.27-2.28dL/g) could affect intrinsic interactions and conformation of F25 in solution, leading to molecular non-entanglements and intramolecular associations. This was demonstrated by 3D molecular modeling. Furthermore, the amorphous nature of F25 was revealed with higher crystallinity (25.7%) and crystallite size (7.6nm) compared to other polysaccharides. In this study, the possible relationships between molecular structure and physicochemical properties were obtained for F25, which could be potentially applied in food and pharmaceutical industries.