A critical review of improving mainstream anammox systems: Based on macroscopic process regulation and microscopic enhancement mechanisms.

Full-scale anaerobic ammonium oxidation (anammox) engineering applications are vastly limited by the sensitivity of anammox bacteria to the complex mainstream ambience factors. Therefore, it is of great necessity to comprehensively summarize and overcome performance-related challenges in mainstream anammox process at the macro/micro level, including the macroscopic process variable regulation and microscopic biological metabolic enhancement. This article systematically reviewed the recent important advances in the enrichment and retention of anammox bacteria and main factors affecting metabolic regulation under mainstream conditions, and proposed key strategies for the related performance optimization. The characteristics and behavior mechanism of anammox consortia in response to mainstream environment were then discussed in details, and we revealed that the synergistic nitrogen metabolism of multi-functional bacterial genera based on anammox microbiome was conducive to mainstream anammox nitrogen removal processes. Finally, the critical outcomes of anammox extracellular electron transfer (EET) at the micro level were well presented, carbon-based conductive materials or exogenous electron shuttles can stimulate and mediate anammox EET in mainstream environments to optimize system performance from a micro perspective. Overall, this review advances the extensive implementation of mainstream anammox practice in future as well as shedding new light on the related EET and microbial mechanisms.

Application of a nomogram to radiomics labels in the treatment prediction scheme for lumbar disc herniation.

OBJECTIVE: To investigate and verify the efficiency and effectiveness of a nomogram based on radiomics labels in predicting the treatment of lumbar disc herniation (LDH). METHODS: By reviewing medical records that were analysed over the past three years, clinical and imaging data of 200 lumbar disc patients at the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine were obtained. The collected cases were randomly divided into a training group (n = 140) and a testing group (n = 60) at a ratio of 7:3. Two radiologists with experience in reading orthopaedics images independently segmented the ROIs. The whole intervertebral disc with the most obvious protrusion in the sagittal plane T2WI lumbar MRI as a mask (ROI) is sketched. The LASSO (Least Absolute Shrinkage And Selection Operator) algorithm was used to filter the features after extracting the radiomics features. The multivariate logistic regression model was used to construct a quantitative imaging Rad­Score for the selected features with nonzero coefficients. The radiomics labels and nomogram were evaluated using the receiver operating characteristic curve (ROC) and the area under the curve (AUC). The calibration curve was used to evaluate the consistency between the nomogram prediction and the actual treatment plan. The DCA decision curve was used to evaluate the clinical applicability of the nomogram. RESULT: Following feature extraction, 11 radiomics features were used to construct the radiomics label for predicting the treatment plan of LDH. A nomogram was then constructed. The AUC was 0.93 (95% CI: 0.90-0.97), with a sensitivity of 89%, a specificity of 91%, a positive predictive value of 92.7%, a negative predictive value of 89.4%, and an accuracy of 91%. The calibration curve showed that there was good consistency between the prediction and the actual observation. The DCA decision curve analysis showed that the nomogram of the imaging group has great potential for clinical application when the risk threshold is between 5 and 72%. CONCLUSION: A nomogram based on radiomics labels has good predictive value for the treatment of LDH and can be used as a reference for clinical decision-making.

Dynamic Behavior Analysis and Stability Control of Tethered Satellite Formation Deployment.

In recent years, Tethered Space Systems (TSSs) have received significant attention in aerospace research as a result of their significant advantages: dexterousness, long life cycles and fuel-less engines. However, configurational conversion processes of tethered satellite formation systems in a complex space environment are essentially unstable. Due to their structural peculiarities and the special environment in outer space, TSS vibrations are easily produced. These types of vibrations are extremely harmful to spacecraft. Hence, the nonlinear dynamic behavior of systems based on a simplified rigid-rod tether model is analyzed in this paper. Two stability control laws for tether release rate and tether tension are proposed in order to control tether length variation. In addition, periodic stability of time-varying control systems after deployment is analyzed by using Floquet theory, and small parameter domains of systems in asymptotically stable states are obtained. Numerical simulations show that proposed tether tension controls can suppress in-plane and out-of-plane librations of rigid tethered satellites, while spacecraft and tether stability control goals can be achieved. Most importantly, this paper provides tether release rate and tether tension control laws for suppressing wide-ranging TSS vibrations that are valuable for improving TSS attitude control accuracy and performance, specifically for TSSs that are operating in low-eccentricity orbits.

Prediction of histologic grade of hepatocellular carcinoma using dual-layer spectral-detector computed tomography (CT): comparison of two region of interest plotting methods.

Background: Multi-parameter imaging technology, which is based on substance separation, helps to predict the pathological grade of tumors. When using dual-layer spectral-detector computed tomography (DLCT) to quantify tumor properties, different methods of placing regions of interest (ROIs) directly impact the measurement of parameters, thus affecting the clinical diagnosis of lesions. Consequently, in this study, we aimed to compare the performance of 2 different ROI plotting methods on DLCT in differentiating the histologic grade of hepatocellular carcinoma (HCC). Methods: This retrospective study included 48 consecutive patients with pathologically confirmed HCC, who underwent DLCT from May 2022 to March 2023. The attenuation value of conventional computed tomography (CT), electron density relative to water (EDW), normalized effective atomic number (NZeff), and normalized iodine density (NID) were measured by 2 radiologists using the conventional planar sketching (PS) method and the volumetric analysis method, respectively. The differences in parameters between the arterial phase (AP) and venous phase (VP) were calculated for each parameter (∆CT, ∆EDW, ∆NZeff, ∆NID). We used 2-sample t-test or Mann-Whitney U test was used to compare the differences in parameters between the 2 methods. Spearman correlation analysis was used to determine the correlation between each parameter and histologic grade. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance. Results: The mean values for the spectral quantitative parameters (CTAP, NZeffAP, NIDAP) and the difference between the arterial phase and venous phase (AP-VP) of parameters (∆CT, ∆EDW, ∆NZeff) measured using the volumetric analysis method were significantly lower than those of the PS method (P<0.05). For the ∆NZeff, the volumetric analysis method achieved the highest area under the curve (AUC) with a value of 0.918 [95% confidence interval (CI): 0.847-0.988], followed by the PS method (AUC =0.853, 95% CI: 0.743-0.963). Conclusions: The spectral parameters of DLCT provide a novel quantitative method for evaluating histological differentiation in patients with HCC, which is worthy of clinical recommendation. Different ROI plotting methods significantly impact the measurement of spectral parameters. Therefore, the whole tumor region should be covered in the parameter measurement of HCC lesions as much as feasible, which is more helpful in predicting the histological grading of tumors before treatment.

Highly efficient and robust treatment of low C/N actual domestic sewage via integrated fermentation, partial-nitrification, partial-denitrification and anammox (IFPNDA).

For achieving efficient and robust treatment of domestic sewage with C/N around 2.8, this study innovatively developed an integrated fermentation, partial-nitrification, partial-denitrification and anammox (IFPNDA) process based on the Anaerobic Baffled Reactor and Continuous-flow Stirred Tank Reactor (ABR-CSTR) bioreactor. Desirable N-removal efficiency of 87.5 ± 2.1% was obtained without external organics, correspondingly effluent total nitrogen (TN) concentration reached 6.1 ± 0.7 mg/L. The N-removal stability was greatly facilitated by the effective linkage between partial nitrification (PN) process and partial denitrification (PD) process in emergency. Highly enriched hydrolytic bacteria (6.9%) and acidogenic bacteria (5.7%) in A1, especially Comamonas (2.8%) and Longilinea (3.5%), induced the significant increase of volatile fatty acids (VFAs) in domestic sewage. Thauera (6.1%) in A2 and Nitrosomonas (5.4%) in A3 acted as the dominant flora of nitrite supplies for anammox in IFPNDA process. Candidatus_Brocadia (2.4%) dominated the advanced nitrogen removal. The IFPNDA process exhibited much potential for achieving energy neutrality during wastewater treatment.

Metagenomics insights into high-rate nitrogen removal from municipal wastewater by integrated nitrification, partial denitrification and Anammox at an extremely short hydraulic retention time.

To achieve high-rate nitrogen removal in municipal wastewater treatment through anaerobic ammonia oxidation (Anammox), the nitrification, partial denitrification, and Anammox processes were integrated by a step-feed strategy. An exceptional nitrogen removal load of 0.224 kg N/(m3·d) was achieved by gradient-reducing the hydraulic retention time (HRT) to 5 h. Metagenomic analysis demonstrated that Nitrosospira could express all genes encoding ammonia oxidation under low nitrogen and dissolved oxygen conditions (less than 0.5 mg/L), enabling complete nitrification. With the short of HRT, the relative abundance of Thauera increased from 2.8 % to 6.4 %. Frequent substrate exchanges at such extremely short HRT facilitated enhanced synergistic interactions among Nitrosospira, Thauera, and Candidatus Brocadia. These findings provide a comprehensive understanding of the utilization of Anammox combined processes for high-speed nitrogen removal in municipal wastewater treatment and the microbial interactions involved.

Efficient nitrogen removal from municipal wastewater by an autotrophic-heterotrophic coupled anammox system: The up-regulation of key functional genes.

The metabolic pathways based on key functional genes were innovatively revealed in the autotrophic-heterotrophic coupled anammox system for real municipal wastewater treatment. The nitrogen removal performance of the system was stabilized at 88.40 ± 3.39 % during the treatment of real municipal wastewater. The relative abundances of the nitrification functional genes ammonia oxidase (amoA/B/C), hydroxylamine oxidoreductase (hao), and nitrite oxidoreductases (nxrA/B) were increased by 1.2-2.4 times, and these three nitrification functional genes were mostly contributed by Nitrospira that dominated the efficient nitrification of the system. The relative abundance of anammox bacteria Candidatus Brocadia augmented from 0.35 % to 0.75 %, accompanied with the increased expression of hydrazine synthase (hzs) and hydrazine dehydrogenase (hdh), resulting in the major role of anammox (81.24 %) for nitrogen removal. The expression enhancement of the functional genes nitrite reductase (narG/H, napA/B) that promoted partial denitrification (PD) of the system weakened the adverse effects of the sharp decline in the population of PD microbe Thauera (from 5.7 % to 2.2 %). The metabolic module analysis indicated that the carbon metabolism pathways of the system mainly included CO2 fixation and organic carbon metabolism, and the stable enrichment of autotrophic bacteria ensured stable CO2 fixation. Furthermore, the enhanced expression of the glucokinases (glk, GCK, HK, ppgk) and the abundant pyruvate kinase (PK) achieved stable hydrolysis ability of organic carbon metabolism function of the system. This study offers research basics to practical application of the mainstream anammox process.

Altered lymphocyte counts in a pediatric patient with H5N1 infection.

Flow cytometry was used to analyze the changes in lymphocyte subsets in the youngest child with avian influenza in China. During the early stage, the absolute CD3 count was 62.9% (lower limit of normal), the CD8 count was 32.5% (slightly higher than normal), and the CD4 count was 28.6% (lower than normal). The CD4/CD8 ratio was also decreased (0.88). The natural killer (CD3CD1656) cell count was 4.9% (lower than normal). During the convalescent stage, the CD4 count and the CD4/CD8 ratio returned to normal. The CD3CD1656 count increased from its value at the early stage of the disease.

Estimating reed loss caused by Locusta migratoria manilensis using UAV-based hyperspectral data.

Locusta migratoria manilensis has caused major damage to vegetation and crops. Quantitative evaluation studies of vegetation loss estimation from locust damage have seldom been found in traditional satellite-remote-sensing-based research due to insufficient temporal-spatial resolution available from most current satellite-based observations. We used remote sensing data acquired from an unmanned aerial vehicle (UAV) over a simulated Locusta migratoria manilensis damage experiment on a reed (Phragmites australis) canopy in Kenli District, China during July 2017. The experiment was conducted on 72 reed plots, and included three damage duration treatments with each treatment including six locust density levels. To establish the appropriate loss estimation models after locust damage, a hyperspectral imager was mounted on a UAV to collect reed canopy spectra. Loss components of six vegetation indices (RVI, NDVI, SAVI, MSAVI, GNDVI, and IPVI) and two "red edge" parameters (Dr and SDr) were used for constructing the loss estimation models. Results showed that: (1) Among the six selected vegetation indices, loss components of NDVI, MSAVI, and GNDVI were more sensitive to the variation of dry weight loss of reed green leaves and produced smaller estimation errors during the model test process, with RMSEs ranging from 8.8 to 9.1 g/m;. (2) Corresponding model test results based on loss components of the two selected red edge parameters yielded RMSEs of 27.5 g/m2 and 26.1 g/m2 for Dr and SDr respectively, suggesting an inferior performance of red edge parameters compared with vegetation indices for reed loss estimation. These results demonstrate the great potential of UAV-based loss estimation models for evaluating and quantifying degree of locust damage in an efficient and quantitative manner. The methodology has promise for being transferred to satellite remote sensing data in the future for better monitoring of locust damage of larger geographical areas.

Gene Aging Nexus: a web database and data mining platform for microarray data on aging.

The recent development of microarray technology provided unprecedented opportunities to understand the genetic basis of aging. So far, many microarray studies have addressed aging-related expression patterns in multiple organisms and under different conditions. The number of relevant studies continues to increase rapidly. However, efficient exploitation of these vast data is frustrated by the lack of an integrated data mining platform or other unifying bioinformatic resource to enable convenient cross-laboratory searches of array signals. To facilitate the integrative analysis of microarray data on aging, we developed a web database and analysis platform 'Gene Aging Nexus' (GAN) that is freely accessible to the research community to query/analyze/visualize cross-platform and cross-species microarray data on aging. By providing the possibility of integrative microarray analysis, GAN should be useful in building the systems-biology understanding of aging. GAN is accessible at http://gan.usc.edu.

On the genealogy of a duplicated microsatellite.

When a microsatellite locus is duplicated in a diploid organism, a single pair of PCR primers may amplify as many as four distinct alleles. To study the evolution of a duplicated microsatellite, we consider a coalescent model with symmetric stepwise mutation. Conditional on the time of duplication and a mutation rate, both in a model of completely unlinked loci and in a model of completely linked loci, we compute the probabilities for a sampled diploid individual to amplify one, two, three, or four distinct alleles with one pair of microsatellite PCR primers. These probabilities are then studied to examine the nature of their dependence on the duplication time and the mutation rate. The mutation rate is observed to have a stronger effect than the duplication time on the four probabilities, and the unlinked and linked cases are seen to behave similarly. Our results can be useful for helping to interpret genetic variation at microsatellite loci in species with a very recent history of gene and genome duplication.

An extended PROSPECT: Advance in the leaf optical properties model separating total chlorophylls into chlorophyll a and b.

The PROSPECT leaf optical model has, to date, well-separated the effects of total chlorophyll and carotenoids on leaf reflectance and transmittance in the 400-800 nm. Considering variations in chlorophyll a:b ratio with leaf age and physiological stress, a further separation of total plant-based chlorophylls into chlorophyll a and chlorophyll b is necessary for advanced monitoring of plant growth. In this study, we present an extended version of PROSPECT model (hereafter referred to as PROSPECT-MP) that can combine the effects of chlorophyll a, chlorophyll b and carotenoids on leaf directional hemispherical reflectance and transmittance (DHR and DHT) in the 400-800 nm. The LOPEX93 dataset was used to evaluate the capabilities of PROSPECT-MP for spectra modelling and pigment retrieval. The results show that PROSPECT-MP can both simultaneously retrieve leaf chlorophyll a and b, and also performs better than PROSPECT-5 in retrieving carotenoids concentrations. As for the simulation of DHR and DHT, the performances of PROSPECT-MP are similar to that of PROSPECT-5. This study demonstrates the potential of PROSPECT-MP for improving capabilities of remote sensing of leaf photosynthetic pigments (chlorophyll a, chlorophyll b and carotenoids) and for providing a framework for future refinements in the modelling of leaf optical properties.

Statistical tests of the coalescent model based on the haplotype frequency distribution and the number of segregating sites.

Several tests of neutral evolution employ the observed number of segregating sites and properties of the haplotype frequency distribution as summary statistics and use simulations to obtain rejection probabilities. Here we develop a "haplotype configuration test" of neutrality (HCT) based on the full haplotype frequency distribution. To enable exact computation of rejection probabilities for small samples, we derive a recursion under the standard coalescent model for the joint distribution of the haplotype frequencies and the number of segregating sites. For larger samples, we consider simulation-based approaches. The utility of the HCT is demonstrated in simulations of alternative models and in application to data from Drosophila melanogaster.

Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost.

Most areas planted with sugarcane are located in southern China. However, remote sensing of sugarcane has been limited because useable remote sensing data are limited due to the cloudy climate of this region during the growing season and severe spectral mixing with other crops. In this study, we developed a methodology for automatically mapping sugarcane over large areas using time-series middle-resolution remote sensing data. For this purpose, two major techniques were used, the object-oriented method (OOM) and data mining (DM). In addition, time-series Chinese HJ-1 CCD images were obtained during the sugarcane growing period. Image objects were generated using a multi-resolution segmentation algorithm, and DM was implemented using the AdaBoost algorithm, which generated the prediction model. The prediction model was applied to the HJ-1 CCD time-series image objects, and then a map of the sugarcane planting area was produced. The classification accuracy was evaluated using independent field survey sampling points. The confusion matrix analysis showed that the overall classification accuracy reached 93.6% and that the Kappa coefficient was 0.85. Thus, the results showed that this method is feasible, efficient, and applicable for extrapolating the classification of other crops in large areas where the application of high-resolution remote sensing data is impractical due to financial considerations or because qualified images are limited.

Defected expression of E-cadherin in non-small cell lung cancer.

Reduced expression of E-cadherin, a cell-cell adhesion molecule, was frequently observed in several types of human carcinomas, and the protein plays a role as an invasion suppressor in vitro. In an attempt to evaluate the significance of E-cadherin gene in non-small cell lung cancer (NSCLC), we undertook the immunohistochemical and molecule structural analyses of E-cadherin gene in 40 resection specimens of NSCLC and the corresponding paracarcinoma controls. E-cadherin expression was explored by immunohistochemistry with a monoclonal antibody, and the E-cadherin gene was studied by polymerase chain reaction single-strand conformation polymorphism analysis (PCR-SSCP). The analysis represented in this study demonstrated clear reduction in the expression of E-cadherin proteins in the cancer tissues. However, only in one amplicon were aberrant bands detected, which was a single polymorphic site (codon 692; exon 13), and no somatic mutation was found. These results indicated that defected E-cadherin expression might play a role in the development of malignant phenotype in NSCLC, even though the genetic mutation of E-cadherin gene is not involved in the pathogenesis of NSCLC and does not appear to be direct cause for the reduced expression of E-cadherin gene.

Evolution of Drosophila ribosomal protein gene core promoters.

The coordinated expression of ribosomal protein genes (RPGs) has been well documented in many species. Previous analyses of RPG promoters focus only on Fungi and mammals. Recognizing this gap and using a comparative genomics approach, we utilize a motif-finding algorithm that incorporates cross-species conservation to identify several significant motifs in Drosophila RPG promoters. As a result, significant differences of the enriched motifs in RPG promoter are found among Drosophila, Fungi, and mammals, demonstrating the evolutionary dynamics of the ribosomal gene regulatory network. We also report a motif present in similar numbers of RPGs among Drosophila species which does not appear to be conserved at the individual RPG gene level. A module-wise stabilizing selection theory is proposed to explain this observation. Overall, our results provide significant insight into the fast-evolving nature of transcriptional regulation in the RPG module.

Discovering cancer genes by integrating network and functional properties.

BACKGROUND: Identification of novel cancer-causing genes is one of the main goals in cancer research. The rapid accumulation of genome-wide protein-protein interaction (PPI) data in humans has provided a new basis for studying the topological features of cancer genes in cellular networks. It is important to integrate multiple genomic data sources, including PPI networks, protein domains and Gene Ontology (GO) annotations, to facilitate the identification of cancer genes. METHODS: Topological features of the PPI network, as well as protein domain compositions, enrichment of gene ontology categories, sequence and evolutionary conservation features were extracted and compared between cancer genes and other genes. The predictive power of various classifiers for identification of cancer genes was evaluated by cross validation. Experimental validation of a subset of the prediction results was conducted using siRNA knockdown and viability assays in human colon cancer cell line DLD-1. RESULTS: Cross validation demonstrated advantageous performance of classifiers based on support vector machines (SVMs) with the inclusion of the topological features from the PPI network, protein domain compositions and GO annotations. We then applied the trained SVM classifier to human genes to prioritize putative cancer genes. siRNA knock-down of several SVM predicted cancer genes displayed greatly reduced cell viability in human colon cancer cell line DLD-1. CONCLUSION: Topological features of PPI networks, protein domain compositions and GO annotations are good predictors of cancer genes. The SVM classifier integrates multiple features and as such is useful for prioritizing candidate cancer genes for experimental validations.

Integrative Array Analyzer: a software package for analysis of cross-platform and cross-species microarray data.

The rapid accumulation of microarray data translates into an urgent need for tools to perform integrative microarray analysis. Integrative Array Analyzer is a comprehensive analysis and visualization software toolkit, which aims to facilitate the reuse of the large amount of cross-platform and cross-species microarray data. It is composed of the data preprocess module, the co-expression analysis module, the differential expression analysis module, the functional and transcriptional annotation module and the graph visualization module.