Non-Negative Low-Rank Representation With Similarity Correction for Cell Type Identification in scRNA-Seq Data.

Single-cell RNA sequencing (scRNA-Seq) technology has emerged as a powerful tool to investigate cellular heterogeneity within tissues, organs, and organisms. One fundamental question pertaining to single-cell gene expression data analysis revolves around the identification of cell types, which constitutes a critical step within the data processing workflow. However, existing methods for cell type identification through learning low-dimensional latent embeddings often overlook the intercellular structural relationships. In this paper, we present a novel non-negative low-rank similarity correction model (NLRSIM) that leverages subspace clustering to preserve the global structure among cells. This model introduces a novel manifold learning process to address the issue of imbalanced neighbourhood spatial density in cells, thereby effectively preserving local geometric structures. This procedure utilizes a position-sensitive hashing algorithm to construct the graph structure of the data. The experimental results demonstrate that the NLRSIM surpasses other advanced models in terms of clustering effects and visualization experiments. The validated effectiveness of gene expression information after calibration by the NLRSIM model has been duly ascertained in the realm of relevant biological studies. The NLRSIM model offers unprecedented insights into gene expression, states, and structures at the individual cellular level, thereby contributing novel perspectives to the field.

WITHDRAWN: HCST Expression Distinguishes Immune-hot and Immune-cold Subtypes in Pancreatic Ductal Adenocarcinoma

Since the authors are not responding to the editor's requests to fulfill the editorial requirement, therefore, the article has been withdrawn.Bentham Science apologizes to the readers of the journal for any inconvenience this may have caused.The Bentham Editorial Policy on Article Withdrawal can be found at https://benthamscience.com/editorial-policies-main.php BENTHAM SCIENCE DISCLAIMER: It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.

A new framework for drug-disease association prediction combing light-gated message passing neural network and gated fusion mechanism.

With the development of research on the complex aetiology of many diseases, computational drug repositioning methodology has proven to be a shortcut to costly and inefficient traditional methods. Therefore, developing more promising computational methods is indispensable for finding new candidate diseases to treat with existing drugs. In this paper, a model integrating a new variant of message passing neural network and a novel-gated fusion mechanism called GLGMPNN is proposed for drug-disease association prediction. First, a light-gated message passing neural network (LGMPNN), including message passing, aggregation and updating, is proposed to separately extract multiple pieces of information from the similarity networks and the association network. Then, a gated fusion mechanism consisting of a forget gate and an output gate is applied to integrate the multiple pieces of information to extent. The forget gate calculated by the multiple embeddings is built to integrate the association information into the similarity information. Furthermore, the final node representations are controlled by the output gate, which fuses the topology information of the networks and the initial similarity information. Finally, a bilinear decoder is adopted to reconstruct an adjacency matrix for drug-disease associations. Evaluated by 10-fold cross-validations, GLGMPNN achieves excellent performance compared with the current models. The following studies show that our model can effectively discover novel drug-disease associations.

A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection.

Single-cell RNA sequencing (scRNA-seq) technology is famous for providing a microscopic view to help capture cellular heterogeneity. This characteristic has advanced the field of genomics by enabling the delicate differentiation of cell types. However, the properties of single-cell datasets, such as high dropout events, noise, and high dimensionality, are still a research challenge in the single-cell field. To utilize single-cell data more efficiently and to better explore the heterogeneity among cells, a new graph autoencoder (GAE)-based consensus-guided model (scGAC) is proposed in this article. The data are preprocessed into multiple top-level feature datasets. Then, feature learning is performed by using GAEs to generate new feature matrices, followed by similarity learning based on distance fusion methods. The learned similarity matrices are fed back to the GAEs to guide their feature learning process. Finally, the abovementioned steps are iterated continuously to integrate the final consistent similarity matrix and perform other related downstream analyses. The scGAC model can accurately identify critical features and effectively preserve the internal structure of the data. This can further improve the accuracy of cell type identification.

A novel anti-p21Ras scFv antibody reacting specifically with human tumour cell lines and primary tumour tissues.

BACKGROUND: The ras genes play an important role in the development and progression of human tumours. Neutralizing Ras proteins in the cytoplasm could be an effective approach to blocking ras signalling. In this study, we prepared anti-p21Ras single chain fragment variable antibody (scFv) and investigated its immunoreactivity with human tumours. METHODS: The coding sequences of H-ras, K-ras, and N-ras were separately ligated into the vector pET-28a(+). Then, recombinant expressing plasmids were induced by IPTG for p21Ras expression in E. coli. Hybridoma cell lines producing anti-p21Ras monoclonal antibodies were isolated using wildtype p21Ras proteins as immunogens. Anti-p21Ras scFv antibody was prepared from the hybridoma by the phage scFv display method. The immunoreactivity of the anti-p21Ras monoclonal antibody and the scFv antibody was identified by ELISA and immunocytochemistry. RESULTS: We prokaryotically expressed wildtype H-p21Ras, K-p21Ras and N-p21Ras and generated the hybridoma cell line KGH-R1, producing anti-p21Ras monoclonal antibodies. It was demonstrated that KGH-R1 monoclonal antibody could recognize wildtype and mutated H-p21Ras, K-p21Ras and N-p21Ras in human tumour cell lines. In all 14 types of primary human cancer tissues tested, the monoclonal antibody presented strong immunoreactivity but showed weak or negative immunoreactivity in the corresponding normal tissues. Subsequently, we prepared anti-p21Ras scFv from hybridoma KGH-R1, which showed the same immunoreactivity as the original monoclonal antibody. Sequence analysis demonstrated that the nucleotides and amino acids of the scFv exhibited an approximately 50 % difference from the anti-p21Ras scFv reported previously. CONCLUSIONS: This study presents a novel anti-p21Ras scFv antibody. Our data suggest that the scFv may be useful for ras signalling blockage and may be a potential therapeutic antibody for ras-derived tumours.

[Polyhydroxyalkanoate (PHA) Synthesis by Glycerol-based Mixed Culture and Its Relation with Oxygen Uptake Rate (OUR)].

Polyhydroxyalkanoate (PHA) is one of the most promising biopolymers with the advantages of biodegradable biocompatible and renewable. A glycerol-fed PHA-producing mixed culture was enriched in a feast-famine regime. The substrate versatility and PHA production capacity of the mixed culture were studied using acetate,propionate,butyric, glucose and lactate as substrate, respectively. The results showed a high PHA content with lactate and acetate as the sole substrate, respectively. When acetate and propionate were used as mixed substrates to produce PHA, the PHA contents increased with the proportion of acetate and the PHA content was the highest as the ratio acetate/propionate was 3:1.The results based on the modeling of simultaneously storage and growth and the linear fitting under three different acetate/propionate ratios showed that there was a linear relation between PHA synthesis and OUR. Thus, it is feasible to estimate PHA content based on in-situ real-time monitoring data of OUR.

[Characteristics of Nitrobacteria in SBR with Trace N2H4 Addition].

A sequencing batch reactor (SBR) was conducted to perform nitrification process. The influence of long-term trace hydrazine (N2H4) addition (about 3 mg·L-1) on ammonium oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) in nitrifying sludge was investigated. The result indicated that Nitrosococcu, Nitrosomonas and Nitrosospira were related to AOB, and Nitrobacter was related to NOB in nitrifying sludge with N2H4 addition, respectively. The estimates of AOB population (in dry sludge) with N2H4 addition decreased from 1.0×109 to 2.09×104 copies·g-1, and those of NOB decreased from 1.28×107 to 2.56×105 copies·g-1. AOB was more sensitive to environmental factors than NOB, the effect of inhibition and toxicity on nitrobacteria caused more loss of AOB abundances than that of NOB, but quantitative real-time PCR could not determine the inhibition of N2H4 on microbial activity of AOB and NOB. The nitrobacteria activity was destroyed with long-term trace N2H4 addition, and the reactor collapsed. Consequently, it was possibly unable to inhibit NOB activity by controlling the added N2H4 concentration, and further take off NOB in nitrification process for improving nitrogen removal.

[On-line Estimation for the Amount of Stored PHA in Activated Sludge Based on OUR-HPR Measurements].

Activated sludge process is an important approach for industrial Polyhydroxyalkanoate ( PHA ) production. Off-line measurement with a time lag and complex analysis, is a common method for PHA, but is not suitable for the process control of PHA production. Based on a model for simultaneous storage and growth-soluble microbial products (SSAG-SMP), it is assumed that there is the linear relationship between the PHA synthesized and OUR or HPR, respectively. Further, a novel method to estimate PHA content based on in-situ monitoring data of oxygen uptake rate (OUR) and hydrogen-ion production rate (HPR) is established in this paper. The results of modeling OUR and HPR under different substrate concentrations showed that oxygen consumption proportion (kPHA,OUR) and proton consumption proportion (kPHA,HPR) of PHA synthesis were 0.67 and 0.57, respectively. The predicted results based on the linear relationship were essentially consistent with measured ones, and indicated that the method is feasible

[Influencing factors of floc size distribution and fractal dimension of activated sludge].

Floc size distribution (FSD) and fractal dimension are the important parameters for activated sludge. FSD of aerobic activated sludge during flocculation process was measured by a laser particle size analyzer, and the influence of velocity gradient, VSS/ SS, EPS content and Zeta potential on FSD was investigated. The results showed that the floc volume-average size was negatively correlated to velocity gradient (R > 0. 80) , and the order-of-magnitude of the floc volume-average size was equivalent to that of Kolmogorov scale (their differences were dependent on sludge VSS/SS, floc strength and etc). At a fixing velocity gradient, the floc volume-average size was positively correlated to VSS/SS or EPS (R2 >0. 85) , whereas negatively correlated to Zeta potential. Organic matter and EPS played important roles on the flocculation of activated sludge by enhancing the floc strength and improving the flocculation effect. Compared with polysaccharides, proteins in EPS seemed to be more beneficial for the flocculation of activated sludge. Based on microscopy and image analysis, the 2D and 3D fractal dimension of aerobic activated sludge floc was determined to be 1.28-1.72 and 1.70-2.69, respectively. It was found that fractal dimension (2D and 3D)was decreased with increasing VSS/SS (or EPS content). For the same activated sludge, the 3D fractal dimension was decreased with increasing floc size, and the relationship between 3D fractal dimension and floc size could be approximately described by a power function.

The enhancement of completely autotrophic nitrogen removal over nitrite (CANON) by N2H4 addition.

The long-term addition of N2H4 to completely autotrophic nitrogen removal over nitrite (CANON) sequencing batch reactors (SBRs) recovered and enhanced their autotrophic nitrogen removal capacity while simultaneously reducing their production of NO3(-). The total nitrogen (TN) removal rate and TN removal efficiency of the process increased from 0.202±0.011 to 0.370±0.016 kg N/m(3)/d and from 65.1±3.75% to 77.4±3.8%, respectively, and the molar ratio of NO3(-) production to NH4(+) removal (MRNN) decreased to 0.058. The most effective concentration of N2H4 addition was approximately 3.99 mg/L. N2H4 could increase the specific growth rate of anaerobic ammonium-oxidizing bacteria (AnAOB) and inhibit aerobic ammonia oxidation. The electrons released from the oxidation of additional N2H4 using hydrazine dehydrogenase (HDH), which substituted the electrons from NO2(-) oxidation to NO3(-), replenished the consumption of AnAOB anabolism and significantly reduced the consequent NO3(-) production.

[Monitoring the stoichiometric relation of ammonium oxidation with the titrimetry of hydrogen ion variation].

A set of automatically titrimetric system to monitor the hydrogen ion variation during biological wastewater treatment process in a batch bioreactor was developed, which consists of a batch bioreactor, data auto-acquisition and preservation unit, and titrant autodosing unit. The accuracy of measurement for the system was evaluated by measuring the stoichiometric ratio of hydrogen ion production amount to ammonium consumption amount of ammonium oxidation in an activated sludge system. The ratios measured in a 1L bioreactor with NH4+ -N concentrations of 1.67, 3.33, 8.33, 16. 66 and 30.00 mg/L as N respectively were very close to the theoretical value, and the relative errors were among 2.09%-6.34%. However, the relative errors in bioreactors of 1, 2, 3 and 4 L with NH4+ -N concentration of 16.66 mg/L as N were among 2.09%- -18.57%, and increased significantly with accretion of the volume of bioreactor. The buffers of bicarbonate and the ammonium, especially the titrimetric dynamic effects in a larger bioreactor are the primarily factors resulting in errors. This study provides an important approach for monitoring hydrogen ion variation in the process of biological wastewater treatment by titrimetry.

[Simultaneous chracterization of RBCOD and SBCOD in wastewater by hybrid respirometer].

Respirometry was made using wastewater and activated sludge from a WWTP of Chongqing through self-developed hybrid respirometer. And complete oxygen uptake rate (OUR) curves containing OUR of biodegradation process of RBCOD and SBCOD and endogenous process were obtained. A new method based on respirometry was proposed to characterize RBCOD and SBCOD in wastewater simultaneously, in which hydrolysis model was selected to analyze OUR curves of SBCOD according to the two-phases nature of exogenous OUR and trend-test method for endogens OUR. Compared with the traditional OUR-stages method, the new method reduces the man-made error and improves the accuracy of wastewater COD fractions characterization.

[Implement of completely autotrophic nitrogen removal in EGSB reactor and its operation optimization].

An expanded granular sludge bed (EGSB) reactor inoculated simultaneously with aerobic ammonium oxidation sludge and anaerobic ammonium oxidation sludge were start-up to enrich completely autotrophic nitrogen removal granular sludge. Total nitrogen (TN) removal rate reached 0.101 kg x (m3 x d)(-1). Based on hypothesis of boundary layer, the transfer process between granular sludge and bulk liquid was modified, which was coupled with substance transfer process in granular sludge and aerobic ammonium oxidation, anaerobic ammonium oxidation, nitrite oxidation process, and completely autotrophic nitrogen removal model was found. The model was validated with the experimental results. According to simulation results, the operation of the reactor was optimized, TN removal efficiency and TN removal rate were increased from 52% to 61% and 0.103 kg x (m3 x d)(-1) to 0.114 kg x (m3 x d)(-1) respectively.

[Determination of 16S rRNA gene sequence for a new ANAMMOX bacterial species].

The anaerobic ammonium oxidation (ANAMMOX) activity of the sludge was about 9.84 x 10(-4) mg x (mg x h)(-1) by measuring the simultaneous consumption of ammonium and nitrite under anoxic conditions in the batch tests. The consumption of NO2(-) -N and NH4+ -N was 1.311 for ANAMMOX bacteria. The partial 16S rDNA sequence was obtained by using molecule biology methods. Crude DNA of the total bacteria in granular sludge from EGSB reactor was extracted and purified. Then, PCR amplification by using specific primer, clone and sequence determination was performed. ANAMMOX bacterial species(anaerobic ammonium-oxidizing Planctomycete cquenviron-1) which was enrichment cultivated from EGSB reactor were the same genera with Candidatus "Anammoxoglobus propionicus" and Candidatus "Jettenia asiatica" by analyzing phylogenetic tree. The maximum identities of anaerobic ammonium-oxidizing Planctomycete cquenviron-1 with other ANAMMOX bacterial species was about 93%. The results showed that a new ANAMMOX bacterial species which was enrichment cultivated from EGSB reactor was found and anaerobic ammonium-oxidizing Planctomycete cquenviron-1 was denominated.

[Effect of trace NO2 and kinetic characteristics for anaerobic ammonium oxidation of granular sludge].

The effect of trace NO2 and kinetic characteristics for anaerobic ammonium oxidation of granular sludge was investigated by batch experiment. The sludge anammox rates could be described by the Haldane model. The kinetic parameters were determined, where the maximum anammox rate was 6.65 x 10(-3) mg (mg h)(-1). The half saturate coefficient and inhibition coefficient for ammonium nitrogen were 87.1 mg L(-1) and 1,123 mg L(-1) respectively, and the half saturate coefficient and inhibition coefficient for nitrite nitrogen were 15.39 mg L(-1) and 159.5 mg L(-1) respectively. Trace NO2 apparently enhanced anammox under trace NO2 atmosphere conditions. The function for NO2 to enhance anammox was suggested by the Haldane based model. The parameters in the function were estimated, where the maximum enhancing anammox coefficient was 48.79, and the half saturate coefficient and inhibition coefficient for NO2 were 2480 mg m(-3) and 4.22 mg m(-3) respectively, and the basic rate coefficient was 0.0182. The most of NOx in the experiment was lost.

[Ammonia oxidation kinetics of ammonia oxidizer mixed culture under the conditions of O2 and trace NO2 mixed gasses].

The kinetics of the NO2-dependent ammonia oxidation was developed for ammonia oxidizer mixed culture when there was no molecular oxygen in the batch tests. The kinetics parameters were determined, where the half saturate coefficient of NO2 was 0.821 micromol x L(-1), inhibition coefficient of NO2 concentration was 1.721 micromol x L(-1), and the maximum ammonia oxidation rate were 0.144 mg x (mg x h)(-1). After adding the volume fraction of O2 was 2% to trace NO2, the ammonia oxidation rates increased obviously. The maximum ammonia oxidation rate, 0.198 mg x (mg x h)(-1) occurred under the condition of the mixed gasses containing the volume fraction of O2 was 2% and 50 x 10(-6) NO2. Under the condition of mixed gasses containing the volume fraction of O2 was 21% to trace NO2, the ammonia oxidation rates further increased greatly. The maximum ammonia oxidation rate, 0.477 mg x (mg x h)(-1) occurred when the volume fraction of O2 was 21% and 100 x 10(-6) NO2 in the mixed gas, which is 3 times higher than the general aerobic ammonia oxidation rate. The function for NO2 apparently to enhance ammonia oxidation was suggested. The kinetics model of ammonia oxidation under the conditions of O2 and trace NO2 mixed gasses was developed. The model was validated by the results of ammonia oxidation experiments under the conditions of the mixed gasses containing 2% O2 and trace NO2. The mechanism for NO2 to enhance ammonia oxidation under the conditions of O2 and trace NO2 mixed gasses was discussed.