Designing and Evaluating a VR Lobby for a Socially Enriching Remote Opera Watching Experience.

The latest social VR technologies have enabled users to attend traditional media and arts performances together while being geographically removed, making such experiences accessible despite budget, distance, and other restrictions. In this work, we aim at improving the way remote performances are shared by designing and evaluating a VR theatre lobby which serves as a space for users to gather, interact, and relive the common experience of watching a virtual opera. We conducted an initial test with experts ($\mathrm{N}=10$, i.e., designers and opera enthusiasts) in pairs using our VR lobby prototype, developed based on the theoretical lobby design concept. A unique aspect of our experience is its highly realistic representation of users in the virtual space. The test results guided refinements to the VR lobby structure and implementation, aiming to improve the user experience and align it more closely with the social VR lobby's intended purpose. With the enhanced prototype, we ran a between-subject controlled study ($\mathrm{N}=40$) to compare the user experience in the social VR lobby between individuals and paired participants. To do so, we designed and validated a questionnaire to measure the user experience in the VR lobby. Results of our mixed-methods analysis, including interviews, questionnaire results, and user behavior, reveal the strength of our social VR lobby in connecting with other users, consuming the opera in a deeper manner, and exploring new possibilities beyond what is common in real life. All supplemental materials are available at https://github.com/cwi-dis/IEEEVR2024-VRLobby.

Regional cerebral metabolism alterations and functional connectivity in individuals with opioid use disorder: An integrated resting-state PET/fMRI study.

Individuals with opioid use disorder (OUD) have been reported to show abnormal brain metabolism and impaired coupling among brain networks such as the default mode network (DMN), salience network (SN), and executive control network (ECN). However, the characteristics of brain glucose metabolism and its related functions in the brain networks in individuals with OUD remain unknown. Thirty-six individuals with OUD and thirty matched healthy controls (HCs) were recruited in this integrated positron emission tomography/magnetic resonance imaging (PET/MRI) study. Differences in glucose metabolism were analyzed by using 18F-fluorodeoxyglucose (18F-FDG), and the corresponding coupling characteristics of the individuals with OUD were also analyzed. The individuals with OUD showed widespread bilateral hypometabolism in the middle temporal gyrus (MTG), superior temporal gyrus, angular gyrus, supramarginal gyrus, inferior parietal lobe, Rolandic operculum, and left insula, but obvious hypermetabolism in the brainstem and left cerebellum. Meanwhile, in individuals with OUD, the hypometabolism of right MTG which is included in the DMN was accompanied by decreased coupling with the left superior frontal gyrus and right superior parietal gyrus which are included in the ECN. Furthermore, individuals with OUD showed a positive correlation between the duration of heroin use and glucose metabolism of the left MTG. The individuals with OUD were characterized by widespread bilateral hypometabolism in the temporal and parietal regions but obvious hypermetabolism in the brainstem and left cerebellum. The results suggest that the hypometabolism in the temporal and parietal regions might be related to DMN dysfunction and the hypermetabolism in the brainstem and left cerebellum may be compensate for other brain regions showing hypometabolism. In particular, hypometabolism in the self-referential-related DMN regions in OUD might attenuate their relationships with the inhibitory-control-related ECN regions. These findings highlight the importance of evaluating the metabolic and functional profiles of the right MTG in future studies on the treatment of OUD.

Abnormal cerebral metabolism and metabolic connectivity in individuals with heroin dependence: an integrated resting-state PET/fMRI study in large-scale networks.

BACKGROUND: Increasing evidence suggests that heroin addiction may be related to the dysfunction among the triple brain network (default mode network [DMN], salience network [SN] and executive control network [ECN]). However, the characteristics of glucose metabolism and metabolic connectivity among core regions of the triple brain network remain unknown. Therefore, we hypothesized that individuals with heroin dependence would show abnormal glucose metabolism and accompanied abnormal metabolic connectivity within the triple brain network. METHODS: Individuals with heroin dependence and healthy controls matched for age and sex underwent integrated positron emission tomography/magnetic resonance imaging (PET/MRI). Differences in glucose metabolism and metabolic connectivity among the DMN, SN and ECN were analyzed based on 18F-fluorodeoxyglucose PET and resting-state fMRI data. RESULTS: We included 36 individuals with heroin dependence and 30 matched healthy controls in our study. The heroin dependence group showed a significant reduction of glucose metabolism in the bilateral anterior insula (AI) and inferior parietal lobule (IPL), and a significantly decreased metabolic connectivity between the right AI and the left dorsolateral prefrontal cortex (DLPFC). The daily dose of methadone was negatively correlated with glucose metabolism of the right AI and right IPL. LIMITATIONS: The results revealed the glucose metabolism alterations and metabolic connectivity only within the triple brain network in individuals with heroin dependence; additional brain networks should be investigated in future studies. Although methadone is an opioid with a similar neurophysiological mechanism as heroin, the specific chronic effects of methadone on cerebral metabolism and metabolic connectivity should also be investigated in future studies. CONCLUSION: Our findings suggest that long-term opioid use might, to some extent, be associated with reduced synergistic ability between the SN and ECN, which may be associated with the dysfunction of cognitive control. In particular, the right AI, which showed hypometabolism and related reduction in SN-ECN metabolic connectivity, should receive increasing attention in future studies.

Rapid and reliable ultrasensitive detection of pathogenic H9N2 viruses through virus-binding phage nanofibers decorated with gold nanoparticles.

The rapid and sensitive detection of pathogenic viruses is important for controlling pandemics. Herein, a rapid, ultrasensitive, optical biosensing scheme was developed to detect avian influenza virus H9N2 using a genetically engineered filamentous M13 phage probe. The M13 phage was genetically engineered to bear an H9N2-binding peptide (H9N2BP) at the tip and a gold nanoparticle (AuNP)-binding peptide (AuBP) on the sidewall to form an engineered phage nanofiber, M13@H9N2BP@AuBP. Simulated modelling showed that M13@H9N2BP@AuBP enabled a 40-fold enhancement of the electric field enhancement in surface plasmon resonance (SPR) compared to conventional AuNPs. Experimentally, this signal enhancement scheme was employed for detecting H9N2 particles with a sensitivity down to 6.3 copies/mL (1.04 × 10-5 fM). The phage-based SPR scheme can detect H9N2 viruses in real allantoic samples within 10 min, even at very low concentrations beyond the detection limit of quantitative polymerase chain reaction (qPCR). Moreover, after capturing the H9N2 viruses on the sensor chip, the H9N2-binding phage nanofibers can be quantitatively converted into plaques that are visible to the naked eye for further quantification, thereby allowing us to enumerate the H9N2 virus particles through a second mode to cross-validate the SPR results. This novel phage-based biosensing strategy can be employed to detect other pathogens because the H9N2-binding peptides can be easily switched with other pathogen-binding peptides using phage display technology.

Solid-liquid-gas reaction accelerated by gas molecule tunnelling-like effect.

Solid-liquid-gas reactions are ubiquitous and are encountered in both nature and industrial processes1-4. A comprehensive description of gas transport in liquid and following reactions at the solid-liquid-gas interface, which is substantial in regard to achieving enhanced triple-phase reactions, remains unavailable. Here, we report a real-time observation of the accelerated etching of gold nanorods with oxygen nanobubbles in aqueous hydrobromic acid using liquid-cell transmission electron microscopy. Our observations reveal that when an oxygen nanobubble is close to a nanorod below the critical distance (~1 nm), the local etching rate is significantly enhanced by over one order of magnitude. Molecular dynamics simulation results show that the strong attractive van der Waals interaction between the gold nanorod and oxygen molecules facilitates the transport of oxygen through the thin liquid layer to the gold surface and thus plays a crucial role in increasing the etching rate. This result sheds light on the rational design of solid-liquid-gas reactions for enhanced activities.

Detection of serum EphA2-EVs for pancreatic cancer diagnosis by light initiated chemiluminescent assay.

Pancreatic cancer has led to an extremely high mortality rate because of its insidious onset and lack of early clinical symptoms. Effective early diagnosis is essential to improve the treatment of pancreatic cancer. Tumor-secreted extracellular vesicles (EVs) have attracted great interest as potential tumor biomarkers. However, most of the methods for detecting serum EVs have some general problems such as cumbersome, time-consuming extraction steps, and high cost, which limit greatly the research on cancer detection based on EVs. Herein, we report a light-initiated chemiluminescent assay (LICA) method using photosensitive beads for direct detection of EVs in serum enriched with ephrin type-A receptor 2 (EphA2), which show high expression in pancreatic cancer patients. Combining with a serum biomarker CA19-9, pancreatic cancer patients could be distinguished rapidly by sensitive detection of EphA2-EVs from serum without any purification. This developed method could be extended to improve the diagnosis efficiency for other cancers and gain an insight into EV detection.

TMZ magnetic temperature-sensitive liposomes-mediated magnetothermal chemotherapy induces pyroptosis in glioblastoma.

Glioblastoma (GBM) is the most fatal and common type of primary malignant tumors in central nervous system. Chemotherapy drugs are difficult to reach the encephalic region effectively due to blood-brain barrier (BBB), but functional nanoparticle drug carriers can help to solve the problem. Herein, we developed a controllable drug carrier called temozolomide magnetic temperature-sensitive liposomes (TMZ/Fe-TSL) to investigate its feasibility and molecular mechanisms on GBM. Our research found TMZ/Fe-TSL exposed to alternating magnetic field (AMF) could induce significantly GBM cell death and promote the production of ROS. It also showed that the expression of NLRP3, CASP1 and N-GSDMD was upregulated compared to the control group, while the expression of CASP3 showed a reverse change. The results indicated that TMZ/Fe-TSL exposed to the AMF was capable of inducing GBM cells death. And the way and mechanisms of cell death may involve in ROS and pyroptosis, but not apoptosis.

Simultaneous Detection of Bladder Cancer Exosomal MicroRNAs Based on Inorganic Nanoflare and DNAzyme Walker.

Bladder cancer (BC) is one of the most common cancers in the world, with high morbidity and mortality. It is essential to develop a non-invasive, highly accurate, and simple method for BC diagnosis. This work proposed a fluorescent biosensor based on inorganic nanoflares combined with a DNAzyme walker for the simultaneous detection of BC exosomal microRNAs (miRNAs). This biosensor was constructed on the Au nanoparticle (AuNP) modified with the carbon dot (CD)-labeled substrates and DNAzyme strands (AuNP@CDs inorganic nanoflares-DNAzyme, APCD). In the presence of target miRNAs, DNAzyme was activated and then cleaved the CD-labeled substrates and automatically walked along the AuNP, allowing fluorescence recovery. Due to the structure and functional composition, the APCD biosensors demonstrated high sensitivity and specificity, with the reached limit of detection for a single miRNA at the femtomolar level and wide linear range from 50 fM to 10 nM. Furthermore, the simultaneous analysis of BC-related exosomal miR-133b and miR-135b in clinical serum specimens was achieved and consistent with qRT-PCR, suggesting it is a potential method for the diagnosis of BC and other cancers.

Strategic synthesis of trimetallic Au@Ag-Pt nanorattles for ultrasensitive colorimetric detection in lateral flow immunoassay.

Achieving metal nanoparticles with high peroxidase activity and visible-light plasmonic property for lateral flow immunoassay has attracted extensive attention in the industry. However, the major challenge lies in establishing a general and robust preparation strategy. In this contribution, we developed a citrate-capped trimetallic Au@Ag-Pt nanorattle by employing seed-mediated growth and galvanic replacement reaction under a convenient condition, which can be translated directly to industrialized production. The rattle-like architecture empowers the Au@Ag-Pt NPs peroxidase-like activity while retaining the plasmonic property with intense color in the visible-light range. According to testing requirements, Au@Ag-Pt NPs-LFIA provides two colorimetric modes: low-sensitivity mode based on the color from their intrinsic plasmonic property and the high-sensitivity mode based on the nanozyme-triggered chromogenic reaction. Human cardiac troponin I (cTnI), one of the most specific markers for cardiac injury, was chosen as the detection model. Mainly, ultrasensitive colorimetric detection of human cTnI was successfully achieved as low as ∼20 pg mL-1. This strategy is robust to guarantee the stability and repeatability of the peroxidase activity without exact control, which can directly dock with the industrialized production of traditional LFIA strips and be readily adapted for on-demand clinical diagnosis.

Seagrass-inspired design of soft photocatalytic sheets based on hydrogel-integrated free-standing 2D nanoassemblies of multifunctional nanohexagons.

Natural leaves are virtually two-dimensional (2D) flexible photocatalytic system. In particular, seagrass can efficiently harvest low-intensity sunlight to drive photochemical reactions continuously in an aqueous solution. To mimic this process, we present a novel 2D hydrogel-integrated photocatalytic sheet based on free-standing nanoassemblies of multifunctional nanohexagons (mNHs). The mNHs building blocks is made of plasmonic gold nanohexagons (NHs) decorated with Pd nanoparticles in the corners and CdS nanoparticles throughout their exposed surfaces. The mNHs can self-assemble into free-standing 2D nanoassemblies and be integrated with thin hydrogel films, which can catalyze chemical reactions under visible light illumination. Hydrogels are translucent, porous, and soft, allowing for continuous photochemical conversion in an aqueous environment. Using methylene blue (MB) as a model system, we demonstrate a soft seagrass-like photodegradation design, which offers high efficiency, continuous operation without the need of catalyst regeneration, and omnidirectional light-harvesting capability under low-intensity sunlight irradiation, defying their rigid substrate-supported random aggregates and solution-based discrete counterparts.

Gold nanoparticles alleviates the lipopolysaccharide-induced intestinal epithelial barrier dysfunction.

Nanotechnology is used in the immune response manipulation to treat various human diseases. In the present study, we explored the effects of Au nanoparticles (AuNPs) on the lipopolysaccharide (LPS)-induced epithelial barrier dysfunction and inflammatory response of colonic epithelial NCM460 cells. According to the results of cell counting kit-8 and flow cytometry analysis, the viability of NCM460 cells was inhibited, and the apoptosis was increased after LPS treatment, and AuNPs reversed these changes in a dose-dependent way. The permeability was evaluated by detecting the flux of fluorescein isothiocyanate-dextran and transepithelial electrical resistance. LPS enhanced the permeability and promoted barrier dysfunction of NCM460 cells. Enzyme-linked immunosorbent sorbent assay results revealed that the concentrations of pro-inflammatory factors and nitric oxide were elevated by LPS treatment and decreased by the AuNPs. LPS aggravated the inflammatory response, which was rescued by the AuNPs. Moreover, LPS promoted the activation of the nuclear factor kappa-B and extracellular signal-regulated kinase/c-Jun NH-terminal kinase signaling pathways, which were inhibited by AuNPs.

Citrate-Stabilized Gold Nanorods-Directed Osteogenic Differentiation of Multiple Cells.

OBJECTIVE: Gold nanorods (AuNRs) show great potential for versatile biomedical applications, such as stem cell therapy and bone tissue engineering. However, as an indispensable shape-directing agent for the growth of AuNRs, cetyltrimethylammonium bromide (CTAB) is not optimal for biological studies because it forms a cytotoxic bilayer on the AuNR surface, which interferes with the interactions with biological cells. METHODS: Citrate-stabilized AuNRs with various aspect-ratios (Cit-NRI, Cit-NRII, and Cit-NRIII) were prepared by the combination of end-selective etching and poly(sodium 4-styrenesulfonate)-assisted ligand exchange method. Their effects on osteogenic differentiation of the pre-osteoblastic cell line (MC3T3-E1), rat bone marrow mesenchymal stem cells (rBMSCs), and human periodontal ligament progenitor cells (PDLPs) have been investigated. Potential signaling pathway of citrate-stabilized AuNRs-induced osteogenic effects was also investigated. RESULTS: The experimental results showed that citrate-stabilized AuNRs have superior biocompatibility and undergo aspect-ratio-dependent osteogenic differentiation via expression of osteogenic marker genes, alkaline phosphatase (ALP) activity and formation of mineralized nodule. Furthermore, Wnt/ß-catenin signaling pathway might provide a potential explanation for the citrate-stabilized AuNRs-mediated osteogenic differentiation. CONCLUSION: These findings revealed that citrate-stabilized AuNRs with great biocompatibility could regulate the osteogenic differentiation of multiple cell types through Wnt/ß-catenin signaling pathway, which promote innovative AuNRs in the field of tissue engineering and other biomedical applications.

Unravelling the shell growth pathways of Au-Ag core-shell nanoparticles by in situ liquid cell transmission electron microscopy.

Controlling the growth, structure and morphology of core-shell nanoparticles (NPs) is significant for catalytic applications and it can be achieved by adding chemical additives to the synthesis reaction mixture. However, achieving precise control over NP synthesis would require a comprehensive understanding of the mechanisms of NP formation under different chemical conditions, which is quite challenging. Here, using in situ liquid cell transmission electron microscopy (TEM), the overgrowth mechanisms of Ag on Au nanobipyramids (NBPs) are studied in AgNO3 aqueous solution with ascorbic acid as the reducing agent. Au-Ag core-shell NPs are formed via two mechanistic modes: (1) atom deposition during which the Ag atoms are deposited directly onto Au NBPs without the addition of poly(vinyl)pyrrolidone (PVP) and (2) nuclei coalescence during which the Ag nanocrystals (NCs) adsorb onto Au NBPs in the presence of PVP. High-resolution imaging reveals the dynamics of the coalescence process of Ag NCs upon addition of PVP. This study helps us to understand the effect of chemical additives during the evolution of a core seed into core-shell NPs with a well-defined composition and shape. It is useful for synthesizing NPs with greater design flexibility and expanding their various technological applications.

Prediction and analysis of prokaryotic promoters based on sequence features.

Promoter recognition is an important part of functional genomic annotation but a difficult problem. Many studies have been carried out to address this issue. However, they still cannot meet application needs. Most of the methods exhibit specificity, and the objects analyzed are relatively simple, especially for prokaryotes. Hence, more research on prokaryotic promoters is lacking. In this study, the similarity between gene expression and the transmission of information inspired us to analyze promoter sequences by calculating the information content of the sequences and the correlation between sequences in the subregion. We also calculated other sequence features as supplements, such as the Hurst exponent, GC content, and sequence bending property. Then, we employed an artificial neural network to build a classifier and applied it to identify promoters in three organisms, Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. The experiments on the benchmark test set indicate that our method has good capability to distinguish promoters from randomly selected nonpromoters. The maximal AUC for the classifier is 0.90, and the minimal AUC score is 0.80. Additionally, cross-species experiments were conducted. The AUC of the cross-experiment on three organisms yielded 0.8, suggesting that our approach has better generalization ability, which is conducive to revealing the more common characteristics of prokaryotic promoters.

Predicting essential genes of 41 prokaryotes by a semi-supervised method.

Essential genes are vitally important to the survival and reproduction of organisms. Many machine learning methods have been widely employed to predict essential genes and have obtained satisfactory results. However, most of these methods are supervised methods and may not obtain the desired result when the labeled data are insufficient. In this paper, we proposed a learning with local and global consistency (LGC) method-based classifier, which was employed to predict the essential genes of 41 prokaryotes. LGC is a graph-based semi-supervised learning method that can construct a prediction model using finite label and constraint information. The performance of the proposed classifier was evaluated by employing intra-organism prediction and leave-one-species-out validation. The average AUC value of 41 organisms in intra-organisms prediction was 0.723 when the labeled sample ratio was 0.5. The results of this study indicate that the proposed method can achieve acceptable prediction performance with limited labeled data. Additionally, the results demonstrate that this method has good universality.

Exosome-transmitted microRNA-133b inhibited bladder cancer proliferation by upregulating dual-specificity protein phosphatase 1.

Bladder Cancer (BC) is the ninth most common tumor in the world and one of the most common malignant tumors of the urinary system. Some studies reported that miR-133b expression is reduced in BC, but whether it plays a role in the development of BC and its mechanism is unclear. microRNAs can be packaged into exosomes to mediate communication between tumor cells, affecting their proliferation and apoptosis. The objective of this study was to investigate the effect of exosomal miR-133b on BC proliferation and its molecular mechanism. Firstly, the expression of miR-133b was evaluated in BC and adjacent normal tissues, as well as in serum exosomes of BC patients and healthy controls. Then the delivery and internalization of exosomes in cells was observed through fluorescence localization. Cell viability and apoptosis were assessed in BC cells transfected with mimics and incubated with exosomes. The role of exosomal miR-133b was also analyzed in nude mice transplant tumors. Furthermore, the target gene of miR-133b was predicted through bioinformatics. The level of miR-133b was significantly decreased in BC tissues and in exosomes from serum of patients, which was correlated with poor overall survival in TCGA. Exosomal miR-133b could be obtained using BC cells after transfection with miR-133b mimics. The miR-133b expression increased after incubation with exosomal miR-133b, which lead to the inhibition of viability and increase of apoptosis in BC cells. Exosomal miR-133b could suppress tumor growth in vivo. In addition, we found that exosomal miR-133b may play a role in suppressing BC proliferation by upregulating dual-specificity protein phosphatase 1 (DUSP1). These findings may offer promise for new therapeutic directions of BC.

Vertically Aligned Gold Nanowires as Stretchable and Wearable Epidermal Ion-Selective Electrode for Noninvasive Multiplexed Sweat Analysis.

The noninvasive continuous analysis of human sweat is of great significance for improved healthcare diagnostics and treatment in the future, for which a wearable potentiometry-based ion-selective electrode (ISE) has attracted increasing attention, particularly involving ion detection. Note that traditional solid-state ISE electrodes are rigid ion-to-electron transducers that are not conformal to soft human skin and cannot function under stretched states. Here, we demonstrated that vertically aligned mushroom-like gold nanowires (v-AuNW) could serve as stretchable and wearable ion-to-electron transducers for multiplexed, in situ potentiometric analysis of pH, Na+, and K+ in sweat. By modifying v-AuNW electrodes with polyaniline, Na ionophore X, and a valinomycin-based selective membrane, we could specifically detect pH, Na+, and K+, respectively, with high selectivity, reproducibility, and stability. Importantly, the electrochemical performance could be maintained even under 30% strain and during stretch-release cycles without the need of extrinsic structural design. Furthermore, our stretchable v-AuNW ISEs could be seamlessly integrated with a flexible printed circuit board, enabling wireless on-body detection of pH, Na+, and K+ with fast response and negligible cross-talk, indicating considerable promise for noninvasive wearable sweat analysis.

Stretchable gold fiber-based wearable electrochemical sensor toward pH monitoring.

Sweat pH is a key health indicator related to metabolism and homeostasis level through hydrogen ion concentration in biological bio-fluid. Therefore, increasing research efforts have been directed to develop wearable pH sensors towards continuous non-invasive monitoring of sweat pH values in the out-of-hospital environments. Herein, we report a stretchable gold fiber-based electrochemical pH sensor based on our recently developed elastomer-bonded gold nanowire coating technology. The densely packed gold film offers superior strain-insensitive conductivity, high stretchability and large electrochemical active surface area (EASA). By electrodepositing polyamine (PANI) and Ag/AgCl onto the gold fibers, we could selectively detect the pH based on open circuit potentials in an ion-selective electrode design. The obtained fiber-based pH sensors feature a great sensitivity (60.6 mV per pH), high selectivity against cationic interference and high stretchability (up to 100% strain). One of the attributes for the fiber-based sensors is that they can be weaved into textiles, holding great potential for integration into everyday clothing for "unfeelable" personal health monitoring.

Serum exosomal miR-122 as a potential diagnostic and prognostic biomarker of colorectal cancer with liver metastasis.

Background: Liver is the most common site for metastatic spread of CRC at the time of diagnosis which leads to high mortality. This study aimed to identify novel circulating exosomal miRNAs as biomarkers of colorectal cancer (CRC) with liver metastasis (LM). Materials and methods: Candidate miRNAs were selected through integrated analysis of Gene Expression Omnibus (GEO) database as well as clinical samples. Exosomes isolated from serum and cultured media were identified by using transmission electron microscopy (TEM) and western blot. The expression levels and diagnostic value of candidate miRNAs were further tested and validated through qRT-PCR and receiver operating characteristic curve (ROC) analysis. The association of candidate miRNA expressions with patients' prognosis was analyzed with logistic regression and Cox proportional hazards regression models. Results: After integrated analysis of three GEO datasets and clinical samples, miR-122 was discovered to be remarkably overexpressed in tissues of CRC patients. Then we revealed that elevated serum miR-122 was tumor-derived by being packaged into exosomes. The expressions of serum exosomal miR-122 were significantly upregulated in CRC patients, especially in those with LM. Serum exosomal miR-122 expressions could differentiate CRC patients with LM from healthy controls and patients without LM with area under the ROC curve (AUC) of 0.89 and 0.81. Uni- and multivariate logistic regression showed that serum exosomal miR-122 was an independent prognostic indicator of CRC patients. Conclusions: Serum exosomal miR-122 was a novel potential diagnostic and prognostic biomarker in CRC patients with LM.

Prediction of essential genes in prokaryote based on artificial neural network.

BACKGROUND: Rapid identification of new essential genes is necessary to understand biological mechanisms and identify potential targets for antimicrobial drugs. Many computational methods have been proposed. OBJECTIVES: To construct an essential genes classifier which satisfies more different organisms, and to study the redundancy of features used in the prediction of essential genes. METHODS: We designed a 57-12-1 artificial neural network model to predict the essential genes of 31 prokaryotic genomes. Four methods including self-predictions of each organism, the leave-one-genome-out method, predicting all by one organism, and self-predictions of all organisms were applied to assess the predictive performance. Additionally, the 57 features used in the artificial neural network model were analyzed by weighted principal component analysis to screen the key features strongly related to the essentiality of genes. RESULTS: Our results compared with previous researches indicate that our models had better generalizability. Furthermore, this method reduced the features to 29 while maintaining stable prediction performance overall, suggesting that some features are redundant for gene essentiality, and the screened features contained more important biological information for gene essentiality. CONCLUSION: This study showed the effectiveness and generalizability of our artificial neural network model. In addition, the screened features could be used as key features in computational analysis and biological experiments.