NFMCLDA: Predicting miRNA-based lncRNA-disease associations by network fusion and matrix completion.

In recent years, emerging evidence has revealed a strong association between dysregulations of long non-coding RNAs (lncRNAs) and sophisticated human diseases. Biological experiments are adequate to identify such associations, but they are costly and time-consuming. Therefore, developing high-quality computational methods is a challenging and urgent task in the field of bioinformatics. This paper proposes a new lncRNA-disease association inference approach NFMCLDA (Network Fusion and Matrix Completion lncRNA-Disease Association), which can effectively integrate multi-source association data. In this approach, miRNA information is used as the transition path, and an unbalanced random walk method on three-layer heterogeneous network is adopted in the preprocessing. Therefore, more effective information between networks can be mined and the sparsity problem of the association matrix can be solved. Finally, the matrix completion method accurately predicts associations. The results show that NFMCLDA can provide more accurate lncRNA-disease associations than state-of-the-art methods. The areas under the receiver operating characteristic curves are 0.9648 and 0.9713, respectively, through the cross-validation of 5-fold and 10-fold. Data from published case studies on four diseases - lung cancer, osteosarcoma, cervical cancer, and colon cancer - have confirmed the reliable predictive potential of NFMCLDA model.

Predicting potential microbe-disease associations based on multi-source features and deep learning.

Studies have confirmed that the occurrence of many complex diseases in the human body is closely related to the microbial community, and microbes can affect tumorigenesis and metastasis by regulating the tumor microenvironment. However, there are still large gaps in the clinical observation of the microbiota in disease. Although biological experiments are accurate in identifying disease-associated microbes, they are also time-consuming and expensive. The computational models for effective identification of diseases related microbes can shorten this process, and reduce capital and time costs. Based on this, in the paper, a model named DSAE_RF is presented to predict latent microbe-disease associations by combining multi-source features and deep learning. DSAE_RF calculates four similarities between microbes and diseases, which are then used as feature vectors for the disease-microbe pairs. Later, reliable negative samples are screened by k-means clustering, and a deep sparse autoencoder neural network is further used to extract effective features of the disease-microbe pairs. In this foundation, a random forest classifier is presented to predict the associations between microbes and diseases. To assess the performance of the model in this paper, 10-fold cross-validation is implemented on the same dataset. As a result, the AUC and AUPR of the model are 0.9448 and 0.9431, respectively. Furthermore, we also conduct a variety of experiments, including comparison of negative sample selection methods, comparison with different models and classifiers, Kolmogorov-Smirnov test and t-test, ablation experiments, robustness analysis, and case studies on Covid-19 and colorectal cancer. The results fully demonstrate the reliability and availability of our model.

Three-dimensional spheroid formation of adipose-derived stem cells improves the survival of fat transplantation by enhance their therapeutic effect.

Adipose-derived stem cells (ADSCs) have important applications in basic research, especially in fat transplantation. Some studies have found that three-dimensional (3D) spheroids formed by mesenchymal stem cells have enhanced therapeutic potential. However, the fundamental basics of this effect are still being discussed. ADSCs were harvested from subcutaneous adipose tissues and 3D spheroids were formed by the automatic aggregation of ADSCs in a non-adhesive 6-well plate. Oxygen glucose deprivation (OGD) was used to simulate the transplantation microenvironment. We found that 3D culture of ADSCs triggered cell autophagy. After inhibiting autophagy by Chloroquine, the rates of apoptosis were increased. When the 3D ADSC-spheroids were re-planked, the number of senescent ADSCs decreased, and the proliferation ability was promoted. In addition, there were more cytokines secreted by 3D ADSC-spheroids including VEGF, IGF-1, and TGF-ß. After adding the conditioned medium with human umbilical vein endothelial cells (HUVECs), 3D ADSC-spheroids were more likely to promote migration, and tube formation, stimulating the formation of new blood vessels. Fat grafting experiments in nude mice also showed that 3D ADSC-spheroids enhanced survival and neovascularization of fat grafts. These results suggested that 3D spheroids culturing of ADSCs can increase the therapeutic potential in fat transplantation.

Development of a model for early differentiation of adenovirus pneumonia from Mycoplasma pneumoniae pneumonia.

Background: Adenovirus pneumonia (AVP) and Mycoplasma pneumoniae pneumonia (MPP) have similar clinical manifestations such as a high prevalence of lung consolidation, making the differential diagnosis difficult before the etiology is reported. This study aimed to compare AVP and MPP, and to build a predictive model to differentiate them early. Methods: We selected 198 cases of AVP and 876 cases of MPP. Clinical manifestations, computed tomography (CT) features, and biomarkers were compared. A logistic regression model was built to predict AVP. The area under the curve (AUC) of the receiver-operating characteristic was calculated to evaluate the discriminant ability of the prediction model. Results: Patients in the AVP group were mainly infants and toddlers, while the MPP group had more pre-school age children. The rate of hypoxemia and severe pneumonia was 3- and 11-times higher, respectively, in the AVP group than in the MPP group (5.6% vs. 1.8%, 27.8% vs. 2.5%, P<0.01). The proportion of patients with a Pediatric Logistic Organ Dysfunction-2 score ≥2 was 10 times higher in the AVP group than in the MPP group (17.4% vs. 1.7%, P<0.01). Bilateral pneumonia was present in 90.2% of the AVP group. Biomarkers, such as interleukin (IL)-2 receptor, IL-10 and lactic dehydrogenase (LDH), were considerably higher in the AVP group than in the MPP group (P<0.01). The predictive model included eight variables, namely: age, severe pneumonia, bilateral pneumonia, ground-glass attenuation, consolidation, atelectasis, C-reactive protein, and LDH. The AUC was 86.6%. Conclusions: Compared with MPP, AVP affects younger children, presents a more severe respiratory tract involvement, results in a larger range of lung lesions, and is associated with higher inflammatory biomarkers. Our predictive model includes a combination of clinical features, imaging findings, and biomarkers. It may help pediatricians in the early differentiation of AVP from MPP.

scBPGRN: Integrating single-cell multi-omics data to construct gene regulatory networks based on BP neural network.

The deterioration and metastasis of cancer involve various aspects of genomic changes, including genomic DNA changes, epigenetic modifications, gene expression, and other complex interactions. Therefore, integrating single-cell multi-omics data to construct gene regulatory networks containing more omics information is of great significance for understanding the pathogenesis of cancer. In this article, an algorithm integrating single-cell RNA sequencing data and DNA methylation data to construct a gene regulatory network based on the back-propagation (BP) neural network (scBPGRN) is proposed. This algorithm uses biweight extreme correlation coefficients to measure the correlation between factors and uses neural networks to calculate generalized weights to construct gene regulation networks. Finally, the node strength is calculated to identify the genes associated with cancer. We apply the scBPGRN algorithm to hepatocellular carcinoma (HCC) data. We construct a regulatory network and identify top-ranked genes, such as MYCBP, KLHL35, PRKCZ, and SERPINA6, as the key HCC-related genes. We analyze the top 100 genes, and the HCC-related genes are concentrated in the top 20. In addition, the single cell data is found to consist of two subpopulations. We also apply scBPGRN to two subpopulations. We analyze the top 50 genes in them, and the HCC-related genes are concentrated in the top 20. The consequences of functional enrichment analysis indicate that the gene regulatory network we have constructed is valid. Our results have been verified in several pieces of literature. This study provides a reference for the integration of single-cell multi-omics data to construct gene regulatory networks.

Lung infection of avian pathogenic Escherichia coli co-upregulates the expression of cSP-A and cLL in chickens.

The host innate defense-pathogen interaction in the lung has always been a topic of concern. The respiratory tract is a common entry route for Avian pathogenic Escherichia coli (APEC). Chicken surfactant protein A (cSP-A) and chicken lung lectin (cLL) can bind to the carbohydrate moieties of various microorganisms. Despite their detection in chickens, their role in the innate immune response is largely unknown. This study aimed to examine whether the expression levels of cSP-A and cLL in the chicken respiratory system were affected by APEC infection. A lung colonization model was established in vivo using 5-day-old specific-pathogen-free chickens infected intratracheally with APEC. The chickens were euthanized 12 h post-infection (hpi) and 1-3 days post-infection (dpi) to detect various indicators. The results of quantitative reverse transcription-polymerase chain reaction and fluorescence multiplex immunohistochemical staining showed that the mRNA and protein expression levels of cSP-A and cLL in the lung and trachea were significantly co-upregulated at 2dpi.Transcriptome RNA-sequencing analysis indicated that the inoculation with APEC AE17 at 2 dpi resulted in differential gene expression of approximately 810 genes compared with control birds, but only a few genes were expressed with astatistically significant ≧2-fold difference. cLL and cSP-A were among the significantly upregulated genes involved in innate immunity. These findings indicated that cSP-A and cLL might play an important role in lung innate host defense against APEC infection at the early stage.

Pathologic Characterization of Coinfection with Histomonas meleagridis, Marek's Disease Virus, and Subtype J Avian Leukosis Virus in Chickens.

Histomonas meleagridis is a trichomonad protozoan parasite that can cause an important poultry disease known as histomoniasis; Marek's disease virus (MDV) and subtype J avian leukosis virus (ALV-J) usually cause avian oncogenic diseases. Although these diseases have been reported in a single pathogen infection, information about their coinfection is scarce. This study reports a naturally occurring case of coinfection with H. meleagridis, MDV, and ALV-J in a local chicken flock at the age of 150 days. Necropsy revealed necrosis and swelling in the liver and spleen. Histologic analysis showed large areas of mild to severe necrosis of hepatocytes, with numerous intralesional trophozoites of H. meleagridis by H&E and periodic acid-Schiff staining; H&E staining showed pleomorphic and neoplastic lymphoid tumor cells in the liver and myeloid cells with eosinophilic cytoplasmic granules in the spleen. Coexpression of MDV and ALV-J antigens was detected in the liver by fluorescence multiplex immunohistochemistry staining. The 18S rRNA gene of H. meleagridis, meq gene of MDV, and gp85 gene of ALV-J were identified in mixed liver and spleen tissues by PCR and sequencing, respectively.

Reporte de caso­Caracterización patológica de la coinfección con Histomonas meleagridis, el virus de la enfermedad de Marek y el virus de la leucosis aviar subtipo J en pollos Histomonas meleagridis es un parásito protozoario tricomonial que puede causar una enfermedad avícola importante conocida como histomoniasis; El virus de la enfermedad de Marek (MDV) y el virus de la leucosis aviar subtipo J (ALV-J) suelen causar enfermedades oncogénicas aviares. Aunque estas enfermedades se han reportado como infecciones patógenas separadas, la información sobre coinfección es escasa. Este estudio reporta un caso natural de coinfección con H. meleagridis, el virus de la enfermedad de Marek y el virus de la leucosis aviar subtipo J en una parvada de pollos local a la edad de 150 días. La necropsia reveló necrosis e inflamación del hígado y el bazo. El análisis histológico mostró grandes áreas de necrosis de hepatocitos de leve a severa, con numerosos trofozoítos intralesionales de H. meleagridis por tinción de hematoxilina y eosina y por tinción de ácido periódico-Schiff. La tinción de hematoxilina y eosina mostró células linfoides neoplásicas y pleomórficas en el hígado y en el bazo presencia de células mieloides con gránulos citoplásmicos eosinofílicos. La coexpresión de antígenos del virus de Marek y de la leucosis aviar subtipo J se detectó en el hígado mediante tinción inmunohistoquímica de fluorescencia múltiple. El gene de ARNr 18S de H. meleagridis, el gene meq del virus de Marek y el gene gp85 del virus de la leucosis aviar subtipo J se identificaron en tejidos mixtos de hígado y bazo mediante PCR y secuenciación, respectivamente.

Resistance Mechanism to Metsulfuron-Methyl in Polypogon fugax.

Polypogon fugax is a common winter weed in China and other Asia countries. We have previously found a P. fugax biotype (R) resistant to acetyl co-enzyme A carboxylase (ACCase) herbicides also cannot be effectively controlled by some acetolactate synthase (ALS) herbicides. This study evaluated the level of resistance to four ALS herbicides (metsulfuron-methyl, chlorsulfuron, monosulfuron, pyribambenz isopropyl) in the R biotype and the associated resistance mechanism. The R biotype exhibited moderate level of resistance to metsulfuron-methyl (6.0-fold) compared with the sensitive biotype (S). Sequence analysis of ALS gene revealed that two ALS genes existed in P. fugax. However, no substitution associated with ALS resistance mechanism were found in ALS genes between the S and R biotypes. The activity of ALS enzyme isolated from the R biotype was inherently higher and less sensitive to metsulfuron-methyl than the S biotype. Glutathione S-transferases (GST) activity was also less sensitive to metsulfuron-methyl in the R than as the S biotypes. Malathion, a cytochrome P450 (CYP) monooxygenase inhibitor, had much greater synergistic effect with metsulfuron-methyl on the R than as the S plants, reducing the ED50 value (herbicide dose to inhibit growth by 50%) of metsulfuron-methyl by 23- and 6-fold, respectively, suggesting that CYP mediated enhanced metabolism might contribute to the resistance to ALS herbicides. These results suggest that metsulfuron-methyl resistance in the R biotype was associated with the up-regulated ALS enzymatic activity and the GST and CYP-mediated enhanced herbicide metabolism.

Photoelectrochemical determination of the activity of histone acetyltransferase and inhibitor screening by using MoS2 nanosheets.

The enzyme histone acetyltransferase (HAT) catalyzes the acetylation of a substrate peptide, and acetyl coenzyme A is converted to coenzyme A (CoA). A photoelectrochemical method is described for the determination of the HAT activity by using exfoliated MoS2 nanosheets, phos-tag-biotin, and ß-galactosidase (ß-Gal) based signal amplification. The MoS2 nanosheets are employed as the photoactive material, graphene nanosheets as electron transfer promoter, gold nanoparticles as recognition and capture reagent for CoA, and phos-tag-biotin as the reagent to link CoA and ß-Gal. The enzyme ß-Gal catalyzes the hydrolysis of substrate O-galactosyl-4-aminophenol to generate free 4-aminophenol which is a photoelectrochemical electron donor. The photocurrent increases with the activity of HAT. Under optimal conditions, the response is linear in the 0.3 to 100 nM activity range, and the detection limit is 0.14 nM (at S/N = 3). The assay was applied to HAT inhibitor screening, specifically for the inhibitors C646 and anacardic acid. The IC50 values are 0.28 and 39 µM, respectively. The method is deemed to be a promising tool for epigenetic research and HAT-targeted cancer drug discovery. Graphical abstract Histone acetyltransferase was detected using a sensitive photoelectrochemical method using MoS2 nanosheets as photoactive material.

Amplified electrochemical immunoassay for 5-methylcytosine using a nanocomposite prepared from graphene oxide, magnetite nanoparticles and ß-cyclodextrin.

A nanocomposite was prepared from ß-cyclodextrin (ß-CD) functionalized graphene oxide and magnetic nanoparticles (GO/Fe3O4/ß-CD). In parallel, a polyamidoamine dendrimer conjugated to avidinylated alkaline phosphatase (PAMAM-avidin-ALP) was prepared and exploited as a signal amplification unit in a voltammetric immunoassay for 5-methylcytosine (5mC) in genomic DNA. The GO/Fe3O4/ß-CD as a substrate material exhibited good solubility, electrical conductivity and large surface. This is beneficial for the further modification of antibodies (Ab) by host-guest interaction and amide bonds. By taking advantage of three-dimensional structure to capture avidin-ALP by amide linkages, PAMAM was used as a catalytic signal amplification element in this assay. Under the optimized condition and at a typical working potential of 0.94 V, the response to 5mC is linear in the 0.01-50 nM concentration range with a detection limit of 3.2 pM (at S/N = 3). The method is stable, selective and reproducible. It was applied to the determination of 5mC in genomic DNA of human tissue. Graphical abstract An electrochemical immunoassay was constructed for 5-methylcytosine detection based on nanocomposite of graphene oxide, magnetite nanoparticles and ß-cyclodextrin, and enzymatic signal amplification.

c-Met and ERß expression differences in basal-like and non-basal-like triple-negative breast cancer.

Basal-like breast cancer (BLBC) and triple-negative breast cancer (TNBC) are two entities of breast cancer that share similar poor prognosis. Even though both cancers have overlaps, there are still some differences between those two types. It has been reported that the c-Met high expression was associated with poor prognosis not only in breast cancer but also in many other cancers. The role of ERß in pathogenesis and treatment of breast cancer has remained controversial. In this study, we firstly distinguished basal-like from nonbasal-like cancer patients in TNBC patients using CK5/6 and EGFR as markers and next determined the relationship of basal-like breast cancer with c-Met or ERß expression levels and prognosis in TNBC patients. One hundred twenty-seven patients who had been diagnosed with TNBC were enrolled. The clinical and pathological characteristics of the patients were recorded. The expression of EGFR, CK5/6, ERß, and c-Met were evaluated with immunohistochemical methods using paraffin blocks. The median age of patients was 50.7 years. CK5/6 immunopositivity was 31.5 % (40/127), and EGFR was 40.2 % (51/127). Of the TNBC cases, 55.1 % (71/127) were positive for either CK5/6 or EGFR and were thus classified as basal-like breast cancer. C-Met (P < 0.001) and ERß (P = 0.002) overexpression, small tumor sizes, a ductal subtype, and high-grade tumor were significantly correlated with BLBC. High c-Met expression was detected in 43.3 % patients. Metastatic lymph nodes and tumor size (>5 cm), which were both important prognostic predictors, were significantly associated with recurrence and mortality. BLBC typically demonstrates a unique profile. CK5/6 and EGFR expression combination indicates a higher basal-like phenotype possibility. The expression of c-Met and ERß were significantly related to the basal-like phenotype. The classical markers, lymph node metastasis, and tumor size were found to have important prognostic value. However, high c-Met expression and basal-like phenotypes did not show a direct correlation with poor prognosis.