Predicting lncRNA-disease associations based on combining selective similarity matrix fusion and bidirectional linear neighborhood label propagation.

Recent studies have revealed that long noncoding RNAs (lncRNAs) are closely linked to several human diseases, providing new opportunities for their use in detection and therapy. Many graph propagation and similarity fusion approaches can be used for predicting potential lncRNA-disease associations. However, existing similarity fusion approaches suffer from noise and self-similarity loss in the fusion process. To address these problems, a new prediction approach, termed SSMF-BLNP, based on organically combining selective similarity matrix fusion (SSMF) and bidirectional linear neighborhood label propagation (BLNP), is proposed in this paper to predict lncRNA-disease associations. In SSMF, self-similarity networks of lncRNAs and diseases are obtained by selective preprocessing and nonlinear iterative fusion. The fusion process assigns weights to each initial similarity network and introduces a unit matrix that can reduce noise and compensate for the loss of self-similarity. In BLNP, the initial lncRNA-disease associations are employed in both lncRNA and disease directions as label information for linear neighborhood label propagation. The propagation was then performed on the self-similarity network obtained from SSMF to derive the scoring matrix for predicting the relationships between lncRNAs and diseases. Experimental results showed that SSMF-BLNP performed better than seven other state of-the-art approaches. Furthermore, a case study demonstrated up to 100% and 80% accuracy in 10 lncRNAs associated with hepatocellular carcinoma and 10 lncRNAs associated with renal cell carcinoma, respectively. The source code and datasets used in this paper are available at: https://github.com/RuiBingo/SSMF-BLNP.

4 mC site recognition algorithm based on pruned pre-trained DNABert-Pruning model and fused artificial feature encoding.

DNA 4 mC plays a crucial role in the genetic expression process of organisms. However, existing deep learning algorithms have shortcomings in the ability to represent DNA sequence features. In this paper, we propose a 4 mC site identification algorithm, DNABert-4mC, based on a fusion of the pruned pre-training DNABert-Pruning model and artificial feature encoding to identify 4 mC sites. The algorithm prunes and compresses the DNABert model, resulting in the pruned pre-training model DNABert-Pruning. This model reduces the number of parameters and removes redundancy from output features, yielding more precise feature representations while upholding accuracy.Simultaneously, the algorithm constructs an artificial feature encoding module to assist the DNABert-Pruning model in feature representation, effectively supplementing the information that is missing from the pre-trained features. The algorithm also introduces the AFF-4mC fusion strategy, which combines artificial feature encoding with the DNABert-Pruning model, to improve the feature representation capability of DNA sequences in multi-semantic spaces and better extract 4 mC sites and the distribution of nucleotide importance within the sequence. In experiments on six independent test sets, the DNABert-4mC algorithm achieved an average AUC value of 93.81%, outperforming seven other advanced algorithms with improvements of 2.05%, 5.02%, 11.32%, 5.90%, 12.02%, 2.42% and 2.34%, respectively.

LUNCRW: Prediction of potential lncRNA-disease associations based on unbalanced neighborhood constraint random walk.

Accumulating evidence suggests that long non-coding RNAs (lncRNAs) are associated with various complex human diseases. They can serve as disease biomarkers and hold considerable promise for the prevention and treatment of various diseases. The traditional random walk algorithms generally exclude the effect of non-neighboring nodes on random walking. In order to overcome the issue, the neighborhood constraint (NC) approach is proposed in this study for regulating the direction of the random walk by computing the effects of both neighboring nodes and non-neighboring nodes. Then the association matrix is updated by matrix multiplication for minimizing the effect of the false negative data. The heterogeneous lncRNA-disease network is finally analyzed using an unbalanced random walk method for predicting the potential lncRNA-disease associations. The LUNCRW model is therefore developed for predicting potential lncRNA-disease associations. The area under the curve (AUC) values of the LUNCRW model in leave-one-out cross-validation and five-fold cross-validation were 0.951 and 0.9486 ± 0.0011, respectively. Data from published case studies on three diseases, including squamous cell carcinoma, hepatocellular carcinoma, and renal cell carcinoma, confirmed the predictive potential of the LUNCRW model. Altogether, the findings indicated that the performance of the LUNCRW method is superior to that of existing methods in predicting potential lncRNA-disease associations.

Canine Parvovirus Infections in Taiwanese Pangolins (Manis pentadactyla pentadactyla).

Canine parvovirus type 2 (CPV-2) is among the most important and highly contagious pathogens that cause enteric or systemic infections in domestic and nondomestic carnivores. However, the spillover of CPV-2 to noncarnivores is rarely mentioned. Taiwanese pangolins (Manis pentadactyla pentadactyla) are threatened due to habitat fragmentation and prevalent animal trafficking. Interactions between Taiwanese pangolins, humans, and domestic animals have become more frequent in recent years. However, information about the susceptibility of pangolins to common infectious agents of domestic animals has been lacking. From October 2017 to June 2019, 4 pangolins that were rescued and treated in wildlife rescue centers in central and northern Taiwan presented with gastrointestinal signs. Gross and histopathological examination revealed the main pathologic changes to be necrotic enteritis with involvement of the crypts in all intestinal segments in 2 pangolins. By immunohistochemistry for CPV-2, there was positive labeling of cryptal epithelium throughout the intestine, and immunolabeling was also present in epidermal cells adjacent to a surgical amputation site, and in mononuclear cells in lymphoid tissue. The other 2 pangolins had mild enteritis without crypt involvement, and no immunolabeling was detected. The nucleic acid sequences of polymerase chain reaction (PCR) amplicons from these 4 pangolins were identical to a Chinese CPV-2c strain from domestic dogs. Quantitative PCR revealed a higher ratio of CPV-2 nucleic acid to internal control gene in the 2 pangolins with severe intestinal lesions and positive immunoreactivity. Herein, we present evidence of CPV-2 infections in pangolins.

Prediction of miRNA-disease associations based on strengthened hypergraph convolutional autoencoder.

Most existing graph neural network-based methods for predicting miRNA-disease associations rely on initial association matrices to pass messages, but the sparsity of these matrices greatly limits performance. To address this issue and predict potential associations between miRNAs and diseases, we propose a method called strengthened hypergraph convolutional autoencoder (SHGAE). SHGAE leverages multiple layers of strengthened hypergraph neural networks (SHGNN) to obtain robust node embeddings. Within SHGNN, we design a strengthened hypergraph convolutional network module (SHGCN) that enhances original graph associations and reduces matrix sparsity. Additionally, SHGCN expands node receptive fields by utilizing hyperedge features as intermediaries to obtain high-order neighbor embeddings. To improve performance, we also incorporate attention-based fusion of self-embeddings and SHGCN embeddings. SHGAE predicts potential miRNA-disease associations using a multilayer perceptron as the decoder. Across multiple metrics, SHGAE outperforms other state-of-the-art methods in five-fold cross-validation. Furthermore, we evaluate SHGAE on colon and lung neoplasms cases to demonstrate its ability to predict potential associations. Notably, SHGAE also performs well in the analysis of gastric neoplasms without miRNA associations.

Conductive Polymer (Graphene/PPy)-BiPO4 Composite Applications in Humidity Sensors.

In this particular experiment, a chain of conductive polymer graphene/polypyrrole (Gr/PPy) and BiPO4-or (Gr/PPy)-BiPO4-materials were prepared and used as moisture-sensitive materials. The structure and morphology of the conductive polymer (Gr/PPy)-BiPO4 materials were analyzed using an X-ray diffractometer, scanning electron microscopy, transmission electron microscopy, and energy-dispersive X-ray spectroscopy. Moreover, properties such as hysteresis loop, impedance, sensing response, and response and recovery time were calculated and evaluated using an inductance-capacitance-resistance analyzer. The data expressed that PPy/BiPO4, as prepared in this study, exhibited excellent sensing properties, with impedance changing by only a few orders of range. Furthermore, the response time and time of recovery were 340 s and 60 s, respectively, and negligible humidity hysteresis occurred at different relative humidities. Therefore, conductive PPy/BiPO4, as prepared in the present study, is an excellent candidate for application in humidity sensors.

[Clinical significance of serum differential protein examination in chronic hepatitis B related liver fibrosis].

OBJECTIVE: To investigate the clinical significance of the expression of serum differential protein in patients with chronic hepatitis B (CHB) related liver fibrosis. METHODS: One hundred and ten CHB patients confirmed by liver biopsies were enrolled, 83 for modeling and 27 for verification. According to Ishak staging, 55 patients in the modeling group were with significant liver fibrosis ( F is more than or equal to 3 ) and 28 patients with normal/mild liver fibrosis ( F0-F2 ). While that in the verification group were 15 ( F is more than or equal to 3 ) and 12 ( F0-F2 ), respectively. MALDI-TOF-MS/MS was used to detect serum proteins and the spectrum for each sample was analyzed in FlexAnalysis3.0 to produce the spectrum of differential proteins. The results were compared with clinicopathologic diagnosis and the diagnosis model based on genetic algorithm was established and evaluated. RESULTS: There were 15 proteins differentially expressed in significant liver fibrosis group and normal/mild fibrosis group ( P value is less than 0.01), in which the differences on proteins 2081.73 m/z and 1944.41 m/z were the most significant. Based on these two proteins, the coordinate system was set up and the diagnosis model based on genetic algorithm was established by six characteristic peaks. After detecting 12 cases of normal/mild liver fibrosis and 15 cases of significant liver fibrosis, the results showed that the diagnostic model could identify significant fibrosis ( F is more than or equal to 3 ) and normal/mild liver fibrosis ( F0-F2 ) at 100% recognition, 94.14% prediction and 100% accuracy. CONCLUSION: Serum differential proteins examination can be used for early prediction of CHB related fibrosis. The study provides the basis for non-invasive diagnosis of hepatic fibrosis according to identifying the potential differences of the serum samples from patients with HBV related fibrosis.

Associations of cytosine deaminase gene polymorphisms with effectiveness of gemcitabine/cisplatin chemotherapy in patients of Xinjiang Uyghur and Han nationality with non-small cell lung cancer.

BACKGROUND: Cytidine deaminase (CDA) polymorphisms may affect the response to gemcitabine/cisplatin chemotherapy in patients with non-small cell lung cancer (NSCLC). This study is designed to investigate the associations of CDA-79A>C and 208G>A polymorphisms and gemcitabine/cisplatin chemotherapy effectiveness in Xinjiang Uyghur and Han patients. METHODS: This prospective cohort study enrolled consecutive patients with stage IIIb/IV NSCLC administered gemcitabine/cisplatin chemotherapy at the First Affiliated Hospital, Medical College of Shihezi University and the First People's Hospital, Kashgar Region. CDA-A79C and CDA-G208A polymorphisms were detected by direct sequencing. Progression-free survival was analyzed by the Kaplan-Meier method. Associations of A79C and G208A polymorphisms with treatment effectiveness and progression-free survival were analyzed using logistic regression and multivariate Cox regression analyses. Subgroup analyses based on ethnicity were performed. RESULTS: The study enrolled 120 patients. A79C and G208A polymorphisms followed the Hardy-Weinberg equilibrium. The frequencies of the AA, AC, and CC genotypes and the A and C alleles of A79C were 52.2%, 29.9%, 17.9%, 67.2%, and 32.8%, respectively, in Han patients and 75.4%, 18.9%, 5.7%, 84.9%, and 5.1%, respectively, in Uyghur patients. Uyghur patients had lower frequencies of A79C-AC/CC genotypes, A79C-C allele, G208A-GA genotype, and G208A-A allele (P<0.05). Compared with A79C-AA, the odds of ineffective chemotherapy were increased for A79C-AC (odds ratio [OR] 2.818; 95% confidence interval [95% CI] 1.031, 7.705; P=0.043) and A79C-CC (OR 9.864; 95% CI 1.232, 78.966; P=0.031). G208A polymorphisms did not influence chemotherapy effectiveness. Chemotherapy was more effective in Han patients than in Uyghur patients for A79C-AC and G208A-GG. Progression-free survival was longer for A79C-AA versus A79C-AC/CC (10 vs. 7 months, P=0.004) and G208A-GA/AA vs. G208A-AA (12 vs. 8 months, P=0.010). Polymorphisms of A79C (hazard ratio [HR] 1.617; 95% CI 1.009, 2.592; P=0.046) and G208A (HR 2.193; 95% CI 1.055, 4.557; P=0.035) were associated with progression-free survival. CONCLUSION: For Uyghur and Han ethnic groups, A79C and G208A polymorphisms can be used as a promising biomarker for the chemotherapy efficacy and prognosis of NSCLC.

[The relationship between the genotype of hepatitis B virus and clinical and liver pathological features of infected patients in the Zhoushan Islands, China].

OBJECTIVE: To investigate the relationship between the genotypes of hepatitis B virus and the clinical and liver pathological features of patients with chronic hepatitis in the Zhoushan Islands. METHODS: One hundred eighty HBV DNA positive chronic hepatitis patients with HBV markers were enrolled in this study. They were at least second generation Zhoushan Island residents. One hundred forty-seven of them were males and 33 were females with an average age of 39.0+/-11.3. Among the 180 patients, 17 had ASC, 57 had mild CHB, 48 moderate CHB, 9 severe CHB, 6 SHB, 39 LC, and 4 had HCC. The genotypes of their serum HBV were detected by using PCR integrated with Tagman MGB probe technology, and their serum HBV markers, HBV DNA and liver functions were also examined. Out of 180 patients, 129 accepted a liver biopsy. A pathological evaluation was then performed. RESULTS: HBVs of genotype C, 135 cases (75.0%), of B, 40 cases (22.2%), and of B+C, 5 cases (2.8%) were found among these 180 patients. No genotype A or D HBV were found. The proportions of genotype C virus were 7/17, 86/114, 34/39, 6/6 in ASC, CHB, LC and SHB patients. In the hepatocellular carcinoma patients, there were 2 each of genotype B and C. Among the 99 patients with genotype C HBV, 84 cases (84.8%) showed moderate and severe inflammation histologically in their livers and among the 30 patients with B, 7 cases (23.3%) showed moderate to severe inflammation in their livers (z = 6.47, P less than 0.01). The proportion of genotype C HBV was significantly different from that of genotype B HBV in those that showed moderate and severe (S3-4) liver fibrosis. In patients infected with genotype C HBV who had moderate and severe liver pathological changes, their clinical manifestations reflected better the histological alterations of their livers. CONCLUSION: Genotypes C, B and B+C HBV were found in CHB patients in the Zhoushan Islands of China, and type C was the predominant one. The liver pathological damage level of genotype C HBV infected patients is more serious than that of genotype B.

MicroRNA-155 silencing enhances inflammatory response and lipid uptake in oxidized low-density lipoprotein-stimulated human THP-1 macrophages.

It has been proposed that the inflammatory response of monocytes/macrophages induced by oxidized low-density lipoprotein (oxLDL) is a key event in the pathogenesis of atherosclerosis. MicroRNA-155 (miR-155) is an important regulator of the immune system and has been shown to be involved in acute inflammatory response. However, the function of miR-155 in oxLDL-stimulated inflammation and atherosclerosis remains unclear. Here, we show that the exposure of human THP-1 macrophages to oxLDL led to a marked up-regulation of miR-155 in a dose-dependent manner. Silencing of endogenous miR-155 in THP-1 cells using locked nucleic acid-modified antisense oligonucleotides significantly enhanced oxLDL-induced lipid uptake, up-regulated the expression of scavenger receptors (lectinlike oxidized LDL receptor-1, cluster of differentiation 36 [CD36], and CD68), and promoted the release of several cytokines including interleukin (IL)-6, -8, and tumor necrosis factor α (TNF-α). Luciferase reporter assay showed that targeting miR-155 promoted nuclear factor-kappa B (NF-κB) nuclear translocation and potentiated the NF-κB-driven transcription activity. Moreover, miR-155 knockdown resulted in a marked increase in the protein amount of myeloid differentiation primary response gene 88 (MyD88), an important adapter protein used by Toll-like receptors to activate the NF-κB pathway. Our data demonstrate that miR-155 serves as a negative feedback regulator in oxLDL-stimulated THP-1 inflammatory responses and lipid uptake and thus might have potential therapeutic implications in atherosclerosis.

Who survives cardiac arrest in the intensive care units?

OBJECTIVE: The aim of this study was to evaluate the factors related to outcome regarding in-intensive care unit (ICU) cardiac arrest (IICA) in a university hospital. PATIENTS AND METHODS: Adult nontraumatic ICU patients who sustained IICA were prospectively enrolled. Several patient and event-related variables, as well as outcomes, were recorded and summarized based on the revised Utstein-style template. RESULTS: A total of 202 episodes of IICA happened during the study period. Return of spontaneous circulation (ROSC) was achieved in 127 patients (62.9%), whereas the overall survival-to-discharge rate was 15.3% (31 patients). In univariate analysis, a shorter duration of resuscitation and pulseless ventricular tachycardia/ventricular fibrillation (VT/VF) as initial arrest rhythm represented better outcomes. Independent predictors of survival to hospital discharge were VT/VF as the initial rhythm (odds ratio [OR], 3.81; 95% confidence interval [CI], 1.50-9.67; P = .005), lower Acute Physiology and Chronic Health Evaluation II score (OR 0.92, 95% CI 0.87-0.98, P = .008), and shorter resuscitation durations (OR 0.91, 95% CI 0.87-0.96, P < .001). CONCLUSION: Shorter resuscitation duration and initial VT/VF are predictors for both ROSC and hospital survival, whereas lower Acute Physiology and Chronic Health Evaluation II scores predict the latter.