Phylogenetic and Morphological Evidence for Three New Species of Diaporthales (Ascomycota) from Fujian Province, China.

Members of the fungal order Diaporthales are sac fungi that include plant pathogens (the notorious chestnut blight fungus), as well as saprobes and endophytes, and are capable of colonizing a wide variety of substrates in different ecosystems, habitats, and hosts worldwide. However, many Diaporthales species remain unidentified, and various inconsistencies within its taxonomic category remain to be resolved. Here, we aimed to identify and classify new species of Diaporthales by using combined morphological and molecular characterization and coupling this information to expand our current phylogenetic understanding of this order. Fungal samples were obtained from dead branches and diseasedleaves of Camellia (Theaceae) and Castanopsis (Fagaceae) in Fujian Province, China. Based on morphological characteristics and molecular phylogenetic analyses derived from the combined nucleotide sequences of loci of the internal transcribed spacer regions with the intervening 5.8S nrRNA gene (ITS), the 28S large subunit of nuclear ribosomal RNA gene (LSU), the translation elongation factor 1-α gene (tef1), the partial beta-tubulin gene (tub2), and partial RNA polymerase II second-largest subunit gene (rpb2), three new species of Diaporthales were identified and characterized. They are as follows: Chrysofolia camelliae sp. nov., Dendrostoma castanopsidis sp. nov., and Pseudoplagiostoma wuyishanense sp. nov. They are described and illustrated. This study extends our understanding of species diversity within the Diaporthales.

LOC102553417 silencing facilitates the apoptosis of hepatic stellate cells via the miR­30e/MTDH axis.

Hepatic fibrosis is an inevitable pathological process in the progression of multiple chronic liver diseases and remains a major challenge in the treatment of liver diseases. The purpose of the present study was to demonstrate whether silencing of the long non­coding RNA LOC102553417 promoted hepatic stellate cell (HSC) apoptosis via the microRNA (miR)­30e/metadherin (MTDH) axis. A LOC102553417 silencing lentivirus was constructed and transduced into HSC­T6 cells. After confirming the silencing efficiency by reverse transcription­quantitative PCR, cell proliferation was assessed using the Cell Counting Kit­8 assay and apoptosis was assessed using flow cytometry. The interaction between LOC102553417 and miR­30e, and that between miR­30e and MTDH, was demonstrated using the dual­luciferase reporter assay and RNA binding protein immunoprecipitation. The apoptosis of HSC­T6 cells was detected after transfection of miR­30e mimics and inhibitors with or without silencing LOC102553417. Silencing of LOC102553417 curbed HSC­T6 cell proliferation and expedited their apoptosis. LOC102553417 was demonstrated to target miR­30e, whereas miR­30e targeted MTDH. In addition, LOC102553417 silencing significantly upregulated miR­30e expression levels, and significantly downregulated MTDH mRNA and protein expression levels, which resulted in a significantly reduced p­Akt/Akt ratio and significantly elevated p53 protein expression levels. Transfection with miR­30e mimic alone significantly enhanced HSC­T6 cell apoptosis and inhibits LOC102553417 and MTDH expressions, In addition, miR­30e mimic expedites the apoptosis of HSCs stimulated by LOC102553417 silencing; consistent results were obtained by reverse validation of miR­30e inhibitor. In conclusion, the present study demonstrated that LOC102553417 silencing stimulated the apoptosis of HSCs via the miR­30e/MTDH axis.

Harris hawks optimization algorithm and BP neural network for ultra-wideband indoor positioning.

Traditional back propagation neural networks (BPNNs) for ultrawideband (UWB) indoor localization can effectively improve localization accuracy, although there is high likelihood of becoming trapped in nearby minima. To solve this problem, the random weights and thresholds of the BPNN are optimized using the Harris Hawks optimization algorithm (HHO) to obtain the optimal global solution to enhance the UWB indoor positioning accuracy and NLOS resistance. The results show that the predicted trajectory of the HHO and BPNN hybrid algorithm (HHO-BP) matches the actual position in the two-dimensional localization scenario with four base stations; the optimized average positioning error is effectively reduced in both indoor LOS and NLOS environments. In the LOS environment, the total mean error of the traditional BPNN algorithm is 6.52 cm, which is 26.99% better than the UWB measurement error; in the NLOS environment, the total mean error of the conventional BPNN is 14.82 cm, which is 50.08% better than the UWB measurement error. The HHO-BP algorithm is further optimized on this basis, and the total mean error in the LOS environment is 4.50 cm, which is 22.57% better than the conventional BPNN algorithm; in the NLOS environment, the total mean error is 9.56 cm, which is 17.54% better than the conventional BPNN algorithm. The experimental findings suggest that the approach has greater calibration accuracy and stability than BPNN, making it a viable choice for scenarios requiring high positional precision.

Prevalence and molecular characterization of common thalassemia among people of reproductive age in the border area of Guangxi-Yunnan-Guizhou province in Southwestern China.

Objectives: Thalassemia, the most common global monogenetic disorder, is highly prevalent in southern China. Epidemiological and molecular characterization of thalassemia is important for designing appropriate prevention strategies in high-risk areas, especially the border area of Guangxi-Yunnan-Guizhou province in southwestern China.Methods: We recruited 38812 reproductive age couples and screened them for thalassemia. Routine blood tests as well as hemoglobin components and levels were evaluated. In addition, suspected thalassemia were identified by gap polymerase chain reaction (Gap-PCR) and PCR-based reverse dot blot (PCR-RDB).Results: The overall prevalence of thalassemia was 26.76%. Specifically, incidences of α-thalassemia, ß-thalassemia, and concurrent α- and ß-thalassemia were 17.52%, 6.92%, and 2.32%, respectively. The diagnosed α-thalassemia anomalies were associated with six gene mutations and 25 genotypes. The ß-thalassemia anomalies were associated with 12 gene mutations and 15 genotypes. Moreover, among the 1799 concurrent mutated α- and ß-thalassemia genes, 95 different genotypes were identified. Couples in which both partners were positive for α-thalassemia and ß-thalassemia isotypes were 8.80% and 2.08%, respectively. The proportion of couples at a risk of having children with thalassemia major or intermedia was high.Conclusions: This study elucidates on the prevalence and molecular characterization of thalassemia in the border area of Guangxi-Yunnan-Guizhou provinces. These findings provide valuable baseline data for genetic counseling and prenatal diagnosis, with the overarching goal of preventing and controlling severe thalassemia.

Potential lncRNA Biomarkers for HBV-Related Hepatocellular Carcinoma Diagnosis Revealed by Analysis on Coexpression Network.

BACKGROUND: Increasing evidence demonstrated that long noncoding RNA (lncRNA) could affect inflammatory tumor immune microenvironment by modulating gene expression and could be used as a biomarker for HBC-related hepatocellular carcinoma (HCC) but still needs further research. The aim of the present study was to determine an lncRNA signature for the diagnosis of HBV-related HCC. METHODS: HBV-related HCC expression profiles (GSE55092, GSE19665, and GSE84402) were abstracted from the GEO (Gene Expression Omnibus) data resource, and R package limma and RobustRankAggreg were employed to identify common differentially expressed genes (DEGs). Using machine learning, optimal diagnostic lncRNA molecular markers for HBV-related HCC were identified. The expression of candidate lncRNAs was cross-validated in GSE121248, and an ROC (receiver operating characteristic) curve of lncRNA biomarkers was carried out. Additionally, a coexpression network and functional annotation was built, after which a PPI (protein-protein interaction) network along with module analysis were conducted with the Cytoscape open source software. RESULT: A total of 38 DElncRNAs and 543 DEmRNAs were identified with a fold change larger than 2.0 and a P value < 0.05. By machine learning, AL356056.2, AL445524.1, TRIM52-AS1, AC093642.1, EHMT2-AS1, AC003991.1, AC008040.1, LINC00844, and LINC01018 were screened out as optional diagnostic lncRNA biosignatures for HBV-related HCC. The AUC (areas under the curve) of the SVM (support vector machine) model and random forest model were 0.957 and 0.904, respectively, and the specificity and sensitivity were 95.7 and 100% and 94.3 and 86.5%, respectively. The results of functional enrichment analysis showed that the integrated coexpressed DEmRNAs shared common cascades in the p53 signaling pathway, retinol metabolism, PI3K-Akt signaling cascade, and chemical carcinogenesis. The integrated DEmRNA PPI network complex was found to be comprised of 87 nodes, and two vital modules with a high degree were selected with the MCODE app. CONCLUSION: The present study identified nine potential diagnostic biomarkers for HBV-related HCC, all of which could potentially modulated gene expression related to inflammatory conditions in the tumor immune microenvironment. The functional annotation of the target DEmRNAs yielded novel evidence in evaluating the precise functions of lncRNA in HBV-related HCC.

Psychometric properties of the metacognitions about smartphone use questionnaire (MSUQ) in Chinese college students.

AIMS: Over the last ten years, several studies investigating the role of metacognitions in addictive behaviors, including technological addictions, have been published. Problematic Smartphone use has been conceptualized as a behavioural addiction and a psychometrically sound self-report measure to assess metacognitions about PSU has been recently published. The objective of this study was to evaluate some psychometric properties (e.g., factor structure, reliability, and validity) of the Chinese Metacognitions about Smartphone Use Questionnaire (Chinese MSUQ). METHODS: A sample of 698 undergraduates (F = 54.70%, mean age = 19.89 ±â€¯1.38 years) were enrolled in China. An exploratory factor analysis was first performed in a randomly allocated subsample of 349 participants. A confirmatory factor analysis was then computed on a second subsample of 349 participants to test its fitting with the identified factor structure. Internal consistency and predictive validity were verified. RESULTS: The result of exploratory factor analysis showed a 2-factor structure, which consists of positive metacognitions concerning emotional and cognitive regulation and social advantages of smartphone use (MSUQ-PM) and negative metacognitions about uncontrollability and cognitive harm of smartphone use (MSUQ-NM). The confirmatory factor analysis indicated that the 2-factor structure of Chinese MSUQ had appropriate fit. Cronbach's Alphas ranged from 0.90 to 0.92. Additionally, regression analysis showed that MSUQ-PM and MSUQ-NM positively predicted PSU. Notably, MSUQ-NM is a stronger predictor of PSU compared with MSUQ-PM, with a rescaled importance of 86.36%. CONCLUSIONS: The Chinese MSUQ has appropriate psychometric properties, suggesting it is a reliable instrument to assess metacognitions about smartphone use in the Chinese context.