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Abstract Background Hearing loss in children and adolescents is attracting increasing attention as a growing public health problem. This study aimed to analyze the burden of hearing loss in children and adolescents from 1990 to 2021 to provide a new basis for further epidemiological research, disease prevention, and public health policy development. Methods The prevalence and years lived with disability (YLDs) of hearing loss in children and adolescents from 1990 to 2021 at the global, regional, and national levels were extracted from the Global Burden of Disease 2021 database. The estimated annual percentage change (EAPC) was used to assess trends in prevalence and YLDs. Pearson correlation analysis was used to assess the relationships between sociodemographic index (SDI) and prevalence and YLDs. Results In 2021, approximately 97.83 million children and adolescents under the age of 20 years were affected by hearing loss globally, resulting in approximately 3.91 million YLDs. From 1990 to 2021, the prevalence rate increased from 3537 per 100,000 to 3711 per 100,000, with an EAPC of 0.15% (95% CI: 0.12–0.17). The burden of hearing loss was greater in low-middle-SDI region and low-SDI region. Mild hearing loss accounted for 62.1% of the total cases and was the predominant type of hearing loss. Otitis media was the leading preventable cause of hearing loss, with 46.9% of hearing loss attributed to otitis media. Moreover, in children under 5 years of age, 68.7% of hearing loss was attributed to otitis media. Pearson correlation analysis revealed that the prevalence rates and YLDs rates of hearing loss were negatively correlated with the SDI (R = -0.57, P

Objectives: Artificial intelligence (AI) with white light imaging (WLI) is not enough for detecting non-polypoid colorectal polyps and it still has high false positive rate (FPR). We developed AIs using blue laser imaging (BLI) and linked color imaging (LCI) to detect them with specific learning sets (LS). Methods: The contents of LS were as follows, LS (WLI): 1991 WLI images of lesion of 2-10 mm, LS (IEE): 5920 WLI, BLI, and LCI images of non-polypoid and small lesions of 2-20 mm. LS (IEE) was extracted from videos and included both in-focus and out-of-focus images. We designed three AIs as follows: AI (WLI) finetuned by LS (WLI), AI (IEE) finetuned by LS (WLI)+LS (IEE), and AI (HQ) finetuned by LS (WLI)+LS (IEE) only with images in focus. Polyp detection using a test set of WLI, BLI, and LCI videos of 100 non-polypoid or non-reddish lesions of 2-20 mm and FPR using movies of 15 total colonoscopy were analyzed, compared to 2 experts and 2 trainees. Results: The sensitivity for LCI in AI (IEE) (83%) was compared to that for WLI in AI (IEE) (76%: p=0.02), WLI in AI (WLI) (57%: p

Microglia-mediated neuroinflammation and synaptic damage contribute to the pathogenesis of major depressive disorder. Coeloglossum viride var. bracteatum extract (CE) has anti-inflammatory and neuroprotective effects. Therefore, we hypothesized that CE could inhibit the pathogenesis of depression. To test this hypothesis, we evaluated the antidepressant effects of CE in a lipopolysaccharide (LPS)-induced mouse model. We showed that CE ameliorated LPS-induced depressive-like phenotypes such as increased preference for sucrose, decreased immobility, and improved willingness to move in mice. Consistently, CE reduced the levels of pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 in the brain. Mechanistically, CE transformed the phenotypic polarization of microglia by inhibiting the enhancement of aerobic glycolysis and improving oxidative phosphorylation, mediated by the HIF-1α/PKM2 signaling axis. CE reversed the reduction in synaptic proteins, dendritic spines, and neuronal loss. Thus, CE may alleviate LPS-induced depression through anti-inflammation, alteration of microglial energy metabolism and protection of synaptic plasticity, thus highlighting its potential as antidepressant.

Wood-rotting fungi are organisms that can decompose wood substrates and extract nutrients from them to support their growth. They play a crucial role in the material cycle of forest ecosystems. The genus Pluteus plays a significant role in wood decomposition. In this study, the morphology and molecular systematics of the sect. Celluloderma of the genus Pluteus were carried out. Pluteus brunneodiscus was identified as a new species, along with the discovery of two new records, P. cystidiosus and P. chrysophlebius, and a common species, P. romellii. Pluteus brunneodiscus is characterized by the brown center of the pileus that transitions to white towards the margins, with the surface cracking to form irregular granules. It is typically found in Populus forests growing on decomposing twigs or wood chips. Line drawings, color photographs, and phylogenetic analyses of related species within the genus Pluteus accompany the descriptions of these four species. The analyses are based on ITS + TEF1-α sequence data. Finally, a key for the twenty species within the sect. Celluloderma of the genus Pluteus, which has been documented in China, is provided.

BackgroundMetagenomic next-generation sequencing (mNGS) has been widely reported to identify pathogens in infectious diseases (IDs). In this work, we intended to investigate the diagnostic value and clinical acceptance of paired-samples mNGS as compared to the culture method.MethodsA total of 361 patients with suspected infection were retrospectively included. With reference to the clinical diagnosis, we compared the diagnostic performance and clinical acceptance in pathogen detection between mNGS and culture tests. Moreover, the pathogen concordance of paired blood and respiratory tract (RT) samples in mNGS assay was investigated.ResultsAmong 511 samples, 62.04% were shown to be pathogen positive by mNGS, and that for clinical diagnosis was 51.86% (265/511). When compared to culture assay (n = 428), mNGS had a significantly higher positivity rate (51.87% vs. 33.18%). With reference to the clinical diagnosis, the sensitivity of mNGS outperformed that of culture (89.08% vs. 56.72%). Importantly, mNGS exhibited a clinically accepted rate significantly superior to that of culture. In addition, the mNGS result from 53 paired blood and RT samples showed that most pairs were pathogen positive by both blood and RT, with pathogens largely being partially matched.ConclusionThrough this large-scale study, we further illustrated that mNGS had a clinically accepted rate and sensitivity superior to those of the traditional culture method in diagnosing infections. Moreover, blood and paired RT samples mostly shared partial-matched positive pathogens, especially for pathogens with abundant read numbers in RT, indicating that both blood and RT mNGS can aid the identification of pathogens for respiratory system infection.

Objectives: Metagenomic next-generation sequencing (mNGS) is a powerful tool for pathogen detection. The accuracy depends on both wet lab and dry lab procedures. The objective of our study was to assess the influence of read length and dataset size on pathogen detection. Methods: In this study, 43 clinical BALF samples, which tested positive via clinical mNGS and were consistent with the diagnosis, were subjected to re-sequencing on the Illumina NovaSeq 6000 platform. The raw re-sequencing data, consisting of 100 million (M) paired-end 150 bp (PE150) reads, were divided into simulated datasets with eight different data sizes (5 M, 10 M, 15 M, 20 M, 30 M, 50 M, 75 M, 100 M) and five different read lengths (single-end 50 bp (SE50), SE75, SE100, PE100, and PE150). Both Kraken2 and IDseq bioinformatics pipelines were employed to analyze the previously diagnosed pathogens in the simulated data. Detection of pathogens was based on read counts ranging from 1 to 10 and RPM values ranging from 0.2 to 2. Results: Our results revealed that increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection. However, a larger data sizes for mNGS require higher economic costs and longer turnaround time for data analysis. Our findings indicate 20 M reads being sufficient for SE75 mode to achieve high recall rates. Additionally, high nucleic acid loads in samples can lead to increased stability in pathogen detection efficiency, reducing the impact of sequencing strategies. The choice of bioinformatics pipelines had a significant impact on recall rates achieved in pathogen detection. Conclusions: Increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection but increase the economic and time costs of sequencing and data analysis. Currently, the 20 M reads in SE75 mode may be the best sequencing option.

Acute liver injury (ALI) is a prevalent clinical condition featured by liver inflammation and functional abnormalities resulting from various causes. Prolonged damage to liver cells can progress to chronic inflammation, fibrosis, and cirrhosis. Astragalin (AST), a natural flavonoid present in traditional medicinal and edible plants, exhibits anti-inflammatory and antioxidative properties, making it a potential therapeutic candidate for ALI. Using network pharmacology analysis, we explored the targets and pathways implicated in the regulation of AST against ALI. Our study using an ALI mouse model showed that AST effectively mitigates oxidative stress and inflammation induced by lipopolysaccharide (LPS), offering protection against LPS-induced ALI. The mechanism may involve inhibiting the tumor necrosis factor-α-driven necroptosis pathway and downregulating the hypoxia-inducible factor-1α/pyruvate kinase M2 signaling pathway, thereby suppressing enhanced glycolysis-mediated inflammatory response. Through the synergistic modulation of multiple targets and pathways, AST emerges as a promising therapeutic option for ALI, offering potential for clinical application.