Explore the vast range of titles available.

Abstract Background Metagenomic next-generation sequencing (mNGS) was suggested to potentially replace traditional microbiological methodology because of its comprehensiveness. However, clinical experience with application of the test is relatively limited. Methods From April 2017 to December 2017, 511 specimens were collected, and their retrospective diagnoses were classified into infectious disease (347 [67.9%]), noninfectious disease (119 [23.3%]), and unknown cases (45 [8.8%]). The diagnostic performance of pathogens was compared between mNGS and culture. The effect of antibiotic exposure on detection rate was also assessed. Results The sensitivity and specificity of mNGS for diagnosing infectious disease were 50.7% and 85.7%, respectively, and these values outperformed those of culture, especially for Mycobacterium tuberculosis (odds ratio [OR], 4 [95% confidence interval {CI}, 1.7-10.8]; P < .01), viruses (mNGS only; P < .01), anaerobes (OR, ∞ [95% CI, 1.71-∞]; P < .01) and fungi (OR, 4.0 [95% CI, 1.6-10.3]; P < .01). Importantly, for mNGS-positive cases where the conventional method was inconclusive, 43 (61%) cases led to diagnosis modification, and 41 (58%) cases were not covered by empirical antibiotics. For cases where viruses were identified, broad-spectrum antibiotics were commonly administered (14/27), and 10 of 27 of these cases were suspected to be inappropriate. Interestingly, the sensitivity of mNGS was superior to that of culture (52.5% vs 34.2%; P < .01) in cases with, but not without, antibiotic exposure. Conclusions mNGS could yield a higher sensitivity for pathogen identification and is less affected by prior antibiotic exposure, thereby emerging as a promising technology for detecting infectious diseases.

The coastal zone is abundant in natural resources but has become increasingly fragile in recent years due to climate change and extensive, improper exploitation. Accurate land use and land cover (LULC) mapping of coastal zones using remotely sensed data is crucial for monitoring environmental changes. Traditional classification methods based on statistical learning require significant spectral differences between ground objects. However, state-of-the-art end-to-end deep learning methods can extract advanced features from remotely sensed data. In this study, we employed ResNet50 as the feature extraction network within the U-Net architecture to achieve accurate classification of coastal areas and assess the model’s performance. Experiments were conducted using Gaofen-2 (GF-2) high-resolution remote sensing data from Shuangyue Bay, a typical coastal area in Guangdong Province. We compared the classification results with those obtained from two popular deep learning models, SegNet and DeepLab v3+, as well as two advanced statistical learning models, Support Vector Machine (SVM) and Random Forest (RF). Additionally, this study further explored the significance of Gray Level Co-occurrence Matrix (GLCM) texture features, Histogram Contrast (HC) features, and Normalized Difference Vegetation Index (NDVI) features in the classification of coastal areas. The research findings indicated that under complex ground conditions, the U-Net model achieved the highest overall accuracy of 86.32% using only spectral channels from GF-2 remotely sensed data. When incorporating multiple features, including spectrum, texture, contrast, and vegetation index, the classification accuracy of the U-Net algorithm significantly improved to 93.65%. The major contributions of this study are twofold: (1) it demonstrates the advantages of deep learning approaches, particularly the U-Net model, for LULC classification in coastal zones using high-resolution remote sensing images, and (2) it analyzes the contributions of spectral and spatial features of GF-2 data for different land cover types through a spectral and spatial combination method.

Pleural effusion (PE) is commonly observed in advanced lung cancer and was suggested to contain both cell-free tumor DNA and tumor cells. Molecular profiling of PE represents a minimally invasive approach of detecting tumor driver mutations for clinical decision making, especially when tumor tissues are not available. The objective of this study is to investigate the efficacy and precision of detecting gene alterations in PE samples to address the feasibility in clinical use. Sixty-three metastatic lung cancer patients with (n=30, cohort 1) or without (n=33, cohort 2) matched tumor tissues were enrolled in this study. PE and plasma samples of each patient were collected simultaneously. Supernatant and cell precipitate of PE were processed separately to extract cfDNA (PE-cfDNA) and sediment DNA (sDNA). All samples were subjected to targeted next-generation sequencing (NGS) of 416 cancer-related genes. PE supernatants contain more abundant tumor DNA than PE sediments and plasma samples, suggested by higher mutant allele frequencies (MAF) and elevated mutation detection rate in PE-cfDNA (98.4% vs. 90.5% in PE sDNA vs. 87% in plasma cfDNA). In Cohort 1 with matched tumor tissue, tumor mutational burden (TMB) of PE-cfDNA was similar as tumor tissues (6.4 vs. 5.6), but significantly higher than PE sDNA (median TMB: 3.3) and plasma cfDNA (median TMB: 3.4). Ninety-three percent (27 out of 29) of tissue-determined driver mutations were detected in PE-cfDNA, including alterations in , , , , , and , while only 62% were captured in plasma cfDNA. PE-cfDNA also has the highest detection rate of driver mutations in the full cohort (71% vs. 68% in PE sDNA vs. 59% in plasma cfDNA). Mutation detection from cytological negative and hemorrhagic PE is challenging. Comparatively, PE-cfDNA demonstrated absolute superiority than PE sDNA in such a scenario, suggesting that it is an independent source of tumor DNA and therefore less influenced by the abundance of tumor cells. Genomic profiling of PE-cfDNA offers an alternative, and potentially more meticulous approach in assessing tumor genomics in advanced lung cancer when tumor tissue is not available. Our data further demonstrate that in hemorrhagic or cytologically negative PE samples, PE-cfDNA has higher mutation detection sensitivity than sDNA and plasma cfDNA, and therefore is a more reliable source for genetic testing.

Background Chromodomain helicase DNA-binding protein 4 (CHD4) has been shown to contribute to DNA repair and cell cycle promotion; however, its roles in cancer initiation and progression remain largely unknown. This study aimed to demonstrate the role of CHD4 in the development of non-small cell lung cancer (NSCLC) and determine the potential mechanisms of action. Methods By using immunohistochemistry, the expression levels were evaluated in both cancer and non-cancerous tissues. Subsequently, CHD4 knockdown and overexpression strategies were employed to investigate the effects of CHD4 on cell proliferation, migration, along with the growth and formation of tumors in a xenografts mouse model. The protein expression levels of CHD4, PHF5A and ROCK/RhoA markers were determined by Western blot analysis. Results Compared with non-cancerous tissues, CHD4 was overexpressed in cancer tissues and CHD4 expression levels were closely related to clinical parameters of NSCLC patients. In H292 and PC-9 cell lines, CHD4 overexpression could promote the proliferative and migratory potential of NSCLC cells. Furthermore, down-regulation of CHD4 could reduce the proliferative and migratory ability in A549 and H1299 cell lines. Meanwhile, knockdown of CHD4 could decrease the tumorigenicity in nude mice. Finally, we demonstrated that one of the mechanisms underlying the promotive effect of CHD4 on NSCLC proliferation and migration may be through its interaction with PHD finger protein 5A (PHF5A) and subsequent activation of the RhoA/ROCK signaling pathway. Conclusions CHD4, which is highly expressed in cancer tissue, could be an independent prognostic factor for NSCLC patients. CHD4 plays an important role in regulating the proliferative and migratory abilities of NSCLC via likely the RhoA/ROCK pathway by regulating PHF5A.

Background: Lung cancer is now the leading cause of cancer mortality worldwide for both men and women. In non-small cell lung cancer (NSCLC), matching a specifically targeted drug to the identified driver mutation in each patient resulted in dramatically improved therapeutic efficacy, often in conjunction with decreased toxicity. Mutations in HER2 have been identified as an oncogenic driver gene for NSCLC. This retrospective study was conducted to better understand the clinical outcomes of advanced lung cancer patients harboring HER2 mutations treated with chemotherapies and HER2-targeted agents, as well as the optimal clinical choice. Methods: Patients who were diagnosed with advanced lung cancer (stage IIIB/IV) and had undergone molecular testing at Zhongshan Hospital, Fudan University, Shanghai, China from April 2016 to December 2018 were reviewed. For patients that had HER2 mutant advanced lung cancer, we analyzed their clinical and molecular features and clinical outcomes, including overall survival (OS), progression-free survival (PFS), disease control rate (DCR) and objective response rate (ORR). Results: We identified 44 patients harboring HER2 mutations. Their median age was 56 years, with the majority being women (n = 24), never smokers (n = 32), and having the adenocarcinoma genotype (n = 42). Amongst the HER2 mutations present, a 12 base pair in-frame insertion in exon 20 with p.771insAYVM was the most common subtype in patients with known detail variants of HER2 mutation (9/27). The median OS from the date of advanced disease diagnosis was 9.9 months with 24 deaths, and a median follow-up of 12.7 months for survivors. For patients with a known HER2 exon 20 insertion mutation, OS tended to be superior (though not statistically) in the first-line HER2-TKI group to that in the group receiving chemotherapy (10.8 versus 9.8 months, p = 0.40). However, patients that received first-line chemotherapy had a median PFS of 5.9 months, numerically longer than that of the HER2-TKI group (4.6 months, p = 0.63). Patients who received HER2-targeted therapy as first-line therapy had an improved OS (10.8 versus 10.1 months, p = 0.30) and PFS (4.6 versus 2.8 months, p = 0.36) relative to those who received HER2-targeted therapy as subsequent-line therapy, although they did not meet the threshold for statistical significance. Furthermore, patients with AYVM mutation were associated with poor clinical outcomes. Conclusion: Pemetrexed-based chemotherapy remains an important component of care for patients with HER2-mutant NSCLC. HER2-TKI given as an initial therapy may bring more clinical benefits than when given as a subsequent-line therapy. Refining the patient population based on patterns of HER2 variants may help improve the efficacy of anti-HER2 treatment in lung cancer. Developing highly effective and tolerable HER2-targeted agents is urgently needed for this population.

Objectives The exploration of how dysbiosis relates to lung masses is still nascent, with few studies focusing on the microbial characteristics across various sites. Therefore, we categorized the microbiota into feces and bronchoalveolar fluid (BALF) groups to compare microbial characteristics between benign and malignant masses, analyze their clinical correlations, and develop predictive models for lung cancer. Methods A total of 238 fecal samples and 34 BALF samples were collected from patients with benign and malignant masses and then analyzed by 16 SrRNA. We explored the distinct composition of the gut and lung microbiota and their associations with clinical features. The diagnostic models were constructed using microbial features identified through two approaches: random forest algorithm with five-fold cross-validation and comparative analysis of significantly differential taxa. The performance evaluation was subsequently conducted using receiver operating characteristic (ROC) analysis. Results There was no significant difference in α-and β-diversity between feces and BALF groups. The relative abundance of Lachnospiraceae_NK4A136_group ( P  = 0.003232) and Erysipelotrichaceae_UCG-003 ( P  = 0.01316) in feces group and Proteobacteria ( P  = 0.03654) in BALF group were significantly increased in lung cancer patients. We also found Bacteroides ( P  = 0.01458) was abundant in NSCLC than those of SCLC in feces group, while the BALF group was dominated by norank_c_Cyanobacteria ( P  = 0.03384). Smoking history appeared to be related to the distribution of microbiota, with enrichment of Parabacteroides ( P  = 0.02054) in feces and Prevotella_1 ( P  = 0.03286) in BALF. Furthermore, the patients with Sellimonas ( P  = 0.04148) in feces and Alloprevotella ( P  = 0.04283) in BALF seemed to have better response to chemotherapy combined with immunotherapy. For differentiating benign and malignant masses, the combination of Megasphaera and norank_p__Saccharibacteria in BALF demonstrated superior predictive performance, with an AUC reaching 0.8 (95% CI 0.59-1). Conclusion The microbiota composition significantly differed between benign and malignant masses in both fecal and BALF groups, with minimal evidence supporting microbial migration between these two sites. Our findings suggest that BALF microbiota may serve as a more reliable biomarker for lung masses classification, offering valuable insights for early diagnosis and clinical decision-making.

Nearshore fringing reefs have been shown to establish and accrete within sediment-laden coastal environments over millennial timescales. However, the mechanisms governing the evolution of turbid-water reefs remain inadequately understood. This study focuses on a fringing reef in the Changpi (CP) region along the eastern coast of Hainan Island, China. Sedimentological and geochronological analyses of four drill cores provided the first comprehensive growth history for this marginal reef setting through a systematic reconstruction of its developmental chronology, architectural framework, and ecological characteristics. Radiocarbon dating reveals reef initiated at about 7,400 cal yr BP and ceased accretion after 4,000 cal yr BP. By integrating core observations, thin-section petrography, and X-ray diffraction results, five distinct lithofacies were identified. These lithofacies exhibit varying degrees of mixing between siliciclastic and carbonate components, revealing that the reef system was periodically influenced by terrigenous siliciclastic input. The vertical accretion of the CP reef underwent three primary stages: (1) colonization stage (7,400-6,400 cal yr BP), characterized by well-preserved coral assemblages in high-energy, clear-water conditions with relatively low accretion rates (ca 0.35 mm/yr) and gradual coral diversification; (2) turbid stage (6,400-5,500 cal yr BP), marked by rapid terrigenous clastic deposition that produced persistent turbidity, leading to accelerated accretion rates (up to 6.29 mm/yr) and reduced coral diversity; and (3) stabilization stage (5,500-4,000 cal yr BP), during which stabilized siliciclastic input restored clear-water conditions, supporting renewed coral growth at moderate accretion rates (ca 2.70 mm/yr). This case study demonstrates that terrestrial sediment fluxes can exert a greater influence on nearshore reef trajectories than sea-level changes, particularly in regions or periods characterized by high sediment input. As suggested by the findings, this underscores the necessity of integrated coastal zone management strategies aimed at reducing agricultural runoff and controlling construction sediment to enhance reef resilience.

The role of gut dysbiosis in shaping immunotherapy responses is well-recognized, yet its effect on the therapeutic efficacy of chemotherapy and immunotherapy combinations remains poorly understood. We analyzed gut microbiota in non-small cell lung cancer (NSCLC) patients treated with chemo-immunotherapy, comparing responders and non-responders using 16S rRNA sequencing. Responders showed higher microbial richness and abundance of specific genera like Faecalibacterium and Subdoligranulum , and the phylum Firmicutes. Support vector machine (SVM), a machine learning model based on microbial composition, predicted treatment efficacy with the area under the curve (AUC) values of 0.763 for genera and 0.855 for species. Metagenomic analysis revealed significant differences in metabolic pathways, with responders exhibiting higher short-chain fatty acids (SCFAs) production. Fecal microbiota transplantation (FMT) and SCFAs supplementation in mouse models enhanced treatment efficacy by promoting effector T cell activity in tumors. Our study suggests that gut microbiota, through SCFAs production, regulates chemo-immunotherapy efficacy, offering new strategies to improve NSCLC treatment outcomes.

Background: Chronic obstructive pulmonary disease (COPD) has become a major cause of morbidity and mortality worldwide. Increasing evidence indicates that aberrantly expressed microRNAs (miRNAs) are involved in the pathogenesis of COPD. However, an integrative exploration of miRNA-mRNA regulatory network in COPD plasma remains lacking. Methods: The microarray datasets GSE24709, GSE61741, and GSE31568 were downloaded from the GEO database and analyzed using GEO2R tool to identify differentially expressed miRNAs (DEMs) between COPD and normal plasma. The consistently changing miRNAs in the three datasets were screened out as candidate DEMs. Potential upstream transcription factors and downstream target genes of candidate DEMs were predicted by FunRich and miRNet, respectively. Next, GO annotation and KEGG pathway enrichment analysis for target genes were performed using DAVID. Then, PPI and DEM-hub gene network were constructed using the STRING database and Cytoscape software. Finally, GSE56768 was used to evaluate the hub gene expressions. Results: A total of nine (six upregulated and three downregulated) DEMs were screened out in the above three datasets. SP1 was predicted to potentially regulate most of the down-regulated DEMs, while YY1 and E2F1 could regulate both upregulated and downregulated DEMs. 1139 target genes were then predicted, including 596 upregulated DEM target genes and 543 downregulated DEM target genes. Target genes of DEMs were mainly enriched in PI3K/Akt signaling pathway, mTOR signaling pathway, and autophagy. Through the DEM-hub gene network construction, most of the hub genes were found to be potentially modulated by miR-497-5p, miR-130b-5p, and miR-126-5p. Among the top 12 hub genes, MYC and FOXO1 expressions were consistent with that in the GSE56768 dataset. Conclusion: In the study, potential miRNA-mRNA regulatory network was firstly constructed in COPD plasma, which may provide a new insight into the pathogenesis and treatment of COPD. Keywords: microRNAs (miRNAs), chronic obstructive pulmonary disease (COPD), bioinformatics analysis, miRNA-mRNA regulatory network

Bronchopleural fistula (BPF) with empyema caused by severe necrotizing pulmonary infection is a complicated clinical problem that is often associated with poor general condition so surgical interventions cannot be tolerated in most cases. Here, we present the successful management of multiple BPF with empyema in a mechanically ventilated patient with aspiration lung abscess. Occlusion utilizing Gelfoam followed by endobronchial valves (EBVs) implanted inverted via bronchoscope decreased the air leaking significantly and made intrapleural irrigation for empyema achievable and safe. This is the first report of a novel way of EBV placement and the combination use with other occlusive substances in BPF with empyema in a patient on mechanical ventilation. This method may be an option for refractory BPF cases with pleural infection.