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Abstract Objective Bladder cancer(BCa) was a disease that seriously affects patients’ quality of life and prognosis. To address this issue, many researches suggested that the gut microbiota modulated tumor response to treatment; however, this had not been well-characterized in bladder cancer. In this study, our objective was to determine whether the diversity and composition of the gut microbiota or the density of specific bacterial genera influence the prognosis of patients with bladder cancer. Methods We collected fecal samples from a total of 50 bladder cancer patients and 22 matched non-cancer individuals for 16S rDNA sequencing to investigate the distribution of Parabacteroides in these two groups. Further we conducted follow-up with cancer patients to access the impact of different genera of microorganisms on patients survival. We conducted a Fecal Microbiota Transplantation (FMT) and mono-colonization experiment with Parabacteroides distasonis to explore its potential enhancement of the efficacy of anti-PD-1 immunotherapy in MB49 tumor-bearing mice. Immunohistochemistry, transcriptomics and molecular experiment analyses were employed to uncover the underlying mechanisms. Results The 16S rDNA showed that abundance of the genus Parabacteroides was elevated in the non-cancer control group compared to bladder cancer group. The results of tumor growth curves showed that a combination therapy of P. distasonis and ICIs treatment significantly delayed tumor growth and increased the intratumoral densities of both CD4+T and CD8+T cells. The results of transcriptome analysis demonstrated that the pathways associated with antitumoral immune response were remarkably upregulated in the P. distasonis gavage group. Conclusion P. distasonis delivery combined with α-PD-1 mAb could be a new strategy to enhance the effect of anti-PD-1 immunotherapy. This effect might be achieved by activating immune and antitumor related pathways.

The drive to propel innovative development within the marine industry is an essential requirement in constructing a distinct marine powerhouse for China. The pivotal element in achieving innovation within this industry lies in augmenting the innovative capabilities of enterprises through the digitization transformation. This study is anchored in the panel data of 92 publicly listed Chinese marine companies spanning from 2007 to 2021. Leveraging Python technology, keywords related to "digitization transformation" were systematically extracted from annual corporate reports, aggregating their frequency to formulate a digitization transformation intensity index. Building upon this foundation, a panel fixed-effects model was employed to empirically examine the impact of enterprise digitization transformation on their innovation capabilities. The findings reveal a significant positive influence of digitization transformation within Chinese marine listed companies on their innovation capabilities, a conclusion upheld even after robustness tests. When distinguishing among different corporate natures, it becomes apparent that, in comparison to non-state-owned listed enterprises, digitization transformation within state-owned marine listed companies exerts a more substantial and conspicuous positive effect on enhancing research and development innovation capabilities. Hence, advancing digital technological development among marine listed companies, enhancing their capability for digitization transformation, and prioritizing the cultivation of state-owned exemplary digital marine enterprises stand as critically imperative measures to drive innovation development within marine enterprises.

ABSTRACT: Objectives: Prevotella bivia is a species that commonly colonizes various human body sites, and it is associated with lots of human infections. However, until now, no complete genome sequence of this species has been published. Here, we assembled the first complete genome of P. bivia from a clinically derived strain PLW0727, to characterize its general genomic features, and to profile the capacity in encoding antibiotic resistance and virulence factors. Methods: Whole-genome sequencing was performed using Illumina and Nanopore platforms. Hybrid assembly was conducted using flye v2.9.1 and Unicycler v0.4.9b. Assembly completeness was assessed using CheckM v1.0.12. Comprehensive genome annotation was performed using eggNOG-mapper v2.1.5 and PATRIC v3.6.10. Results: The complete genome of PLW0727 consists of two circular chromosomes, chr1 and chr2, exhibiting a completeness of 99.66%, a G+C content of 39.5%, and a total size of 2.43 Mb. Chr1 and chr2 have lengths of 1 272 652 bp and 1 155 021 bp, harbouring 1 132 CDSs and 1 055 CDSs, respectively. Completion of the genome significantly reduced the proportion of hypothetical CDS annotations compared with the draft genomes. A gene-encoding antibiotic resistance to beta-lactams (i.e., cfxA3) has been annotated in chr2. By providing the genome sequence, strain PLW0727 was identified as a human pathogen with a probability of 0.614 using the PathogenFinder. Furthermore, genes involved in virulence-related functions, including host cell adherence and capsule immune modulation were also annotated. Conclusions: This study assembles the first complete genome for P. bivia, providing valuable genomic insights into its phylogeny, pathogenicity, and antibiotic resistance. These findings have important implications for the clinical management and prevention of P. bivia infections.

BackgroundWinkia neuii, previously known as Actinomyces neuii, is increasingly recognized as a causative agent of various human infections, while its taxonomy and genomic insights are still understudied.MethodsA Winkia strain NY0527 was isolated from the hip abscess of a patient, and its antibiotic susceptibility was assessed. The genome was hybrid assembled from long-reads and short-reads sequencing. Whole-genome-based analyses on taxa assignment, strain diversity, and pathogenesis were conducted.ResultsThe strain was found to be highly susceptible to beta-lactam antibiotics, but resistant to erythromycin, clindamycin, and amikacin. The complete genome sequences of this strain were assembled and found to consist of a circular chromosome and a circular plasmid. Sequence alignment to the NCBI-nt database revealed that the plasmid had high sequence identity (>90%) to four Corynebacterium plasmids, with 40–50% query sequence coverage. Furthermore, the plasmid was discovered to possibly originate from the sequence recombination events of two Corynebacterium plasmid families. Phylogenomic tree and genomic average nucleotide identity analyses indicated that many Winkia sp. strains were still erroneously assigned as Actinomyces sp. strains, and the documented subspecies within W. neuii should be reclassified as two separate species (i.e., W. neuii and W. anitratus). The core genome of each species carried a chromosome-coded beta-lactamase expression repressor gene, which may account for their broadly observed susceptibility to beta-lactam antibiotics in clinical settings. Additionally, an ermX gene that expresses fluoroquinolone resistance was shared by some W. neuii and W. anitratus strains, possibly acquired by IS6 transposase-directed gene transfer events. In contrast, tetracycline resistance genes were exclusively carried by W. neuii strains. In particular, W. neuii was found to be more pathogenic than W. anitratus by encoding more virulence factors (i.e., 35–38 in W. neuii vs 27–31 in W. anitratus). Moreover, both species encoded two core pathogenic virulence factors, namely hemolysin and sialidase, which may facilitate their infections by expressing poreformation, adhesion, and immunoglobulin deglycosylation activities.ConclusionThis study highlights the underappreciated taxonomic diversity of Winkia spp. and provides populational genomic insights into their antibiotic susceptibility and pathogenesis for the first time, which could be helpful in the clinical diagnosis and treatment of Winkia spp. infections.

This study addresses dynamic task allocation challenges in coordinated surveillance involving multiple unmanned aerial vehicles (UAVs). A significant concern is the increased UAV flight distance resulting from the assignment of new missions, leading to decreased reconnaissance efficiency. To tackle this issue, we introduce a collaborative multi-target and multi-UAV reconnaissance scheme. Initially, the multitasking constrained multi-objective optimization framework (MTCOM) is employed to optimize task allocation and reconnaissance time in static scenarios. Subsequently, in case of emergency, we iteratively refine the outcomes of static task allocation through an enhanced auction-based distributed algorithm, effectively reducing UAV flight costs in response to new missions, UAV withdrawal, or damage. Simulation results demonstrate the efficacy of our proposed multi-UAV and multi-target cooperative reconnaissance scheme in resolving dynamic task allocation issues. Additionally, our approach achieves a 5.4% reduction in UAV flight distance compared to traditional allocation methods. The main contribution of this paper is to consider a dynamic scenario model involving UAV damage and the emergence of new reconnaissance areas. Then we propose an innovative collaborative multi-target and multi-UAV reconnaissance scheme to address this issue and, finally, conduct experimental simulations to verify the effectiveness of the algorithm.

ObjectiveOveractive bladder (OAB) is a disease that seriously affects patients’ quality of life and mental health. To address this issue, more and more researchers are examining the relationship between OAB treatment and urinary microecology. In this study, we sought to determine whether differences in treatment efficacy were related to microbiome diversity and composition as well as the abundance of specific genera. Machine learning algorithms were used to construct predictive models for urine microbiota-based treatment of OAB.MethodsUrine samples were obtained from 64 adult female OAB patients for 16S rRNA gene sequencing. Patients’ overactive bladder symptom scores (OABSS) were collected before and after mirabegron treatment and patients were divided into effective and ineffective groups. The relationship between the relative abundance of certain genera and OABSS were analyzed. Three machine learning algorithms, including random forest (RF), supporting vector machine (SVM) and eXtreme gradient boosting (XGBoost) were utilized to predict the therapeutic effect of mirabegron based on the relative abundance of certain genera in OAB patients’ urine microbiome.ResultsThe species composition of the two groups differed. For one, the relative abundance of Lactobacillus was significantly higher in the effective group than in the ineffective group. In addition, the relative abundance of Gardnerella and Prevotella in the effective group was significantly lower than in the ineffective group. Alpha-diversity and beta-diversity differed significantly between the two groups. LEfSe analysis revealed that Lactobacillus abundance increased while Prevotella and Gardnerella abundance decreased in the effective group. The Lactobacillus abundance ROC curve had high predictive accuracy. The OABSS after treatment was negatively correlated with the abundance of Lactobacillus, whereas the relationship between OABSS and Prevotella and Gardnerella showed the opposite trend. In addition, RF, SVM and XGBoost models demonstrated high predictive ability to assess the effect of mirabegron in OAB patients in the test cohort.ConclusionsThe results of this study indicate that urinary microbiota might influence the efficacy of mirabegron, and that Lactobacillus might be a potential marker for evaluating the therapeutic efficacy of mirabegron in OAB patients.

Although it is known that changes in bacterial components of the urinary microbiome are associated with overactive bladder (OAB), the specific role of viruses is still insufficiently investigated. The aim of the present study is to evaluate the role of urinary viruses in woman with OAB, and analyze the potential relationship between viruses, bacteria and disease. Catheterized urine samples were collected from 55 women with OAB and 18 control individuals. OAB patients fulfilling the following criteria were considered eligible for this study: female, 18 years of age or older; presented with classic OAB symptoms defined by the International Continence Society; and OAB Symptom Score (OABSS) total score ≥ 3 points and question 3 (urgency) score ≥ 2 points. Based on results of metagenomic next-generation sequencing (mNGS), all participants were divided into virus-infected and virus-uninfected groups for analysis. The results of mNGS showed that the diversity of the OAB group was lower than that of the control group when focused on bacterial sequences, which was consistent with our previous study. According to the questionnaire filled out by the patients, OABSS and 8-item OAB questionnaire, female OAB patients who had viruses detected in their urine had more severe symptoms. In parallel, John Cunningham virus (mainly subtype 7 and subtype 2) was the most frequently detected virus in urine. Correlation analysis indicated that risk factors for virus infection in OAB patients include age, habit of holding urine and pelvic surgery history. Given our preliminary data, viral infection can aggravate OAB severity and affect the composition of bacterial. Further research is required to explain how viral infections can aggravate OAB patient symptoms and cause bacterial changes.