Metabolic and Microbial Dysregulation in Preterm Infants with Neonatal Respiratory Distress Syndrome: An Early Developmental Perspective.

Neonatal respiratory distress syndrome (NRDS) is one of the most severe respiratory disorders in preterm infants (PTIs) due to immature lung development. To delineate the serum metabolic alterations and gut microbiota variations in NRDS and assess their implications on neonatal development, we enrolled 13 NRDS neonates and 12 PTIs and collected fecal and serum specimens after birth. Longitudinal fecal sampling was conducted weekly for a month in NRDS neonates. NRDS neonates were characterized by notably reduced gestational ages and birth weights and a higher rate of asphyxia at birth relative to PTIs. Early postnatal disturbances in tryptophan metabolism were evident in the NRDS group, concomitant with elevated relative abundance of Haemophilus, Fusicatenibacter, and Vibrio. Integrative multiomics analyses revealed an inverse relationship between tryptophan concentrations and Blautia abundance. At one-week old, NRDS neonates exhibited cortisol regulation anomalies and augmented hepatic catabolism. Sequential microbial profiling revealed distinct gut microbiota evolution in NRDS subjects, characterized by a general reduction in potentially pathogenic bacteria. The acute perinatal stress of NRDS leads to mitochondrial compromise, hormonal imbalance, and delayed gut microbiota evolution. Despite the short duration of NRDS, its impact on neonatal development is significant and requires extended attention.

Collateral sensitivity between tetracyclines and aminoglycosides constrains resistance evolution in carbapenem-resistant Klebsiella pneumoniae.

AIMS: The acquisition of resistance to one antibiotic may confer an increased sensitivity to another antibiotic in bacteria, which is an evolutionary trade-off between different resistance mechanisms, defined as collateral sensitivity (CS). Exploiting the role of CS in treatment design could be an effective method to suppress or even reverse resistance evolution. METHODS: Using experimental evolution, we systematically studied the CS between aminoglycosides and tetracyclines in carbapenem-resistant Klebsiella pneumoniae (CRKP) and explored the underlying mechanisms through genomic and transcriptome analyses. The application of CS-based therapies for resistance suppression, including combination therapy and alternating antibiotic therapy, was further evaluated in vitro and in vivo. RESULTS: Reciprocal CS existed between tetracyclines and aminoglycosides in CRKP. The increased sensitivity of aminoglycoside-resistant strains to tetracyclines was associated with the alteration of bacterial membrane potential, whereas the unbalanced oxidation-reduction process of tetracycline-resistant strains may lead to an increased bacterial sensitivity to aminoglycosides. CS-based combination therapy could efficiently constrain the evolution of CRKP resistance in vitro and in vivo. In addition, alternating antibiotic therapy can re-sensitize CRKP to previously resistant drugs, thereby maintaining the trade-off. CONCLUSIONS: These results provide new insights into constraining the evolution of CRKP resistance through CS-based therapies.

[Identification of chemical components in Qinggu San reference sample of classial prescription based on UHPLC-Q/Orbitrap HRMS combined with molecular network technology].

The method of ultra-high performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry(UHPLC-Q/Orbitrap HRMS)combined with molecular network was developed in this study for rapidly analyzing the chemical components of the Qinggu San reference sample of classical prescription. Firstly, an ACQUITY UPLC BEH Shield RP_(18) column(2.1 mm×100 mm, 1.7 µm)was used, and acetonitrile and 0.1% formic acid were taken as the mobile phases for gradient elution. The flow rate was 0.4 mL·min~(-1), and the column temperature was 30 ℃. Under these conditions, the mass spectrum data were collected in both positive and negative ion modes of the heated electrospray ionization source. Subsequently, the mass spectrum data of the Qinggu San reference sample were uploaded to the Global Natural Products Social Molecular Network(GNPS)platform for calculation and analysis, and a visual molecular network was built with Cytoscape 3.8.2 software. On this basis, the chemical components of the Qinggu San reference sample were identified by fragmentation regularity of standard compounds, retention time, accurate relative molecular weight of HR-MS, characteristic fragment ions information, literature, and databases. Finally, a total of 105 chemical components were identified and speculated in the Qinggu San reference sample, including 19 iridoid glycosides, 23 flavonoids, 15 phenylpropanoids, 11 triterpene saponins, and 37 other components. Meanwhile, two of these components are potential new compounds. The method used in this study not only achieved rapid and accurate identification of chemical components in the Qinggu San reference sample and provided a scie-ntific basis for the study of pharmacological substances and quality control of Qinggu San compound preparations but also provided a refe-rence for the rapid identification of chemical components in traditional Chinese medicine compound preparations.

Metabolic landscape dysregulation in bronchoalveolar lavage fluid of checkpoint inhibitor pneumonitis.

BACKGROUND: Checkpoint inhibitor pneumonitis (CIP) is a potentially fatal adverse event resulting from immunotherapy in patients with malignant tumors. However, the pathogenesis of CIP remains poorly understood. METHODS: We collected bronchoalveolar lavage fluid (BALF) from cohorts of patients with CIP, new-onset lung cancer (LC), and idiopathic pulmonary fibrosis (IPF). Non-targeted metabolomics analysis was conducted to analyze metabolic signatures. Flow cytometry was used to evaluate immune cell subsets. RESULTS: Lymphocytes were predominant in the BALF of patients with CIP. A total of 903 metabolites were identified, among which lipid compounds were the most abundant. In a comparison between patients with CIP and LC, enrichment analysis of the altered metabolites showed suppressed amino sugar metabolism, and spermidine and spermine biosynthesis in the CIP group. Metabolism of alpha linolenic acid, linoleic acid, and their fatty acid derivatives was enriched in the CIP group relative to the IPF group. The twelve metabolites found to be enriched in the CIP group were positively correlated with the proportion of CD8+ T cells. One cluster of BALF metabolites, 57.14% of which were lipid molecules, was inversely correlated with the proportion of natural killer cells. CONCLUSIONS: In this study, the metabolomic landscape of BALF in patients with CIP was determined. We elucidated suppressed tumor metabolic signatures, enhanced pulmonary inflammatory signaling, and the characteristics of responsible immune cells, which helps to understand the pathogenesis of CIP.

Relationship between clinical features and droplet digital PCR copy number in non-HIV patients with pneumocystis pneumonia.

OBJECTIVE: Droplet digital PCR (ddPCR) is a novel assay to detect pneumocystis jjrovecii (Pj) which has been defined to be more sensitive than qPCR in recent studies. We aimed to explore whether clinical features of pneumocystis pneumonia (PCP) were associated with ddPCR copy numbers of Pj. METHODS: A total of 48 PCP patients were retrospectively included. Pj detection was implemented by ddPCR assay within 4 h. Bronchoalveolar fluid (BALF) samples were collected from 48 patients with molecular diagnosis as PCP via metagenomic next generation sequencing (mNGS) or quantitative PCR detection. Univariate and multivariate logistic regression were performed to screen out possible indicators for the severity of PCP. The patients were divided into two groups according to ddPCR copy numbers, and their clinical features were further analyzed. RESULTS: Pj loading was a pro rata increase with serum (1,3)-beta-D glucan, D-dimmer, neutrophil percentage, procalcitonin and BALF polymorphonuclear leucocyte percentage, while negative correlation with albumin, PaO2/FiO2, BALF cell count, and BALF lymphocyte percentage. D-dimmer and ddPCR copy number of Pj were independent indicators for moderate/severe PCP patients with PaO2/FiO2 lower than 300. We made a ROC analysis of ddPCR copy number of Pj for PaO2/FiO2 index and grouped the patients according to the cut-off value (2.75). The high copy numbers group was characterized by higher level of inflammatory markers. Compared to low copy number group, there was lower level of the total cell count while higher level of polymorphonuclear leucocyte percentage in BALF in the high copy numbers group. Different from patients with high copy numbers, those with high copy numbers had a tendency to develop more severe complications and required advanced respiratory support. CONCLUSION: The scenarios of patients infected with high ddPCR copy numbers of Pj showed more adverse clinical conditions. Pj loading could reflect the severity of PCP to some extent.

BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation.

BACKGROUND: X chromosome inactivation (XCI) is an epigenetic phenomenon that one of two X chromosomes in females is transcriptionally silenced during early embryonic development. Skewed XCI has been reported to be associated with some X-linked diseases. There have been several methods measuring the degree of the skewness of XCI. However, these methods may still have several limitations. RESULTS: We propose a Bayesian method to obtain the point estimate and the credible interval of the degree of XCI skewing by incorporating its prior information of being between 0 and 2. We consider a normal prior and a uniform prior for it (respectively denoted by BN and BU). We also propose a penalized point estimate based on the penalized Fieller's method and derive the corresponding confidence interval. Simulation results demonstrate that the BN and BU methods can solve the problems of extreme point estimates, noninformative intervals, empty sets and discontinuous intervals. The BN method generally outperforms other methods with the lowest mean squared error in the point estimation, and well controls the coverage probability with the smallest median and the least variation of the interval width in the interval estimation. We apply all the methods to the Graves' disease data and the Minnesota Center for Twin and Family Research data, and find that SNP rs3827440 in the Graves' disease data may undergo skewed XCI towards the allele C. CONCLUSIONS: We recommend the BN method for measuring the degree of the skewness of XCI in practice. The R package BEXCIS is publicly available at https://github.com/Wen-YiYu/BEXCIS .

Enhanced DNA and RNA pathogen detection via metagenomic sequencing in patients with pneumonia.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) is an important supplement to conventional tests for pathogen detections of pneumonia. However, mNGS pipelines were limited by irregularities, high proportion of host nucleic acids, and lack of RNA virus detection. Thus, a regulated pipeline based on mNGS for DNA and RNA pathogen detection of pneumonia is essential. METHODS: We performed a retrospective study of 151 patients with pneumonia. Three conventional tests, culture, loop-mediated isothermal amplification (LAMP) and viral quantitative real-time polymerase chain reaction (qPCR) were conducted according to clinical needs, and all samples were detected using our optimized pipeline based on the mNGS (DNA and RNA) method. The performances of mNGS and three other tests were compared. Human DNA depletion was achieved respectively by MolYsis kit and pre-treatment using saponin and Turbo DNase. Three RNA library preparation methods were used to compare the detection performance of RNA viruses. RESULTS: An optimized mNGS workflow was built, which had only 1-working-day turnaround time. The proportion of host DNA in the pre-treated samples decreased from 99 to 90% and microbiome reads achieved an approximately 20-fold enrichment compared with those without host removal. Meanwhile, saponin and Turbo DNase pre-treatment exhibited an advantage for DNA virus detection compared with MolYsis. Besides, our in-house RNA library preparation procedure showed a more robust RNA virus detection ability. Combining three conventional methods, 76 (76/151, 50.3%) cases had no clear causative pathogen, but 24 probable pathogens were successfully detected in 31 (31/76 = 40.8%) unclear cases using mNGS. The agreement of the mNGS with the culture, LAMP, and viral qPCR was 60%, 82%, and 80%, respectively. Compared with all conventional tests, mNGS had a sensitivity of 70.4%, a specificity of 72.7%, and an overall agreement of 71.5%. CONCLUSIONS: A complete and effective mNGS workflow was built to provide timely DNA and RNA pathogen detection for pneumonia, which could effectively remove the host sequence, had a higher microbial detection rate and a broader spectrum of pathogens (especially for viruses and some pathogens that are difficult to culture). Despite the advantages, there are many challenges in the clinical application of mNGS, and the mNGS report should be interpreted with caution.

Chemical profiling of Qingfei Paidu Decoction by triplex off-line two-dimensional liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

Qingfei Paidu Decoction is a Chinese medicine formula that has been proved effective in the treatment of coronavirus disease 2019. However, the comprehensive separation and characterization of Qingfei Paidu Decoction are of a great challenge due to the diversity of chemical components in a wide range of polarity. In this study, a triplex off-line two-dimensional liquid chromatography coupled with quadrupole time-of-flight mass spectrometry is developed for the analysis of Qingfei Paidu Decoction. One reversed-phase liquid chromatography×hydrophilic interaction liquid chromatography system and two reversed-phase liquid chromatography×reversed phase liquid chromatography systems were constructed to separate polar components and weak-polar components in Qingfei Paidu Decoction, respectively. Benefiting from the good orthogonality of two-dimensional liquid chromatography and high sensitivity of quadrupole time-of-flight MS, chemical components with different polarities and content were discovered. A total of 749 peaks were detected in positive and negative ionization mode and presented as a four-dimensional data plot. Meanwhile, 498 compounds belonging to 14 categories were tentatively identified. These results provide good supplementary to elucidate the material basis of Qingfei Paidu Decoction. The triplex off-line two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry strategy can be a powerful and efficient tool for the separation and characterization of chemical substances in traditional Chinese medicine formulas.

Characteristics of oral microbiome of healthcare workers in different clinical scenarios: a cross-sectional analysis.

The environment of healthcare institutes (HCIs) potentially affects the internal microecology of medical workers, which is reflected not only in the well-studied gut microbiome but also in the more susceptible oral microbiome. We conducted a prospective cross-sectional cohort study in four hospital departments in Central China. Oropharyngeal swabs from 65 healthcare workers were collected and analyzed using 16S rRNA gene amplicon sequencing. The oral microbiome of healthcare workers exhibited prominent deviations in diversity, microbial structure, and predicted function. The coronary care unit (CCU) samples exhibited robust features and stability, with significantly higher abundances of genera such as Haemophilus, Fusobacterium, and Streptococcus, and a lower abundance of Prevotella. Functional prediction analysis showed that vitamin, nucleotide, and amino acid metabolisms were significantly different among the four departments. The CCU group was at a potential risk of developing periodontal disease owing to the increased abundance of F. nucleatum. Additionally, oral microbial diversification of healthcare workers was related to seniority. We described the oral microbiome profile of healthcare workers in different clinical scenarios and demonstrated that community diversity, structure, and potential functions differed markedly among departments. Intense modulation of the oral microbiome of healthcare workers occurs because of their original departments, especially in the CCU.

Comparative analysis of oropharyngeal microbiota in healthcare workers post-COVID-19.

Background: To date, more than 770 million individuals have become coronavirus disease 2019 (COVID-19) convalescents worldwide. Emerging evidence highlights the influence of COVID-19 on the oral microbiome during both acute and convalescent disease phases. Front-line healthcare workers are at an elevated risk of exposure to viral infections, and the effects of COVID-19 on their oral microbiome remain relatively unexplored. Methods: Oropharyngeal swab specimens, collected one month after a negative COVID-19 test from a cohort comprising 55 healthcare workers, underwent 16S rRNA sequencing. We conducted a comparative analysis between this post-COVID-19 cohort and the pre-infection dataset from the same participants. Community composition analysis, indicator species analysis, alpha diversity assessment, beta diversity exploration, and functional prediction were evaluated. Results: The Shannon and Simpson indexes of the oral microbial community declined significantly in the post-COVID-19 group when compared with the pre-infection cohort. Moreover, there was clear intergroup clustering between the two groups. In the post-COVID-19 group, the phylum Firmicutes showed a significant increase. Further, there were clear differences in relative abundance of several bacterial genera in contrast with the pre-infection group, including Streptococcus, Gemella, Granulicatella, Capnocytophaga, Leptotrichia, Fusobacterium, and Prevotella. We identified Gemella enrichment in the post-COVID-19 group, potentially serving as a recovery period performance indicator. Functional prediction revealed lipopolysaccharide biosynthesis downregulation in the post-COVID-19 group, an outcome with host inflammatory response modulation and innate defence mechanism implications. Conclusion: During the recovery phase of COVID-19, the oral microbiome diversity of front-line healthcare workers failed to fully return to its pre-infection state. Despite the negative COVID-19 test result one month later, notable disparities persisted in the composition and functional attributes of the oral microbiota.

The potential role of lung microbiota and lauroylcarnitine in T-cell activation associated with checkpoint inhibitor pneumonitis.

BACKGROUND: Checkpoint inhibitor pneumonitis (CIP) is a potentially fatal adverse event characterized by new pulmonary infiltrates in cancer patients receiving immune checkpoint inhibitor therapy. This study aims to explore the interplay between lung microbiota, dysregulated metabolites, and host immunity in CIP. METHODS: We recruited thirteen hospitalized CIP patients, eleven idiopathic pulmonary fibrosis (IPF) patients, and ten new-onset non-small cell lung cancer patients. Bronchoalveolar lavage fluid samples were collected for 16S rRNA gene sequencing. The percentages of immune cells were determined using manual counting and flow cytometry. Interactions among microbiota, metabolites, and lymphocytes were analyzed using cultured mouse splenocytes and human T cells. FINDINGS: Proteobacteria emerged as the dominant phylum, notably abundant in both the CIP and IPF groups. Vibrio, Halomonas, Mangrovibacter, and Salinivibrio were the predominant microbiota because of their discriminative abundance patterns. Vibrio (r = 0.72, P-adj = 0.007) and Halomonas (r = 0.65, P-adj = 0.023) demonstrated strong correlations with lymphocytes. Vibrio metschnikovii and Mangrovibacter plantisponsors were more abundant in the CIP group than in the IPF group. Lauroylcarnitine, a key intermediary metabolite co-occurring with the predominant microbiota, exhibited a potent effect on cytokine secretion by mouse and human T cells, notably enhancing IFN-γ and TNF-α production from CD4 and CD8 cells in vitro. INTERPRETATION: Lauroylcarnitine, co-occurring with the predominant lung microbiota in CIP, could activate T cells in vitro. These findings suggest potential involvement of lung microbiota and acylcarnitine metabolism dysregulation in the pathogenesis of CIP. FUNDING: This work was supported by Peking University People's Hospital Scientific Research Development Funds (RDJ2022-15) and Provincial Key Clinical Specialty Capacity Building Project 2020 (Department of the Respiratory Medicine).

An algorithm-driven intelligent mining and identification strategy for natural product mass spectrometry.

Efficiently mining and identification of new compounds from the extensive MS/MS datasets of plant extracts poses a significant challenge due to the structural diversity and compositional complexity inherent in natural products (NPs). Various data post-processing techniques have been developed to simplify the interpretation of MS/MS data; however, they often suffer from limited specificity and precision. Meanwhile, structure annotation following data post-processing is particularly time-consuming. In this study, we introduced an innovative strategy named MS-SMART, which integrates three intelligent algorithms: automatic mining of diagnostic ions, rapid filtration of alkaloids from untargeted MS/MS data, and structural recommendations for filtered components. The feasibility of this approach for rapidly discovering novel compounds was demonstrated using berberine-type alkaloids as an example. Firstly, diagnostic ions were automatically extracted and validated using available reference data. Subsequently, berberine-type compounds were filtered from raw MS/MS data. Finally, the structures of the target components were recommended using building blocks derived from berberines reported in various plants. A total of 103, 198, 60, 80 and 51 berberines were efficiently identified in diverse families and genera, including Stephaniae Epigaeae Radix, Coptidis Rhizoma, Phellodendri Chinensis Cortex, Phellodendri Amurensis Cortex and Corydalis Decumbentis Rhizoma, with 99, 169, 50, 64 and 40 new compounds identified, respectively. Among these, 8, 14, 8, 7 and 12 berberines were confirmed by reference compounds. This strategy provides a new research paradigm for the rapid discovery and identification of different types of new compounds in complex samples.

Single-cell landscape of bronchoalveolar immune cells in patients with immune checkpoint inhibitor-related pneumonitis.

The pathophysiology of immune checkpoint inhibitor-related pneumonitis remains incompletely understood. We conducted single-cell and T-cell receptor transcriptomic sequencing on the bronchoalveolar lavage fluid from five patients with grade ≥2 immune checkpoint inhibitor-related pneumonitis. Our analyses revealed a prominent enrichment of T cells in the bronchoalveolar lavage fluid of patients with immune checkpoint inhibitor-related pneumonitis. Within the CD4 + T cell subset, Tfh-like T cells were highly enriched and exhibited signatures associated with inflammation and clonal expansion. Regulatory T cells were also enriched and displayed enhanced inhibitory functions. Within the CD8 + T-cell subset, effector memory/tissue-resident memory T cells with an elevated cytotoxic phenotype were highly infiltrated. Among myeloid cells, alveolar macrophages were depleted, while pro-inflammatory intermediate monocytes were elevated. Dendritic cells demonstrated enhanced antigen presentation capabilities. Cytokines CXCR4, CXCL13, TNF-α, IFN-α, IFN-γ, and TWEAK were elevated. Through a comprehensive single-cell analysis, we depicted the landscape of immune checkpoint inhibitor-related pneumonitis.

Plasma proteome analysis and validation of patients with community-acquired pneumonia: A cohort study.

PURPOSE: This study aimed to investigate the diagnostic potential of plasma biomarkers of community-acquired pneumonia (CAP) and their severity grading. EXPERIMENTAL DESIGN: Plasma proteomes from cohort I (n = 32) with CAP were analyzed by data-independent acquisition mass spectrometry (MS). MetaboAnalyst 5.0 was used to statistically evaluate significant differences in proteins from different samples, and demographic and clinical data were recorded for all enrolled patients. Cohort II (n = 80) was used to validate candidate biomarkers. Plasma protein levels were determined using quantitative enzyme-linked immunosorbent assay (ELISA). Correlations were assessed using Pearson's correlation coefficient. A receiver operating characteristic curve was used to verify the association between the variables, CAP diagnosis, and prognosis. RESULTS: 121 differentially expressed proteins (DEPs) were obtained between CAP and controls. These DEPs were mainly aggregated in pathways of phagosome(hsa04145) and complement and coagulation cascades (hsa04610). No significant differential proteins were detected in bacterial, viral, and mixed infection groups. The plasma levels of fetuin-A, alpha-1-antichymotrypsin (AACT), α1-acid glycoprotein (A1AG), and S100A8/S100A9 heterodimers detected by ELISA were consistent with those of MS. AACT, A1AG, S100A8/S100A9 heterodimer, and fetuin-A can potentially be used as diagnostic predictors, and fetuin-A and AACT are potential predictors of SCAP. CONCLUSIONS AND CLINICAL RELEVANCE: Plasma protein profiling can successfully identify potential biomarkers for CAP diagnosis and disease severity assessment. These biomarkers should be further studied for their clinical application.

Serum metabolomics profile identifies patients with community-acquired pneumonia infected by bacteria, fungi, and viruses.

PURPOSE: Patients with bacterial, fungal, and viral community-acquired pneumonia (CAP) were studied to determine their metabolic profiles. METHODS: Loop-mediated isothermal amplification technology and nucleic acid sequence-dependent amplification combined with microfluidic chip technology were applied to screen multiple pathogens from respiratory tract samples. Eighteen patients with single bacterial infection (B-CAP), fifteen with single virus infection (V-CAP), twenty with single fungal infection (F-CAP), and twenty controls were enrolled. UHPLC-MS/MS analysis of untargeted serum samples for metabolic profiles. Multiple linear regression and Spearman's rank correlation analysis were used to determine associations between metabolites and clinical parameters. The sensitivity and specificity of the screened metabolites were also examined, along with their area under the curve. RESULTS: The metabolic signatures of patients with CAP infected by bacteria, viruses, and fungi were markedly different from those of controls. The abundances of 45, 56, and 79 metabolites were significantly unbalanced. Among these differential metabolites, 11, 13, and 29 were unique to the B-CAP, V-CAP, and F-CAP groups, respectively. Bacterial infections were the only known causes of disturbances in the pentose and glucuronate and aldarate and ascorbate metabolism interconversions metabolic pathway. CONCLUSIONS: Serum metabolomic techniques based on UHPLC-MS/MS may identify differences between individuals with CAP who have been infected by various pathogens, and they can also build a metabolite signature for early detection of the origin of infection and prompt care.

Elucidation of active components and target mechanism in Jinqiancao granules for the treatment of prostatitis and benign prostatic hyperplasia.

ETHNOPHARMACOLOGICAL RELEVANCE: Prostatitis and benign prostatic hyperplasia (BPH) are inflammations of the prostate gland, which surrounds the urethra in males. Jinqiancao granules are a traditional Chinese medicine used to treat kidney stones and this medicine consists of four herbs: Desmodium styracifolium (Osbeck) Merr., Pyrrosia calvata (Baker) Ching, Plantago asiatica L. and stigma of Zea mays L. AIM OF THE STUDY: We hypothesized that Jinqiancao granules could be a potential therapy for prostatitis and BPH, and this work aimed to elucidate active compounds in Jinqiancao granules and their target mechanisms for the potential treatment of the two diseases. MATERIALS AND METHODS: Jinqiancao granules were commercially available and purchased. Database-driven data mining and networking were utilized to establish a general correlation between Jinqiancao granules and the two diseases above. Ultra-performance liquid chromatography-mass spectrometry was used for compound separation and characterization. The characterized compounds were evaluated on four G-protein coupled receptors (GPCRs: GPR35, muscarinic acetylcholine receptor M3, alpha-1A adrenergic receptor α1A and cannabinoid receptor CB2). A dynamic mass redistribution technique was applied to evaluate compounds on four GPCRs. Nitric acid (NO) inhibition was tested on the macrophage cell line RAW264.7. Molecular docking was conducted on GPR35-active compounds and GPR35 crystal structure. Statistical analysis using GEO datasets was conducted. RESULTS: Seventy compounds were isolated and twelve showed GPCR activity. Three compounds showed potent GPR35 agonistic activity (EC50 < 10 µM) and the GPR35 agonism action of PAL-21 (Scutellarein) was reported for the first time. Docking results revealed that the GPR35-targeting compounds interacted at the key residues for the agonist-initiated activation of GPR35. Five compounds showed weak antagonistic activity on M3, which was confirmed to be a disease target by statistical analysis. Seventeen compounds showed NO inhibitory activity. Several compounds showed multi-target properties. An experiment-based network reflected a pharmacological relationship between Jinqiancao granules and the two diseases. CONCLUSIONS: This study identified active compounds in Jinqiancao granules that have synergistic mechanisms, contributing to anti-inflammatory effects. The findings provide scientific evidence for the potential use of Jinqiancao granules as a treatment for prostatitis and BPH.

Clinical performance of BALF droplet digital PCR for differential diagnosis of Pneumocystis jirovecii pneumonia and Pneumocystis jirovecii colonization.

BACKGROUND: Accurate differentiation between Pneumocystis jirovecii (Pj) infection and colonization is crucial for effective treatment. METHODS: From September 2016 to June 2022, 89 immunocompromised patients with unexplained lung infiltrates and clinical suspicion of Pj pneumonia were enrolled at Peking University People's Hospital. Bronchoalveolar lavage fluid (BALF) of these patients were detected by quantitative PCR (qPCR) and droplet digital PCR (ddPCR). RESULTS: The performance of ddPCR was superior to qPCR in detecting Pj infection. Area under the curve was 0.97 (95 %CI: 0.94-1) for ddPCR of the BALF in all patients. The optimal threshold value for discriminating Pj infection from colonization by ddPCR was 13.98 copies/test, with a sensitivity of 97.96 %, specificity of 85.71 %. No obvious correlation between ddPCR copy number and disease severity was observed. CONCLUSION: BALF ddPCR exhibits robust potential in detecting Pj and effectively discriminating colonization and infection.

Heterogeneity of SARS-CoV-2 immune responses after the nationwide Omicron wave in China.

It remains unclear how previous infections and vaccinations influenced and shaped heterogeneous immune responses against Omicron and its variants in diverse populations in China. After the national wave of Omicron in early 2023, we evaluated serum levels of neutralizing antibodies (nAbs) against Omicron (B.1.1.529) and its variants (BA.5, BF.7, and CH1.1) in 33 COVID-19 convalescents and 40 uninfected vaccinees, using vesicular stomatitis virus-based pseudovirus neutralizing assay. In addition, we followed 34 Delta convalescent patients to compare their immune responses against Omicron before (late 2021) and after the Omicron wave (early 2023). NAbs at the acute phase of the disease were investigated in 50 Omicron inpatients, including 24 vaccinated and 26 unvaccinated patients. Among them, nasal mucosal IgA levels were measured in 42 subjects. Compared to vaccination, breakthrough infections significantly increased the breadth and magnitude of serum nAbs and mucosal IgA levels against Omicron variants. Exposure to Omicron but not Delta elicited stronger pan-Omicron responses. In Omicron inpatients, nAbs continued to rise as vaccination doses increased. However, in both vaccinees and convalescents, a fourth dose vaccination did not elicit higher nAbs against Omicron. Furthermore, nAbs against Omicron variants lasted longer than nAbs against WT SARS-CoV-2. Breakthrough infections of Omicron variants elicited specific immune responses against Omicron compared to vaccination and Delta infection. Although repeated vaccination revealed limited impacts on serum nAbs, populations at high risk of hospitalization may still benefit from continued vaccination.IMPORTANCEThe study described the specific humoral immunity against Omicron and its variants (BA.5, BF.7, and CH1.1) in diverse populations, including Delta-positive convalescent patients, Omicron-infected patients with a previous or current confirmed Delta infection, Omicron-positive patients, and healthy controls. In addition, we followed Delta convalescents for 1 year to evaluate the effect of a booster vaccine, breakthrough infection, and reinfection. Nasal mucosal IgA levels against SARS-CoV-2 were also examined. The findings of this study demonstrated the varied responses of individuals in different states following the outbreak of Omicron, highlighting the potential advantages of ongoing immunization for groups that are more vulnerable and have a greater likelihood of being hospitalized.