Infantile eczema is an immunological disease that is characterized by itchy and dry skin. Recent studies have suggested that gut microbiota (GM) plays a role in the development and progression of eczema. To further evaluate this potential link, we collected feces from 19 infants with eczema and 14 infants without eczema and analyzed the molecular discrepancies between the two groups using 16S rDNA analysis.

Background: In recent years, the morbidity of Mycoplasma pneumoniae pneumonia (MPP) has increased significantly in China. A growing number of studies indicate that imbalanced respiratory microbiota is associated with various respiratory diseases. Methods: We enrolled 119 children, including 60 pneumonia patients and 59 healthy children. Nasopharyngeal (NP) and oropharyngeal (OP) sampling was performed for 16S ribosomal RNA (16S rRNA) gene analysis of all children. Sputum and OP swabs were obtained from patients for pathogen detection. Results: Both the NP and OP microbiota of patients differ significantly from that of healthy children. Diseased children harbor lower microbial diversity and a simpler co-occurrence network in NP and OP. In pneumonia patients, NP and OP microbiota showed greater similarities between each other, suggesting transmission of NP microbiota to the OP. Aside from clinically detected pathogens, NP and OP microbiota analysis has also identified possible pathogens in seven cases with unknown infections. Conclusion: NP and OP microbiota in MPP and non-MPP are definitely similar. Respiratory infection generates imbalanced NP microbiota, which has the potential to transmit to OP. Microbiota analysis also promises to compliment the present means of detecting respiratory pathogens.

A cluster of influenza-associated deaths occurred among children during pandemic 2009 influenza A (H1N1) in China, but the risk factors and causes for death have not been clarified.

Despite that obesity is associated with many metabolic diseases, a significant proportion (10-30 %) of obese individuals is recognized as 'metabolically healthy obeses' (MHOs). The aim of the current study is to characterize the gut microbiome for MHOs as compared to 'metabolically unhealthy obeses' (MUOs). We compared the gut microbiome of 172 MHO and 138 MUO individuals from Chongqing (China) (inclined to eat red meat and food with a spicy taste), and performed validation with selected biomarkers in 40 MHOs and 33 MUOs from Quanzhou (China) (inclined to eat seafood and food with a light/bland taste). The genera Alistipes, Faecalibacterium and Odoribacter had increased abundance in both Chongqing and Quanzhou MHOs. We also observed different microbial functions in MUOs compared to MHOs, including an increased abundance of genes associated with glycan biosynthesis and metabolism. In addition, the microbial gene markers identified from the Chongqing cohort bear a moderate accuracy [AUC (area under the operating characteristic curve)=0.69] for classifying MHOs distinct from MUOs in the Quanzhou cohort. These findings indicate that gut microbiome is significantly distinct between MHOs and MUOs, implicating the potential of the gut microbiome in stratification and refined management of obesity.

Respiratory symptoms are the earliest clinical manifestation of Talaromyces marneffei (TM) infection. In this study, we aimed to improve the early identification of TM infection in human immunodeficiency virus (HIV)-negative children with respiratory symptoms as the first manifestation, analyze the risk factors, and provide evidence for diagnosis and treatment.

Influenza A virus (IAV) has had the highest morbidity globally over the past decade. A growing number of studies indicate that the upper respiratory tract (URT) microbiota plays a key role for respiratory health and that a dysfunctional respiratory microbiota is associated with disease; but the impact of microbiota during influenza is understudied.

In recent years, the morbidity of Mycoplasma pneumoniae pneumonia (MPP) has dramatically increased in China. An increasing number of studies indicate that an imbalance in the respiratory microbiota is associated with respiratory infection. We selected 28 hospitalized patients infected with M. pneumoniae and 32 healthy children. Nasopharyngeal (NP) and oropharyngeal (OP) swabs were collected from healthy children, whereas NP, OP and bronchoalveolar lavage (BAL) specimens were collected from patients. Microbiota analysis was performed on all microbial samples using 16 S ribosomal RNA (16 S rRNA) sequencing. The NP microbial samples in healthy children were divided into two groups, which were dominated by either Staphylococcus or mixed microbial components. The respiratory microbiota in pneumonia patients harbored a lower microbial diversity compared to healthy children, and both the NP and OP microbiota of patients differed significantly from that of healthy children. Hospitalized MPP children with a higher abundance of Mycoplasma in the BAL fluid (BALF) microbiota tended to suffer longer hospitalization lengths and higher peak fevers and serum C-reactive protein levels. Concordance analysis explained the succession of imbalanced NP microbiota to the OP and lung in diseased children. However, the association of the abundance of Mycoplasma in BALF microbiota with that in NP or OP microbiota varied among individuals, which suggested the sensitivity of BALF in MPP diagnostics, mirroring MPP severity.

Pneumonia is one of the most important causes of morbidity and mortality in children. Identification and characterization of pathogens that cause infections are crucial for accurate treatment and accelerated recovery. However, in most cases, the causative agent cannot be identified, which is partly due to the limited spectrum of pathogens covered by current diagnostics based on nucleic acid amplification. Therefore, in this study, we explored the application of metagenomic next-generation sequencing (mNGS) for the diagnosis of children with severe pneumonia. From April to July 2017, 32 hospitalized children with severe nonresponding pneumonia in Shenzhen Children's Hospital were included in this study. Blood tests were conducted immediately after hospitalization to assess cell counts and inflammatory markers, oropharyngeal swabs were collected to identify common pathogens by qPCR and culture. After bronchoscopy, bronchoalveolar lavage fluid (BALF) samples were collected for further pathogen identification using standardized diagnostic tests and mNGS. Blood tests were normal in 3 of the 32 children. In 9 oropharyngeal swabs, bacterial pathogens were detected, in 5 of these Mycoplasma pneumoniae was detected. Adenovirus was detected in 5 BALF samples, using the Direct Immunofluorescence Assay (DFA). In 15 cases, no common pathogens were found in BALF samples, using the current standard diagnostic tests, while in all 32 BALFs, pathogens were identified using mNGS, including adenovirus, Mycoplasma pneumoniae, Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, cytomegalovirus and bocavirus. This study shows that, with mNGS, the sensitivity of detection of the causative pathogens in children with severe nonresponding pneumonia is significantly improved. In addition, mNGS gives more strain specific information, helps to identify new pathogens and could potentially help to trace and control outbreaks. In this study, we have shown that it is possible to have the results within 24 hours, making the application of mNGS feasible for clinical diagnostics.

Knowledge on the etiology of LRTIs is essential for improvement of the clinical diagnosis and accurate treatment. Molecular detection methods were applied to identify a broad range of bacterial and viral pathogens in a large set of bronchial alveolar lavage (BAL) fluid samples. The patterns of detected pathogens were correlated to the clinical symptoms.

Introduction: The airway microbiota has been linked to specific paediatric respiratory diseases, but studies are often small. It remains unclear whether particular bacteria are associated with a given disease, or if a more general, non-specific microbiota association with disease exists, as suggested for the gut. We investigated overarching patterns of bacterial association with acute and chronic paediatric respiratory disease in an individual participant data (IPD) meta-analysis of 16S rRNA gene sequences from published respiratory microbiota studies. Methods: We obtained raw microbiota data from public repositories or via communication with corresponding authors. Cross-sectional analyses of the paediatric (<18 years) microbiota in acute and chronic respiratory conditions, with >10 case subjects were included. Sequence data were processed using a uniform bioinformatics pipeline, removing a potentially substantial source of variation. Microbiota differences across diagnoses were assessed using alpha- and beta-diversity approaches, machine learning, and biomarker analyses. Results: We ultimately included 20 studies containing individual data from 2624 children. Disease was associated with lower bacterial diversity in nasal and lower airway samples and higher relative abundances of specific nasal taxa including Streptococcus and Haemophilus. Machine learning success in assigning samples to diagnostic groupings varied with anatomical site, with positive predictive value and sensitivity ranging from 43 to 100 and 8 to 99%, respectively. Conclusion: IPD meta-analysis of the respiratory microbiota across multiple diseases allowed identification of a non-specific disease association which cannot be recognised by studying a single disease. Whilst imperfect, machine learning offers promise as a potential additional tool to aid clinical diagnosis.

The gut microbiota (GM) is related to obesity and other metabolic diseases. To detect GM markers for obesity in patients with different metabolic abnormalities and investigate their relationships with clinical indicators, 1,914 Chinese adults were enrolled for 16S rRNA gene sequencing in this retrospective study. Based on GM composition, Random forest classifiers were constructed to screen the obesity patients with (Group OA) or without metabolic diseases (Group O) from healthy individuals (Group H), and high accuracies were observed for the discrimination of Group O and Group OA (areas under the receiver operating curve (AUC) equal to 0.68 and 0.76, respectively). Furthermore, six GM markers were shared by obesity patients with various metabolic disorders (Bacteroides, Parabacteroides, Blautia, Alistipes, Romboutsia and Roseburia). As for the discrimination with Group O, Group OA exhibited low accuracy (AUC = 0.57). Nonetheless, GM classifications to distinguish between Group O and the obese patients with specific metabolic abnormalities were not accurate (AUC values from 0.59 to 0.66). Common biomarkers were identified for the obesity patients with high uric acid, high serum lipids and high blood pressure, such as Clostridium XIVa, Bacteroides and Roseburia. A total of 20 genera were associated with multiple significant clinical indicators. For example, Blautia, Romboutsia, Ruminococcus2, Clostridium sensu stricto and Dorea were positively correlated with indicators of bodyweight (including waistline and body mass index) and serum lipids (including low density lipoprotein, triglyceride and total cholesterol). In contrast, the aforementioned clinical indicators were negatively associated with Bacteroides, Roseburia, Butyricicoccus, Alistipes, Parasutterella, Parabacteroides and Clostridium IV. Generally, these biomarkers hold the potential to predict obesity-related metabolic abnormalities, and interventions based on these biomarkers might be beneficial to weight loss and metabolic risk improvement.

Probiotic bacteria can induce immune regulation or immune tolerance in patients with allergic diseases, but the underlying mechanisms are still unclear. There has been a growing interest in the use of beneficial bacteria for allergic diseases recently. This study aimed at exploring whether Clostridium butyricum CGMCC0313-1 (C. butyricum) can reduce β-lactoglobulin(BLG)-induced intestinal anaphylaxis in a murine model of food allergy.

No abstract available

The upper respiratory tract (URT) is home to various microbial commensals, which function as competitors to pathogens and help train the immune system. However, few studies have reported the normal microbiota carriage in the URT of healthy Chinese children. In this study, we performed a 16S rDNA gene sequencing analysis of 83 anterior nares (ANs), 60 nasopharynx (NP), and 97 oropharynx (OP) samples from 98 healthy children in Shenzhen, China (≤12 years of age). The microbiota in ANs and NP is the same at different ages and typical species in these sites include Moraxella, Staphylococcus, Corynebacterium, Streptococcus, and Dolosigranulum. By contrast, the OP is primarily colonized by Streptococcus, Prevotella, Neisseria, Veillonella, Rothia, Leptotrichia, and Haemophilus. Streptococcus and Rothia keep low abundance in OP microbiota of children ≤1 year old, whereas Prevotella, Neisseria, Haemophilus, and Leptotrichia amass significantly in individuals >1 year old. This work furnishes an important reference for understanding microbial dysbiosis in the URT of Chinese paediatric patients.

Bronchiolitis is one of the most severe diseases affecting infants worldwide. An imbalanced oropharynx (OP) microbiota has been reported in infants hospitalized with bronchiolitis; however, the microbiota dynamics in the OP and faeces during therapy remain unexplored. In total, 27 infants who were hospitalized with bronchiolitis were selected for this study, and sampling was conducted before therapy and after clinical recovery. We also recruited 22 age-matched healthy infants for this study. The faecal and OP microbiota diversity in the patients was lower than that in the healthy children. The faecal microbiota (FM) in the diseased children significantly differed from that in the healthy subjects and contained accumulated Bacteroides and Streptococcus. The OP microbiota in both the healthy and diseased infants was dominated by Streptococcus. After the treatment, the FM and OP microbiota in the patients was comparable to that before the treatment. This study may serve as an additional reference for future bronchiolitis studies, and the "risk microbiota model" of clinically recovered infants suggests an increased susceptibility to pathogen intrusion.

The imbalanced respiratory microbiota observed in pneumonia causes high morbidity and mortality in childhood. Respiratory metagenomic analysis demands a comprehensive microbial gene catalogue, which will significantly advance our understanding of host-microorganism interactions.

The pandemic of Coronavirus Disease 2019 (COVID-19) brings new challenges for pediatricians, especially in the differentiation with non-COVID-19 pneumonia in the peak season of pneumonia. We aimed to compare the clinical characteristics of pediatric patients with COVID-19 and other respiratory pathogens infected pneumonias.

PCV13 introduction in China has led to a significant reduction of vaccine serotype Streptococcus pneumoniae. However, non-vaccine serotypes with highly resistance and invasiveness were often reported in the post-pneumococcal conjugate vaccine era and there was regional differences.

Mycoplasma pneumoniae is a common pathogen causing respiratory disease in children. We sought to investigate the epidemiology of M. pneumoniae among outpatient children with mild respiratory tract infections (RTIs) during the coronavirus disease 2019 (COVID-19) pandemic. Eligible patients were prospectively enrolled from January 2020 to June 2021. Throat swabs were tested for M. pneumoniae RNA. M. pneumoniae IgM was tested by a colloidal gold assay. Macrolide resistance and the effect of the COVID-19 countermeasures on M. pneumoniae prevalence were assessed. Symptom scores, treatments, and outcomes were evaluated. Eight hundred sixty-two eligible children at 15 centers in China were enrolled. M. pneumoniae was detected in 78 (9.0%) patients. Seasonally, M. pneumoniae peaked in the first spring and dropped dramatically to extremely low levels over time until the next summer. Decreases in COVID-19 prevalence were significantly associated with decreases in M. pneumoniae prevalence (r = 0.76, P = 0.001). The macrolide resistance rate was 7.7%. The overall sensitivity and specificity of the colloidal gold assay used in determining M. pneumoniae infection were 32.1% and 77.9%, respectively. No more benefits for improving the severity of symptoms and outcomes were observed in M. pneumoniae-infected patients treated with a macrolide than in those not treated with a macrolide during follow-up. The prevalences of M. pneumoniae and macrolide resistance in outpatient children with mild RTIs were at low levels in the early stage of the COVID-19 pandemic but may have rebounded recently. The colloidal gold assay for M. pneumoniae IgM may be not appropriate for diagnosis of M. pneumoniae infection. Macrolides should be used with caution among outpatients with mild RTIs. IMPORTANCE This is the first and largest prospective, multicenter, active, population-based surveillance study of the epidemiology of Mycoplasma pneumoniae among outpatient children with mild respiratory tract infections (RTIs) during the COVID-19 pandemic. Nationwide measures like strict face mask wearing and restrictions on population movement implemented to prevent the spread of COVID-19 might also effectively prevent the spread of M. pneumoniae. The prevalence of M. pneumoniae and the proportion of drug-resistant M. pneumoniae isolates in outpatient children with mild RTIs were at low levels in the early stage of the COVID-19 pandemic but may have rebounded recently. The colloidal gold assay for M. pneumoniae IgM may be not appropriate for screening and diagnosis of M. pneumoniae infection. Macrolides should be used with caution among outpatients with mild RTIs.