Background The diagnosis of cow’s milk protein allergy(CMPA) may be easily misdiagnosed due to its lack of specific symptoms. Thus, experts have proposed the use of Cow’s milk-related symptom scores (CoMiSS) to predict CMPA. There has been no relevant report on the clinical application value of CoMiSS in Chinese children. This study aimed to evaluate the effect of CoMiSS in early identification of CMPA in Chinese infants. Methods We calculated CoMiSS for 38 infants with suspected CMPA diagnosed in the pediatric gastroenterologic clinic in our hospital. After 4 weeks of dietary elimination and symptomatic improvement, these infants returned to our hospital to undergo oral food challenge (OFC). The ROC curve was used to determine the sensitivity and specificity of CoMiSS and evaluate the effect of CoMiSS in early identification of CMPA in Chinese infants. We didn’t determine the CoMiSS of presumed healthy infants as control group. Results Of 38 infants who underwent OFC testing, the average CoMiSS of infants with positive OFC testing was 7.4 ± 2.3, while the average CoMiSS of infants with negative OFC testing was 4.1 ± 1.6, and there was a significant difference between two groups( F = 2.13, P< 0.05). The area under the ROC curve (AUC) of CoMiSS was 0.89, and the best diagnostic cut-off point was 5.5. The sensitivity of CoMiSS was 87.5%, while the specificity of CoMiSS was 78.6%. Conclusion CoMiSS is a simple and operable method to screen for CMPA, though there may be a risk of under-diagnosis when CoMiSS≥12 is used as the criterion for early identification of CMPA in Chinese infants. More multi-center studies are needed to evaluate whether the factors such as bloody stool should be included in CoMiSS or CoMiSS≥6 can be used as the criterion for early identification of CMPA in Chinese infants.

Idiopathic central precocious puberty (ICPP) is a relatively common condition in preadolescent girls, and its pathogenesis remains to be uncovered. A variety of studies have highlighted the association of gut microbiota (GM) with endocrine diseases, such as obesity, which is commonly associated with ICPP. However, the relationship between GM and ICPP remains unexplored. Feces samples were collected from 25 girls with ICPP (ICPP group) and 23 healthy girls (Control group). We applied 16S rDNA sequencing to compare the GM between two groups. The ICPP group had higher GM diversity and was enriched for several GM species, including Ruminococcus gnavus, Ruminococcus callidus, Ruminococcus bromii, Roseburia inulinivorans, Coprococcus eutactus, Clostridium leptum, and Clostridium lactatifermentans, which are known to be associated with obesity and are related to the production of short-chain fatty acids. Additionally, 36 candidate GM biomarkers for patients with ICPP screening were identified with high accuracy (AUC = 0.95, 95% CI 0.88 to 1). We observed that the GM of the ICPP group was enriched for the microbial functions of cell motility, signal transduction, and environmental adaptation. Positive correlations were also detected between Fusobacterium and follicle-stimulating hormone, and Gemmiger and luteinizing hormone. This study documents relationships between GM and ICPP, and the implication of these findings remains to be determined.

Objective Cardiac diseases lead to heart failure (HF), but the progression can take several years. Using blood samples to monitor changes in the heart before clinical symptoms begin may help to improve patient management. Methods Microarray data GSE42955 and GSE9128 were used as study datasets and GSE16499, GSE57338, and GSE59867 were used as validation groups. The “limma” package from R Language was used to identify differentially expressed genes. Functional enrichment analyses of gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways were performed using Database for Annotation, Visualization and Integrated Discovery. We also investigated the correlation between the heart and blood using the mRNA expression level. Results Three hub genes, CD14, CD163, and CCR1, were identified. Functional enrichment analyses showed their involvement in the immune response and in the inflammatory response, which are the critical biochemical processes in ischemic HF. The mRNA expression level further demonstrated that a special model may exist to help to predict the mRNA level in the heart based on that in blood. Conclusions Our study identified three biomarkers that can connect the heart and blood in ischemic heart diseases, which may be a new approach to help better manage ischemic cardiac disease patients.

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