A bunch of microRNAs (miRNAs) have been demonstrated to be aberrantly expressed in cancer tumor tissue and serum. The miRNA signatures identified from the serum samples could serve as potential noninvasive diagnostic markers for breast cancer. The role of the miRNAs in cancerigenesis is unclear. In this study, we generated the expression profiles of miRNAs from the paired breast cancer tumors, normal, tissue, and serum samples from eight patients using small RNA-sequencing. Serum samples from eight healthy individuals were used as normal controls. We identified total 174 significantly differentially expressed miRNAs between tumors and the normal tissues, and 109 miRNAs between serum from patients and serum from healthy individuals. There are only 10 common miRNAs. This suggests that only a small portion of tumor miRNAs are released into serum selectively. Interestingly, the expression change pattern of 28 miRNAs is opposite between breast cancer tumors and serum. Functional analysis shows that the differentially expressed miRNAs and their target genes form a complex interaction network affecting many biological processes and involving in many types of cancer such as prostate cancer, basal cell carcinoma, acute myeloid leukemia, and more.

Background The gold standard for the diagnosis of central precocious puberty (CPP) is gonadotropin-releasing hormone (GnRH) or GnRH analogs (GnRHa) stimulation test. But the stimulation test is time-consuming and costly. Our objective was to develop a risk score model readily adoptable by clinicians and patients. Methods A cross-sectional study based on the electronic medical record system was conducted in the Children’s Hospital, Fudan University, Shanghai, China from January 2010 to August 2016. Patients with precocious puberty were randomly split into the training (n = 314) and validation (n = 313) sample. In the training sample, variables associated with CPP (P < 0.2) in univariate analyses were introduced in a multivariable logistic regression model. Prediction model was selected using a forward stepwise analysis. A risk score model was built with the scaled coefficients of the model and tested in the validation sample. Results CPP was diagnosed in 54.8% (172/314) and 55.0% (172/313) of patients in the training and validation sample, respectively. The CPP risk score model included age at the onset of puberty, basal luteinizing hormone (LH) concentration, largest ovarian volume, and uterine volume. The C-index was 0.85 (95% CI: 0.81–0.89) and 0.86 (95% CI: 0.82–0.90) in the training and the validation sample, respectively. Two cut-off points were selected to delimitate a low- (< 10 points), median- (10–19 points), and high-risk (≥ 20 points) group. Conclusions A risk score model for the risk of CPP had a moderate predictive performance, which offers the advantage of helping evaluate the requirement for further diagnostic tests (GnRH or GnRHa stimulation test).

Early passage of a stone may reduce the renal injury induced by melamine-contaminated milk powder-associated urolithiasis.

Adverse drug reaction (ADR) is a common clinical problem, sometimes accompanying with high risk of mortality and morbidity. It is also one of the major factors that lead to failure in new drug development. Unfortunately, most of current experimental and computational methods are unable to evaluate clinical safety of drug candidates in early drug discovery stage due to the very limited knowledge of molecular mechanisms underlying ADRs. Therefore, in this study, we proposed a novel na€ıve Bayesian model for rapid assessment of clinical ADRs with frequency estimation. This model was constructed on a gene-ADR association network, which covered 611 US FDA approved drugs, 14,251 genes, and 1,254 distinct ADR terms. An average detection rate of 99.86 and 99.73 percent were achieved eventually in identification of known ADRs in internal test data set and external case analyses respectively. Moreover, a comparative analysis between the estimated frequencies of ADRs and their observed frequencies was undertaken. It is observed that these two frequencies have the similar distribution trend. These results suggest that the naıve Bayesian model based on gene-ADR association network can serve as an efficient and economic tool in rapid ADRs assessment.

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Background: Gynecological laparoscopic surgery is the main method to treat gynecological diseases, but postoperative gastrointestinal reactions are more common in patients. Auricular therapy, as a characteristic therapy of Traditional Chinese Medicine, can improve gastrointestinal symptoms such as nausea and vomiting by stimulating the conduction of acupoints through the nervous system on internal organs, but there are studies questioning the efficacy of auricular therapy. Therefore, the purpose of this study is to prove the efficacy and safety of auricular therapy in promoting gastrointestinal function recovery after gynecological laparoscopic surgery, and to provide reference value for future clinical practice. Methods: To search English databases (PubMed, Excerpta Medical Database [Embase], Web of Science, the Cochrane Library) and Chinese databases (Chinese National Knowledge Internet [CNKI], WanFang, Viper, Chinese Biomedical Literature Database) by computer, and conduct a randomized controlled trial on the effect of aural point therapy on gastrointestinal function recovery of patients after gynecological laparoscopic surgery from the establishment of the database to October 2020. Two researchers independently evaluate the quality of the included studies and extract the data, and meta-analysis of the included literature is carried out using RevMan5.3 software. Results: In this study, the efficacy and safety of auricular therapy in the recovery of gastrointestinal function after gynecological laparoscopic surgery are evaluated from the aspects of first anal exhaust time, bowel sound recovery time, and incidence of gastrointestinal complications. Conclusion: This study will provide reliable evidence-based evidence for auricular therapy in the treatment of gastrointestinal function after gynecologic laparoscopic surgery. Ethics and dissemination: Private information from individuals will not be published. This systematic review also does not involve endangering participant rights. Ethical approval was not required. The results may be published in a peer-reviewed journal or disseminated at relevant conferences. OSF Registration number: DOI 10.17605 / OSF.IO / ZSPGA

Background The gold standard for the diagnosis of central precocious puberty (CPP) is gonadotropin-releasing hormone (GnRH) or GnRH analogs (GnRHa) stimulation test. But the stimulation test is time-consuming and costly. Our objective was to develop a risk score model with readily available features.Methods A cross sectional study based on the electronic medical record system including 627 girls with precocious puberty were conducted in the Children’s Hospital, Fudan University, Shanghai, China from January 2010 to August 2016. Patients were randomly split into the training (n=314) and validation (n=313) sample. In the training sample, variables associated with CPP (P<0.2) in univariate analyses were introduced in a multivariable logistic regression model and selected using a forward stepwise analysis. A risk score model was built with the scaled coefficients of the model and tested in the validation sample.Results CPP was diagnosed in 54.8% (172/314) and 55.0% (172/313) of patients in the training and validation sample respectively. The CPP risk score model included variables of age at onset of puberty, basal luteinizing hormone (LH) concentration, largest ovarian volume, and uterine volume. The C-index was 0.85 (95% CI: 0.81-0.89) for the training sample and 0.86 (95% CI: 0.82-0.90) for the validation sample. Two cut-off points were selected to delimitate a low- (<10 points), median- (10-19 points), and high-risk (≥ 20 points) group. Conclusions A risk score model developed among girls with precocious pubertal development had moderate discrimination to stratify CPP risk, which could help make decisions on the need for GnRH (GnRHa) stimulation test.