[Association between neonatal discharge preparedness and adverse health events]. / æ–°ç”Ÿå„¿å‡ºé™¢å‡†å¤‡åº¦ä¸Žä¸è‰¯å¥åº·äº‹ä»¶çš„å ³ç³».

OBJECTIVES: To study the association between neonatal discharge preparedness and adverse health events. METHODS: The neonates who were born in hospitals from different regions of Gansu Province in China and their parents were enrolled as subjects, and an investigation was performed for the discharge preparedness. According to the level of discharge preparedness, the subjects were divided into low-, middle-, and high-level groups. The neonates were followed up to observe the incidence rate of adverse health events within one month after discharge. The association between neonatal discharge preparedness and adverse health events was analyzed. RESULTS: The neonates with adverse health events had a significantly lower level of discharge preparedness than those without adverse events (P<0.05). The multivariate logistic regression analysis showed that the incidence rate of adverse health events was reduced by 34.8% in the middle-level group and 78.7% in the high-level group compared with the low-level group (P<0.05). The readmission rate of neonates was 8.1% (35/430), and the neonates readmitted had a significantly lower level of discharge preparedness than those not readmitted (P<0.05). The multivariate logistic regression analysis showed that the readmission rate of neonates was reduced by 67.4% in the middle-level group and 84.2% in the high-level group compared with the low-level group (P<0.05). CONCLUSIONS: Discharge preparedness may affect the incidence of adverse health events and the rate of readmission within one month after discharge. Medical staff should adopt effective intervention measures to improve discharge preparedness, so as to reduce the incidence of adverse health events and the rate of readmission.

A sub-pathway based method to identify candidate drugs for glioblastomas.

Glioblastomas (GBM) are the most common primary malignant brain tumors with a high invasiveness and resistance to radiation and other treatments. The need for the development of new therapeutic agents for GBM is urgent. Here, we aimed to explore the metabolic mechanism of GBM and identified potential novel drugs for GBM by a sub-pathway-based method. By using the GBM microarray data from "The Cancer Genome Atlas" database, we first identified the 274 differentially expressed genes between GBM and normal samples. Then, we identified 18 significant enriched metabolic sub-pathways that may involve in the development of GBM. Finally, by an integrated analysis of GBM-involved sub-pathways and drug-affected sub-pathways, we identified 66 novel small-molecular drugs capable to target the GBM-involved sub-pathways. Our method could not only identify existing drug (paclitaxel) for GBM, but also predict potentially novel agents (pergolide) that might have therapeutic effects. We also experimentally verified that pergolide could induce GBM cell death. These candidate small-molecular drugs identified by our approach may provide insights into a novel therapy approach for GBM.

WITHDRAWN: Discrimination of Parkinson-associated LRRK2 alleles by introduction of a single nucleotide mismatch into siRNA.

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[Comparison of MGMT and ERCC2 expression in temozolomide for the treatment of malignant glioma drug resistance and their genetic relationship].

OBJECTIVE: To study the impact of two human glioma tissue resistance genes MGMT and ERCC(2) on the temozolomide-based treatment of malignant gliomas and detect the relationship of their expressions. METHODS: A total of 58 malignant glioma patients aged 19 - 68 years old receiving a chemotherapy of temozolomide were followed up and classified as non-sensitive group (n = 30) and sensitive group (n = 28). Immunohistochemistry was employed to detect the expression rates of MGMT and ERCC(2). And the correlation between the expressions of two genes was analyzed by immunohistochemistry and RT-PCR (reverse transcription-polymerase chain reaction). RESULTS: The expression rates of MGMT and ERCC(2) were 10.71% and 3.57% in the sensitive group and 63.33% and 56.67% in the non-sensitive group. It had an obvious correlation with the expressions of MEGT and ERCC(2) through an analysis of immunohistochemistry and RT-PCR (both P < 0.01). CONCLUSION: The expressions of MGMT and ERCC(2) in the sensitive group are markedly lower than those in the non-sensitive group. The expression of two genes may be related to tumor prognosis. Maybe these two genes have an intrinsic link between their expressions. Both participate in the repair of cellular DNA damage and the formation of tumor drug resistance. And the prognosis has obvious relevance.