DRMDA: deep representations-based miRNA-disease association prediction.

Recently, microRNAs (miRNAs) are confirmed to be important molecules within many crucial biological processes and therefore related to various complex human diseases. However, previous methods of predicting miRNA-disease associations have their own deficiencies. Under this circumstance, we developed a prediction method called deep representations-based miRNA-disease association (DRMDA) prediction. The original miRNA-disease association data were extracted from HDMM database. Meanwhile, stacked auto-encoder, greedy layer-wise unsupervised pre-training algorithm and support vector machine were implemented to predict potential associations. We compared DRMDA with five previous classical prediction models (HGIMDA, RLSMDA, HDMP, WBSMDA and RWRMDA) in global leave-one-out cross-validation (LOOCV), local LOOCV and fivefold cross-validation, respectively. The AUCs achieved by DRMDA were 0.9177, 08339 and 0.9156 ± 0.0006 in the three tests above, respectively. In further case studies, we predicted the top 50 potential miRNAs for colon neoplasms, lymphoma and prostate neoplasms, and 88%, 90% and 86% of the predicted miRNA can be verified by experimental evidence, respectively. In conclusion, DRMDA is a promising prediction method which could identify potential and novel miRNA-disease associations.

A heterogeneous label propagation approach to explore the potential associations between miRNA and disease.

BACKGROUND: Research on microRNAs (miRNAs) has attracted increasingly worldwide attention over recent years as growing experimental results have made clear that miRNA correlates with masses of critical biological processes and the occurrence, development, and diagnosis of human complex diseases. Nonetheless, the known miRNA-disease associations are still insufficient considering plenty of human miRNAs discovered now. Therefore, there is an urgent need for effective computational model predicting novel miRNA-disease association prediction to save time and money for follow-up biological experiments. METHODS: In this study, considering the insufficiency of the previous computational methods, we proposed the model named heterogeneous label propagation for MiRNA-disease association prediction (HLPMDA), in which a heterogeneous label was propagated on the multi-network of miRNA, disease and long non-coding RNA (lncRNA) to infer the possible miRNA-disease association. The strength of the data about lncRNA-miRNA association and lncRNA-disease association enabled HLPMDA to produce a better prediction. RESULTS: HLPMDA achieved AUCs of 0.9232, 0.8437 and 0.9218 ± 0.0004 based on global and local leave-one-out cross validation and 5-fold cross validation, respectively. Furthermore, three kinds of case studies were implemented and 47 (esophageal neoplasms), 49 (breast neoplasms) and 46 (lymphoma) of top 50 candidate miRNAs were proved by experiment reports. CONCLUSIONS: All the results adequately showed that HLPMDA is a recommendable miRNA-disease association prediction method. We anticipated that HLPMDA could help the follow-up investigations by biomedical researchers.

The LCLS variable-energy hard X-ray single-shot spectrometer.

The engineering design, implementation, operation and performance of the new variable-energy hard X-ray single-shot spectrometer (HXSSS) for the LCLS free-electron laser (FEL) are reported. The HXSSS system is based on a cylindrically bent Si thin crystal for dispersing the incident polychromatic FEL beam. A spatially resolved detector system consisting of a Ce:YAG X-ray scintillator screen, an optical imaging system and a low-noise pixelated optical camera is used to record the spectrograph. The HXSSS provides single-shot spectrum measurements for users whose experiments depend critically on the knowledge of the self-amplified spontaneous emission FEL spectrum. It also helps accelerator physicists for the continuing studies and optimization of self-seeding, various improved mechanisms for lasing mechanisms, and FEL performance improvements. The designed operating energy range of the HXSSS is from 4 to 20 keV, with the spectral range of order larger than 2% and a spectral resolution of 2 × 10(-5) or better. Those performance goals have all been achieved during the commissioning of the HXSSS.

MDAD: A Special Resource for Microbe-Drug Associations.

The human-associated microbiota is diverse and complex. It takes an essential role in human health and behavior and is closely related to the occurrence and development of disease. Although the diversity and distribution of microbial communities have been widely studied, little is known about the function and dynamics of microbes in the human body or the complex mechanisms of interaction between them and drugs, which are important for drug discovery and design. A high-quality comprehensive microbe and drug association database will be extremely beneficial to explore the relationship between them. In this article, we developed the Microbe-Drug Association Database (MDAD), a collection of clinically or experimentally supported associations between microbes and drugs, collecting 5,055 entries that include 1,388 drugs and 180 microbes from multiple drug databases and related publications. Moreover, we provided detailed annotations for each record, including the molecular form of drugs or hyperlinks from DrugBank, microbe target information from Uniprot and the original reference links. We hope MDAD will be a useful resource for deeper understanding of microbe and drug interactions and will also be beneficial to drug design, disease therapy and human health.

DLREFD: a database providing associations of long non-coding RNAs, environmental factors and phenotypes.

Database URL: http://chengroup.cumt.edu.cn/DLREFD.

NRDTD: a database for clinically or experimentally supported non-coding RNAs and drug targets associations.

Database URL: http://chengroup.cumt.edu.cn/NRDTD.

[Temporary ectopic implantation of amputated fingers and dorsalis pedis flaps for thumb reconstruction and skin defect repair of hands].

OBJECTIVE: To investigate the feasibility of temporary ectopic implantation of amputated fingers and dorsalis pedis flaps for thumb reconstruction and skin defect repair of the hand. METHODS: Between February 2006 and February 2012, 9 patients with thumb amputation having no replanted condition were treated. There were 7 males and 2 females with an average age of 35 years (range, 20-45 years). The injury causes included explosive injury in 1 case, puncher injury in 1 case, stiring machine injury in 1 case, gear injury in 3 cases, and heavy pound injury in 3 cases. At 2-5 hours after injury, one-stage temporary ectopic implantation of amputated finger to foot was performed. After debridement, thumb defect was rated as degree III in 1 case, as degree IV in 3 cases, and as degree V in 5 cases. When amputated fingers survived completely after 1-4 months, the amputated finger was replanted to its anatomic position, skin defect was repaired with dorsalis pedis flap. The area of skin defect ranged from 5 cm x 4 cm to 7 cm x 6 cm. The area of flaps ranged from 6 cm x 5 cm to 8 cm x 7 cm. The donor site was repaired by the skin grafting. RESULTS: Arterial crisis occurred in 1 case after 1 day of one-stage operation, and was cured after vascular exploration, and the amputated fingers survived in the others. The reconstructed thumbs and flaps survived after two-stage operation, and the skin graft at donor site survived. The patients were followed up 1-4 years (mean, 2.8 years). The reconstructed thumbs had good appearance and satisfactory opposition and finger-to-finger functions. According to the standard functional evaluation issued by Hand Surgery Association of Chinese Medical Association, the scores of survival fingers were 73-91 (mean, 84); the results were excellent in 7 cases and good in 2 cases with an excellent and good rate of 100%. CONCLUSION: Temporary ectopic implantation of amputated finger to foot combined with dorsalis pedis flap can be used to reconstruct thumb and repair skin defect of the hand.