Investigating the Effects and Mechanism of Rhodiola Rosea Injection on Cardiac Function in Rats with Chronic Heart Failure.

AIM: To study the effect of Rhodiola Rosea injection on cardiac function and the reninangiotensin- aldosterone system (RASS) in rats with chronic heart failure. BACKGROUND: Rhodiola Rosea injection, a traditional Chinese medication for relieving blood stasis and improving blood circulation, is an excellent therapeutic for treating coronary heart disease-angina pectoris. Rhodiola Rosea injection's major component, salidroside, protects the cardiovascular system. But there isn't much first-hand evidence about how injectable Rhodiola Rosea affects heart failure. OBJECTIVES: In this study, a rat model of heart failure was established, and the effect of Rhodiola rosea injection on myocardial cell morphology, cardiac function, and ventricular remodelling in rats with heart failure was investigated. METHODS: 66 SD male rats were selected; 10 were randomly selected as a blank control group, and 56 were treated intraperitoneally with doxorubicin (4 g/g). After 6 weeks, all animals had LVEF 60%. Established a heart failure model. Each group had 14 rats: model control, low-dose, mediumdose, and high-dose Rhodiola Rosea injection. The 2 mL/kg of Rhodiola Rosea injection was injected into the tail vein once a day for 2 weeks. Both the blank and control groups received normal daily saline. After 2 weeks, the echocardiographic index, RASS-related index, and serum BNP level were assessed in all rats, and myocardial tissue morphology was observed. MiRNA423-5p, miRNA499-5p, and miRNA210-3p were extracted from peripheral blood. Rhodiola rosea injection on its expression was compared to healthy control rats. RESULTS: 6 mL/kg Rhodiola Rosea injection lowered LVEDV and LVESV while increasing LVEF and LVFS. Injections of 6 mL/kg Rhodiola Rosea reduce plasma levels of miR-210-3p, miR-423- 5p, miRNA-499, and BNP in heart failure model rats. The 6 mL/kg Rhodiola Rosea injection can restore the RASS indexes of heart failure rats to the level of the normal group. CONCLUSION: The present study offers preliminary evidence supporting the use of Rhodiola Rosea injection in the treatment of heart failure and offers a solid foundation for clinical off-label medication use.

The N-terminal acetyltransferase Naa50 regulates tapetum degradation and pollen development in Arabidopsis.

The N-terminal acetylation of proteins is a key modification in eukaryotes. However, knowledge of the biological function of N-terminal acetylation modification of proteins in plants is limited. Naa50 is the catalytic subunit of the N-terminal acetyltransferase NatE complex. We previously demonstrated that the absence of Naa50 leads to sterility in Arabidopsis thaliana. In the present study, the lack of Naa50 resulted in collapsed and sterile pollen in Arabidopsis. Further experiments showed that the mutation in Naa50 accelerated programmed cell death in the tapetum. Expression pattern analysis revealed the specific expression of Naa50 in the tapetum cells of anthers at 9-11 stages during pollen development, when tapetal programmed cell death occurred. Reciprocal cross analyses indicated that male sterility in naa50 is caused by sporophytic effects. mRNA sequencing and quantitative PCR of the closed buds showed that the deletion of Naa50 resulted in the upregulation of the cysteine protease coding gene CEP1 and impaired the expression of several genes involved in pollen wall deposition and pollen mitotic division. The collective data suggest that Naa50 balances the degradation of tapetum cells during anther development and plays an important role in pollen development by affecting several pathways.

Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug-gene-adverse drug reaction (ADR) interaction network. For the first time, the drug safety was assessed in a broad landscape of 1,156 distinct ADRs. We also designed a parameter ToxicityScore to quantify the overall drug safety. Moreover, we determined association strength for every 3,807,631 gene-ADR interactions, which clues mechanistic exploration of ADRs. For convenience, we deployed the model as a web service ADRAlert-gene at http://www.bio-add.org/ADRAlert/. In summary, this study offers insights into prioritizing safe drug therapy. It helps reduce the attrition rate of new drug discovery by providing a reliable ADR profile in the early preclinical stage.

Facilitating accurate health provider directories using natural language processing.

BACKGROUND: Accurate information in provider directories are vital in health care including health information exchange, health benefits exchange, quality reporting, and in the reimbursement and delivery of care. Maintaining provider directory data and keeping it up to date is challenging. The objective of this study is to determine the feasibility of using natural language processing (NLP) techniques to combine disparate resources and acquire accurate information on health providers. METHODS: Publically available state licensure lists in Connecticut were obtained along with National Plan and Provider Enumeration System (NPPES) public use files. Connecticut licensure lists textual information of each health professional who is licensed to practice within the state. A NLP-based system was developed based on healthcare provider taxonomy code, location, name and address information to identify textual data within the state and federal records. Qualitative and quantitative evaluation were performed, and the recall and precision were calculated. RESULTS: We identified nurse midwives, nurse practitioners, and dentists in the State of Connecticut. The recall and precision were 0.95 and 0.93 respectively. Using the system, we were able to accurately acquire 6849 of the 7177 records of health provider directory information. CONCLUSIONS: The authors demonstrated that the NLP- based approach was effective at acquiring health provider information. Furthermore, the NLP-based system can always be applied to update information further reducing processing burdens as data changes.