In recent years, mRNA drugs have shown a great potential for the treatment of genetic diseases and attracted the attention of many researchers. This article has reviewed the advance in the research of mRNA drugs for the treatment of genetic diseases over the past 30 years, including their mechanisms of action and structure design, with a focus on their advantages as alternative therapies such as high specificity, low dosage, and sustained expression. Meanwhile, challenges for the effective delivery and storage methods for the mRNA drugs are discussed, with an aim to provide guidance for subsequent researches.

AIM: To investigate the effect of 3-bro-mopyruvate cholesterol ester (3-BP-Cl) on the sensitivity of breast cancer to tamoxifen (TAM). METHODS: MTT assay and Calcein AM/PI staining were used to detect the effect of drugs on the viability of breast cancer cells. Kim's formula was used to detect synergistic anti-breast cancer effect of cholesterol 3-bromopyruvate and tamoxifen. The inhibitory effect of drugs on proliferation of breast cancer cells was detected by colony-forming assay. Flow cytometry was used to detect the apoptosis of breast cancer cells. Western blot assay was used to detect the expression of hexokinase 2, Bcl-2 and Bax proteins. RESULTS: MTT results showed that combination 3-BP-Cl and TAM could significantly inhibit the activity of MCF-7 cells (P<0.05). The results of King's formula showed that 3-BP-Cl and TAM had synergistic inhibitory effect on the proliferation of MCF-7 cells (q>1.15). Calcein AM / PI staining showed that the number of dead cells was the highest in the combination group. Colony-forming assay showed that the combination group had stronger inhibitory effect on the proliferation of MCF-7 cells than that of single drug groups. AnnexinV flow cytometry results showed that, the cell apoptosis in the combination group was significantly increased (P<0.01). Western blot results showed that 3-BP-Cl inhibited the expressions of hexoktokinase 2 and Bcl-2, and enhanced the expression of Bax in MCF-7 cells. CONCLUSION: 3-BP-Cl could increase the sensitivity of breast cancer cells to tamoxifen, and synergically inhibit the proliferation of breast cancer cells. The mechanism is possibly related to its effects of inhibiting the expression of HK2/Bcl-2, and enhancing the expression of Bax.

Objective:To screen highly expressed inflammatory factors in diabetic nephropathy models using protein microarray, analyze differential genes and their regulatory networks, and predict potential therapeutic small molecular compounds.Methods:The inflammatory factor microarray was used to screen the inflammatory factors with the same tendency in the cell model and animal model of diabetic nephropathy. The differential genes screened by R language were enriched and analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG). STRING builds a protein interaction network online, Cytoscape software analyzes the core subnetwork, and Connectivity Map searches for and predicts small molecule compounds.Results:Diabetic nephropathy model was established using 16-week-old db/db mice and mesangial cells stimulated with high glucose, and the expression of C-X-C motif chemokine ligand 1(CXCL1) was elevated in both models. Multiple GEO datasets indicated a strong association between the high expression of CXCL1 and diabetic nephropathy. Specifically, GSE30122 showed an upregulation of 30 genes and a downregulation of 23 genes. GO enrichment analysis focused on biological processes such as humoral immunity and lipopolysaccharide response; While KEGG enrichment was mainly in pertussis and coagulation cascade pathways. CytoHubba identified 10 hub genes, such as ALB, LUM, and CXCL1. In addition, 10 small molecule compounds were predicted as potential therapeutic drugs using Connectivity Map.Conclusions:CXCL1 may serve as a key gene in the occurrence and development of diabetic nephropathy. ALB, LUM, CXCL1, MMP7, TGFBI, CCL2, S100A4, SOX9, VCAN, and CLU may participate in the regulatory network centered around CXCL1. There are 10 small molecular compounds demenestrating the potential to be therapeutic agents.

OBJECTIVE: To explore the regulatory mechanism of human hepatocyte apoptosis induced by lysosomal membrane protein Sidt2 knockout. METHODS: The Sidt2 knockout (Sidt2^-/-) cell model was constructed in human hepatocyte HL7702 cells using Crispr-Cas9 technology.The protein levels of Sidt2 and key autophagy proteins LC3-II/I and P62 in the cell model were detected using Western blotting, and the formation of autophagosomes was observed with MDC staining.EdU incorporation assay and flow cytometry were performed to observe the effect of Sidt2 knockout on cell proliferation and apoptosis.The effect of chloroquine at the saturating concentration on autophagic flux, proliferation and apoptosis of Sidt2 knockout cells were observed. RESULTS: Sidt2^-/- HL7702 cells were successfully constructed.Sidt2 knockout significantly inhibited the proliferation and increased apoptosis of the cells, causing also increased protein expressions of LC3-II/I and P62(P < 0.05) and increased number of autophagosomes.Autophagy of the cells reached a saturated state following treatment with 50 μmol/L chloroquine, and at this concentration, chloroquine significantly increased the expressions of LC3B and P62 in Sidt2^-/- HL7702 cells. CONCLUSION Sidt2 gene knockout causes dysregulation of the autophagy pathway and induces apoptosis of HL7702 cells, and the latter effect is not mediated by inhibiting the autophagy-lysosomal pathway.
Humans ; Lysosome-Associated Membrane Glycoproteins/metabolism* ; Autophagy ; Apoptosis ; Hepatocytes ; Lysosomes/metabolism* ; Chloroquine/pharmacology* ; Nucleotide Transport Proteins/metabolism*

Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.

Objective: As the prevention and control of COVID-19continues to advance, the active nucleic acid test screening in the close contacts of the patients has been carrying out in many parts of China. However, the false-positive rate of positive results in the screening has not been reported up to now. But to clearify the false-positive rate during screening is important in COVID-19 control and prevention. Methods: Point values and reasonable ranges of the indicators which impact the false-positive rate of positive results were estimated based on the information available to us at present. The false-positive rate of positive results in the active screening was deduced, and univariate and multivariate-probabilistic sensitivity analyses were performed to understand the robustness of the findings. Results: When the infection rate of the close contacts and the sensitivity and specificity of reported results were taken as the point estimates, the positive predictive value of the active screening was only 19.67%, in contrast, the false-positive rate of positive results was 80.33%. The multivariate-probabilistic sensitivity analysis results supported the base-case findings, with a 75% probability for the false-positive rate of positive results over 47%. Conclusions In the close contacts of COVID-19 patients, nearly half or even more of the 'asymptomatic infected individuals’ reported in the active nucleic acid test screening might be false positives.

Objective:To summarize the patient profiles and therapeutic efficacies of ABO-incompatible living-related kidney transplantations at 19 domestic transplant centers and provide rationales for clinical application of ABOi-KT.Methods:Clinical cases of ABO-incompatible/compatible kidney transplantation (ABOi-KT/ABOc-KT) from December 2006 to December 2009 were collected. Then, statistical analyses were conducted from the aspects of tissue matching, perioperative managements, complications and survival rates of renal allograft or recipients.Results:Clinical data of 342 ABOi-KT and 779 ABOc-KT indicated that (1) no inter-group differences existed in age, body mass index (BMI), donor-recipient relationship or waiting time of pre-operative dialysis; (2) ABO blood type: blood type O recipients had the longest waiting list and transplantations from blood type A to blood type O accounted for the largest proportion; (3) HLA matching: no statistical significance existed in mismatch rate or positive rate of PRA I/II between two types of surgery; (4) CD20 should be properly used on the basis of different phrases; (5) hemorrhage was a common complication during an early postoperative period and microthrombosis appeared later; (6) no difference existed in postoperative incidence of complications or survival rate of renal allograft and recipients at 1/3/5/10 years between ABOi-KT and ABOc-KT. The acute rejection rate and serum creatinine levels of ABOi-KT recipients were comparable to those of ABOc-KT recipients within 1 year.Conclusions:ABOi-KT is both safe and effective so that it may be applied at all transplant centers as needed.

With the increasing cost of drug development and clinical trials, it is of great value to make full use of all kinds of data to improve the efficiency of drug development and to provide valid information for medication guidelines. Model-based meta-analysis (MBMA) combines mathematical models with meta-analysis to integrate information from multiple sources (preclinical and clinical data, etc.) and multiple dimensions (targets/mechanisms, pharmacokinetics/pharmacodynamics, diseases/indications, populations, regimens, biomarkers/efficacy/safety, etc.), which not only provides decision-making for all key points of drug development, but also provides effective information for rational drug use and cost-effectiveness analysis. The classical meta-analysis requires high homogeneity of the data, while MBMA can combine and analyze the heterogeneous data of different doses, different time courses, and different populations through modeling, so as to quantify the dose-effect relationship, time-effect relationship, and the relevant impact factors, and thus the efficacy or safety features at the level of dose, time and covariable that have not been involved in previous studies. Although the modeling and simulation methods of MBMA are similar to population pharmacokinetics/pharmacodynamics (Pop PK/PD), compared with Pop PK/PD, the advantage of MBMA is that it can make full use of literature data, which not only improves the strength of evidence, but also can answer the questions that have not been proved or can not be answered by a single study. At present, MBMA has become one of the important methods in the strategy of model-informed drug development (MIDD). This paper will focus on the application value, data analysis plan, data acquisition and processing, data analysis and reporting of MBMA, in order to provide reference for the application of MBMA in drug development and clinical practice.

OBJECTIVE:To establish the method for dissolution determination of Metoprolol tartrate tablets,and to evaluate the similarity of dissolution curves of generics and original drugs. METHODS:The paddle method was adopted with rotational the speed of 50 r/min,using pH 1.2 hydrochloric acid solution,pH 4.5 acetate buffer solution and pH 6.8 phosphate buffer solution as dissolution media. Fiber-optical drug dissolution real-time measurement instrument was used to determine the dissolution curves of generic and original Metoprolol tartrate tablets with optical distance of 10 mm. Similarity factor (f2) method was used to evaluate its similarity. RESULTS:In 3 dissolution mediums,the f2 of generic and original Metoprolon tartrate tablets were 80.5,66.8, 69.4,respectively,which indicated that the dissolution curves showed similarity. CONCLUSIONS:Established real-time dissolution process analysis method is suitabe for the dissolution determination of Metoprolol tartrate tablets. Generic and eriginal show the sim-ilarity in dissolation behavier,so they have good consistency in quality.

Wistar rats were intragastrically administered with different doses (2, 5 and 10 g / kg body weight) of haematitum. 1H NMR-based metabonomic analysis coupled with multivariate statistical analysis (principal component analysis and partial least squares-discriminant analysis) was used to analyze the metabolic profiles of the urine samples collected from the treated rats. Univariate analysis on the 1H NMR spectra of urine (1 d before administration, 1-5 d post administration) was used to screen out the potential features of haematitum. Significant treatment related changes were observed for the levels of citrate, tuarine, creatinine,α-ketoglutarate, succinate and dimethylglycine, which could be used as potential features of haematitum. A trend of recovery in connection with dose levels was observed overtime. Such biochemical changes indicated that haematitum treatment at the dose of 2, 5 and 10 g / kg body weight affected the Krebs cycle and glucose metabolism, energy metabolism, choline metabolism and dimethylglycine metabolism in rats. These changes may attribute to the disturbances of hepatic function in 10 g / kg body weight group.