BACKGROUND:Some studies have confirmed the changes in the function of immune cell subsets such as monocytes,T cells,B cells,and natural killer cells(NK cells)in patients with osteoarthritis,but the specific regulatory mechanisms are unclear.OBJECTIVE:To explore the causal relationship between plasma metabolite-mediated immune cells and hip osteoarthritis.METHODS:The Genome-Wide Association Studies(GWAS)data of 731 immune cells were used as the exposure,the GWAS data of hip osteoarthritis were used as the outcome,and 1 400 plasma metabolites were selected as mediating factors.The GWAS database is an important database for genetic association studies,maintained by international organizations with no country-specific affiliation.The inverse variance weighting method in the two-sample Mendelian randomization method was the main method,and the Bayesian weighted Mendelian randomization method was used to analyze the prior distribution,sample data and weights,which were then used to calculate the posterior distribution.The accuracy and reliability of the inverse variance weighting results were evaluated according to the posterior distribution,supplemented by MR-Egger,weighted median,simple model,and weighted mode methods.The pliotropy test and heterogeneity test were used to ensure the robustness of the process.The results of the inverse variance weighting method were used for subsequent mediating effect analysis.RESULTS AND CONCLUSION:(1)The inverse variance weighting method identified 4 immune cells strongly correlated with hip osteoarthritis,and 20 metabolites strongly associated with hip osteoarthritis,all of which had no reverse causal relationship.At the same time,the validation results of Bayesian weighted Mendelian randomization method showed that the posterior mean value was similar to the estimated value of the inverse variance weighting,and the posterior variance was relatively lower.One monocyte subtype(PDL-1 on CD14-CD16+)was finally screened out to have a causal relationship with hip osteoarthritis,with a total effect of-0.047(odds ratio=0.954,95％confidence interval:0.926-0.983),and a mediating effect of-0.004(odds ratio=0.939,95％confidence interval:0.902-0.978)mediated by alliin levels,accounting for 8.5％of the total effect.It was concluded that alliin is a protective factor in the progression of hip osteoarthritis,in which this metabolite plays a mediating role.(2)The large amount of data from international databases and European population analysis is of great significance to Chinese biomedicine,which can provide clues for research on the genetic susceptibility to similar diseases in the Chinese population,aiding in discovering the unique associations.The pharmacogenomic approaches used can be adapted to screen for drug response genes in the Chinese population,enhancing the precision of personalized medicine.Additionally,the advanced high-throughput technologies and statistical methods employed can be learned and applied to disease prevention and treatment research.

BACKGROUND:Some studies have confirmed the changes in the function of immune cell subsets such as monocytes,T cells,B cells,and natural killer cells(NK cells)in patients with osteoarthritis,but the specific regulatory mechanisms are unclear.OBJECTIVE:To explore the causal relationship between plasma metabolite-mediated immune cells and hip osteoarthritis.METHODS:The Genome-Wide Association Studies(GWAS)data of 731 immune cells were used as the exposure,the GWAS data of hip osteoarthritis were used as the outcome,and 1 400 plasma metabolites were selected as mediating factors.The GWAS database is an important database for genetic association studies,maintained by international organizations with no country-specific affiliation.The inverse variance weighting method in the two-sample Mendelian randomization method was the main method,and the Bayesian weighted Mendelian randomization method was used to analyze the prior distribution,sample data and weights,which were then used to calculate the posterior distribution.The accuracy and reliability of the inverse variance weighting results were evaluated according to the posterior distribution,supplemented by MR-Egger,weighted median,simple model,and weighted mode methods.The pliotropy test and heterogeneity test were used to ensure the robustness of the process.The results of the inverse variance weighting method were used for subsequent mediating effect analysis.RESULTS AND CONCLUSION:(1)The inverse variance weighting method identified 4 immune cells strongly correlated with hip osteoarthritis,and 20 metabolites strongly associated with hip osteoarthritis,all of which had no reverse causal relationship.At the same time,the validation results of Bayesian weighted Mendelian randomization method showed that the posterior mean value was similar to the estimated value of the inverse variance weighting,and the posterior variance was relatively lower.One monocyte subtype(PDL-1 on CD14-CD16+)was finally screened out to have a causal relationship with hip osteoarthritis,with a total effect of-0.047(odds ratio=0.954,95％confidence interval:0.926-0.983),and a mediating effect of-0.004(odds ratio=0.939,95％confidence interval:0.902-0.978)mediated by alliin levels,accounting for 8.5％of the total effect.It was concluded that alliin is a protective factor in the progression of hip osteoarthritis,in which this metabolite plays a mediating role.(2)The large amount of data from international databases and European population analysis is of great significance to Chinese biomedicine,which can provide clues for research on the genetic susceptibility to similar diseases in the Chinese population,aiding in discovering the unique associations.The pharmacogenomic approaches used can be adapted to screen for drug response genes in the Chinese population,enhancing the precision of personalized medicine.Additionally,the advanced high-throughput technologies and statistical methods employed can be learned and applied to disease prevention and treatment research.

Objective:To identify and analyze the genuine medicinal plant Gentiana scabra Bge. from 9 regions in Liaoning Province using DNA barcode technology based on the base sequence of internal transcribed spacer. Methods:DNA was extracted from the medicinal parts of 26 Gentiana scabra Bge. samples by using DNA kit extraction method. The ITS sequence was amplified through polymerase chain reaction (PCR), and then two-way sequencing was carried out. Other sources and outgroup sequences of the medicinal plant Gentiana scabra Bge. were downloaded from Genbank. After the sequencing results were spliced by using SeqMan 7.1.0 software, MEGA 7.0 software was used to analyze and compare the data, and calculate the genetic distance of K2P (Kimura 2-parameter). The phylogenetic tree was established by Neighbor-Joining (NJ) method for analysis. Results:According to the results of NJ cluster tree, all Gentiana scabra Bge. samples from different sources were clustered into one large branch, and Gentiana scabra Franch. and Gentiana triflora Pall. were clustered into one branch respectively, with obvious differences; Gentiana scabra and Gentiana manshurica Kitag. were clustered into one branch, and the genetic relationship was relatively close. In combination with the variation site and genetic distance, the base sequences of Gentiana scabra and Gentianamanshurica were very similar, and the interspecific differences were very small. Except for the intraspecific variation of only one sample collected in Liaoning Province, the base sequences of the other samples were the same, and there was no difference between " Gentiana scabra Bge. in Qingyuan" and Gentiana scabra Bge. samples from other regions in Liaoning Province. Conclusion:The DNA barcode technology of ITS sequence can be used to differentiate and identify medicinal plant Gentiana scabra Bge. and its original plants from different sources with a high success rate.

Objective:To use rbcL sequences to identify the rhizomes of the Liaoning collection of Atractylodes chinensis (DC.) Koidz.; To provide a basis for ensuring the feasibility of cultivation of the native herb in Liaoning Province. Methods:A total of 30 rhizomes of Atractylodes chinensis (DC.) Koidz. were collected from 10 regions cultivated in Liaoning Province, and the total DNA was extracted. DNA barcodes were screened by PCR, and the rbcL sequences of the samples were amplified and sequenced, and the amplification and sequencing success rates were calculated. Sequence alignment was performed using MEGA 7.0 software; a systematic clustering tree was constructed using the neighbour-joining method. Results:The success rates of DNA extraction from the rhizomes of Atractylodes chinensis (DC.) Koidz. were all 93.3%, and the success rates of PCR amplification and sequencing were all 100%. Among the 30 samples of Atractylodes chinensis (DC.) Koidz. in Liaoning Province, two samples had intraspecific variation, and the rest of the base sequences of Atractylodes chinensis (DC.) Koidz. were identical. Atractylodes chinensis (DC.) Koidz. was closer to the herbs of the genus Cangzhu, a relative species of Asteraceae, and was genetically more distant from the rest of Asteraceae. The NJ tree could distinguish Atractylodes chinensis (DC.) Koidz. and its relatives. Conclusion:The quality of Atractylodes chinensis (DC.) Koidz. cultivars in Liaoning Province is basically similar, and the rbcL sequence can be used as a valid sequence fragment for the identification of Atractylodes chinensis (DC.) Koidz. DNA barcode.

Background::A phase II trial on recombinant human tenecteplase tissue-type plasminogen activator (rhTNK-tPA) has previously shown its preliminary efficacy in ST elevation myocardial infarction (STEMI) patients. This study was designed as a pivotal postmarketing trial to compare its efficacy and safety with rrecombinant human tissue-type plasminogen activator alteplase (rt-PA) in Chinese patients with STEMI.Methods::In this multicenter, randomized, open-label, non-inferiority trial, patients with acute STEMI were randomly assigned (1:1) to receive an intravenous bolus of 16 mg rhTNK-tPA or an intravenous bolus of 8 mg rt-PA followed by an infusion of 42 mg in 90 min. The primary endpoint was recanalization defined by thrombolysis in myocardial infarction (TIMI) flow grade 2 or 3. The secondary endpoint was clinically justified recanalization. Other endpoints included 30-day major adverse cardiovascular and cerebrovascular events (MACCEs) and safety endpoints.Results::From July 2016 to September 2019, 767 eligible patients were randomly assigned to receive rhTNK-tPA ( n = 384) or rt-PA ( n = 383). Among them, 369 patients had coronary angiography data on TIMI flow, and 711 patients had data on clinically justified recanalization. Both used a –15% difference as the non-inferiority efficacy margin. In comparison to rt-PA, both the proportion of patients with TIMI grade 2 or 3 flow (78.3% [148/189] vs. 81.7% [147/180]; differences: –3.4%; 95% confidence interval [CI]: –11.5%, 4.8%) and clinically justified recanalization (85.4% [305/357] vs. 85.9% [304/354]; difference: –0.5%; 95% CI: –5.6%, 4.7%) in the rhTNK-tPA group were non-inferior. The occurrence of 30-day MACCEs (10.2% [39/384] vs. 11.0% [42/383]; hazard ratio: 0.96; 95% CI: 0.61, 1.50) did not differ significantly between groups. No safety outcomes significantly differed between groups. Conclusion::rhTNK-tPA was non-inferior to rt-PA in the effect of improving recanalization of the infarct-related artery, a validated surrogate of clinical outcomes, among Chinese patients with acute STEMI.Trial registration::www.ClinicalTrials.gov (No. NCT02835534).

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: To investigate the association between macrophage migration inhibitory factor (MIF) -173G/C gene polymorphism and the susceptibility to immune-related diseases in Chinese Han population. Methods: Databases of Wanfang, China National Knowledge Infrastructure (CNKI), PubMed, Excerpta Medica dataBASE (EMbase) and Web of Science (WOS) were comprehensively searched for pertinent articles published in Chinese and English. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were used as effect size measures. Publication bias was examined by Brgge′s funnel plots and Egger′s test. Revman 5.3 and STATA 12.0 software were used for statistical analysis. Results: Nine articles were included in this meta-analysis and the studied immune-related diseases included UC (ulcerative colitis), CD (Crohn′s disease), RA (rheumatoid arthritis), PS (psoriasis), asthma, BD (Behçet′s disease), VKH (Vogt-Koyanagi-Harada syndrome), AOSD (adult-onset Still′s disease) and AD (atopic dermatitis). The overall result of the meta-analysis showed that the MIF 173G/C gene polymorphism could increase the susceptibility to immune-related diseases in Chinese Han people (recessive genetic model: OR=1.92, 95%CI: 1.44-2.58; dominant genetic model: OR=1.44, 95%CI: 1.28-1.61; allele model: OR=1.34, 95%CI: 1.22-1.34; homozygote model: OR=1.98, 95%CI: 1.51-2.60; heterozygote model: OR=1.24, 95%CI: 1.11-1.40; all P<0.01). In addition, a subgroup analysis of the North and South of China showed that except for the heterozygote model in the North group, the recessive model (OR=2.03, 95%CI: 1.24-3.31), dominant genetic model (OR=1.51, 95%CI: 1.24-1.83), allele model (OR=1.37, 95%CI: 1.22-1.54) and homozygote model (OR=2.08, 95%CI: 1.31-2.30) all had statistical significance. All of the five models in the South group showed statistical significance (recessive model: OR=1.88, 95%CI: 1.31-2.69; dominant genetic model: OR=1.40, 95%CI: 1.22-1.61; allele model: OR=1.29, 95%CI: 1.10-1.52; homozygote model: OR=1.93, 95%CI: 1.38-2.71; heterozygote model: OR=1.19, 95%CI: 1.08-1.31; all P<0.05). Conclusion The polymorphism of MIF -173G/C gene may be a susceptible gene to immune-related diseases in Chinese Han people.

Objective: To investigate the heart rate control situation of chronic heart failure (CHF) patients who received cardiovascular implantable electronic device (CIED) therapy, and to assess the heart rate control efficacy by optimized medication adjustment. Methods: We performed a perspective study in heart failure with reduced left ventricular ejection fraction (HFrEF) patients who received CIED according to guideline recommendations, patients were enrolled from January 2012 to January 2017. Resting heart rate (RHR) recorded by electrocardiogram after 10 minutes' rest and medication usage within 1 month were recorded at baseline. RHR less than 70 beats per minute (bpm) was regarded as well controlled. β-receptor blockers and (or) ivabradine would be added in patients whose RHR were over 70 bpm. RHR after optimized medication adjustment was recorded during follow-up period. Results: One hundred and fifty patients were included in this study with average RHR (80.6±11.9) bpm. RHR was<70 bpm in 27.3% (41/150) patients at baseline and β-receptor blockers was underused in 80.7% patients (88/109) whose RHR was>70 bpm. The overall RHR decreased to (73.1±10.4) bpm and percent of patients with RHR<70 bpm increased to 70.0% (105/150) after up-titration of β-receptor blockers compared to baseline (χ²=52.958, P<0.001). Ivabradine was added in the rest 45 patients and RHR was<70 bpm in 43 out of 45 patients after ivabradine use. The overall RHR decreased to (67.1±2.7) bpm and percent of RHR<70 bpm significantly increased to 98.7% (148/150) (χ²=44.504, P<0.001 vs. up-titration of β-receptor blockers only). Conclusion RHR in CHF patients who received CIED therapy is not ideally controlled in this patient cohort, individual up-titration ofβ-receptor blockers and ivabradine use may help to optimize RHR in these patients.

A s an im portant part of epigenetic m arker, D N A m ethylation involves in the gene regulation and attracts a w ide spread attention in biological auxology, geratology and oncology fields. In forensic science, because of the relative stable, heritable, abundant, and age-related characteristics, D N A m ethyla-tion is considered to be a useful com plem ent to the classic genetic m arkers for age-prediction, tissue-identification, and m onozygotic tw ins' discrim ination. V arious m ethods for D N A m ethylation detection have been validated based on m ethylation sensitive restriction endonuclease, bisulfite m odification and m ethylation-C pG binding protein. In recent years, it is reported that the third generation sequencing m ethod can be used to detect D N A m ethylation. T his paper aim s to m ake a review on the detection m ethod of D N A m ethylation and its applications in forensic science.

OBJECTIVETo detect potential mutation of MLC1 gene in a child affected with megalencephalic leukoencephalopathy with subcortical cysts (MLC).

METHODSClinical symptoms of the patient were retrieved. Peripheral blood DNA samples from the patient, her parents and healthy controls were collected. Potential mutation of the MLC1 gene was detected by polymerase chain reaction and Sanger sequencing.

RESULTSThe patient presented with severe motor developmental delay and a giant skull. Magnetic resonance scan showed diffuse white matter swelling in bilateral hemispheres. DNA sequencing identified a novel homozygous c.177-c.180delC mutation of the MLC1 gene. The parents of the patient both carried a heterozygous mutation c.177-c.180delC but had a normal phenotype.

CONCLUSIONA novel MLC1 mutation c.177-c.180delC has been identified in a patient with MLC. The mutation is presumably disease-causing and has derived from parents who are both carriers.

Child, Preschool ; Cysts ; genetics ; Female ; Hereditary Central Nervous System Demyelinating Diseases ; genetics ; Humans ; Membrane Proteins ; genetics ; Mutation