BACKGROUND:As a common disease in middle-aged and elderly,osteoarthritis is difficult to cure,and the pathogenesis is not clear.Long non-coding RNA participates in the pathogenesis of osteoarthritis through many ways,such as regulating translation,promoting or inhibiting mRNA,and adsorbing miRNAs. OBJECTIVE:To review the types of common long non-coding RNA in osteoarthritis,and the influence of multiple long non-coding RNAs on the pathological factors related to osteoarthritis,to analyze the future application of long non-coding RNAs in osteoarthritis. METHODS:Literature retrieval was conducted in CNKI,WanFang Data,VIP database,PubMed,Web of Science and Sciencedirect databases,using the search terms of"osteoarthritis,degenerative joint disease,degenerative arthritis,OA,LncRNA,long non-coding RNA,long noncoding RNA,long intergenic non-coding RNA"in Chinese and English.All relevant literature published from 1976 and May 2024 was retrieved.After literature screening,induction,analysis and summary,93 articles were finally included for review. RESULTS AND CONCLUSION:This review collected 25 long non-coding RNAs that are well studied with osteoarthritis.Long non-coding RNAs,as a molecular sponge for miRNA,are competing endogenous RNAs to competitively adsorb miRNAs and then affect downstream targets.Long non-coding RNAs can regulate physiopathological processes such as chondrocyte apoptosis and proliferation,cartilage extracellular matrix degradation,and inflammatory responses.Long non-coding RNAs are expected to become a biomarker and potential therapeutic target for the clinical diagnosis and therapeutic prognosis of osteoarthritis,and it may become a new strategy for the clinical treatment of osteoarthritis in the future.

Objective:To explore the clinical application value of serum N-glycan profiles for evaluating the severity of liver tissue inflammation in patients with chronic hepatitis B (CHB).Methods:A total of 221 CHB patients who underwent liver biopsy at Mengchao Hepatobiliary Hospital of Fujian Medical University from January 2018 to December 2020 were retrospectively enrolled. The Scheuer scoring system was used to assess the histological inflammation grade of the liver tissue. Serum N-glycan levels were measured using DNA sequencer-assisted N-glycan fingerprinting (NGFP). Using the upper limit of the alanine aminotransferase (ALT) reference value (40 U/L) as a cutoff, logistic regression models were developed to construct diagnostic models under two scenarios: normal ALT or abnormal ALT. Models based on serum N-glycan levels and serum N-glycan levels combined with routine laboratory indicators, were used to non-invasively evaluation of various pathological grades of liver tissue inflammation in CHB patients. The DeLong test was used to compare the diagnostic efficacy of the models by analyzing the areas under the receiver operating characteristic curve (AUC). Glycosylation-related gene expression differences associated with varying degrees of liver inflammation were analyzed using the Gene Expression Omnibus (GEO) database.Results:In CHB patients with normal ALT level, the relative abundances of N-glycan structure peak 1 (NGA2F) and peak 2 (NGA2FB) increased with higher liver inflammation grades, while the relative abundance of peak 5 (NA2) decreased ( P<0.05). The AUCs of the HIS-G model (HIS-G A) and its enhanced version (HIS-G A Plus) for identifying significant inflammation and necrosis (≥G2, indicating the initiation of antiviral therapy) were 0.805 (95% CI 0.690-0.899) and 0.904 (95% CI 0.821-0.960), respectively. In CHB patients with ALT>40 U/L, the relative abundances of peaks 1 (NGA2F), 2 (NGA2FB), and 3 (NG1A2F) increased with higher liver inflammation grades, while the relative abundances of peaks 8 (NA3) and 11 (NA4) decreased ( P<0.05). The AUCs of the HIS-G model (HIS-G B) and its enhanced version (HIS-G B Plus) for identifying significant inflammation (≥G2) were 0.810 (95% CI 0.727-0.889) and 0.838 (95% CI 0.754-0.901), respectively. With increasing liver inflammation grades, the expression levels of four glycosyltransferase genes (CHST4, FUT8, SLC51B, and ST8SIA4) were significantly upregulated ( P<0.05). Conclusions:Serum N-glycan biomarker models can be used to assist in evaluating the severity of liver tissue inflammation in CHB patients with both normal and abnormal ALT levels.

Objective To explore the value of artificial intelligence(AI)based multi-parameter coronary CT angiography(CCTA)features combined with clinical indicators for predicting coronary plaque progression.Methods Totally 143 coronary atherosclerosis(AS)patients were retrospectively enrolled and divided into progression group(arithmetic average annual growth rate of plaque load＞1％,n=73)and non-progression group(arithmetic average annual growth rate of plaque load＜1％,n=70).The baseline clinical data,CT-derived fractional flow reserve(CT-FFR),perivascular fat attenuation index(FAI),and quantitative plaque features were collected and compared between groups.For variables being statistically different between groups,those had collinearity with others were excluded,and then multivariable logistic regression was used to screen independent predictors of plaque progression from the retained variables,and a combined model was constructed.Receiver operating characteristic(ROC)curve was drawn,and the area under the curve(AUC)was calculated to evaluate the predictive efficacy of this model.Results Progression group had higher proportions of hypertension and diabetes,higher apolipoprotein A1(ApoA1)and high-sensitivity C-reactive protein(hs-CRP)levels but lower high-density lipoprotein cholesterol(HDL-C)levels than non-progression group(all P＜0.05).Progression group showed smaller minimum lumen area and lower CT-FFR,but greater degree of lumen stenosis,total plaque volume,plaque load,non-calcified plaque volume,lipid-rich plaque volume,fibrolipid plaque volume and FAI values than non-progression group(all P＜0.05).Plaque types were different between groups(P＜0.05).Diabetes,low HDL-C,small minimum lumen area and large lipid-rich plaque volume were all independent predictors of plaque progression in patients with coronary AS(all P＜0.05),and the AUC of the combined model for predicting plaque progression was 0.859.Conclusion Multi-parameter CCTA features based on AI combined with clinical indicators could be used to effectively predict progression of coronary AS plaque.

Objective:Exploring the association between Life's Crucial 9 (LC9) and the risk of thyroid dysfunction (TD), as well as its potential predictive capacity.Methods:A total of 247 600 TD-free participants from the UK Biobank were enrolled in the study. The LC9 score was divided into three CVH groups: low (0-), medium (50-), and high (80-100). Cox proportional hazards regression models were used to calculate the HRs and 95% CIs of the risk of TD with LC9 CVH status. Calculate Harrell's concordance index ( C-index), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to evaluate the predictive ability of the LC9 score and Life's Essential 8 (LE8) score. Results:During a median follow-up of 12.3 years, 5 515, 911, and 4 869 new cases of TD, hyperthyroidism, and hypothyroidism were documented, respectively. Participants with a high LE8 CVH group had 57.00% ( HR=0.43, 95% CI: 0.38-0.49), 55.00% ( HR=0.45, 95% CI: 0.34-0.60), and 58.00% ( HR=0.42, 95% CI: 0.37-0.47) lower risk of TD, hyperthyroidism, and hypothyroidism, respectively, than those with low CVH group. Compared with the LE8 score, the improvement in C-index for the LC9 score predicted TD risk was 0.004 (95% CI: 0.001-0.007), the NRI was 0.101 (95% CI: 0.021-0.103), and the IDI was 0.001 (95% CI: 0.000-0.001). Conclusions:The better CVH status, defined by LC9, was associated with a lower risk of TD. Compared to the LE8 score, the LC9 score demonstrated a significant enhancement in both risk discrimination and reclassification capability for TD risk.

Objective To explore the value of artificial intelligence(AI)based multi-parameter coronary CT angiography(CCTA)features combined with clinical indicators for predicting coronary plaque progression.Methods Totally 143 coronary atherosclerosis(AS)patients were retrospectively enrolled and divided into progression group(arithmetic average annual growth rate of plaque load＞1％,n=73)and non-progression group(arithmetic average annual growth rate of plaque load＜1％,n=70).The baseline clinical data,CT-derived fractional flow reserve(CT-FFR),perivascular fat attenuation index(FAI),and quantitative plaque features were collected and compared between groups.For variables being statistically different between groups,those had collinearity with others were excluded,and then multivariable logistic regression was used to screen independent predictors of plaque progression from the retained variables,and a combined model was constructed.Receiver operating characteristic(ROC)curve was drawn,and the area under the curve(AUC)was calculated to evaluate the predictive efficacy of this model.Results Progression group had higher proportions of hypertension and diabetes,higher apolipoprotein A1(ApoA1)and high-sensitivity C-reactive protein(hs-CRP)levels but lower high-density lipoprotein cholesterol(HDL-C)levels than non-progression group(all P＜0.05).Progression group showed smaller minimum lumen area and lower CT-FFR,but greater degree of lumen stenosis,total plaque volume,plaque load,non-calcified plaque volume,lipid-rich plaque volume,fibrolipid plaque volume and FAI values than non-progression group(all P＜0.05).Plaque types were different between groups(P＜0.05).Diabetes,low HDL-C,small minimum lumen area and large lipid-rich plaque volume were all independent predictors of plaque progression in patients with coronary AS(all P＜0.05),and the AUC of the combined model for predicting plaque progression was 0.859.Conclusion Multi-parameter CCTA features based on AI combined with clinical indicators could be used to effectively predict progression of coronary AS plaque.

Objective:Exploring the association between Life's Crucial 9 (LC9) and the risk of thyroid dysfunction (TD), as well as its potential predictive capacity.Methods:A total of 247 600 TD-free participants from the UK Biobank were enrolled in the study. The LC9 score was divided into three CVH groups: low (0-), medium (50-), and high (80-100). Cox proportional hazards regression models were used to calculate the HRs and 95% CIs of the risk of TD with LC9 CVH status. Calculate Harrell's concordance index ( C-index), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to evaluate the predictive ability of the LC9 score and Life's Essential 8 (LE8) score. Results:During a median follow-up of 12.3 years, 5 515, 911, and 4 869 new cases of TD, hyperthyroidism, and hypothyroidism were documented, respectively. Participants with a high LE8 CVH group had 57.00% ( HR=0.43, 95% CI: 0.38-0.49), 55.00% ( HR=0.45, 95% CI: 0.34-0.60), and 58.00% ( HR=0.42, 95% CI: 0.37-0.47) lower risk of TD, hyperthyroidism, and hypothyroidism, respectively, than those with low CVH group. Compared with the LE8 score, the improvement in C-index for the LC9 score predicted TD risk was 0.004 (95% CI: 0.001-0.007), the NRI was 0.101 (95% CI: 0.021-0.103), and the IDI was 0.001 (95% CI: 0.000-0.001). Conclusions:The better CVH status, defined by LC9, was associated with a lower risk of TD. Compared to the LE8 score, the LC9 score demonstrated a significant enhancement in both risk discrimination and reclassification capability for TD risk.

Objective:To explore the clinical application value of serum N-glycan profiles for evaluating the severity of liver tissue inflammation in patients with chronic hepatitis B (CHB).Methods:A total of 221 CHB patients who underwent liver biopsy at Mengchao Hepatobiliary Hospital of Fujian Medical University from January 2018 to December 2020 were retrospectively enrolled. The Scheuer scoring system was used to assess the histological inflammation grade of the liver tissue. Serum N-glycan levels were measured using DNA sequencer-assisted N-glycan fingerprinting (NGFP). Using the upper limit of the alanine aminotransferase (ALT) reference value (40 U/L) as a cutoff, logistic regression models were developed to construct diagnostic models under two scenarios: normal ALT or abnormal ALT. Models based on serum N-glycan levels and serum N-glycan levels combined with routine laboratory indicators, were used to non-invasively evaluation of various pathological grades of liver tissue inflammation in CHB patients. The DeLong test was used to compare the diagnostic efficacy of the models by analyzing the areas under the receiver operating characteristic curve (AUC). Glycosylation-related gene expression differences associated with varying degrees of liver inflammation were analyzed using the Gene Expression Omnibus (GEO) database.Results:In CHB patients with normal ALT level, the relative abundances of N-glycan structure peak 1 (NGA2F) and peak 2 (NGA2FB) increased with higher liver inflammation grades, while the relative abundance of peak 5 (NA2) decreased ( P<0.05). The AUCs of the HIS-G model (HIS-G A) and its enhanced version (HIS-G A Plus) for identifying significant inflammation and necrosis (≥G2, indicating the initiation of antiviral therapy) were 0.805 (95% CI 0.690-0.899) and 0.904 (95% CI 0.821-0.960), respectively. In CHB patients with ALT>40 U/L, the relative abundances of peaks 1 (NGA2F), 2 (NGA2FB), and 3 (NG1A2F) increased with higher liver inflammation grades, while the relative abundances of peaks 8 (NA3) and 11 (NA4) decreased ( P<0.05). The AUCs of the HIS-G model (HIS-G B) and its enhanced version (HIS-G B Plus) for identifying significant inflammation (≥G2) were 0.810 (95% CI 0.727-0.889) and 0.838 (95% CI 0.754-0.901), respectively. With increasing liver inflammation grades, the expression levels of four glycosyltransferase genes (CHST4, FUT8, SLC51B, and ST8SIA4) were significantly upregulated ( P<0.05). Conclusions:Serum N-glycan biomarker models can be used to assist in evaluating the severity of liver tissue inflammation in CHB patients with both normal and abnormal ALT levels.

OBJECTIVE: A prospective randomized controlled study was conducted to investigate the early postoperative analgesic effectiveness of using liposomal bupivacaine (LB) for local infiltration anesthesia (LIA) in unicompartmental knee arthroplasty (UKA). METHODS: Between January 2024 and July 2024, a total of 80 patients with knee osteoarthritis (KOA) who met the selection criteria were enrolled in the study. Patients were randomly assigned to either the LB group or the "cocktail" group in a 1∶1 ratio using a random number table, with 40 patients in each group. Baseline characteristics, including gender, age, body mass index, operated side, Kellgren-Lawrence grade, and preoperative American Society of Anesthesiologists (ASA) classification, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, and knee joint range of motion, showed no significant difference between the two groups ( P>0.05). Both groups received LIA and comprehensive pain management. The surgical duration, incision length, pain-related indicators [resting and activity visual analogue scale (VAS) scores, total dosage of oral morphine, WOMAC scores], knee joint range of motion, first ambulation time after operation, length of hospital stay, and postoperative adverse events. RESULTS: There was no significant difference between the two groups in surgical duration, incision length, first ambulation time after operation, length of hospital stay, total dosage of oral morphine, and pre-discharge satisfaction with surgery and WOMAC scores ( P>0.05). At 4, 12, and 24 hours after operation, the resting and activity VAS scores in the "cocktail" group were lower than those in the LB group; at 60 and 72 hours postoperatively, the resting VAS scores in the LB group were lower than those in the "cocktail" group, with the activity VAS scores also being lower at 60 hours; all showing significant differences ( P<0.05). There was no significant difference in the above indicators between the two groups at other time points ( P>0.05). On the second postoperative day, the sleep scores of the LB group were significantly higher than those of the "cocktail" group ( P<0.05), while there was no significant difference in sleep scores on the day of surgery and the first postoperative day ( P>0.05). Additionally, the incidence of complications showed no significant difference between the two groups ( P>0.05). CONCLUSION The use of LB for LIA in UKA can provide prolonged postoperative pain relief; however, it does not demonstrate a significant advantage over the "cocktail" method in terms of short-term analgesic effects or reducing opioid consumption and early functional recovery after UKA. Nevertheless, LB may help reduce postoperative sleep disturbances, making it a recommended option for UKA patients with cardiovascular diseases and insomnia or other mental health issues.
Aged ; Female ; Humans ; Male ; Middle Aged ; Anesthesia, Local/methods* ; Anesthetics, Local/administration & dosage* ; Arthroplasty, Replacement, Knee/methods* ; Bupivacaine/administration & dosage* ; Liposomes ; Osteoarthritis, Knee/surgery* ; Pain Measurement ; Pain, Postoperative/prevention & control* ; Prospective Studies ; Treatment Outcome

OBJECTIVE To establish a liquid chromatography-tandem mass spectrometry （LC-MS/MS） method for the simultaneous determination of bepotastine and hydroxychloroquine concentrations in human breast milk and apply it in clinical practice. METHODS The milk samples （50 μL） were precipitated with 200 μL methanol containing the internal standard （100 ng/mL chloroquine）， and the supernatant was taken for analysis after vortexing and centrifugation. The separation was performed on a Waters ACQUITY UPLC HSS T3 column with mobile phase consisted of 0.1% formic acid-10 mmol/L ammonium acetate solution （phase A） and methanol （phase B） at gradient elution of 0.35 mL/min. The injection volume was 2 μL， and the analysis time was 4 min. The detection of the analytes was performed by electrospray ionization in positive mode by multiple reaction monitoring with the transition of m/z 388.9→201.9 （bepotastine）， m/z 336.3→247.1 （hydroxychloroquine）， and m/z 320.2→247.2 （chloroquine）. The established LC-MS/MS method was researched in methodology and used to determine the drug concentrations in the breast milk of 1 case of lactating patient. RESULTS The linear range of bepotastine was 2-200 ng/mL（ r＝0.999）， and hydroxychloroquine was 50-1 000 ng/mL （r＝0.998）. The intra-assay and inter-assay precisions were both ≤15%， and the accuracy， extraction recovery， matrix effect， and stability all met the acceptance criteria for bioanalytical method validation. The concentration result of bepotastine and hydroxychloroquine in the breast milk of the lactating patient showed， after 2 h and 14 h， the concentrations of bepotastine in the breast milk of the patient were 34.95 ng/mL and 5.72 ng/mL； those of hydroxychloroquine were 211.92 ng/mL and 104.18 ng/mL， respectively. The relative infant doses were 1.83% and 0.56%， respectively. CONCLUSIONS The established method is simple， rapid， and sensitive. It is suitable for simultaneous determination of bepotastine and hydroxychloroquine concentrations in human milk and can provide reference for safe drug use during lactation.

OBJECTIVE To establish a liquid chromatography-tandem mass spectrometry （LC-MS/MS） method for the simultaneous determination of bepotastine and hydroxychloroquine concentrations in human breast milk and apply it in clinical practice. METHODS The milk samples （50 μL） were precipitated with 200 μL methanol containing the internal standard （100 ng/mL chloroquine）， and the supernatant was taken for analysis after vortexing and centrifugation. The separation was performed on a Waters ACQUITY UPLC HSS T3 column with mobile phase consisted of 0.1% formic acid-10 mmol/L ammonium acetate solution （phase A） and methanol （phase B） at gradient elution of 0.35 mL/min. The injection volume was 2 μL， and the analysis time was 4 min. The detection of the analytes was performed by electrospray ionization in positive mode by multiple reaction monitoring with the transition of m/z 388.9→201.9 （bepotastine）， m/z 336.3→247.1 （hydroxychloroquine）， and m/z 320.2→247.2 （chloroquine）. The established LC-MS/MS method was researched in methodology and used to determine the drug concentrations in the breast milk of 1 case of lactating patient. RESULTS The linear range of bepotastine was 2-200 ng/mL（ r＝0.999）， and hydroxychloroquine was 50-1 000 ng/mL （r＝0.998）. The intra-assay and inter-assay precisions were both ≤15%， and the accuracy， extraction recovery， matrix effect， and stability all met the acceptance criteria for bioanalytical method validation. The concentration result of bepotastine and hydroxychloroquine in the breast milk of the lactating patient showed， after 2 h and 14 h， the concentrations of bepotastine in the breast milk of the patient were 34.95 ng/mL and 5.72 ng/mL； those of hydroxychloroquine were 211.92 ng/mL and 104.18 ng/mL， respectively. The relative infant doses were 1.83% and 0.56%， respectively. CONCLUSIONS The established method is simple， rapid， and sensitive. It is suitable for simultaneous determination of bepotastine and hydroxychloroquine concentrations in human milk and can provide reference for safe drug use during lactation.