ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

Objective To analyze the characteristics of methadone-related poisoning cases and provide a reference for forensic identification.Methods A total of 71 cases of methadone-related poisoning re-ported from 1998 to 2023 in China and 26 cases of methadone-related deaths reported from 2013 to 2018 in Italy were retrieved from databases including PubMed,Wanfang and CNKI.The general infor-mation,forensic pathological and toxicological characteristics were analyzed.Results Among the 71 methadone-related poisoning cases in China,there were 54 cases(76.06%)of poisoning without death and 17 cases(23.94%)of death from poisoning.There were 54 male cases(76.06%),and 51 cases(71.83%)aged 19 to 39 years old.There were 35 cases(49.30%)of poisoning caused by methadone alone,and 32 cases(45.07%)were poisoning caused by methadone combined with other substances or drugs including heroin and benzodiazepines.Most of the poisoned showed coma,respiratory depres-sion and miosis.Signs of asphyxia were often found by autopsy.The mass concentration of methadone detected in the blood of 6 deceased ranged from 0.112 to 3.000 mg/L.Among the 26 methadone-related deaths in Italy,22 cases were male(84.62%).There were 6 cases(23.08%)caused by methadone alone,and 20 cases(76.92%)died from methadone combined with other substances or drugs.The mass concentration of methadone in blood ranged from 0.181 to 4.059 mg/L.Conclusion The propor-tions of poisoning cases caused by methadone alone and methadone combined with other substances or drugs are comparable in China.The majority of deceased caused by methadone poisoning shows typi-cal triad of coma,respiratory depression and miosis,which helps forensic experts determine the cause of death related to methadone.Additionally,it is necessary to increase the routine testing of the con-centration of methadone and its combined substances or drugs in deceased,and collect data for the in-terpretation of the results of related cases.

Objective:Constructing a risk prediction model to assess the impact of various factors on the need for auxiliary bone grafting with implant placement following alveolar ridge preservation (ARP) in posterior teeth.Methods:According to the sample size calculation formula, the sample size was calculated using the pmsampsize package of R 4.1.3 software, based on inclusion and exclusion criteria, a total of 110 posterior teeth in 98 patients who underwent ARP at the Department of Periodontology, School and Hospital of Stomatology, China Medical University, from January 2018 to May 2024 were conducted. Teeth were randomly divided into modeling group and validation group with 7∶3 ratio according to the random number table. The modeling group was divided into direct implantation group and auxiliary bone grafting group on the basis of whether auxiliary bone grafting was performed 6 months after ARP. Univariate and multivariate analyses were conducted to identify factors influencing auxiliary bone grafting with implant placement following ARP. Nomogram was constructed using R software. Receiver operator characteristic (ROC) curve and calibration curve were drawn to evaluate model differentiation and consistency. The decision curve analysis (DCA) was used to assess the clinical application value of the model.Results:Age ( OR=1.06, P=0.001), maximum attachment loss (AL) ( OR=1.75, P<0.001), reason of tooth extraction ( OR=12.73, P<0.001), smoking [<10 cigarettes/d ( OR=7.59, P<0.001);≥10 cigarettes/d ( OR=28.12, P<0.001)] and stage of periodontitis [stage Ⅱ ( OR=2.57, P=0.430); stage Ⅲ ( OR=21.00, P=0.007); stage Ⅳ ( OR=76.50, P<0.001)] influenced the necessity for auxiliary bone grafting with implant placement after ARP. After multivariate analysis of the above influencing factors, it was found that smoking [<10 cigarettes/d ( OR=7.02, P=0.009);≥10 cigarettes/d ( OR=10.27, P=0.026)] was an independent risk factor for the need of auxiliary bone grafting with implant placement after ARP. The area under the ROC curve for internal verification was 0.90 (95 %CI: 0.84-0.97), and the H-L goodness of fit test results were χ 2=4.79, P=0.780, indicating a good agreement. The area under the externally verified ROC curve was 0.97 (95 %CI: 0.92-1.00), suggesting that the fitting effect was slightly lower than that of the modeling group, and the predicted value of the model was slightly lower than the true value, which might underestimate the risk of additional surgery in patients. Results:of H-L goodness of fit test were χ 2=5.03, P=0.754. The DCA curve showed that when the probability of high-risk threshold was between 0.06 and 0.93, the clinical application value of the prediction model was higher. Conclusions:Age, smoking, reason of tooth extraction, stage of periodontitis, and maximum AL of the affected teeth were related to the necessity for auxiliary bone grafting with implant placement 6 months after ARP. Smoking was an independent risk factor for auxiliary bone grafting surgery. The constructed nomogram model had good discrimination and consistency.

Andrographolide sulfonate (AS) is a sulfonated derivative of andrographolide extracted from Andrographis paniculata (Burm.f.) Nees, and has been approved for several decades in China. The present study aimed to investigate the novel therapeutic application and possible mechanisms of AS in the treatment of rheumatoid arthritis. Results indicated that administration of AS by injection or gavage significantly reduced the paw swelling, improved body weights, and attenuated pathological changes in joints of rats with adjuvant-induced arthritis. Additionally, the levels of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and IL-1β in the serum and ankle joints were reduced. Bioinformatics analysis, along with the spleen index and measurements of IL-17 and IL-10 levels, suggested a potential relationship between AS and Th17 cells under arthritic conditions. In vitro, AS was shown to block Th17 cell differentiation, as evidenced by the reduced percentages of CD4⁺ IL-17A⁺ T cells and decreased expression levels of RORγt, IL-17A, IL-17F, IL-21, and IL-22, without affecting the cell viability and apoptosis. This effect was attributed to the limited glycolysis, as indicated by metabolomics analysis, reduced glucose uptake, and pH measurements. Further investigation revealed that AS might bind to hexokinase2 (HK2) to down-regulate the protein levels of HK2 but not glyceraldehyde-3-phosphate dehydrogenase (GAPDH) or pyruvate kinase M2 (PKM2), and overexpression of HK2 reversed the inhibition of AS on Th17 cell differentiation. Furthermore, AS impaired the activation of phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signals in vivo and in vitro, which was abolished by the addition of lactate. In conclusion, AS significantly improved adjuvant-induced arthritis (AIA) in rats by inhibiting glycolysis-mediated activation of PI3K/AKT to restrain Th17 cell differentiation.
Animals ; Th17 Cells/immunology* ; Diterpenes/pharmacology* ; Arthritis, Rheumatoid/metabolism* ; Proto-Oncogene Proteins c-akt/immunology* ; Glycolysis/drug effects* ; Cell Differentiation/drug effects* ; Phosphatidylinositol 3-Kinases/genetics* ; Rats ; Male ; Rats, Sprague-Dawley ; Humans ; Andrographis paniculata/chemistry* ; Arthritis, Experimental/drug therapy* ; Interleukin-17/immunology* ; Signal Transduction/drug effects*

The aim of this study was to qualitatively and quantitatively detect coronavirus(CoV)in the feces of bats from Qinghua Cave,Yunnan Province,China.CoV was qualitatively tested with reverse transcription polymerase chain reaction(RT-PCR),and homology and genetic evolution were analyzed with bioinformatics software.The established reverse transcription real-time fluores-cence quantitative PCR(qRT-PCR)method was applied to CoV quantification in bat feces.The positivity rate of CoV in 306 fecal samples collected from the fulvous fruit bat(Rousettus leschenaultia)was 7.8%(24/306)according to RT-PCR.All 24 strains of CoV belonged to β-CoV,and showed a similarity of 86.8%-100.0%at the nucleotide level and 95.2%-100.0%at the amino acid level,with respect to other β-CoV sequences in the NCBI database.The positivity rate of CoV was 18.6%(57/306)according to qRT-PCR,a value higher than that according to RT-PCR(χ2=25.3,P<0.05).The mean β-CoV load was 1.3×103 copies/μL.In conclusion,the bats in Qinghua Cave,Yunnan Province,carried CoV belonging to β-CoV.The established qRT-PCR method achieved good sensitiv-ity,accuracy,reproducibility,and a higher detection rate than that of RT-PCR,and can be used for rapid detection of β-CoV in bats.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Objective:Constructing a risk prediction model to assess the impact of various factors on the need for auxiliary bone grafting with implant placement following alveolar ridge preservation (ARP) in posterior teeth.Methods:According to the sample size calculation formula, the sample size was calculated using the pmsampsize package of R 4.1.3 software, based on inclusion and exclusion criteria, a total of 110 posterior teeth in 98 patients who underwent ARP at the Department of Periodontology, School and Hospital of Stomatology, China Medical University, from January 2018 to May 2024 were conducted. Teeth were randomly divided into modeling group and validation group with 7∶3 ratio according to the random number table. The modeling group was divided into direct implantation group and auxiliary bone grafting group on the basis of whether auxiliary bone grafting was performed 6 months after ARP. Univariate and multivariate analyses were conducted to identify factors influencing auxiliary bone grafting with implant placement following ARP. Nomogram was constructed using R software. Receiver operator characteristic (ROC) curve and calibration curve were drawn to evaluate model differentiation and consistency. The decision curve analysis (DCA) was used to assess the clinical application value of the model.Results:Age ( OR=1.06, P=0.001), maximum attachment loss (AL) ( OR=1.75, P<0.001), reason of tooth extraction ( OR=12.73, P<0.001), smoking [<10 cigarettes/d ( OR=7.59, P<0.001);≥10 cigarettes/d ( OR=28.12, P<0.001)] and stage of periodontitis [stage Ⅱ ( OR=2.57, P=0.430); stage Ⅲ ( OR=21.00, P=0.007); stage Ⅳ ( OR=76.50, P<0.001)] influenced the necessity for auxiliary bone grafting with implant placement after ARP. After multivariate analysis of the above influencing factors, it was found that smoking [<10 cigarettes/d ( OR=7.02, P=0.009);≥10 cigarettes/d ( OR=10.27, P=0.026)] was an independent risk factor for the need of auxiliary bone grafting with implant placement after ARP. The area under the ROC curve for internal verification was 0.90 (95 %CI: 0.84-0.97), and the H-L goodness of fit test results were χ 2=4.79, P=0.780, indicating a good agreement. The area under the externally verified ROC curve was 0.97 (95 %CI: 0.92-1.00), suggesting that the fitting effect was slightly lower than that of the modeling group, and the predicted value of the model was slightly lower than the true value, which might underestimate the risk of additional surgery in patients. Results:of H-L goodness of fit test were χ 2=5.03, P=0.754. The DCA curve showed that when the probability of high-risk threshold was between 0.06 and 0.93, the clinical application value of the prediction model was higher. Conclusions:Age, smoking, reason of tooth extraction, stage of periodontitis, and maximum AL of the affected teeth were related to the necessity for auxiliary bone grafting with implant placement 6 months after ARP. Smoking was an independent risk factor for auxiliary bone grafting surgery. The constructed nomogram model had good discrimination and consistency.

Objective:To establish 30-day of age transcutaneous bilirubin (TcB) reference curves for healthy neonates, and to investigate regional variations in bilirubin dynamics.Methods:A multicenter retrospective cohort study was conducted. A total of 220 950 healthy neonates born at a gestational age of 35-<42 weeks, with a birth weight ≥2 000 g, who did not receive phototherapy within 60 h after birth were recruited. All of them underwent remote TcB monitoring using the Bilibaby remote jaundice monitoring system between August 1 st, 2020 and December 31 st, 2024 in 426 hospitals. TcB data were collected within the period from birth to 30-day of age. The P40, P75, and P95 of TcB values were calculated, and dynamic TcB curves for 30-day of age were constructed. Patterns of bilirubin change, rates of change, and transition outcomes were described. Regional comparisons between South and North were conducted using linear mixed-effects models for TcB trajectories and Pearson′s chi-square test for outcome differences. Results:A total of 220 950 neonates were included, of whom 101 711 (46.03%) were female. Gestational age at birth was (38.75±1.12) weeks, and birth weight was (3 272±417) g. TcB levels increased rapidly within 3-day of age, peaked at 4-6-day of age, with peak values at P40, P75, and P95 of 200.6, 239.7 and 275.4 μmol/L (11.8, 14.1 and 16.2 mg/dl), respectively. TcB levels gradually declined thereafter and stabilized after 13-day of age, with values at P40, P75, and P95 fluctuating between 147.9-159.8, 190.4-200.6, and 231.2-239.7 μmol/L (8.7-9.4, 11.2-11.8, 13.6-14.1 mg/dl), respectively. Notably, among neonates categorized as low-or low-intermediate-risk within 3-day of age, 6 700 (12.76%) progressed to intermediate-high or high risk between 4 and 30 days of age. Before 13-day of age, TcB levels in the southern regions were consistently higher than those in the northern regions ( P=0.039); from 14 to 30 days of age, the overall TcB levels had no statistically difference, but the temporal changes in TcB still showed regional differences (degrees of freedom=3, all interaction P<0.05). Among neonates classified as low-or low-intermediate risk within 3-day of age, 25 326 were from southern regions, of whom 4 254 (16.80%) progressed to intermediate-high or high risk between 4 and 30 days of age. In northern regions, 27 193 neonates were classified as low-or low-intermediate risk within 3-day of age, among whom 2 446 (8.99%) progressed to intermediate-high or high risk. The risk progression between the 2 regions had statistically difference ( χ2=716.49, P<0.001). Conclusions:A TcB percentile curve for neonates within 30-day of age was established, revealing that both the overall TcB level and its temporal trend were higher in southern than in northern newborns. These findings provide baseline data to support continuous management of neonatal jaundice.

The patient is a 63-year-old man with a history of chronic illness, presenting with intermittent low-grade fever, recurrent dry cough, and shortness of breath upon exertion. Lung CT showed a nodule in the left lung and a large mass in the right lung with liquefactive necrosis and an air-fluid level accompanied by pleural effusion. Laboratory findings showed significantly increasedf immunoglobulin G (IgG), IgG4, and total immunoglobulin E, along with a mild increase in eosinophils, and moderate elevations in erythrocyte sedimentation rate and high-sensitivity C-reactive protein. Malignant tumors, immunological, and hematological diseases were ruled out. Various antibiotic treatments were ineffective and the condition was recurrent. Conventional methods failed to identify the pathogen. Metagenomic next-generation sequencing (mNGS) technology was used to detect Mycobacterium monacense from lung tissue. Targeted antibiotic treatment was effective with no further episodes of low-grade fever and alleviation of dry cough symptoms. This case underscores the clinical significance of mNGS technology for the diagnosis and treatment of unexplained pulmonary infections, providing a useful reference for clinical diagnostic and treatment.