Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Objective To construct a glioma grading evaluation model based on magnetic resonance diffusion tensor imaging(DTI)parameters,systemic immune-inflammation index(SII),and albumin to globulin ratio(AGR),and analyze its evaluation effect.Methods A total of 120 patients with brain glioma treated in our hospital from January 2022 to January 2024 were selected and divided into a high-grade glioma(HGG)group of 53 cases and a low-grade glioma(LGG)group of 67 cases according to the WHO tumor classification.The magnetic resonance DTI parameters,SII,and AGR of patients between the two groups were compared.A binary Logistic regression analysis model was constructed to analyze the risk factors for the occurrence of HGG;the receiver operating characteristic(ROC)curve was drawn,and the area under the curve(AUC)was calculated to analyze the evaluation value of the glioma grading model.Results Compared with the LGG group,the HGG group had lower fractional anisotropy(FA)value,apparent diffusion coefficient(ADC),and AGR of the tumor body and the peritumoral edema area(P<0.05),and higher SII(P<0.05).Binary Logistic regression analysis showed that decresed ADC value of the tumor body and the peritumoral edema area,decreased AGR,and increased SII were all the risk factors for the occurrence of HGG(P<0.05).The ROC curve analysis showed that the AUC of the combined assessment of FA value and ADC of the tumor body,FA value and ADC of the peritumoral edema area,SII and AGR for glioma grading was higher than that of their individual assessment(P<0.05).Conclusion The occurrence of HGG is related to the ADC of the tumor body and peritumoral edema area,SII,and AGR.The model constructed based on magnetic resonance DTI parameters,SII and AGR has high evaluation value for the grading of glioma.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Objective To construct a glioma grading evaluation model based on magnetic resonance diffusion tensor imaging(DTI)parameters,systemic immune-inflammation index(SII),and albumin to globulin ratio(AGR),and analyze its evaluation effect.Methods A total of 120 patients with brain glioma treated in our hospital from January 2022 to January 2024 were selected and divided into a high-grade glioma(HGG)group of 53 cases and a low-grade glioma(LGG)group of 67 cases according to the WHO tumor classification.The magnetic resonance DTI parameters,SII,and AGR of patients between the two groups were compared.A binary Logistic regression analysis model was constructed to analyze the risk factors for the occurrence of HGG;the receiver operating characteristic(ROC)curve was drawn,and the area under the curve(AUC)was calculated to analyze the evaluation value of the glioma grading model.Results Compared with the LGG group,the HGG group had lower fractional anisotropy(FA)value,apparent diffusion coefficient(ADC),and AGR of the tumor body and the peritumoral edema area(P<0.05),and higher SII(P<0.05).Binary Logistic regression analysis showed that decresed ADC value of the tumor body and the peritumoral edema area,decreased AGR,and increased SII were all the risk factors for the occurrence of HGG(P<0.05).The ROC curve analysis showed that the AUC of the combined assessment of FA value and ADC of the tumor body,FA value and ADC of the peritumoral edema area,SII and AGR for glioma grading was higher than that of their individual assessment(P<0.05).Conclusion The occurrence of HGG is related to the ADC of the tumor body and peritumoral edema area,SII,and AGR.The model constructed based on magnetic resonance DTI parameters,SII and AGR has high evaluation value for the grading of glioma.

MADS-box protein family are important transcriptional regulatory factors in plant growth and development. The AGAMOUS 12 (AGL12) subfamily is believed to play an important regulatory role in the process of plant flowering transition. To explore the potential mechanism of AGL12 subfamily involved in regulating the flower development of Lonicera macranthoides, quantitative real-time polymerase chain reaction (qRT-PCR), prokaryotic expression and yeast two-hybrid techniques were used to analyze the expression pattern, protein expression, and protein-protein interaction pattern of LmAGL12 based on transcriptome data. The results showed that the LmAGL12 gene contains a 603 bp open reading frame (ORF), encoding 200 amino acids, and the encoded protein was stable and hydrophilic without a transmembrane region and signal peptide. Through homologous sequence alignment and phylogenetic analysis, it was confirmed that LmAGL12 protein belongs to the MADS-box protein family and is closely related to the AGL12 protein of Heracleum sosnowskyi and Daucus carota subsp. sativus. The LmAGL12 gene was cloned into prokaryotic expression vector pET-28a and the recombinant constructs were transformed into Escherichia coli BL21 (DE3), which inducing the target protein successfully. The yeast two-hybrid results showed that LmAGL12 protein interacts with LmSVP protein, LmSOC1 protein and LmAP1 protein, respectively. The qRT-PCR results showed that LmAGL12 gene were differentially expressed in different development stages of flower bud, stem, and leaves of 'Longhua' and 'Baiyun' in L. macranthoides. The LmAGL12 gene showed the highest expression level in the middle stage of the 'Longhua' floral bud; For the 'Baiyun' variety, the relative expression level of LmAGL12 gene is the highest in the stem. This study cloned the LmAGL12 gene in L. macranthoides and analyzed it expression for the first time, enriching the research on flower organ development and providing a research basis for further exploring the molecular mechanisms of long bud stage and non-unfolded corolla in L. macranthoides, as well as for variety improvement.

In order to study the compounds from Glechoma longituba (Nakai) Kupr. and explore the substance bases of its dissipating blood stasis, MCI, silica gel, Sephadex LH-20, ODS column chromatography and preparative thin layer chromatography were used to isolate and purify the compounds. The structures were identified by MS, 1D NMR, and 2D NMR spectra analysis, etc. Eight triterpenoids were isolated from dichloromethane fraction of ethanol extract from G. longituba and identified as 2α,3α,16β-trihydroxy-13α,27-cyclours-11-en-28-oic acid (1), 28-norurs-12-ene-3β,17β-diol (2), 28-norolean-12-ene-3β,17β-diol (3), oleanonic acid (4), 3β,13β-dihydroxyurs-11-en-28-oic acid (5), uvaol (6), oleanolic acid (7), ursolic acid (8). Compound 1 is a new hexacyclic triterpene with 13α,27-cyclopropane structure, named euscaphic acid H; compounds 2 and 3 were isolated from Lamiaceae for the first time while compounds 4 and 5 were isolated from this genus. The in vitro anticoagulant activity of triterpenoids was evaluated by four coagulation indexes (activated partial thromboplastin time, APTT; thrombin time, TT; prothrombin time, PT; fibrinogen, FIB). Among them, compounds 1 and 6 showed obvious anticoagulant effects.

The MADS-box gene family is a very important transcriptional regulator gene, which plays a role in the whole growth and development process of plants. The APETALA1 (AP1) gene is considered to play an important regulatory role in the transformation of plant flowering, but also to control the characteristic development of floral organs. Lonicera macranthoides is used as medicine with dry buds and early flowers. Therefore, studying the potential mechanism of AP1 gene in regulating flower organ development can provide a basis for improving its medicinal value by molecular means. To explore the potential mechanism of the AP1 gene in the regulation of floral organ development in L. macranthoides, the full-length cDNA of the AP1 was cloned by reverse transcription PCR (RT-PCR) and named LmMADS4. The results show that the CDS of the LmMADS4 gene is 729 bp and encodes 242 amino acids, and the LmMADS4 protein contains no signal peptide and no transmembrane structure, which is an unstable hydrophilic protein. Through homologous sequence alignment and phylogenetic analysis, LmMADS4 and L. japonica MADS27 protein cluster into one class and are closely related. Finally, the expression pattern and protein interaction pattern of LmMADS4 were analyzed by real-time reverse transcription-PCR (qRT-PCR) and yeast two-hybrid technology. The qRT-PCR showed that LmMADS4 gene was differentially expressed in the stems, leaves and flower bud at different developmental stages, including bud type variety Longhua and common variety Baiyun; and LmMADS4 gene was highly expressed in the flower buds, and with the development of flower buds, LmMADS4 gene was continuously up-regulated in the flower bud variety Longhua, however, the expression level of LmMADS4 in the Baiyun terminal flower bud was lower than that in the late flower bud, but the difference was not significant. The yeast two-hybrid results showed that the bait vector pGBKT7-LmMADS4 was not toxic to yeast strains and had no self-activating activity. LmMADS4 protein interacted with LmSVP1, LmSVP3 and LmSOC1s proteins. This study can provide a theoretical basis for exploring the mechanism of long flower bud stage and corolla non-unfolding at the molecular level and variety improvement of L. macranthoides.

OBJECTIVE: To examine the anti-inflammatory effects and potential mechanisms of polypeptide from Moschus (PPM) in lipopolysaccharide (LPS)-induced THP-1 macrophages and BALB/c mice. METHODS: The polypeptide was extracted from Moschus and analyzed by high-performance liquid chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Subsequently, LPS was used to induce inflammation in THP-1 macrophages and BALB/c mice. In LPS-treated or untreated THP-1 macrophages, cell viability was observed by cell counting kit 8 and lactate dehydrogenase release assays; the proinflammatory cytokines and reactive oxygen species (ROS) were measured by enzyme-linked immunosorbent assay and flow cytometry, respectively; and protein and mRNA levels were measured by Western blot and real-time quantitative polymerase chain reaction (qRT-PCR), respectively. In LPS-induced BALB/c mice, the proinflammatory cytokines were measured, and lung histology and cytokines were observed by hematoxylin and eosin (HE) and immunohistochemical (IHC) staining, respectively. RESULTS: The SDS-PAGE results suggested that the molecular weight of purified PPM was in the range of 10-26 kD. In vitro, PPM reduced the production of interleukin 1β (IL-1β), IL-18, tumor necrosis factor α (TNF-α), IL-6 and ROS in LPS-induced THP-1 macrophages (P<0.01). Western blot analysis demonstrated that PPM inhibited LPS-induced nuclear factor κB (NF-κB) pathway and thioredoxin interacting protein (TXNIP)/nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain containing 3 (NLRP3) inflammasome pathway by reducing protein expression of phospho-NF-κB p65, phospho-inhibitors of NF-κB (Iκ Bs) kinase α/β (IKKα/β), TXNIP, NLRP3, apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC), and pro-caspase-1 (P<0.05 or P<0.01). In addition, qRT-PCR revealed the inhibitory effects of PPM on the mRNA levels of TXNIP, NLRP3, ASC, and caspase-1 (P<0.05 or P<0.01). Furthermore, in LPS-induced BALB/c mice, PPM reduced TNF-α and IL-6 levels in serum (P<0.05 or P<0.01), decreased IL-1β and IL-18 levels in the lungs (P<0.01) and alleviated pathological injury to the lungs. CONCLUSION PPM could attenuate LPS-induced inflammation by inhibiting the NF-κB-ROS/NLRP3 pathway, and may be a novel potential candidate drug for treating inflammation and inflammation-related diseases.