AIM To study the chemical constituents from the stems and leaves of Dendrobium formosum Roxb.ex Lindl.and their biological activities.METHODS The 95％ethanol extract from the stems and leaves of D.formosum was isolated and purified by silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their inhibitory activities onα-glucosidase were determined by PNPG method,and their in vitro anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Fifteen compounds were isolated and identified as coniferyl p-coumarate(1),(-)-pinoresinol(2),2,5,7-trihydroxy-4-methoxy-9,10-dihydrophenanthrene(3),naringenin(4),spiropreussomerin A(5),7-hydroxy-14-de-O-methyl-lasiodiplodin(6),(4S,5S,6Z,8E)-5-hydroxydeca-6,8-dien-4-olide(7),(6S,9R)-blumenol C(8),p-hydroxybenzoic acid(9),m-hydroxybenzoic acid(10),p-hydroxy benzenepropanoic acid(11),5,7-dihydroxy-isobenzofuran(12),2-(4-hydroxyphenyl)-ethanol(13),β-sitostenone(14),β-sitosterol(15).The IC50 values of compounds 1 and 4 on α-glucosidase inhibition were(65.60±3.31)and(98.95±2.53)μmol/L,respectively.Compound 3 presented inhibitory activity on NO production in RAW 264.7 cells,with IC50 value of(3.97±0.12)μmol/L.CONCLUSION Compounds 5-6,8 and 12 are isolated from Orchidacae family for the first time,and 2-15 are first isolated from this plant.Compounds 1 and 4 have α-glucosidase inhibitory activities,and 3 has anti-inflammatory activity.

AIM To study the chemical constituents from the stems and leaves of Dendrobium formosum Roxb.ex Lindl.and their biological activities.METHODS The 95％ethanol extract from the stems and leaves of D.formosum was isolated and purified by silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their inhibitory activities onα-glucosidase were determined by PNPG method,and their in vitro anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Fifteen compounds were isolated and identified as coniferyl p-coumarate(1),(-)-pinoresinol(2),2,5,7-trihydroxy-4-methoxy-9,10-dihydrophenanthrene(3),naringenin(4),spiropreussomerin A(5),7-hydroxy-14-de-O-methyl-lasiodiplodin(6),(4S,5S,6Z,8E)-5-hydroxydeca-6,8-dien-4-olide(7),(6S,9R)-blumenol C(8),p-hydroxybenzoic acid(9),m-hydroxybenzoic acid(10),p-hydroxy benzenepropanoic acid(11),5,7-dihydroxy-isobenzofuran(12),2-(4-hydroxyphenyl)-ethanol(13),β-sitostenone(14),β-sitosterol(15).The IC50 values of compounds 1 and 4 on α-glucosidase inhibition were(65.60±3.31)and(98.95±2.53)μmol/L,respectively.Compound 3 presented inhibitory activity on NO production in RAW 264.7 cells,with IC50 value of(3.97±0.12)μmol/L.CONCLUSION Compounds 5-6,8 and 12 are isolated from Orchidacae family for the first time,and 2-15 are first isolated from this plant.Compounds 1 and 4 have α-glucosidase inhibitory activities,and 3 has anti-inflammatory activity.

Objective:To understand the workflow and key tasks of the transformation of scientific and technological achievements in public hospitals,and propose optimization strategies from the perspective of managers.Methods:Based on the research method of Grounded Theory,semi-structured interviews were conducted among 23 managers of scientific and technological achievements transformation in public hospitals,and relevant concepts and categories were summarized by three stages coding with NVivo 12.Results:Through the three stages of coding,64 initial concepts,19 categories and 4 main categories were sorted out,and a framework diagram of the process of transforming scientific and technological achievements in public hospitals covering four stages was constructed.Conclusion:The scientific and technological achievements of public hospitals can be divided into four phases:project initiation and demand docking,research and development process and achievements incubation,achievements transformation and market docking,product promotion and industrial development,which can be used to achieve high-quality development of scientific and technological achievements through standardized management of the whole process,excavation of high-quality results,enhancement of humanistic construction,accumulation of scientific research experience,and standardization of qualification of technological managers.

This study was aimed at establishing a sensitive and specific sandwich ELISA detection method for Brucella.We screened monoclonal capture antibodies and detection antibodies for Brucella detection,and optimized and determined the opti-mal antibody coating time and concentration,as well as the optimal blocking solution,blocking time,and yin-yang critical val-ue.The specificity of this method was verified by examination of other bacteria prone to cross-reacting with Brucella.The sen-sitivity of the method was verified by detection of a gradient dilution of inactivated Brucella.Moreover,the sandwich ELISA detection results were compared with test tube agglutination and qPCR results.The selected capture antibody was 4A12,and the selected detection antibody was 6C12.Experimental analysis indicated that the optimal coating concentration for the 4A12 capture antibody was 5 μg/mL,and the optimal dilution ratio for the 6C12 detection antibody was 1∶2000.The optimal coating conditions were overnight at 4℃,and blocking with 5％skim milk powder for 2 hours.The established double antibody sand-wich ELISA method reacted with only Brucella but not other bacteria,thus demonstrating the method's good specificity.Inac-tivated Brucella solution was still detectable after dilution to 1 × 105 CFU/mL,thus demonstrating the method's good sensitiv-ity.The intra-and inter batch coefficients of variation were both below 10％,thus indicating the method's good repeatability.Thus,this study successfully established a dual antibody sandwich ELISA method for Brucella detection,which has good spe-cificity and sensitivity,and might provide an effective approach for the precise diagnosis and effective prevention and control of brucellosis.

Laccase is a type of polyphenol oxidase that can catalyze the oxidation of various substances,including phenols,aromatic amines,and catecholamines.It has been widely utilized in pollutant degradation and analytical applications.However,the high cost of preparation of natural laccase and its susceptibility to environmental factors,which can lead to denaturation and inactivation,limit its practical applications.Nanozymes,which are nanomaterials that exhibit enzyme-like properties,offer advantages such as easy preparation,adjustable activity,and exceptional stability.Currently,many types of nanozymes have been developed.Inspired by the coordination of Cu2+with amino acids in the active site of natural laccase,researchers have employed coordination synthetic strategies to prepare laccase-like nanozymes.The metal nodes in these laccase-like nanozymes include copper,manganese,and cerium,while the ligands involve a variety of chemicals like nucleotides,amino acids,polypeptides,and aromatic acids.By manipulating factors such as the metal-to-ligand ratio,reducing capacity of ligands,buffer solutions,chloride ions,bromine ions,the catalytic activity of laccase-like nanozymes can be finely tuned.In this paper,laccase-like nanozymes developed through coordination strategies were categorized and summarized,along with review of their analytical applications in detection of phenolic compounds,disease biomarkers,antibiotics,pesticides,sulfur-containing pollutants,and time-temperature indicators.Furthermore,the challenges currently faced in the research of laccase-like nanozymes and future research directions were discussed.

Objective Methyltransferase 3(METTL3)mediated N6-methyladenosine(m6A)methylation modifica-tion of transient receptor potential cation channel subfamily M member 7(TRPM7)regulates ferroptosis and malig-nant progression in cervical cancer(CESC).Methods Totally 40 patients with cervical cancer were collected.Cer-vical cancer tissues and adjacent normal tissues(≥3 cm from the edge of the tumor tissue)were sampled at opera-tion and then divided into experimental group and control group,respectively.RT-qPCR and Western blot were used to detect the differences in TRPM7 mRNA and protein expression between the two groups.TRPM7-interfering cell lines were constructed to investigate the effects of TRPM7 on CESC cells.Cell proliferation and apoptosis were assessed using 5-ethynyl-2'-deoxyuridine(EdU)assay and flow cytometry,respectively.Transwell chamber assays were employed to evaluate cell invasion and migration capabilities.The levels of ferroptosis in CESC cells were measured using kits for reactive oxygen species(ROS),malondialdehyde(MDA),glutathione(GSH),and Fe2+.Bioinformatics tools were utilized to predict methyltransferases associated with TRPM7.The interaction between METTL3 and TRPM7 was examined through RNA immunoprecipitation(RIP)and methylated RNA immunoprecip-itation quantitative PCR(Me-RIP qPCR).The effect of METTL3 on the stability of TRPM7 expression was assessed using actinomycin D assay.Results TRPM7 was highly expressed in CESC tissue and cells.Knockdown of TRPM7 significantly inhibited cell proliferation,promoted cell apoptosis,suppressed cell migration and invasion capabilities,and enhanced ferroptosis levels(P＜0.05).Bioinformatics predictions suggested that METTL3 might act as a methyltransferase for TRPM7.Interference with METTL3 gene expression significantly reduced TRPM7 pro-tein levels,decreased TRPM7 m6A modification levels,and impaired TRPM7 gene stability(P＜0.05).Conclusions METTL3 regulates CESC proliferation,apoptosis,migration,invasion,and ferroptosis by m6A meth-ylation modification of the TRPM7 gene.

This study was aimed at establishing a sensitive and specific sandwich ELISA detection method for Brucella.We screened monoclonal capture antibodies and detection antibodies for Brucella detection,and optimized and determined the opti-mal antibody coating time and concentration,as well as the optimal blocking solution,blocking time,and yin-yang critical val-ue.The specificity of this method was verified by examination of other bacteria prone to cross-reacting with Brucella.The sen-sitivity of the method was verified by detection of a gradient dilution of inactivated Brucella.Moreover,the sandwich ELISA detection results were compared with test tube agglutination and qPCR results.The selected capture antibody was 4A12,and the selected detection antibody was 6C12.Experimental analysis indicated that the optimal coating concentration for the 4A12 capture antibody was 5 μg/mL,and the optimal dilution ratio for the 6C12 detection antibody was 1∶2000.The optimal coating conditions were overnight at 4℃,and blocking with 5％skim milk powder for 2 hours.The established double antibody sand-wich ELISA method reacted with only Brucella but not other bacteria,thus demonstrating the method's good specificity.Inac-tivated Brucella solution was still detectable after dilution to 1 × 105 CFU/mL,thus demonstrating the method's good sensitiv-ity.The intra-and inter batch coefficients of variation were both below 10％,thus indicating the method's good repeatability.Thus,this study successfully established a dual antibody sandwich ELISA method for Brucella detection,which has good spe-cificity and sensitivity,and might provide an effective approach for the precise diagnosis and effective prevention and control of brucellosis.

As an innovative dosage form, traditional Chinese medicine(TCM) dry powder inhalers have emerged as a focal point in the research and development of new preparations due to its high efficiency, safety, and bioavailability. This paper systematically reviewed the relevant literature and patents associated with TCM dry powder inhalers to analyze the origins and the current research and development status. Furthermore, this paper probed into the research and development ideas of TCM dry powder inhalers regarding clinical positioning, prescription screening, and druggability. Additionally, the paper thoroughly analyzed the technical barriers in druggability studies and elaborated on corresponding research techniques and coping measures. Furthermore, it emphasized the need for improved regulations and policies governing TCM dry powder inhalers, advocated for strengthened oversight, and called for the establishment of a scientific quality evaluation system. Measures such as promoting production-education-research collaboration, enhancing personnel training, and fostering international exchanges were proposed to provide a scientific and systematic reference for the future research, development, and application of TCM dry powder inhalers, thereby facilitating the rapid modernization of TCM.
Humans ; Dry Powder Inhalers/trends* ; Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/instrumentation* ; Administration, Inhalation

Metal ion-promoted chemodynamic therapy(CDT) combined with photodynamic therapy(PDT) offers broad application prospects for enhancing anti-tumor effects. In this study, glycyrrhizic acid(GA), copper ions(Cu~(2+)), and norcantharidin(NCTD) were co-assembled to successfully prepare a natural small-molecule, carrier-free hydrogel(NCTD Gel) with excellent material properties. Under 808 nm laser irradiation, NCTD Gel responded to the tumor microenvironment(TME) and acted as an efficient Fenton reagent and photosensitizer, catalyzing the conversion of endogenous hydrogen peroxide(H_2O_2) within the tumor into oxygen(O_2), and hydroxyl radicals(·OH, type Ⅰ reactive oxygen species) and singlet oxygen(~1O_2, type Ⅱ reactive oxygen species), while depleting glutathione(GSH) to stabilize reactive oxygen species and alleviate tumor hypoxia. In vitro and in vivo experiments demonstrated that NCTD Gel exhibited significant CDT/PDT synergistic therapeutic effects. Further safety evaluation and metabolic testing confirmed its good biocompatibility and safety. This novel hydrogel is not only simple to prepare, safe, and cost-effective but also holds great potential for clinical transformation, providing insights and references for the research and development of metal ion-mediated hydrogel-based anti-tumor therapies.
Hydrogels/chemistry* ; Animals ; Photochemotherapy ; Humans ; Mice ; Antineoplastic Agents/administration & dosage* ; Photosensitizing Agents/chemistry* ; Neoplasms/metabolism* ; Female ; Copper/chemistry* ; Reactive Oxygen Species/metabolism* ; Tumor Microenvironment/drug effects* ; Cell Line, Tumor ; Male

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve