Oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLs), are essential in establishing and maintaining brain circuits. Autophagy is a conserved process that keeps the quality of organelles and proteostasis. The role of autophagy in oligodendrocyte lineage cells remains unclear. The present study shows that autophagy is required to maintain the number of OPCs/OLs and myelin integrity during brain aging. Inactivation of autophagy in oligodendrocyte lineage cells increases the number of OPCs/OLs in the developing brain while exaggerating the loss of OPCs/OLs with brain aging. Inactivation of autophagy in oligodendrocyte lineage cells impairs the turnover of myelin basic protein (MBP). It causes MBP to accumulate in the cytoplasm as multimeric aggregates and fails to be incorporated into integral myelin, which is associated with attenuated endocytic recycling. Inactivation of autophagy in oligodendrocyte lineage cells impairs myelin integrity and causes demyelination. Thus, this study shows autophagy is required to maintain myelin quality during aging by controlling the turnover of myelin components.
Animals ; Autophagy/physiology* ; Oligodendroglia/metabolism* ; Myelin Sheath/physiology* ; Aging/pathology* ; Myelin Basic Protein/metabolism* ; Cell Lineage/physiology* ; Mice ; Oligodendrocyte Precursor Cells ; Mice, Inbred C57BL ; Brain/cytology* ; Cells, Cultured ; Cell Count

Natural antimicrobial peptides (AMPs) are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens. They have found extensive applications in the fields of medicine, food, and agriculture. However, efficiently screening AMPs from natural sources poses several challenges, including low efficiency and high antibiotic resistance. This review focuses on the action mechanisms of AMPs, both through membrane and non-membrane routes. We thoroughly examine various highly efficient AMP screening methods, including whole-bacterial adsorption binding, cell membrane chromatography (CMC), phospholipid membrane chromatography binding, membrane-mediated capillary electrophoresis (CE), colorimetric assays, thin layer chromatography (TLC), fluorescence-based screening, genetic sequencing-based analysis, computational mining of AMP databases, and virtual screening methods. Additionally, we discuss potential developmental applications for enhancing the efficiency of AMP discovery. This review provides a comprehensive framework for identifying AMPs within complex natural product systems.

Objective:To establish a quality control method for Aiye standard decoction.Methods:The ultra performance liquid chromatogrphy (UPLC) column Waters ACQUITY HSS T3 C18 (2.1 mm×150 mm,1.8 μm) was used to gradient elution by acetonitrile and 0.1% formic acid in water. 16 batches of Aiye standard decoction fingerprints were established by UPLC and the common peaks were determined in the fingerprints. The contents of 12 components were determined. The 16 batches of Aiye standard decoction were analyzed by similarity calculation, hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for analysis of differential components of Artemisiae Argyi Folium from different origins.Results:A total of 13 common peaks were marked in the fingerprints of 16 batches of Aiye standard decoction, 12 of which were identified by comparison with reference substance, including chlorogenic acid, sochlorogenic acid A, neochlorogenic acid, cryptochlorogenic acid, caffeic acid,1,3-O-Dicaffeoylquinic acid, schaftoside, isochlorogenic acid B,1,5-O-Dicaffeoylquinic acid, isochlorogenic acid C, jaceosidin and eupatilin. Similarity evaluation, PCA and HCA all classified the 16 batches of Aiye standard decoction into 2 categories. Orthogonal partial least squares discriminant analysis screened 5 differential biomarkers from 13 common peaks. The content determination results showed that the phenolic compounds and flavonoids in samples from Hubei were significantly higher than that in samples from other areas.Conclusion:This method can effectively analyze the differences in the quality of Aiye standard decoction from different origins, and provide reference for the formulation of quality standards for Aiye standard decoction and related preparations.

Objective:To establish a method for the determination of triterpenes and nucleosides in Poria based on HPLC; To accurately determine the various bioactive components in Poria.Methods:Similarity evaluation, clustering analysis and principal component analysis were used to analyze the similarities and differences of different medicinal parts of Poria, and the key chromatographic peaks that could reflect the characteristics were found.Results:The Poricoic acid A and dehydroeburiconic acid could be used as the identification basis for Poriae Cutis and White Poria; at the same time, Polyporenic acid C, dehydropachymic acid and dehydrotrametenolic acid could be used to evaluate Rubra Poria and Poriae Cutis; uridine, guanosine and adenosine may be essential ingredients for evaluating the quality of White Poria, Poriae Cutis and Rubra Poria. In different medicinal parts of Poria, the triterpenes were showed significant differences; by contrary, there were little differences among the same medicinal parts.Conclusion:This study reveals the quality differences between different medicinal parts of Poria, which can provide a scientific basis for the rational application and pharmacodynamic standardization of Poria.

The Spt-Ada-Gcn5-acetyltransferase (SAGA) is an ancillary transcription initiation complex which is highly conserved. The ADA1 (alteration/deficiency in activation 1, also called histone H2A functional interactor 1, HFI1) is a subunit in the core module of the SAGA protein complex. ADA1 plays an important role in plant growth and development as well as stress resistance. In this paper, we performed genome-wide identification of banana ADA1 gene family members based on banana genomic data, and analyzed the basic physicochemical properties, evolutionary relationships, selection pressure, promoter cis-acting elements, and its expression profiles under biotic and abiotic stresses. The results showed that there were 10, 6, and 7 family members in Musa acuminata, Musa balbisiana and Musa itinerans. The members were all unstable and hydrophilic proteins, and only contained the conservative SAGA-Tad1 domain. Both MaADA1 and MbADA1 have interactive relationship with Sgf11 (SAGA-associated factor 11) of core module in SAGA. Phylogenetic analysis revealed that banana ADA1 gene family members could be divided into 3 classes. The evolution of ADA1 gene family members was mostly influenced by purifying selection. There were large differences among the gene structure of banana ADA1 gene family members. ADA1 gene family members contained plenty of hormonal elements. MaADA1-1 may play a prominent role in the resistance of banana to cold stress, while MaADA1 may respond to the Panama disease of banana. In conclusion, this study suggested ADA1 gene family members are highly conserved in banana, and may respond to biotic and abiotic stress.
Musa/genetics* ; Phylogeny ; Fungal Proteins ; Cell Nucleus ; Histones ; Stress, Physiological/genetics*

Objective The study aimed to construct and validate a predictive model for pulmonary nodules(PN)nature based on clinicopa-thological features,imaging,and serum biomarkers,so as to provide scientificdecision-making for early diagnosis and treatment of lung cancer.Methods A retrospective was performed on 816 PN patients with definited pathological diagnosis who received surgical resection analysisor lung biopsy in the Department of Thoracic Surgery and Oncology of Shenzhen Traditional Chinese Medicine Hospital from January 2019 to February 2023.Among them,113 cases that did not meet the inclusion criteria were excluded,and the remaining 703 cases were included in the study.The study based on the clinicopathologic features(age,gender,smoking history,smoking cessation history and family history of cancer),chest imaging(maximum diameter of nodule,location of lesion,clear border,Lobulation,spiculation,vascular convergence sign,vacuole,calcification,air bronchial sign,emphysema,nodule type and pleural indentation,nodule number)and serum carcinoembryonic antigen(CEA),cytokeratin 19 fragment(CYFRA21-1),squamous cell carcinoma antigen(SCCA)in patients with PN.These cases were randomly divided into a modeling group(n=552,237 benign,315 malignant)and a validation group(n=151,85 benign,66 malignant).First,univariate analysis was performed to screen for statistically significant predictors of nodules nature.Then,multivariate regression analysis was performed to screen for independent predictors of nodules nature.Finally,the prediction model of PN nature was constructed by logistic regression analysis.Subsequently,the validation group data were entered into the proposed model and Mayo clinic(Mayo)model,veterans affairs(VA)model,Brock University(Brock)model,Peking University(PKU)model and Guangzhou Medical University(GZMU)model,respectively.PN malignancy probability was calculated.The receiver operating characteristic(ROC)curves were plotted.The diagnostic efficiency of each model was compared according to the area under the curve(AUC).Results There were statistically significant variables including age,family history of cancer,maximum nodule diameter,nodule type,upper lobe of lung,calcification,vascular convergence sign,lobulation,clear border,spiculation,and serum CEA,SCCA,CYFRA21-1 using univariate analysis.Multiple regression analysis showed that age,CEA,clear border,CYFRA21-1,SCCA,upper lobe of lung,maximum nodule diameter,family history of cancer,spiculation and nodule type were independent predictors of PN nature.The prediction model equation constructed in this study is as follows:f(x)= ex/(1+ex),X=(-6.318 8+0.020 8×Age+0.527 4×CEA-0.928 4×clear border+0.294 6×Cyfra21-1+0.294×maximum nodule diameter+1.220 1×family history of cancer +0.573 2×upper lobe of lung +0.064 8×SCCA +1.461 5×Spiculation +1.497 6×nodule type).The AUC(0.799 vs 0.659,0.650)of the proposed model was significantly higher compared with Mayo model and VA model,and there were statistically significant differences(Z=3.029,2.638,P=0.003,0.008).However,compared with Brock model,PKU model and GZMU model,the differences of AUC(0.799 vs 0.762,0.773,0.769)were not statistically significant(Z=1.063,0.686,0.757,P=0.288,0.493,0.449).Conclusion The prediction model for PN nature established in this study is accurate and reliable,which can help clinics with early diagnosis and early intervention,and this prediction model deserves to be popularized.

Objective:Farfarae Flos has the effect of cough suppression and phlegm elimination,with cough suppression as the main function.Studies have revealed that certain components of Farfarae Flos may be related to its cough suppressant effect,and some components have been confirmed to have cough suppressant activity.However,the antitussive material basis of Farfarae Flos has not been systematically elucidated.This study aims to elucidate the group of active ingredients in Farfarae Flos with cough suppressant activity by correlating the high performance liquid chromatography(HPLC)fingerprint of Farfarae Flos extract with its cough suppressant activity. Methods:HPLC was used to establish the fingerprint profiles of 10 batches of Farfarae Flos extract and obtain their chemical composition data.Guinea pigs were selected as experimental animals and the citric acid-induced cough model was used to evaluate the antitussive efficacy data of 10 batches of Farfarae Flos extract.SPF-grade healthy male Hartley guinea pigs were randomly divided into the S1 to S10 groups,a positive control group,and a blank control group(12 groups in total),with 10 guinea pigs in each group.The S1 to S10 groups were respectively administered Farfarae Flos extract S1 to S10(4 g/kg),the positive control group was administered pentoverine citrate(10 mg/kg),and the blank control group was administered purified water.Each group received continuous oral administration for 5 days.The guinea pigs were placed in 5 L closed wide-mouth bottles,and 17.5%citric acid was sprayed into the bottle with an ultrasonic atomizer at the maximum spray intensity for 0.5 minutes.The cough latency period and cough frequency in 5 minutes were recorded for each guinea pig.Grey relational analysis(GRA)and partial least squares regression(PLSR)were used to conduct spectral-effect correlation analysis of the chemical composition data of Farfarae Flos extract and the antitussive efficacy data,and predict the group of active ingredients in Farfarae Flos with antitussive activity.The bioequivalence verification was conducted to verify the predicted group of active ingredients in Farfarae Flos with antitussive activity:SPF-grade healthy male Hartley guinea pigs were randomly divided into a S9 group,an active ingredient group,a positive control group,and a blank control group(4 groups in total),with 10 guinea pigs in each group.The S9 group was administered Farfarae Flos extract S9(4 g/kg),the active ingredient group was administered the predicted combination of antitussive active ingredients(dose equivalent to 4 g/kg of Farfarae Flos extract S9),the positive control group was administered pentoverine citrate(10 mg/kg),and the blank control group was administered purified water.Each group received continuous oral administration for 5 days,and animal modeling and observation of efficacy indicators were the same as above. Results:The HPLC fingerprint of 10 batches of Farfarae Flos extract was established,and the peak area data of 14 main common peaks were obtained.The antitussive effect data of 10 batches of Farfarae Flos extract were obtained.Compared with the blank control group,the cough latence in the positive control group and S1,S2,S3,S4,S6,S7,S8,S9,S10 groups was prolonged(all P<0.01),while the cough frequency in 5 minutes in the positive control group and S1,S2,S4,S6,S8,S9,S10 groups was decreased(all P<0.05).The analysis of spectrum-effect relationship revealed that isochlorogenic acid C,isochlorogenic acid A,chlorogenic acid,isochlorogenic acid B,isoquercitrin,and rutin had high contribution to the antitussive effect of Farfarae Flos,and the 6 components were predicted to be the antitussive component group of Farfarae Flos.The verification of bioequivalence showed that there were no statistically significant differences in the antitussive effect between the S9 group and the antitussive component composition group(all P>0.05),which confirmed that isochlorogenic acid C,isochlorogenic acid A,chlorogenic acid,isochlorogenic acid B,isoquercetin,and rutin were the antitussive component group of Farfarae Flos. Conclusion:The analysis of spectrum-effect relationship combined with the verification of bioequivalence could be used to study the antitussive material basis of Farfarae Flos.The antitussive effect of Farfarae Flos is the result of the joint action of many components.

Inducing the degradation of KRAS represents a novel strategy to combat cancers with KRAS mutation. In this study, we identify ubiquitin-specific protease 2 (USP2) as a novel deubiquitinating enzyme of KRAS in multiple myeloma (MM). Specifically, we demonstrate that gambogic acid (GA) forms a covalent bond with the cysteine 284 residue of USP2 through an allosteric pocket, inhibiting its deubiquitinating activity. Inactivation or knockdown of USP2 leads to the degradation of KRAS, resulting in the suppression of MM cell proliferation in vitro and in vivo. Conversely, overexpressing USP2 stabilizes KRAS and partially abrogates GA-induced apoptosis in MM cells. Furthermore, elevated USP2 levels may be associated with poorer prognoses in MM patients. These findings highlight the potential of the USP2/KRAS axis as a therapeutic target in MM, suggesting that strategically inducing KRAS degradation via USP2 inhibition could be a promising approach for treating cancers with KRAS mutations.

Vaccination is the most effective measure for reducing and preventing influenza and related complications. In this study, we analyzed the mutation trend and the antigen dominant site changes of the amino acid sequence of hemagglutinin subunit 1 (HA1) of human influenza A virus (IAV) in the northern hemisphere from 2012 to 2022. According to the HA1 sequences of A/Darwin/6/2021 (H3N2) and A/Wisconsin/588/2019 (H1N1) recommended by the World Health Organization in the 2022 influenza season in northern hemisphere, we employed the mosaic algorithm to design three Mosaic-HA1 antigens through stepwise substitution. Mosaic-HA1 was expressed and purified in 293F cells and then mixed with the alum adjuvant at a volume ratio of 1:1. The mixture was used to immunize BALB/c mice, and the immunogenicity was evaluated. Enzyme-linked immunosorbent assay showed that Mosaic-HA1 induced the production of IgG targeting two types of HA1, the specific IgG titers for binding to H3 protein and H1 protein reached 10⁵ and 10³ respectively. The challenge test showed that Mosaic-HA1 protected mice from H3N2 or H1N1. This study designs the vaccines by recombination of major antigenic sites in different subtypes of IAV, giving new insights into the development of multivalent subunit vaccines against influenza.
Animals ; Influenza A Virus, H1N1 Subtype/genetics* ; Influenza A Virus, H3N2 Subtype/genetics* ; Mice, Inbred BALB C ; Mice ; Influenza Vaccines/genetics* ; Hemagglutinin Glycoproteins, Influenza Virus/genetics* ; Humans ; Antibodies, Viral/blood* ; Antigens, Viral/genetics* ; Immunoglobulin G/immunology* ; Female ; Orthomyxoviridae Infections/prevention & control* ; HEK293 Cells