Cervi Cornu Pantotrichum is a precious animal-derived Chinese medicinal material, while there are often adulterants derived from animals not specified in the Chinese Pharmacopeia in the market, which disturbs the safety of medication. This study was conducted with the aim of strengthening the quality control of Cervi Cornu Pantotrichum and standardizing the medication. To achieve digital identification of Cervi Cornu Pantotrichum from different sources, a digital identification model was constructed based on ultra-high performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry(UHPLC-QTOF-MS~E) combined with an adaptive boosting algorithm(Adaboost). The young furred antlers of sika deer, red deer, elk, and reindeer were processed and then subjected to polypeptide analysis by UHPLC-QTOF-MS~E. Then, the mass spectral data reflecting the polypeptide information were obtained by digital quantification. Next, the key data were obtained by feature screening based on Gini index, and the digital identification model was constructed by Adaboost. The model was evaluated based on the recall rate, F_1 composite score, and accuracy. Finally, the results of identification based on the constructed digital identification model were validated. The results showed that when the Gini index was used to screen the data of top 100 characteristic polypeptides, the digital identification model based on Adaboost had the best performance, with the recall rate, F_1 composite score, and accuracy not less than 0.953. The validation analysis showed that the accuracy of the identification of the 10 batches of samples was as high as 100.0%. Therefore, based on UHPLC-QTOF-MS~E and Adaboost algorithm, the digital identification of Cervi Cornu Pantotrichum can be realized efficiently and accurately, which can provide reference for the quality control and original animal identification of Cervi Cornu Pantotrichum.
Animals ; Algorithms ; Antlers/chemistry* ; Boosting Machine Learning Algorithms ; Chromatography, High Pressure Liquid/methods* ; Deer ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Quality Control ; Reindeer ; Tandem Mass Spectrometry/methods* ; Tissue Extracts/analysis*

To investigate the effects of phosphorus fertilizer on the morphological traits, active ingredients and rhizosphere soil microbial community of Polygala tenuifolia. The phosphorus fertilizer was calculated in terms of P_2O_5. Five treatments were set up: 0(CK), 17(P1), 34(P2), 51(P3), and 68(P4) kg per Mu(1 Mu≈667 m~2). A randomized block design was adopted. Samples of P. tenuifolia and its rhizosphere soil were collected under different superphosphate fertilizer treatments. Illumina high-throughput sequencing was used to analyze the rhizosphere soil microbial community, 9 morphological traits were measured and the content of 11 active ingredients were determined. The results showed that the whole plant weight, shoot fresh weight, root weight, and root peel thickness were the highest under P1 treatment, increasing by 34.41%, 38.80%, 39.21%, and 3.17% respectively compared to CK. Under P2 treatment, the plant height, stem diameter, root thickness, and core thickness were significantly higher than CK. Phosphorus fertilizer had a significant impact on the content of tenuifolin, sibiricose A5, sibiricose A6, arillanin A, 3,6'-disinapoyl sucrose, and polygalaxanthone Ⅲ. Correlation analysis results showed that the relative abundance of Arthrobacter, Bacillus, norank＿f＿Vicinamibacteraceae, norank＿o＿Vicinamibacterales, MND1 and other bacteria, as well as the relative abundance of Neocosmospora, Paraphoma and other fungi were positively correlated with root diameter, wood core diameter, the whole plant weight, root weight, shoot fresh weight of P. tenuifolia. Bacillus, Neocosmospora, Subulicystidium were significantly positively correlated with oligosaccharides such as 3,6'-disinapoyl sucrose, sibiricose A5、sibiricose A6、glomeratose A、arillanin A and tenuifoliside C. Arthrobacter, Humicola, Aspergillus, Paraphoma were positively correlated with tenuifolin and norank＿f＿Vicinamibacteraceae, norank＿o＿Vicinamibacterales, Fusarium were positively correlated with polygalaxanthone Ⅲ. Evidently, appropriate phosphorus application is conducive to the growth and quality improvement of P. tenuifolia, and can increase the abundance of beneficial microorganisms in the soil.
Rhizosphere ; Phosphorus/pharmacology* ; Soil Microbiology ; Polygala/anatomy & histology* ; Fertilizers/analysis* ; Bacteria/metabolism* ; Soil/chemistry* ; Microbiota/drug effects* ; Plant Roots/metabolism*

Mutations in the cyclin-dependent kinase-like 5 gene (CDKL5) cause a severe neurodevelopmental disorder, yet the impact of truncating mutations remains unclear. Here, we introduce the Cdkl5^492stop mouse model, mimicking C-terminal truncating mutations in patients. 492stop/Y mice exhibit altered dendritic spine morphology and spontaneous seizure-like behaviors, alongside other behavioral deficits. After creating cell lines with various Cdkl5 truncating mutations, we found that these mutations are regulated by the nonsense-mediated RNA decay pathway. Most truncating mutations result in CDKL5 protein loss, leading to multiple disease phenotypes, and offering new insights into the pathogenesis of CDKL5 disorder.
Animals ; Disease Models, Animal ; Mice ; Protein Serine-Threonine Kinases/deficiency* ; Mutation/genetics* ; Epileptic Syndromes/genetics* ; Humans ; Dendritic Spines/pathology* ; Spasms, Infantile/genetics* ; Male ; Seizures/genetics* ; Mice, Inbred C57BL

Purpose To investigate the expression of LAMB3 and ITGB4 in esophageal squamous cell carcinoma(ESCC)and analyze their associations with clinicopathological features.Methods Bioinformatics was used to assess the expression of LAMB3 and ITGB4 in pan-cancer and ESCC.Immunohistochemistry was performed to evaluate their expression and distribution in ESCC tissues,and correlations clinicopathological features were analyzed.Follow-up data were collected to construct Kaplan-Meier survival curves,and Cox regression analysis was proformed to determine their prognostic significance.Results Bioinformatics analysis showed that LAMB3 and ITGB4 were highly expressed in ES-CC tissues(P＜0.001).Immunohistochemistry confirmed that both proteins were localized in the cytoplasm and membrane of tumor cells.High LAMB3 expression was significantly associated with poor differentiation(P＜0.001),lymph node metastasis(P=0.015),and T staging(P＜0.001).High ITGB4 expression was significantly correlated with poor differentiation(P=0.004)and advanced T staging(P=0.004).Cox regression analysis identified high ex-pression of LAMB3 and ITGB4 as independent prognostic factors for overall survival[HR=4.97(95％CI:2.73-9.02);HR=2.33(95％CI:1.36-3.99)].Conclusion LAMB3 and ITGB4 are highly expressed in ESCC.High LAMB3 expression is associated with tumor differentiation,lymph node metastasis,and T staging,while high ITGB4 expression is correlated with tumor differentiation and T staging.Patients with high expression of LAMB3 or ITGB4 have poorer overall survival,suggesting that these proteins may serve as prognostic biomarkers for unfavorable outcome in ESCC.

Aim To investigate the anti-acute lung injury(ALI)effect of Sterculiae Lychnophorae Semen(SLS)and its mechanism.Methods The main ac-tive components of SLS and their core targets and path-ways of action against ALI were obtained by network pharmacology methods.Subsequently,molecular doc-king technology and in vitro cellular experiments were applied for validation.Results A total of 19 core tar-gets were obtained,including HSP90AA1,CASP3,TNF,MAPK8 and MAPK14.The mechanisms may in-volve signaling pathways such as cancer,PI3K/Akt and MAPK.Molecular docking confirmed that the key targets of SLS formed a better binding activity with the relevant active ingredients.The in vitro results showed that SLS was able to protect the PM2.5-contaminated BEAS-2B cells,inhibit their NO,IL-1β and TNF-αlevels,and reduce the expression of p-p38 MAPK and p-JNK proteins.Conclusions The study successfully predicts the active ingredients,targets and signaling pathways of SLS against ALI,and in vitro experiments demonstrate that SLS might protect BEAS-2B cells from PM2.5 stimulus-induced inflammation and apoptosis by inhibiting the over-activation of p38 MAPK and JNK signaling pathways.

Objective To develop and validate a fast Monte Carlo(MC)-based patient-specific quality assurance(PSQA)tool using the treatment log files that is suitable to be used in the online adaptive radiotherapy for pencil beam scanning proton therapy(PBSPT-ART).Methods The proposed tool first used the delivery log file of a PBSPT plan to reversely reconstruct the PBSPT(rPBSPT)plan,and then used an in-house developed graphic processing unit(GPU)-accelerated virtual particle MC(VPMC)dose engine to calculate the dose distribution of the rPBSPT plan.The rPBSPT dose calculated by VPMC was then compared to the rPBSPT dose calculated by another independent MC dose engine(MCsquare),using 3D gamma analysis to verify the accuracy of VPMC calculation.As a demonstration of the feasibility of developed log file-based PSQA,the VPMC calculated dose of the rPBSPT plan was compared to the pre-delivery second check dose of the corresponding PBSPT plan calculated by MCsquare,using 3D gamma analysis.3D gamma analysis employes a criterion of 2 mm/2%/10%.Twenty patients with different disease sites were representatively selected to validate the efficiency and accuracy of the tool.Results The average calculation time of a rPBSPT plan by VPMC was(5.88±4.00)s in the accuracy verification.Compared to MCsquare,the passing rate of the 3D gamma analysis was 99.47%±0.72%.In the proposed PSQA tool demonstration,the passing rate of comparing the VPMC calculated rPBSPT dose to MCsquare calculated second check dose of the corresponding PBSPT plan was 98.91%±0.92%.Conclusion The accuracy and efficiency of the tool can meet the requirements of PSQA in the online PBSPT-ART workflow.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To investigate the changes of serum microRNA (miR)-138-5p and microRNA(miR)-574-5p expression levels and their clinical significance in newborns acute respiratory distress syndrome (nARDS). Methods A total of 112 infants with nARDS from September 2018 to August 2023 in the Neonatal Department of Xiaogan Hospital Affiliated to Wuhan University of Science and Technology were collected as the observation group. They were divided into good prognosis group (n=98) and the poor prognosis group (n=14). A total of 104 healthy full-term newborns born at the same time were selected as the control group. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of miR-138-5p and miR-574-5p in serum. ROC curve was used to analyze the diagnostic value of serum miR-574-5p and miR-138-5p levels for poor prognosis of infants with nARDS. Multivariate Logistic regression analysis of factors affecting the poor prognosis of infants with nARDS. Results Compared with the control group,the expression level of serum miR-574-5p in the observation group increased (1.72±0.23 vs 1.04±0.17),with the expression level of miR-138-5p decreased (0.55±0.08 vs 1.02±0.16),with statistically significant differences (t=24.557,25.597,all P<0.05). Compared with the good prognosis group,the serum miR-138-5p expression level in the poor prognosis group decreased (0.41±0.06 vs 0.57±0.08),with the miR-574-5p expression level increased (2.07±0.25 vs 1.67±0.19),with statistically significant differences (t=7.188,7.069,all P<0.05). The age,intrauterine distress,and proportion of abnormal amniotic fluid in the poor prognosis group were higher than those in the good prognosis group (t=5.359,4.257,6.577,all P<0.05). MiR-574-5p was an independent risk factor for poor prognosis with nARDS,and miR-138-5p was a protective factor (all P<0.05).The AUC (95％ CI) of serum miR-138-5p and miR-574-5p alone and combined diagnosis of nADRS were 0.793 (0.706～0.864),0.898 (0.826～0.947) and 0.931 (0.867～0.970),respectively. The combined prediction of miR-138-5p and miR-574-5p were better than that of miR-138-5p alone and miR-574-5p alone (Z=2.151,1.982,all P<0.05). Conclusion The expression levels of miR-138-5p in serum of infant with nARDS were lower and the expression levels of miR-574-5p were higher,both of which have certain diagnostic value for poor prognosis of infant with nARDS .

Objective To develop and validate a fast Monte Carlo(MC)-based patient-specific quality assurance(PSQA)tool using the treatment log files that is suitable to be used in the online adaptive radiotherapy for pencil beam scanning proton therapy(PBSPT-ART).Methods The proposed tool first used the delivery log file of a PBSPT plan to reversely reconstruct the PBSPT(rPBSPT)plan,and then used an in-house developed graphic processing unit(GPU)-accelerated virtual particle MC(VPMC)dose engine to calculate the dose distribution of the rPBSPT plan.The rPBSPT dose calculated by VPMC was then compared to the rPBSPT dose calculated by another independent MC dose engine(MCsquare),using 3D gamma analysis to verify the accuracy of VPMC calculation.As a demonstration of the feasibility of developed log file-based PSQA,the VPMC calculated dose of the rPBSPT plan was compared to the pre-delivery second check dose of the corresponding PBSPT plan calculated by MCsquare,using 3D gamma analysis.3D gamma analysis employes a criterion of 2 mm/2%/10%.Twenty patients with different disease sites were representatively selected to validate the efficiency and accuracy of the tool.Results The average calculation time of a rPBSPT plan by VPMC was(5.88±4.00)s in the accuracy verification.Compared to MCsquare,the passing rate of the 3D gamma analysis was 99.47%±0.72%.In the proposed PSQA tool demonstration,the passing rate of comparing the VPMC calculated rPBSPT dose to MCsquare calculated second check dose of the corresponding PBSPT plan was 98.91%±0.92%.Conclusion The accuracy and efficiency of the tool can meet the requirements of PSQA in the online PBSPT-ART workflow.