ObjectiveThe effects of two microbial fertilizers （Bacillus subtilis fertilizer and Trichoderma harzianum-Purpureocillium lilacinum compound fertilizer） on the growth and development， the accumulation of active ingredients， and the microbial community diversity of rhizosphere soil of Atractylodes chinensis were investigated. MethodsA field experiment was carried out with two-year-old Atractylodes chinensis as the test material. Plant samples were collected during the wilt stage （September 26， 2023） to determine the general agronomic traits of Atractylodes chinensis. High-performance liquid chromatography （HPLC） was utilized to evaluate the effects of microbial fertilizers on the synthesis and accumulation of four active ingredients （atractylodin， atractylon， β-eudesmol， and atractylenolide Ⅰ） in Atractylodes chinensi. PacBio Sequel sequencing technology was used to explore the differences in bacterial community structures and diversity in the rhizosphere soil of Atractylodes chinensis treated with different microbial fertilizers. ResultsThe two microbial fertilizers had significant growth-promoting effects on Atractylodes chinensis. Compared with those of the CK group， the stem diameter， stem and leaf dry and fresh weight， and rhizome dry and fresh weight of Atractylodes chinensis significantly increased by 0.47-1.07 times （P<0.05） after the application of the Bacillus subtilis fertilizer （16 kg/667 m²）， and those significantly increased by 0.62-0.96 times （P<0.05） after the application of the Trichoderma harzianum-Purpureocillium lilacinum compound fertilizer （1.5 kg/667 m²）. The effect on plant height was not significant. The application of two microbial fertilizers was beneficial to the accumulation of atractylodin， atractylon， β-eudesmol， and atractylenolide Ⅰ （P<0.01）， and the effect of the Bacillus subtilis fertilizer on the accumulation of active ingredients of Atractylodes chinensis was better than that of the Trichoderma harzianum-Purpureocillium lilacinum compound fertilizer. The results of high-throughput sequencing showed that compared with the CK group， the Bacillus subtilis fertilizer （8 kg/667 m²） could significantly increase the diversity of rhizosphere bacterial species by regulating the Simpson index and Shannon index （P<0.05）， and the Trichoderma harzianum-Purpureocillium lilacinum compound fertilizer significantly reduced the bacterial diversity （P<0.05）. The relative abundance of dominant bacteria was compared at the phylum and genus levels. The relative abundance of Proteobacteria （45.73%） and Burkholderia_Caballeronia_Paraburkholderia （9.98%） significantly increased after the application of the Bacillus subtilis fertilizer （P<0.01）， and the relative abundance of Acidobacteriota （20.53%） and Sphingomonas （3.63%） increased significantly （P<0.01） after the application of the Trichoderma harzianum-Purpureocillium lilacinum compound fertilizer. The relative abundance of beneficial bacteria in the Bacillus subtilis fertilizer was slightly higher than that in the Trichoderma harzianum-Purpureocillium lilacinum compound fertilizer. Pearson correlation analysis showed that Burkholderia_Caballeronia_Paraburkholderia and Sphingomonas were positively correlated with the content of atractylodin， atractylon， β-eudesmol， and atractylenolide Ⅰ （P<0.05）. ConclusionThe application of the Bacillus subtilis fertilizer and Trichoderma harzianum-Purpureocillium lilacinum compound fertilizer can increase the yield of medicinal materials and promote the synthesis and accumulation of active ingredients by regulating the rhizosphere microecological diversity of Atractylodes chinensis， and the application effect of the Bacillus subtilis fertilizer is better than that of the Trichoderma harzianum-Purpureocillium lilacinum compound fertilizer.

Objective To study the compressive mechanical properties and constitutive models of brain tissue at different strain rates.Methods Quasi-static and medium-velocity compression tests were carried out on the white and gray matter of pig brain tissue using an electronic universal testing machine,and stress-strain curves of pig brain tissue at different strain rates were obtained.The Ogden constitutive model was used to fit the test curve,the parameters of the constitutive model were determined,and the simulation was verified using finite element software.Results The brain tissue stress-strain curves showed nonlinear characteristics,with a strong strain rate correlation and sensitivity.When tissues were compressed to 0.6 strain,the stress of white and gray matter increased by 102%and 129%,respectively,at a strain rate of 5×10-4-5×10-2 s-1,and by 50.7%and 54.6%,respectively,at a strain rate of 1-1.5 s-1.At a strain rate of 1.5 s-1,the stress in the white and gray matter increased by 347%and 413%,respectively,compared with that at 5×10-4 s-1 strain rate.The R2 value of the Ogden model was greater than 0.99,and the error between the simulation and experimental results was within 15%,thereby verifying the validity of the model.Conclusions This study is helpful for the prediction of brain tissue deformation and provides an accurate scientific theoretical basis for the establishment of scientific and reasonable human simulation targets as well as the design and improvement of brain-protective equipment.

Objective:To explore the application effect of the forgetting curve combined with blended learning in extracorporeal membrane oxygenation (ECMO) nursing training for ICU nurses.Methods:A randomized controlled trial was conducted from June to November 2022. Sixty-three ICU nurses from the First Hospital of Quanzhou City were selected using cluster sampling and divided into an observation group ( n=30) and a control group ( n=33). The control group received traditional teaching methods for training, while the observation group received training using the forgetting curve combined with blended learning. Compared the ECMO theoretical scores and skill operation scores of two groups of nurses after 1 day, 1 month, and 3 months of training; observed the core competencies and training satisfaction of ECMO nurses before and after training in two groups of nurses. Results:In the control group, there were 7 males and 26 females with an average age of (27.88 ± 4.36) years old; in the observation group, there were 6 males and 24 females with an average age of (28.67 ± 4.24) years old.Prior to training, there were no statistically significant differences in theoretical scores, skill operation scores, and core competencies between the two groups (all P>0.05). After 1 day, 1 month, and 3 months of training, the observation group′s ECMO theoretical scores were (80.33 ± 3.11), (78.13 ± 3.70), (76.73 ± 3.30) points respectively, higher than those of the control group which were (75.18 ± 3.30), (73.88 ± 2.75), (70.48 ± 2.96) points, with statistically significant differences ( t=6.36, 5.21, 7.92, all P<0.01); the observation group′s ECMO skill operation scores were (84.10 ± 4.16), (82.73 ± 3.71), (81.50 ± 3.40) points respectively, higher than the control group′s (78.09 ± 4.30), (74.97 ± 4.17), (71.85 ± 4.03) points, with statistically significant differences ( t=5.63, 7.77, 10.22, all P<0.01). There were statistically significant differences between two groups of nurses in terms of ECMO theory score and skill operation score, as well as time and interactive effect after training ( Finteraction=11.16, 84.76, both P<0.05). After training, the observation group′s total score for ECMO nurse core competency was (280.23 ± 9.23) points, superior to the control group′s (245.39 ± 14.90) points, with a statistically significant difference ( t=11.26, P<0.01). The observation group′s satisfaction total score and the scores in various dimensions were (99.17 ± 10.79), (4.43 ± 0.50), (4.30 ± 0.53), (4.57 ± 0.68), (4.37 ± 0.67), (4.23 ± 0.57) points, all higher than those of the control group which were (84.30 ± 12.61), (3.67 ± 0.96), (3.48 ± 0.71), (3.67 ± 0.74), (3.73 ± 0.72), (3.82 ± 0.77) points, with statistically significant differences ( t values were 2.42 to 5.09, all P<0.05). Conclusions:The application of the forgetting curve combined with blended learning in ECMO nursing training for ICU nurses is scientifically feasible. It helps nurses master ECMO theory and skill operations, improve ECMO nurse core competencies, enhance training satisfaction, and provides a new method for ECMO nursing training.

Objective To investigate the changes of serum metabolites in patients with occupational chronic lead poisoning using non-targeted metabolomics, and to screen differential metabolic pathways. Methods A total of 14 patients with occupational chronic lead poisoning were selected as the poisoning group, and 14 healthy people without occupational hazard exposure history were selected as the control group using the judgment sampling method. Serum of the individuals from the two groups was collected. Non-targeted metabolomics technology based on ultra high performance liquid chromatography-tandem mass spectrometry was used to detect serum metabolite levels in the two groups. Differential metabolites (DMs) were screened by the principal component analysis, partial least squares discriminant analysis and orthogonal partial least squares discriminant analysis, and related metabolic pathways were explored. Results The blood lead level in the poisoning group was higher than that in the control group (median: 359.59 vs 5.04 μg/L, P<0.01). There were significant differences in serum metabolites between the poisoning group and control group. After the combination of results from the positive and negative ion patterns, a total of 89 DMs were screened in serum of patients in the poisoning group, including 50 upregulated and 39 downregulated metabolites compared with the control group. The serum DMs of poisoning group were mainly enriched in arginine biosynthesis, ABC transporter, purine metabolism, choline metabolism in malignant tumor, glycerophospholipid metabolism and ether lipid metabolism compared with the control group (all P<0.05). Conclusion Abnormal changes of serum metabolic profile occurred in patients with occupational chronic lead poisoning. The metabolic pathways such as arginine biosynthesis, ABC transporter, purine metabolism, choline metabolism, glycerophospholipid metabolism and ether lipid metabolism may be involved in the occurrence and development of lead poisoning.

Objective:To investigate the protective effects of a sunscreen lotion containing Calendula extracts on children′s skin against sun exposure, as well as to evaluate its safety and tolerability when applied to children.Methods:A single-center, randomized, split-body/face study was conducted on 200 healthy children aged 3 - < 18 years, who were enrolled from Beijing Children′s Hospital, Capital Medical University from July to August 2022. The participants were randomly and equally divided into Group A (the left side of the body/face topically treated with the test sunscreen, and the right side with the control sunscreen) and Group B (the right side of the body/face topically treated with the test sunscreen, and the left side with the control sunscreen) at a ratio of 1∶1. After applying the sunscreen, they were engaged in outdoor activities under sunlight. Skin tests were conducted on the temporal area, the extensor aspect of the upper arm and forearm before and after sun exposure. The test product was a mild sunscreen lotion containing Calendula extracts with the sun protection factor (SPF) being 50+ and the long-wave ultraviolet protection factor (PA) being +++, and the control product was a baby sunscreen containing licorice extracts (SPF35, PA++). Bilateral differential scales were used to assess clinical symptoms after sun exposure, erythema values to clinically evaluate erythema after sun exposure, and the multifunctional skin testing platform MPA10 to measure melanin and erythema values, stratum corneum hydration, and transepidermal water loss (TEWL) at the tested sites. Related adverse events were observed and recorded during the study. The paired t-test or Wilcoxon signed-rank test was used for the comparison of quantitative data, and chi-square test (Fisher′s exact test) for the comparison of count data. Results:Totally, 198 children completed the study and visits, including 100 males (50.5%) and 98 females (49.5%), aged from 3 to 17 years (8.11 ± 0.23 years), and there were 99 cases each in the Group A and Group B. The numbers of participants with more obvious sunburn symptoms after sun exposure in the 3 tested areas were all higher on the control side than on the test side (the temporal area: 11 cases vs. 4 cases; the extensor aspect of the upper arm: 16 cases vs. 2 cases; the extensor aspect of the forearm: 33 cases vs. 3 cases), with significant differences between the bilateral sides (all P<0.001). No significant differences were observed in the erythema values between the test side and control side in the 3 tested areas (all P > 0.05). In the extensor aspect of the upper arm and forearm, the difference in the melanin value before and after sun exposure was significantly smaller on the test side (3.57 ± 2.41, 1.74 ± 1.68, respectively) than on the control side (9.50 ± 2.21, 8.13 ± 1.87, respectively, both P < 0.001) ; in the temporal region and the extensor aspect of the upper arm and forearm, the difference in the stratum corneum hydration level before and after sun exposure was significantly greater on the test side (7.72[-2.19, 19.44], 9.56 ± 1.37, 9.05 ± 1.37, respectively) than on the control side (-3.25[-13.54, 9.94], 3.63 ± 1.32, 3.73 ± 1.31, respectively, all P < 0.001) in the temporal region and the extensor aspect of the upper arm and forearm. However, there were no significant differences in the changes in the erythema or TEWL values before and after sun exposure between the test side and control side in either of the 3 tested areas (all P > 0.05). During this study, 1 case (0.51%) experienced transient urticaria on the control side, and no serious adverse events occurred. Conclusion:The mild sunscreen lotion containing Calendula extracts demonstrated superior efficacy to the control product in improving skin symptoms after sun exposure such as hyperpigmentation among healthy children aged 3 - < 18 years, with good tolerability and a relatively low incidence of adverse reactions.

Objective:To construct a classification model for endoscopic ultrasonography (EUS) images of gastrointestinal stromal tumors (GISTs) and leiomyomas (LM) based on deep learning technology, and to verify its value for differential diagnosis.Methods:From October 2014 to October 2021, 69 patients of GISTs and 73 of LM who underwent EUS and were pathologically confirmed by surgery or endoscopic resection in the Second Affiliated Hospital of Soochow University were retrospectively studied. One clear EUS image with typical lesion was selected for each case. Using the hold-out method, the images of each disease were divided into the training set and the validation set according to the ratio of the number of images in the training set to the number of images in the validation set, which was 8∶2. Finally, 113 EUS images (55 GISTs and 58 LM) were used to form the training set, and 29 EUS images (14 GISTs and 15 LM) were used to form the validation set. The training set was used to train and optimize the deep learning model, and the validation set was used to verify the classification model. The main observation indicators included the sensitivity, the specificity, the positive predictive value, the negative predictive value and the accuracy of differential diagnosis.Results:The accuracy of the classification model established by Resnet 34 network structure in the differential diagnosis of GISTs and LM tended to be 0.89, better than the classification model established by Resnet 50 network structure (0.81). The sensitivity, the specificity, the positive predictive value, the negative predictive value and the accuracy of the classification model based on Resnet 34 network structure for differentiating EUS images in the validation set were 85.71% (12/14, 95% CI: 67.38%-100.00%), 93.33% (14/15, 95% CI: 80.71%-100.00%), 92.31% (12/13, 95% CI: 77.82%-100.00%), 87.50% (14/16, 95% CI: 71.30%-100.00%) and 89.66% (26/29, 95% CI: 78.57%-100.00%), respectively. Conclusion:It is feasible to use deep learning technology in the differential diagnosis of EUS images of GISTs and LM, which can provide auxiliary diagnostic opinions for clinicians. The deep learning model based on Resnet 34 network structure shows higher accuracy in the differential diagnosis of EUS images of GISTs and LM.

Objective To investigate the potential mechanism of Jianpi Shenshi Formula for the treatment of hyperuricemia(HUA)by using network pharmacology and molecular docking techniques.Methods The active ingredients of Jianpi Shenshi Formula were searched and screened by combining TCMSP,BATMAN,and TCM-ID database with literature,and then SwissTargetPrediction was used to obtain the corresponding targets of the ingredients.Cytoscape 3.8.0 was used to construct a"drug-ingredients"network to analyze and obtain the main active ingredients of Jianpi Shenshi Formula.The GeneCards,OMIM,and disgenet databases were used to obtain the relevant targets of hyperuricemia.The intersection targets of Jianpi Shenshi Formula and hyperuricemia were imported into the STRING database for protein-protein interaction(PPI)network analysis,and hub targets for network were screened by CytoHubba plug-in.Meanwhile,the GO function and KEGG pathway enrichment analysis of the intersection targets were carried out using R4.2.2 software.Molecular docking of hub targets and key ingredients was performed using CB-DOCK 2.Results A total of 90 active ingredients of Jianpi Shenshi Formula were screened,among which quercetin,kaempferol,luteolin,stigmasterol,and ethyl linoleate were the main active ingredients,and 837 targets corresponding to the ingredients were obtained,with a total of 64 intersecting targets.CASP3,IL1B,IL6,PPARG,SIRT1,MAPK3,TNF,STAT3,TGFβ1,PTGS2,and XDH were the hub targets.The potential targets of action are mainly enriched in signaling pathways such as inflammation,metabolism,environment,cellular processes,biological systems,and hyperuricemia-related pathways.Conclusion Jianpi Shenshi Formula may exert effects on inhibition of uric acid production,and/or enhancement of uric acid excretion,anti-inflammation,and amelioration of related complications through the modulation of hyperuricemia-related signaling pathways(including neoplastic,infectious,metabolic,and cardiovascular diseases),as well as metabolic,immune,inflammatory,and other biological pathways by a variety of active ingredients such as quercetin,kaempferol,luteolin,stigmasterol,and ethyl linoleate.

With the rising aging population, the number of people with stroke, dementia and Parkinson's disease is huge.These patients often have swallowing dysfunction, cognitive decline, decreased immune function, long-term bed rest, malnutrition, and sarcopenia, and are prone to pneumonia.However, the clinical manifestations of these patients with pneumonia are non-specific.The patients often cannot accurately express their complaints, resulting in symptoms being ignored.The underlying diseases of the nervous system increase the risk of pneumonia-related death, and is associated with poor prognosis.This article aimed to review the risk factors, prevention and treatment of these three neurological disorders complicated with pneumonia.

Community acquired pneumonia(CAP)is characterized by high morbidity and mortality in immunocompromised patients, with the elderly as the main vulnerable population.However, current guidelines in China and elsewhere do not offer specific recommendations on the diagnosis and treatment of such patients.This paper reviews the definition, classification, epidemiology, etiological characteristics, clinical manifestations, diagnosis, treatment and prognosis of CAP in immunocompromised elderly patients, to provide a theoretical framework for its diagnosis and treatment and for the formulation of guidelines.

Objective:To develop and verify machine learning(ML)models for the early warning of ventilator-associated pneumonia(VAP)within 24 hours after invasive mechanical ventilation, so as to provide more evidence and ideas for the clinical management of VAP in elderly patients.Methods:In this study, clinical data of elderly patients with acute respiratory failure and invasive mechanical ventilation in intensive care unit were extracted from MIMIC Ⅳ 2.2 database.Using VAP as the outcome index, patients were divided into training set and testing set in a ratio of 7∶3.Four ML algorithms were used to build a model in the training set, and the performance of the model was verified by the test set.The model was compared with SOFA, systemic inflammatory response syndrome(SIRS) and acute physiology score(APS)Ⅲ scores in the same dataset.Results:A total of 1 859 elderly patients were included, 336 of whom were diagnosed with VAP.The area under the curve(AUC)of the receiver operator characteristic curve of ML models were higher than the clinical risk scores(SOFA score: 0.44, SIRS score: 0.49, APS Ⅲ score: 0.46), and the LightGBM model and XGBoost model had better predictive performance, with AUC of 0.85(95% CI: 0.82, 0.88)and 0.84(95% CI: 0.81, 0.87). SHAP was used to further explain the model.The results showed that SOFA neurological score, maximum white blood cell count, maximum respiratory rate, maximum alkali residual and age were important factors for early prediction of elderly VAP. Conclusions:In this study, ML algorithms were used to build an early warning model of VAP in elderly patients, which has important guiding significance for clinical timely initiation and adjustment of treatment plan.In the future, external verification of the model should be further carried out.