Aim To explore the efficacy of levosimendan on hypoxia pulmonary hypertension through animal experiments, and to further explore the potential mechanism of action using network pharmacological methods and molecular docking technique. Methods The rat model of hypoxia pulmonary hypertension was constructed to detect right heart systolic pressure and right heart remodeling index. HE , Masson, and VG staining were core targets were screened out. GO and KEGG pathway enrichment analysis were performed using the DAVID database. Molecular docking of the core targets was performed with the AutoDock software. Results The results of animal experiments showed that levosimendan had obvious therapeutic effect on hypoxia pulmonary hypertension. The network pharmacology results showed that SRC, HSP90AA1, MAPK1, PIK3R1, AKT1, HRAS, MAPK14, LCK, EGFR and ESR1 used to analyze the changes of rat lung histopathology. Search the Swiss Target Prediction, DrugBank Online, BatMan, Targetnet, SEA, and PharmMapper databases were used to screen for drug targets. Disease targets were retrieved from the GeneCards, OMIM databases. The "drug-target-disease" network was constructed after identification of the two intersection targets. The protein interaction network was constructed and the were the key targets to play a therapeutic role. Molecular docking showed good docking of levosimendan with all the top five core targets with degree values. Conclusions Levosimendan may exert a therapeutic effect on hypoxia-induced pulmonary hypertension through multiple targets.

Objective:To investigate the factors influencing phytohemagglutinin (PHA) response in the detection of Mycobacterium tuberculosis infection by gamma interferon release assay (IGRA). Methods:A retrospective case-control study was conducted on 360 hospitalized patients who received IGRA in West China Hospital of Sichuan University from January 2019 to December 2021. According to PHA response (IFN-γ level), they were divided into three groups: negative mitogen response group (IFN-γ<2 pg/ml), weak positive mitogen response group (IFN-γ: 2-100 pg/ml), and normal mitogen response group (IFN-γ>400 pg/ml).Results:Immune diseases were independently associated with negative (OR=0.34, 95%CI: 0.17-0.72, P=0.004) and weak positive mitogen responses (OR=0.29, 95%CI: 0.16-0.55, P<0.001). Infections caused by pathogens other than Mycobacterium tuberculosis was independently associated with negative mitogen response (OR=0.266, 95%CI: 0.09-0.83, P=0.023), while immunodeficiency was independently associated with weak positive mitogen response (OR=0.280, 95%CI: 0.12-0.63, P=0.002). Mitogen response was significantly correlated with the levels of albumin and hemoglobin in serum and the counts of neutrophils and lymphocytes ( P<0.001). Conclusions:Immune diseases and immunodeficiency can affect mitogen response. Therefore, clinicians should give attention to mitogen response in the interpretation of IGRA test results to prevent misdiagnosis and underdiagnosis. Besides, to a certain extent, mitogen response can reflect the infection status of hospitalized patients.

OBJECTIVE To systematically evaluate the therapeutic effect of acupuncture on geriatric insomnia.METHODS Randomized controlled trials(RCTs)on acupuncture in the treatment of senile insomnia were searched in CNKI,VIP,Wanfang,China Biomedical Database,PubMed,Web of science,Embase and Cochrane Library databases from inception dates to June 24,2024.Litera-ture was screened and data were extracted based on the inclusion and exclusion criteria.The literature quality was evaluated according to the risk of bias table recommended by the Cochrane Collaboration Handbook 5.1.0,and the outcome indicators were graded using the GRADE system for the quality of evidence.RevMan5.4 software was used to evaluate the quality of the included literature,and Sta-ta18.0 software was used to conduct Meta-analysis on the included literature.RESULTS A total of 18 studies involving 1399 pa-tients were included.Meta-analysis showed that:compared with the simple western medicine treatment,acupuncture in the treatment of senile insomnia patients could improve the clinical effective rate[RR=1.18,95%CI(1.13,1.24),P<0.001],reduce the total PSQI score[MD=-1.10,95%CI(-1.25,-0.96),P<0.001],daytime dysfunction[MD=-1.38,95%CI(-1.59,-1.16),P<0.001],sleep latency[MD=-0.66,95%CI(-0.86,-0.47),P<0.001],sleep duration[MD=-0.45,95%CI(-0.64,-0.25),P<0.001],sleep efficiency[MD=-0.69,95%CI(-0.89,-0.49),P<0.001],sleep disorder[MD=-1.24,95%CI(-1.47,-1.01),P<0.001],sleep quality[MD=-0.84,95%CI(-1.05,-0.64),P<0.001].GRADE classification showed that the clinical efficacy was advanced evidence;the adverse reactions were intermediate evidence;the total score of PSQI,daytime dysfunction,sleep latency,sleep efficien-cy,sleep quality and sleep disorder were low evidence;sleep time was extremely low evidence.CONCLUSION Acupuncture inter-vention in senile insomnia patients is superior to the control group in clinical efficiency and various PSQI scores.Acupuncture interven-tion is worthy of further promotion and use in clinical practice as the complementary and alternative therapy for the conventional western medication treatment of senile insomnia.However,the evidence levels of some outcome indicators are relatively low,and more high-quality RCTs with large sample sizes are still needed to increase the strength of evidence.

Background Mercury, as a global heavy metal pollutant, poses a serious threat to human health. The toxicity of mercury depends on its chemical form. Distinguishing the forms of mercury in the environment is of great significance for mercury management and reducing human mercury exposure risks. Objective To establish a non-targeted metallomics method based on synchrotron radiation X-ray fluorescence (SRXRF) spectroscopy combined with machine learning to screen inorganic mercury (IHg) or methylmercury (MeHg) exposed rice plants. Methods Rice seeds were exposed to ultra-pure water (control group), 0.1 mg·L⁻¹ IHg (IHg group) or MeHg (MeHg group) solutions, respectively. After germination, the seedlings were cultured for 21 d, and rice leaves were collected, dried, weighed, and pressed. The content of metallome in rice leaves was determined by SRXRF. Machine learning models including soft independent modeling cluster analysis (SIMCA), partial least squares discriminant analysis (PLS-DA), and logistic regression (LR) were used to classify the SRXRF full spectra of different groups and find the best model to distinguish rice exposed to IHg or MeHg. Besides, characteristic elements were selected as input parameters to optimize the model by improving computing speed and reducing model calculation. Results The SRXRF spectral intensities of the control group, IHg group, and MeHg group were different, indicating that exposure to IHg and MeHg can interfere the homeostasis of metallome in rice leaves. The results of principal component analysis (PCA) of SRXRF spectra showed that the control group could be well distinguished from the mercury exposed groups, but the IHg group and the MeHg group were mostly overlapped. The accuracy rates of the three models (PLS-DA, SIMCA, and LR) were higher than 98% for the training set, higher than 95% for the validation set, and higher than 94% for the cross-validation set. Besides, the accuracy of the LR model was higher than that of the PLS-DA model and the SIMCA model. Furthermore, the accuracy was 92.05% when using characteristic elements K, Ca, Mn, Fe, and Zn selected by LR to distinguish the IHg group and the MeHg group. Compared with the full spectra model, although the prediction accuracy of the characteristic spectral model decreased, the input parameters of the model decreased by 99.51%, and precision, recall, and F1 score were above 84.48%, indicating that the model could distinguish rice exposed to different mercury forms. Conclusion Non-targeted metallomics method based on SRXRF and machine learning can be applied for high-throughput screening of rice exposed to different forms of mercury and thus decrease the risks of people being exposed to mercury.

PI3Kγ and PI3Kδ have important regulatory roles in the immune system, and targeting these two subtypes helps to reshape the tumor microenvironment. PI3Kγ and PI3Kδ are potential targets for tumor immunotherapy. In this study, a series of new pyrazolopyrimidine derivatives were designed and synthesized on the basis of our previously reported PI3K inhibitors, resulting in the discovery of compound 16l as a potent and selective PI3Kγ/δ dual inhibitor. Compound 16l demonstrated strong biochemical potencies against PI3Kγ and PI3Kδ with IC₅₀ values of 0.11 and 0.79 nmol·L^-1. In cell-based assays, it potently inhibited the PI3Kγ and PI3Kδ mediated Akt S473 phosphorylation with EC₅₀ values of 3 and 7 nmol·L^-1. In vivo, compound 16l exhibited acceptable pharmacokinetic properties in Sprague-Dawley (SD) rats and suppressed the tumor growth in a MC38 syngeneic mouse model. The animal experiments were approved by the Animal Ethics Committee of Hefei Institutes of Physical Science, Chinese Academy of Sciences (approval number: DWLL-2000-06). In addition, no appreciable human ether-a-go-go-related gene (hERG) inhibition was observed for compound 16l even at 30 μmol·L^-1. These results suggested that compound 16l might be a potential research tool for studying the PI3Kγ/δ mediated signaling pathways.

Objective To propose a method for classifying small bowel capsule endoscopy images by combining the Swin Transformer network with an improved Adapt-RandAugment data augmentation approach,aiming to enhance the accuracy and efficiency of small bowel lesion classification and recognition.Methods An Adapt-RandAugment data augmentation approach was formulated based on the RandAugment data enhancement sub-strategy and the principles of no feature loss and no distortion when enhancing small bowel capsule endoscopy images.In the publicly available Kvasir-Capsule dataset of small bowel capsule endoscopic images,the Adapt-RandAugment data augmentation approach was trained based on the Swin Transformer network,and the convolutional neural networks ResNet152 and DenseNet161 were used as the benchmarks to validate the combined Swin Transformer network and Adapt-RandAugment data augmentation approach for small bowel capsule endoscopy image classification.Results The proposed algorithm gained advantages over ResNet152 and DenseNet161 networks in the indicators,which had the macro average precision(MAC-PRE),macro average recall(MAC-REC),macro average F1 score(MAC-Fi-S)being 0.383 2,0.314 8 and 0.290 5 respectively,the micro average precision(MIC-PRE),micro average recall(MIC-REC)and micro average F1 score(MIC-Fi-S)all being 0.755 3,and the Matthews correlation coe-fficient(MCC)being 0.452 3.Conclusion The proposed small bowel capsule endoscopy image classification method based on Swin Transformer network and Adapt-RandAugment data augmentation approach behaves well in classified recognition efficiency and accuracy.[Chinese Medical Equipment Journal,2024,45(6):9-16]

Non-communicable diseases(NCDs),including cardiovascular diseases,cancer,metabolic diseases,and skeletal diseases,pose significant challenges to public health worldwide.The complex pathogenesis of these diseases is closely linked to oxidative stress and inflammatory damage.Nuclear factor erythroid 2-related factor 2(Nrf2),a critical transcription factor,plays an important role in regulating antioxidant and anti-inflammatory responses to protect the cells from oxidative damage and inflammation-mediated injury.Therefore,Nrf2-targeting therapies hold promise for preventing and treating NCDs.Quercetin(Que)is a widely available flavonoid that has significant antioxidant and anti-inflammatory properties.It modulates the Nrf2 signaling pathway to ameliorate oxidative stress and inflammation.Que modulates mitochondrial function,apoptosis,autophagy,and cell damage biomarkers to regulate oxidative stress and inflammation,highlighting its efficacy as a therapeutic agent against NCDs.Here,we discussed,for the first time,the close association between NCD pathogenesis and the Nrf2 signaling pathway,involved in neurodegenerative diseases(NDDs),cardiovascular disease,cancers,organ damage,and bone damage.Furthermore,we reviewed the availability,pharmacokinetics,pharmaceutics,and therapeutic applica-tions of Que in treating NCDs.In addition,we focused on the challenges and prospects for its clinical use.Que represents a promising candidate for the treatment of NCDs due to its Nrf2-targeting properties.

In this study,a method for detecting heavy metal ions using potentiometric sensor and voltammetric sensor was proposed.By exploiting the complementary advantages of potentiometric and voltammetric electrochemical sensor,the traditional electrochemical electrode without special material preparation and modification could be used for the wide range and accurate detection of heavy metal ions in actual water samples.During detection,the concentration of target ion was measured by a potentiometric electrochemical sensor to determine the concentration range.The amperometric electrochemical sensor was then used for calibration and accurate measurement in the appropriate concentration range.Taking copper ion(Cu2+)as an example,the prepared Cu2+water sample and the actual water sample were tested.First,the copper ion selective electrode was used to determine the concentration range of Cu2+in the sample.Then,based on the gold electrode in different concentration range(0.86-100 μg/L and 100-300 μg/L)using two different optimization parameter settings to calibrate the electrochemical sensor and measure,the test results had a good correlation with those by professional water quality testing institutions.The recoveries ranged from 86.7%to 103.0%.The experimental results showed that the combination of potential sensor and current sensor could improve the accuracy of detection of heavy metal ions in water samples by electrochemical sensor.

Objective To study the anti-inflammatory and analgesic effects of Ski protein overexpression on writing in mice induced by acetic acid.Methods Eight-week-old male ICR mice were administered 0.7%acetic acid solution(0.1 mL/10 g)to induce a writhing reaction.The mice were divided into sham,acetic acid,acetic acid+ibuprofen,acetic acid+ad-EGFP,acetic acid+ad-ski-1,acetic acid+ad-ski-2,and acetic acid+sulfasalazine groups(n=10 mice per group).The time to the first appearance of twisting and the number of twists within 15 min were recorded.Small intestine tissues were removed to identify the effect of adenovirus transfection and to detect protein expression levels of pro-inflammatory factors and pain biomarkers and protein expression of nuclear factor(NF)-κB p65 and its binding with Ski protein.Results Ski protein was successfully overexpressed in small intestine after intraperitoneal injection of Ad-ski adenovirus.Overexpressed Ski protein delayed the start and decreased the frequency of writhing,comparable to ibuprofen(P＞0.05).Groups in which ski protein was overexpressed showed significantly inhibited protein expression of pro-inflammatory factors and pain biomarkers compared with the acetic acid group(P＜0.05).Moreover,NF-κB p65 formed complexes with Ski.Conclusions Overexpression of Ski protein has anti-inflammatory and analgesic effects on acetic acid-induced inflammatory pain by inhibiting the expression of inflammatory factors and pain biomarkers,via regulation of the NF-κB signaling pathway.

Objective To observe the change in the prevalence of post-traumatic stress disorder(PTSD)1 year after trauma exposure and analyze the risk factors of PTSD 1 year after trauma exposure.Methods Convenience sampling was conducted at the initial outbreak of the coronavirus disease 2019 epidemic and 1 year later,respectively.Participants participated in the anonymous online survey.The survey consisted of 2 self-completed questionnaires:1 collected personal information(gender,age,education level,occupation)and subjective sleep quality;the other is the PTSD checklist(PCL-5)from the Diagnostic and Statistical Manual of Mental Disorders,5th edition.Valid questionnaires of 2 091 and 2 092 were respectively retrieved at the initial stage of trauma exposure and 1 year later.Results The prevalence of PTSD at the initial stage of trauma exposure was 5.3％(111/2 091)and 1 year after trauma exposure was 19.1％(399/2 092).Multiple linear regression analysis showed that age(P＜0.01),gender(P＜0.01),and subjective sleep quality(P＜0.01)were risk factors related to PTSD.Conclusions One year after trauma exposure,the prevalence of PTSD increases.Psychological intervention measures should be given at the early stage of trauma exposure,and special attention should be paid to young individuals,women,and those with sleep disorders.