Aim To screen and study the expression of long non-coding RNA (IncRNA) in rats with middle cerebral artery occlusion (MCAO) with MCAO treated with Tao Hong Si Wu decoction (THSWD) and determine the possible molecular mechanism of THSWD in treating MCAO rats. Methods Three cerebral hemisphere tissue were obtained from the control group, MCAO group and MCAO + THSWD group. RNA sequencing technology was used to identify IncRNA gene expression in the three groups. THSWD-regulated IncRNA genes were identified, and then a THSWD-regu-lated IncRNA-mRNA network was constructed. MCODE plug-in units were used to identify the modules of IncRNA-mRNA networks. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) were used to analyze the enriched biological functions and signaling pathways. Cis- and trans-regulatory genes for THSWD-regulated IncRNAs were identified. Reverse transcription real-time quantitative pol-ymerase chain reaction (RT-qPCR) was used to verify IncRNAs. Molecular docking was used to identify IncRNA-mRNA network targets and pathway-associated proteins. Results In MCAO rats, THSWD regulated a total of 302 IncRNAs. Bioinformatics analysis suggested that some core IncRNAs might play an important role in the treatment of MCAO rats with THSWD, and we further found that THSWD might also treat MCAO rats through multiple pathways such as IncRNA-mRNA network and network-enriched complement and coagulation cascades. The results of molecular docking showed that the active compounds gallic acid and a-mygdalin of THSWD had a certain binding ability to protein targets. Conclusions THSWD can protect the brain injury of MCAO rats through IncRNA, which may provide new insights for the treatment of ischemic stroke with THSWD.

Nonalcoholic fatty liver disease （NAFLD） is a multisystem disease associated with obesity， insulin resistance， and dyslipidemia and has a complex pathogenesis. Studies have shown that gut microbiota dysbiosis is closely associated with the onset of NAFLD， and traditional Chinese medicine treatment can improve the laboratory markers and clinical symptoms of NAFLD patients by regulating intestinal microbiota and its metabolites. This article elaborates on the association between NAFLD and gut microbiota， the involvement of gut microbiota dysbiosis in the pathogenesis of NAFLD， and the possible mechanism of traditional Chinese medicine treatment in improving NAFLD from the perspective of gut microbiota， in order to provide new ideas for the treatment of NAFLD.

Human physiological indicators have become an important standard for assessing health in modern society.Traditional detection methods often require a separate laboratory,complex operation process and long detection time,so it is urgent to develop portable,fast and accurate on-site detection technologies for bioanalysis.Point-of-care testing(POCT),which differs from traditional laboratory testing,can realize the rapid in situ detection of biomarkers without the complicated analytical process of the laboratory.Smartphones,which are an essential tool in our daily life,not only have independent operating systems and built-in storage functions,but also have high-definition cameras,which have great application potential in POCT visualization.The combination of various biosensing technologies and smartphones has developed into a new direction in the field of POCT.This review mainly introduced the research progress of smartphone-based visual biosensors in POCT in recent years,including colorimetric sensors,fluorescence sensors,chemiluminescence sensors and electrochemiluminescence sensors.Finally,the problems faced by smart-phone-based visual biosensors in the application of POCT were summarized,and their future development was prospected.

OBJECTIVE To evaluate the cost-effectiveness of ivabradine in the treatment of chronic heart failure （CHF） in the context of “Quadruple Therapy” from the perspective of the health system. METHODS Based on real-world cohort data， the Markov model was constructed according to the natural progression of CHF， with a cycle time of 3 months， a study timeframe of 20 years， and a discount rate of 5%. Using quality-adjusted life year （QALY） and incremental cost-effectiveness ratios （ICER） as the output indexes， the cost-utility analysis was used to evaluate the cost-effectiveness of ivabradine in combination with the “Quadruple Therapy” regimen， compared with the “Quadruple Therapy” regimen for the treatment of CHF， and the robustness of the results of the base analysis was verified by univariate sensitivity analysis and probabilistic sensitivity analysis. RESULTS The results of the base analysis showed that the ICER of ivabradine combined with the “Quadruple Therapy” regimen was 165 065.54 yuan/QALY， compared with the “Quadruple Therapy” regimen， which was lower than the willingness-to-pay （WTP） threshold （257 094 yuan/QALY） based on 3 times of China’s gross domestic product （GDP） per capita in 2022. The results of the univariate sensitivity analysis showed that the discount rate had the greatest impact on the robustness of the model. The probabilistic sensitivity analysis showed that the probability that the ivabradine combined with the “Quadruple Therapy” regimen was cost-effective under the WTP threshold in this study was 59.50%. CONCLUSIONS When using 3 times China’s 2022 GDP per capita （257 094 yuan/ QALY） as the WTP threshold， the combination of ivabradine and the “Quadruple Therapy” regimen for treating CHF is cost- effective.

To explore the application of humanistic care in children's fever clinics,the children's fever clinics of Guangzhou Women and Children's Medical Center conducted relevant research using narrative medicine as a guiding concept.This paper elaborated on the medical humanistic dilemmas and narrative care needs in children's fever clinics,and focused on exploring the practice paths of narrative medicine in pediatric with Chinese characteristics from five dimensions,including the cultivation of nursing staff's abilities of professional narrative and humanistic care,the establishment of health lectures featuring narrative patient education,the alleviation of medical anxiety for children and their families,related support of narrative nursing,and caring services.The aim was to improve the narrative care ability of nurses in children's fever clinics,develop methods for pediatric patients that can eliminate the fear of seeking medical treatment,and protect children's physical and mental health.A carrier of care,support,and emotional expression can be provided for parents.The foundation for nursing staff to achieve professional growth through narrative reflection can be laid.Thus,it can assist in establishing a life narrative community relationship between doctors and patients,and jointly explore the meaning of life.

Objective To evaluate the efficacy and safety of brexpiprazole in treating acute schizophrenia.Methods Patients with schizophrenia were randomly divided into treatment group and control group.The treatment group was given brexpiprozole 2-4 mg·d-1 orally and the control group was given aripiprazole 10-20 mg·d-1orally,both were treated for 6 weeks.Clinical efficacy of the two groups,the response rate at endpoint,the changes from baseline to endpoint of Positive and Negative Syndrome Scale(PANSS),Clinical Global Impression-Improvement(CGI-S),Personal and Social Performance scale(PSP),PANSS Positive syndrome subscale,PANSS negative syndrome subscale were compared.The incidence of treatment-related adverse events in two groups were compared.Results There were 184 patients in treatment group and 186 patients in control group.After treatment,the response rates of treatment group and control group were 79.50％(140 cases/184 cases)and 82.40％(150 cases/186 cases),the scores of CGI-I of treatment group and control group were(2.00±1.20)and(1.90±1.01),with no significant difference(all P＞0.05).From baseline to Week 6,the mean change of PANSS total score wese(-30.70±16.96)points in treatment group and(-32.20±17.00)points in control group,with no significant difference(P＞0.05).The changes of CGI-S scores in treatment group and control group were(-2.00±1.27)and(-1.90±1.22)points,PSP scores were(18.80±14.77)and(19.20±14.55)points,PANSS positive syndrome scores were(-10.30±5.93)and(-10.80±5.81)points,PANSS negative syndrome scores were(-6.80±5.98)and(-7.30±5.15)points,with no significant difference(P＞0.05).There was no significant difference in the incidence of treatment-related adverse events between the two group(69.00％vs.64.50％,P＞0.05).Conclusion The non-inferiority of Brexpiprazole to aripiprazole was established,with comparable efficacy and acceptability.

Objective To evaluate the application of three deep learning algorithms in automatic segmentation of clinical target volumes (CTVs) in high-dose-rate brachytherapy after surgery for endometrial carcinoma. Methods A dataset comprising computed tomography scans from 306 post-surgery patients with endometrial carcinoma was divided into three subsets: 246 cases for training, 30 cases for validation, and 30 cases for testing. Three deep convolutional neural network models, 3D U-Net, 3D Res U-Net, and V-Net, were compared for CTV segmentation. Several commonly used quantitative metrics were employed, i.e., Dice similarity coefficient, Hausdorff distance, 95th percentile of Hausdorff distance, and Intersection over Union. Results During the testing phase, CTV segmentation with 3D U-Net, 3D Res U-Net, and V-Net showed a mean Dice similarity coefficient of 0.90 ± 0.07, 0.95 ± 0.06, and 0.95 ± 0.06, a mean Hausdorff distance of 2.51 ± 1.70, 0.96 ± 1.01, and 0.98 ± 0.95 mm, a mean 95th percentile of Hausdorff distance of 1.33 ± 1.02, 0.65 ± 0.91, and 0.40 ± 0.72 mm, and a mean Intersection over Union of 0.85 ± 0.11, 0.91 ± 0.09, and 0.92 ± 0.09, respectively. Segmentation based on V-Net was similarly to that performed by experienced radiation oncologists. The CTV segmentation time was < 3.2 s, which could save the work time of clinicians. Conclusion V-Net is better than other models in CTV segmentation as indicated by quantitative metrics and clinician assessment. Additionally, the method is highly consistent with the ground truth, reducing inter-doctor variability and treatment time.

italic>Polygonum capitatum is a characteristic Miao medicine in Guizhou, commonly used in clinical practice to treat gastrointestinal and urinary tract infections. Research has found that it has good antibacterial and anti-inflammatory effects, and its main active ingredient is flavonoids. Lavonoid O-methyltransferase (FOMT) is a key enzyme for oxymethylation modification of flavonoid compounds. In order to understand the function and properties of FOMT protein in Polygonum capitatum, the transcriptome was sequenced by Illumina HiSeq 4000 high throughput sequencing technology. Then, the obtained transcripts were annotated and analyzed, and the whole genome of the FOMT gene family in Polygon capitalis was mined and identified. A total of 99 298 Unigenes were obtained, of which 71 514 were successfully annotated by the public database. In the genome of Polygonum capitatum, a total of 50 FOMT genes were identified. The phylogenetic tree showed that FOMT genes were divided into two subfamilies: caffeoyl CoA O-methyltransferase (CCoAOMT) and caffeic acid O-methyltransferase (COMT). Gene sequence analysis showed that the number of FOMT encoded amino acids ranged from 99 to 1 053 aa, the molecular weight ranged from 11 224.91 to 86 687.42 Da, and the isoelectric point ranged from 4.79 to 9.45. The 50 FOMT family members were hydrophobic proteins. Subcellular localization results showed that 54% of FOMT subfamily CCoAOMT and COMT members were located in cytoplasm and 28% were located in chloroplasts. The FOMT gene was tissue specific and highly expressed in the flowers of Polygonum capitatum, followed by the stems, and the least expressed in the roots. In this study, the FOMT gene family of Polygonum capitatum was identified and analyzed to provide theoretical basis for further study of FOMT function and biosynthesis of methylated flavonoids.

Formaldehyde is a prevalent organic solvent in industrial and indoor environment,which can seriously harm human health,so it is of great significance to develop highly sensitive formaldehyde sensors with fast response,low detection limit and long life.In this study,the NiO-In2O3 composite structure was prepared using indium-based metal organic framework(In-MOF)as the precursor,and the formaldehyde gas sensor was constructed with In2O3 and NiO-In2O3 composite structure as the sensitive material.The results demonstrated that the In2O3 material had a microflower-like structure,while the NiO-In2O3 composite structure was composed of NiO nanoparticles attached to the surface of In2O3.The sensor exhibited excellent detection performance for formaldehyde in the environment of relative humidity of 33%and 75%,especially the response characteristic of the NiO-In2O3 composite structure sensor to formaldehyde was considerably better than that of the In2O3 sensor under the same test conditions,which was closely related to the catalytic effect of NiO and the heterogeneous structure formed between NiO and In2O3.The NiO-In2O3 composite structure sensor had a response value of 21.3 and 12.6 to 10 μL/L formaldehyde when the relative humidity was 33%and 75%at 200℃.The response/recovery time was 4/6 s and 7/10 s,and the limit of detection(LOD)was 1.2×10-7 μL/L and 4.1×10-5 μL/L respectively.Meanwhile,the sensor had excellent selectivity and long-term stability.This sensor showed a wide application prospect in the field of high-performance detection of low concentration of formaldehyde gas.

Objective To construct an artificial intelligence assisted diagnosis model based on deep learning for dynamically recognizing gastric lesions and their locations under gastroscopy in real time,and to evaluate its ability to detect and recognize gastric lesions and their locations.Methods The gastroscopy videos of 104 patients in our hospital was retrospectively analyzed,and the video frames were manually annotated.The annotated picture frames of lesion category were divided into the training set and the validation set according to the ratio of 8∶2,and the annotated picture frames of location category were divided into the training set and the validation set according to the patient sources at the ratio of 8∶2.These sets were utilized for training and validating the respective models.YoloV4 model was used for the training of lesion recognition,and ResNet152 model was used for the training of location recognition.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value and location recognition accuracy of the auxiliary diagnostic model were evaluated.Results A total of 68 351 image frames were annotated,with 54 872 frames used as the training set,including 41 692 frames for lesion categories and 13 180 frames for location categories.The validation set consisted of 13 479 frames,comprising 10 422 frames for lesion categories and 3 057 frames for location categories.The lesion recognition model achieved an overall accuracy of 98.8%,with a sensitivity of 96.6%,specificity of 99.3%,positive predictive value of 96.3%,and negative predictive value of 99.3% in validation set.Meanwhile,the location recognition model demonstrated an top-5 accuracy of 87.1% .Conclusion The artificial intelligence assisted diagnosis model based on deep learning for real-time dynamic recognition of gastric lesions and their locations under gastroscopy has good ability in lesion detection and location recognition,and has great clinical application prospects.