AIM:To analyze the efficacy of modified Zhujing formula combined with intravitreal ranibizumab(IVR)injection in the treatment of wet age-related macular degeneration(wARMD).METHODS: A prospective study was conducted on wARMD patients at the Ophthalmology Department of Yulin Hospital of Traditional Chinese Medicine from September 2022 to October 2024. The study subjects were divided into the experimental group and the control group according to the random number table method. The control group received IVR treatment, while the experimental group was treated with modified Zhujing formula in addition to IVR injection. The clinical efficacy, TCM symptom scores, central retinal thickness(CRT), best corrected visual acuity(BCVA), macular hemorrhage area, choroidal neovascularization area(CNV), ocular hemodynamic parameters [resistance index(RI), maximum diastolic blood flow(EDV), maximum systolic blood flow(PSV)], and 1-year recurrence rate were compared between the two groups.RESULTS: This study included 60 eyes from 60 wARMD patients. Among them, the control group consisted of 30 patients and 30 eyes, while the experimental group consisted of 30 patients and 30 eyes. The age of the control group was 67.52±3.12 y, with 17 males and 13 females. The age of the experimental group was 67.62±3.04 y, with 18 males and 12 females.The clinical efficacy of the experimental group(97%)was higher than that of the control group(73%)(P<0.05). After treatment, the scores of blurred vision, soreness and weakness of the waist and knees, restlessness and insomnia, dizziness and tinnitus in the experimental group were all lower than those in the control group(all P<0.05); the EDV and PSV in the experimental group were both higher than those in the control group(both P<0.05); the BCVA, CRT, macular hemorrhage area, CNV and RI of the experimental group were all lower than those of the control group(all P<0.05), and the 1-year recurrence rate in the experimental group(3%)was lower than that in the control group(27%)(P<0.05). CONCLUSION:The combined use of modified Zhujing formula and IVR can effectively alleviate symptoms such as blurred vision and retinal hemorrhage in wARMD patients, improve vision and ocular hemodynamic conditions, and reduce the recurrence rate. This suggests that there may be a synergistic enhancing effect.

Objective To explore the mediating role of intolerance of uncertainty(IU)and moderating role of the negative emotion differentiation in the influence of perceived stress on anxiety among college students from a cognitive perspective.Methods A total of 271 participants were surveyed using the perceived stress scale,intolerance of uncertainty scale,depression anxiety and stress scale(Chinese version),and the test on negative emotional differentiation.SPSS 22.0 was used to perform descriptive statistics and correlation analyses and to test the moderated mediation model.Results Perceived stress affected anxiety and IU played a mediating role-perceived stress could affect anxiety through influencing IU.At the same time,the influence of IU on anxiety could be adjusted through the negative emotion differentiation.The higher the degree of negative emotion differentiation,the lower the degree of anxiety increase(β=0.17,t=5.70,P＜0.01).Conclusion It may be effective to develop training programs to reduce anxiety by regulating perceived stress,increasing acceptance of uncertainty,and improving the negative emotion differentiation,which can help individuals reduce anxiety by perceiving and adjusting anxiety-related emotional or cognitive factors in a timely manner.

Infectious diseases continue to pose a threat to global public health. Successive global shocks caused by emerging and re-emerging pathogens have continuously challenged existing surveillance systems, highlighting the urgent need to build efficient and precise pathogen surveillance networks. Pathogen genomic databases have been developed rapidly in recent two decades, significantly improving the molecular identification, evolutionary analysis, and transmission tracking of pathogens, and changing disease surveillance strategies and patterns. This paper summarizes the developmental history and current state of pathogen genomic databases, and discusses their applications in public health, including pathogen variation surveillance, emerging or suspected pathogen identification, and epidemiological tracing. Furthermore, this paper systematically analyzes the limitations and key challenges faced by current global health prevention and control system, and suggests the focus of the development of online pathogen databases to address existing shortcomings, ultimately improve global infectious disease surveillance and early warning

Objective The aim of this study is to discuss the causal relationship between periodontal disease(PD)and prostate cancer(PCa).Methods A two-sample bidirectional Mendelian randomization(MR)analysis based on publicly statistical data from genome-wide association studies(GWAS)was conducted.MR Egger,weighted medium,simple mode and weighted mode were supplemented,while inverse variance weighted analysis(IVW)was the main method of analysis.Heterogeneity testing,pleiotropy testing and leave-one-out testing were used to assess the sensitivity and stabili-ty.Results The results of MR analysis showed that PD had no significant impact on the occurrence of PCa:East Asian(IVW,PD:OR=1.07,P=0.48);European(IVW,PD:OR=1.00,P=0.37,periodontitis:OR=1.03,P=0.14,chronic gingivitis:OR=0.99,P=0.37,chronic periodontitis:OR=1.03,P=0.22).The reverse MR analysis also did not show a causal relationship between PCa and PD:East Asian(IVW,PD:OR=0.97,P=0.22);European(IVW,PD:OR=0.84,P=0.44,periodontitis:OR=1.01,P=0.75,chronic gingivitis:OR=0.93,P=0.23,chronic periodontitis:OR=0.99,P=0.80).The results of other analysis were consistent with those of IVW analysis.Conclusions The results of our two-sample bidirectional MR analysis do not support a causal relationship between PD and PCa.

Objective To analyze the characteristics of facial and tongue chromaticity parameters in patients with gastrointestinal tumors by setting the inspection image characteristics of patients with gastrointestinal tumors as the main research content;To establish an auxiliary diagnostic model for gastrointestinal tumors.Methods One-way ANOVA,t-test,Mann-whitney U test,canonical correlation analysis and Spearman statistical methods were used to analyze the characteristics of inspection image indexes and correlation of tumor markers of the 391 cases in the control group and 359 patients with gastrointestinal tumors.Machine learning methods such as SVM,Random Forest,KNN,Naive Bayes,XG Boost and Ada Boost were used to establish an auxiliary diagnostic model for gastrointestinal tumors.Results In terms of facial indicators,there were differences in F-R,F-G and F-B indicators among the control group,early-stage gastrointestinal cancer patients,and mid-to late-stage gastrointestinal cancer patients,in the comparison of tongue features among,TC-L,TB-L and TB-a of the control group,patients with early gastrointestinal tumors,and patients with intermediate and advanced gastrointestinal tumors showed a gradual downward trend;the AUC of the auxiliary diagnosis model of gastrointestinal tumor disease based on the chromaticity parameters of face tongue image constructed by Ada Boost algorithm was 0.930.Conclusion The auxiliary diagnostic model of gastrointestinal diseases constructed by facial and tongue images has good diagnostic effect,which can provide objective data support for in-depth exploration of the complex relationship between diagnosis and disease.

Objective To study the compliance and influencing factors of inhalation therapy in patients with stable chronic obstructive pulmonary disease (COPD),and carry out patient education and management accordingly. Methods COPD patients were selected from respiratory clinic of Luodian Hospital of Baoshan District of Shanghai from June to December in 2021. Compliance and inhalation techniques were assessed with the Morisky Medication Adherence Scale and the ten-step inhalation technique, and the factors influencing compliance were analyzed. Results A total of 58 outpatients with COPD were included, in which 25 cases (43.1%) with moderate or above compliance. Univariate analysis showed that the patients with course of disease ≥5 years, COPD assessment test(CAT)≥10 points, used 2 inhalation devices and inhalation technique score ≥8 points had better compliance when compared with other patients (P<0.05). Conclusion Patient education and management should be carried out actively. The patients with course of disease<5 years, CAT<10 points should be highly concerned. The inhalation devices should be chosen according to the patients' condition. Training on the use of devices should be strengthened and regularly follow-up evaluation should be carried out.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective To analyze the antiviral effect of molnupiravir against influenza virus in vitro and in vivo.Methods The antiviral ability of molnupiravir against influenza virus strain H1N1 PR8 was detected in vitro and in vivo.H uman non-small cell lung cancer cell line(A549 cells)was used as an in vitro model of PR8 infection.The antiviral effects of molnupiravir on virus replication,protein synthesis,and viral particle formation were analyzed using real-time fluorescence quantitative polymerase chain reaction(qRT-PCR),Western blot(WB)assay,and plaque assay.PR8 nose-dripping infected C57BL/6 female mice were used as an in vivo infection model.The antivi-ral ability of molnupiravir was evaluated by detecting viral load,pathological changes,and immunohistochemistry in the control group,administration group,inoculation group,and inoculation-administration group.Results In vitro test results showed that molnupiravir had no significant inhibitory effect on influenza virus replication,protein syn-thesis,and virus particle formation(all P＞0.05).In vivo test results showed that compared with mice infected with H1N1 alone,the viral load in the lung tissue of mice treated with molnupiravir declined significantly,and the extent of pathological changes was milder.Immunohistochemical detection showed a significant weakening in nuclear protein(NP)antigen signal,and the expression levels of interferon(IFN)-α,interleukin(IL)-4,and IL-6 in the lungs were lower(all P＜0.01).Conclusion As a precursor with antiviral activity,molnupiravir can not exert anti-viral activity in lung-derived cells cultured in vitro,but can be transformed into an active form in the host,which significantly decreases the ability of H1N1 influenza virus to proliferate in the lungs and thereby alleviates the da-mage of virus to lung tissue.