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 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.

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.

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 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.

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: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 The aim of this study is to investigate the plaque characteristics of different subtypes of middle cerebral artery(MCA)infarction,lenticulostriate artery(LSA)characteristics,and hemodynamic characteristics through high-resolution magnetic resonance vessel wall imaging(HR-MRI VWI)and perfusion weighted imaging(PWI).Methods A retrospective analysis was conducted on patients with unilateral acute or subacute MCA infarction who underwent HR-MRI VWI and PWI examinations at Qinhuangdao First Hospital from January 2022 to April 2024.Patients were divided into three groups according to the type of infarction:artery-to-artery embolism(AA),branch occlusive disease(BOD),branch occlusive disease and artery-to-artery embolism(BOD-AA).Clinical data,plaque characteristics,lenticulostriate artery characteristics,and hemodynamic characteristics were compared and analyzed among the three groups.To determine factors associated with BOD,the BOD and BOD-AA groups were merged into a BOD+group which was then compared with the AA group.To determine factors associated with the AA group,the BOD-AA and AA groups were combined into an AA+group,followed by comparison with the BOD group.Results A total of 42 patients with unilateral acute or subacute MCA infarction were included according to the inclusion and exclusion criteria.Among them,9 patients were classified as having AA,14 patients as having BOD,and 19 as having BOD-AA.The results showed that the degree of stenosis was higher in the AA+group than in the BOD group,and the difference was statistically significant(Z=-2.536,P<0.05);The number of LSA on the affected side was higher in the BOD+group than in the AA group[2.00(1.50,3.00)vs.3.00(3.00,4.00)],and the difference was statistically significant(Z=-2.889,P<0.05);The relative cerebral blood flow(rCBF)of the centrum semiovale was lower in the AA+group than in the BOD group[0.90(0.84,0.93)vs.0.99(0.97,1.03)],and the difference was statistically significant(Z=-4.555,P<0.05);The rCBF in the basal ganglia was lower in the BOD+group than in the AA group[0.89(0.83,0.93)vs.1.01(0.98,1.04)],and the difference was statistically significant(Z=-4.280,P<0.05).Conclusion Patients in BOD+have a lower degree of stenosis compared to AA group.The spatial relationship between plaques and LSA varies across different subtypes of MCA infarction.Plaques in BOD+patients are positioned closer to the LSA orifice and thus have a higher tendency to occlude the LSA orifice.The affected side has few LSAs and the rCBF in the LSA perfusion area.is lower.

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.