Objective To analyze the characteristics of viral hepatitis mortality and life loss among residents in Pudong New Area from 2003 to 2023, and to provide a basis for related prevention and control work. Methods Viral hepatitis mortality data were obtained from the Pudong New Area mortality monitoring system. The crude mortality rate (CMR), standardized mortality rate (SMR), potential years of life lost (PYLL), average years of life lost (AYLL), and standardized potential years of life lost (SPYLL) were calculated to analyze viral hepatitis deaths. The average annual change (AAPC) and annual percentage change (APC) of the mortality rate were calculated by Joinpoint regression analysis to analyze the trend of mortality. Results The CMR and SMR of viral hepatitis among residents in Pudong New Area from 2003 to 2023 were 3.89/100000 and 1.98/100000, respectively. Both CMR and SMR of viral hepatitis showed a decreasing trend over time (CMR:APC=-5.476, t=-13.581, P<0.001; SMR:APC=- 7.624, t= -21.253, P<0.001). The CMR for males was 4.75/100000 and the SMR for males was 2.65/100000; the CMR for females was 3.04/100000 and the SMR for females was 1.32/100000, with a higher mortality rate for males than for females（Z_CME=12.094，P<0.001; Z_SMR=-14.718，P<0.001). Deaths were concentrated in the age groups of 45-64 years old and 65 years old and above, accounting for 91.62% of the total deaths. The PYLL of deaths due to viral hepatitis among residents in Pudong New Area from 2003 to 2023 was 26912 person-years, with a PYLLR of 0.45% and an AYLL of 8.88 years per person. Conclusion The mortality rate of viral hepatitis among the residents of Pudong New Area in 2003-2023 shows a decreasing trend over time. The mortality rate of males is higher than that of females, and the deaths of middle-aged and elderly people account for a large proportion of the total deaths. Chronic hepatitis B is the main cause of death.

ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Tumor immune homeostasis is a dynamic equilibrium state in which the body removes abnormal mutated cells in time to prevent tumor development without damaging other normal cells under the surveillance of the immune system. It is an important concept to understand the process of tumor development. Programmed cell death （PCD） is a kind of regulable cell death including various forms such as apoptosis， autophagy， pyroptosis， necrosis， and ferroptosis. It is regarded as an important way for the body to remove abnormal or mutated cells. In recent years， modern research has found that PCD has a bi-directional regulatory effect on carcinogenesis and tumor development. In the early stage of tumor formation， PCD can control tumor development in time by playing a specific immune clearance role， while in the later tumorigenic stage， PCD can promote the growth and development of tumor cells by forming a tumor-specific microenvironment， resulting in carcinogenic effects. Therefore， PCD is regarded as an important way to maintain tumor immune homeostasis. Based on the idea of ''supporting the vital Qi and cultivating the root'' by professors Yu Guiqing and Piao Bingkui， the team proposed the theory of ''regulating Qi and resolving toxins'' and applied it to clinical tumor prevention and treatment. Based on the theory of ''regulating Qi and resolving toxins''， the research summarized the current progress of modern medical research on mechanisms related to PCD to explore the role of PCD in the regulation of tumor immune homeostasis. The article believed that the harmonious state of Qi movement was the basic condition for normal PCD to maintain tumor immune homeostasis， while the disorder of Qi movement and the evolution of tumor toxicity were the core processes of abnormal PCD and disorder of tumor immunity homeostasis， which led to the escape and development of tumor cells. Therefore， under the guidance of ''regulating Qi and removing toxins''， the idea of full-cycle prevention and treatment of tumors was proposed summarily. In the early stage of tumor formation， the method of ''regulating Qi movement and strengthening vital Qi'' was applied to reestablish tumor immune homeostasis and to promote the elimination of abnormal cells. In the late tumorigenic stage， the method of ''resolving toxins and dispelling evils'' was applied to reverse the specific microenvironment of tumors and inhibit the development of tumor cells， with a view to providing new theoretical support for the prevention and treatment of tumors through traditional Chinese medicine.

Tumor immune homeostasis is a dynamic equilibrium state in which the body removes abnormal mutated cells in time to prevent tumor development without damaging other normal cells under the surveillance of the immune system. It is an important concept to understand the process of tumor development. Programmed cell death （PCD） is a kind of regulable cell death including various forms such as apoptosis， autophagy， pyroptosis， necrosis， and ferroptosis. It is regarded as an important way for the body to remove abnormal or mutated cells. In recent years， modern research has found that PCD has a bi-directional regulatory effect on carcinogenesis and tumor development. In the early stage of tumor formation， PCD can control tumor development in time by playing a specific immune clearance role， while in the later tumorigenic stage， PCD can promote the growth and development of tumor cells by forming a tumor-specific microenvironment， resulting in carcinogenic effects. Therefore， PCD is regarded as an important way to maintain tumor immune homeostasis. Based on the idea of ''supporting the vital Qi and cultivating the root'' by professors Yu Guiqing and Piao Bingkui， the team proposed the theory of ''regulating Qi and resolving toxins'' and applied it to clinical tumor prevention and treatment. Based on the theory of ''regulating Qi and resolving toxins''， the research summarized the current progress of modern medical research on mechanisms related to PCD to explore the role of PCD in the regulation of tumor immune homeostasis. The article believed that the harmonious state of Qi movement was the basic condition for normal PCD to maintain tumor immune homeostasis， while the disorder of Qi movement and the evolution of tumor toxicity were the core processes of abnormal PCD and disorder of tumor immunity homeostasis， which led to the escape and development of tumor cells. Therefore， under the guidance of ''regulating Qi and removing toxins''， the idea of full-cycle prevention and treatment of tumors was proposed summarily. In the early stage of tumor formation， the method of ''regulating Qi movement and strengthening vital Qi'' was applied to reestablish tumor immune homeostasis and to promote the elimination of abnormal cells. In the late tumorigenic stage， the method of ''resolving toxins and dispelling evils'' was applied to reverse the specific microenvironment of tumors and inhibit the development of tumor cells， with a view to providing new theoretical support for the prevention and treatment of tumors through traditional Chinese medicine.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Aim To investigate the therapeutic effects of a newly developed Tadalafil tablets on pathological myocardial hypertrophy induced by abdominal aortic constriction(AAC)in rats,as well as its influence on the activation of the NF-κB signaling pathway in myo-cardial cells.Methods SD rats were randomly divid-ed into 4 groups:the sham operation group(Sham),the model group(AAC),the tadalafil new tablet treat-ment group(N-Tad,5 mg·kg-1),and the positive control drug treatment group(Cialis,10 mg·kg-1g).The AAC model group and treatment group rats under-went blunt dissection and constrictive ligation of the abdominal aorta at the left renal artery branch point during surgery,while the Sham group rats only had their arteries separated without any constrictive liga-tion.Rats in the treatment groups received either N-Tad or Cialis via gavage three days after modeling,while rats in the sham group and the model group re-ceived physiological saline daily for 8 weeks.Small an-imal ultra-high-resolution echocardiography and hemo-dynamic assessment were applied to evaluate left ven-tricular function in each group of rats,and the calcula-tion of the left ventricular mass index was conducted.By employing Western blot and RT-PCR.we assessed the impact of this treatment on the expression of the hy-pertrophy factor atrial natriuretic peptide(ANP),phosphorylated NF-κB p65 protein(p-NF-κB p65),and phosphorylated IκB-α in the left heart tissue of rats and in H9c2 cardiomyocytes.Results Compared to the Sham group,the AAC rats exhibited a significant decrease in left heart function,an increase in left ven-tricular mass index,and a notable increase in ANP and p-p65 expression in the left heart tissue(P＜0.05).Both N-Tad and Cialis treatments could significantly enhance left ventricular function,decrease left ventric-ular mass index,and inhibit the expression of ANP and phosphorylated NF-κB p65 in rats with myocardial hy-pertrophy(P＜0.05).Notably,the therapeutic effect of low-dose N-Tad was comparable to that of high-dose Cialis.At the cellular level,Tadalafil significantly in-hibited the activation of the NF-κB signaling pathway and reduced the expression of associated proteins in H9c2 cardiomyocytes.Conclusions N-Tad can sig-nificantly inhibit p65 and IκB-α phosphorylation,and the activation of the NF-κB signaling pathway,reduce ANP expression,and improve pathological myocardial hypertrophy,as well as mitigate left heart function damage caused by abdominal aortic constriction.