ObjectiveTo understand the surveillance of influenza-like illness (ILI) and influenza vaccination status in Jing’an District, Shanghai, and to provide a basis for optimizing influenza prevention and control strategies. MethodsThe sentinel surveillance data for ILI and virological surveillance data of influenza viruses in Jing’an District were collected from the Chinese influenza surveillance information system, and data for influenza vaccination were collected from Shanghai immunization information system from September 2017 to August 2023. Epidemiological characteristics of ILI, influenza etiology, and the temporal and population distributions of influenza vaccination were analyzed using descriptive epidemiological methods. ResultsILI as a percentage of total visit surveillance units (ILI%) reported by sentinel hospital was increased in Jing’an District of Shanghai from September 2017 to August 2023 (F=18.841, P=0.012). The peak of the influenza cases mainly appeared in winter-spring, but there were two peaks in winter-spring and summer from September 2019 to August 2020, from September 2020 to August 2021, and from September 2021 to August 2022. In particular, there were two peaks in winter-spring from September 2022 to August 2023, with a rebound during the descending process. The average positive rate of ILI was 21.64% (2 421/11 189) during the 6 years. There was a peak in winter-spring during every year with the exception of the period from September 2020 to August 2021. The dominant strains were B/Yamagata and A/H1N1 in winter-spring from September 2017 to August 2018. The dominant strain was A/H1N1 in winter-spring from September 2018 to August 2019 and from September 2022 to August 2023. The dominant strain was B/Victoria in winter-spring from September 2019 to August 2020 and from September 2021 to August 2022. Different subtype strains occurred alternately, and the dominant strains were A/H1N1 and A/H3N2 in recent years. The influenza vaccination coverage was 2.94% from September 2017 to August 2023, and the vaccination coverage was highest in young children. The vaccination coverage for females was higher than that for males (χ²=546.963, P<0.001), and the vaccination coverage for registered residents was higher compared to that for migrants (χ²=123.141, P<0.001). ConclusionILI% exhibits an upward trend in Jing’an District of Shanghai, and the dominant strain is A subtype. The influenza vaccination coverage is still low, which is insufficient to have an impact on the spread of influenza. It is recommended that the surveillance of ILI and variations of influenza virus strains should be improved continuously, and effective steps should be taken to promote influenza vaccination.

Objective To systematically evaluate the radiation impact of radioactive sources used in online elemental analyzers in cement enterprises on the surrounding environment, and to provide a scientific basis for radiation monitoring and safety management at the application sites of this type of radioactive sources. Methods A statistical analysis was conducted on 15 cement enterprises in Guangxi Province using online elemental analyzers with ²⁵²Cf as the radioactive source. On-site investigation of radiation safety management and on-site monitoring of radiation environment were performed, followed by an evaluation based on the collected data. Results Although the gamma radiation ambient dose equivalent rate and neutron ambient dose equivalent rate increased around the sites using online elemental analyzers with ²⁵²Cf as the radioactive source, they all met the requirements of the Radiological Health Protection Requirements for Instruments with Sealed Sources (GBZ 125—2009). Conclusion Under the current usage and management conditions, the application of this type of radioactive sources has controllable radiation impact on the surrounding environment, and will not pose a threat to public health and environmental safety. However, continuous strengthening of radiation safety management measures and regular radiation monitoring work are still needed to ensure the safe use of radioactive sources, further reducing potential radiation risks and providing strong guarantees for the safe application of radioactive sources in online elemental analyzers in cement enterprises.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Hepatic steatosis can be observed in chronic liver diseases of different etiologies. The main predisposing factors for hepatic steatosis include chronic viral hepatitis， cholestatic liver disease， alcoholic liver disease， and nonalcoholic fatty liver disease. Simple fatty liver disease is the initial manifestation of hepatic steatosis， followed by steatohepatitis， liver fibrosis， liver cirrhosis， and even hepatocellular carcinoma. With the development of medical imaging technology， magnetic resonance imaging-proton density fat fraction （MRI-PDFF） has been widely used in the diagnosis of fatty liver disease （FLD） in clinical practice. MRI-PDFF is gradually becoming the gold standard for the noninvasive diagnosis of FLD due to its high accuracy and good repeatability. This article reviews the clinical application of MRI-PDFF in liver fat quantification and related research advances.

Aim To establish a stable hepatic stellate cell ( HSC ) -specific G protein-coupled receptor kinase 2 ( GRK2 ) knockout mice and provide the important animal model for further studying the biological function of GRK2 in HSC. Methods The loxP-labeled Grk2 gene mouse (Grk2

Twelve compounds were isolated from the ethyl acetate fraction of the 80% aqueous ethanol extract of the roots and stems of Dalbergia rimosa Roxb. by silica gel, MCI, Sephadex LH-20 column chromatography, and semi-preparative HPLC. Their structures were identified by spectral analysis such as UV, IR, MS, 1D/2D NMR and by comparison with literature information as dalbergiquinol A (1), dalbergiquinol B (2), R-(-)-3′-hydroxy-2,4,5-trimethoxydalbergiquinol (3), neokhriol A (4), mucronulatol (5), (3R)-7,2′,3′-trihydroxy-4′-methoxy-isoflavane (6), isomucronulatol (7), (3S)-violanone (8), 3′-O-methylviolanone (9), eryvarin M (10), (±)-α,3,4,2′,4′-pentahydroxydihydrochalcone (11) and (-)-butin (12). Compound 1 and 2 are new compounds, and compounds 3-12 were isolated from this plant for the first time. Compounds 1, 2, 4, 6, 8, 11, 12 showed good scavenging effect on DPPH free radical.

The analysis of ammonia nitrogen in real water samples is challenging due to matrix interferences and difficulties for rapid on-site analysis.On the basis of the standard method,i.e.water quality-determination of ammonia nitrogen-salicylic acid spectrophotometry(HJ 536-2009),a simple device for online detecting ammonia nitrogen was developed using a sequential injection analysis(SIA)system in this work.The ammonia nitrogen transformation system,color reaction system,and detection system were built in compatible with the SIA system,respectively.In particular,the detection system was assembled by employing light-emitting diode as the light source,photodiode as the detector,and polyvinylchloride tube as the cuvette,thus significantly reducing the volume,energy consumption and fabricating cost of the detection system.As a result,the accurate analysis of ammonia nitrogen in complex water samples was achieved.A quantitative detection of ammonia nitrogen in water sample was obtained in 12 min,along with linear range extending to 1000 μmol/L,precisions(Relative standard deviation,RSD)of 4.3%(C=10 μmol/L,n=7)and 4.2%(C=500 μmol/L,n=7),and limit of detection(LOD)of 0.65 μmol/L(S/N=3,n=7).The results of interfering experiments showed that the detection of ammonia nitrogen by the developed device was not interfered by the common coexisting ions and components,therefore the environmental water could be directly analyzed,such as reservoir water,domestic sewage,sea water and leachate of waste landfill.The analytical results were consistent with those obtained by the environmental protection standard method(Water quality determination of ammonia nitrogen-salicylic acid spectrophotometry,HJ 536-2009).In addition,the spiking recoveries were in the range of 92.3%-98.1%,further confirming the accuracy and practicality of the developed device.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

Obiective Alzheimer’s disease (AD) is a degenerative disease of the central nervous system (CNS) caused by a variety of risk factors. There are various pathological changes, but apoptosis of the neurological meridian cells is one of the most important pathological bases. Hyperlipidemia is a high-risk factor for the development of AD, which can lead to increased levels of oxidized low-density lipoprotein (ox-LDL) in brain tissues. PCSK9 is a protease closely related to lipid metabolism, but studies have shown that it may be related to the development of AD. LRP1 is abundantly expressed in neuronal cells, and it is an important transporter for the clearance of Aβ. There is now a large amount of literature confirming that PCSK9 can induce the degradation of LRP1. PI3K/AKT is an important signaling pathway in vivo, which plays an important role in apoptosis, and there is now a large amount of literature confirming that LRP1 activates the PI3K/AKT pathway, which has an anti-apoptotic effect. So can PCSK9 affect the PI3K/AKT pathway through LRP1 and thus regulate neuronal apoptosis? This deserves further investigation.The aim of this study was to explore the role of PCSK9 in mediating ox-LDL pro-apoptotic neuronal cell death and its mechanism, and then further elaborate the mechanism of hyperlipidemia leading to neurodegenerative diseases such as AD. MethodsFirstly, PC12 cells were treated with different concentrations of ox-LDL (0, 25, 50, 75 and 100 mg/L) for 24 h. Oil red O staining was used to detect lipid accumulation in PC12 cells, Hoechst33258 staining and flow cytometry to detect apoptosis in PC12 cells, ELISA to detect the content of Aβ secreted by PC12, Western blot to detect expression of SREBP2, PCSK9 and LRP1. Then PC12 cells were treated with 75 mg/L ox-LDL for different times (0, 6, 12, 24, 48 h), and Western blot were performed to detect the expression of SREBP2, PCSK9 and LRP1. Finally, after transfecting 100 nmol/L PCSK9 siRNA into PC12 cells for 48 h, PC12 cells were treated with 75 mg/L ox-LDL for 24 h, Hoechst33258 staining and flow cytometry to detect apoptosis rate of PC12 cells, and Western blot to detect PCSK9, LRP1, PI3K, AKT, P-PI3K , P-AKT, NF-κB, Bcl-2, Bax, Caspase-9 and Caspase-3 expression, and ELISA detected Aβ content secreted by PC12 cells. Resultsox-LDL increased lipid accumulation and promoted apoptosis and Aβ secretion in PC12 cells, as well as increasing the expression of SREBP2 and PCSK9 and decreasing the expression of LRP1 in PC12 cells. pCsk9 siRNA could be inhibited through the PI3K/AKT pathway and the NF-κB-Bcl-2/Bax-Caspase-9/3 pathway to inhibit ox-LDL-induced apoptosis in PC12 cells while increasing Aβ secretion in PC12 cells. Conclusionox-LDL plays a bidirectional regulatory role in ox-LDL-induced apoptosis of PC12 cells by inducing an increase in PCSK9 expression and a decrease in LRP1 expression in PC12 cells, which in turn affects different signaling pathways downstream.

Immunoassays are widely used in medicine, food, environment and other fields due to having the advantages of simpleness, rapidness and accuracy. Combining immunoassays with nanomaterials can improve the performance of immunoassays. Compared with traditional nanomaterials, upconversion nanoparticles (UCNPs) have excellent optical properties such as good photostability, long luminescence lifetime and narrow and tunable emission bands, which can significantly reduce background noise and improve analytical sensitivity when combined with immunoassay. This paper briefly introduces the luminescence mechanism of UCNPs, summarizes the synthesis and surface modification methods of UCNPs. And then 5 UCNPs-based immunoassay techniques, namely, fluorescence resonance energy transfer, inner filter effect, magnetic separation technique, upconversion-linked immunosorbent assay and upconversion immunochromatography, are discussed in detail. These sensing protocols of UCNPs-based immunoassays have been successfully utilized to detect various targets, including small molecules, macromolecules, and pathogens, all of which closely related to food safety, human health, and environmental pollution. Finally, the challenges and prospects of this technique are summarized and prospected. Although the UCNPs immunoassays based on antibodies and antigens have made great progress, most of the research is still in the stage of laboratory, and there is a long way to go to realize its social applications. There is a series of challenges need to be overcome. (1) Designing excellent water soluble and dispersive upconversion nanomaterials is needed. Hydrophilic ligands are bound to smaller upconversion nanoparticles and removing hydrophobic surface ligands are the most widely used methods to improve solubility and dispersity. (2) Multi-detection technology platforms and multi-mode simultaneous detection platforms have great potential, which will improve the efficiency of point of care detection. (3) The researchers also need to focus on some important problems. For examples, the upconversion luminescence efficiency of UCNPs is difficult to maintain, the synthesis method is complex, and the surface modification degree and functionalization are difficult to control.