Acute kidney injury (AKI) is a prevalent and life-threatening clinical syndrome characterised by a rapid decline in renal function and diverse pathological etiologies. The condition has been demonstrated to be associated with elevated mortality rates and an increased risk of progression to chronic kidney disease. At present, clinicians depend heavily on conventional functional markers, such as serum creatinine and urine output, for the diagnosis and staging of the disease. It is evident that these conventional indicators characteristically manifest a considerable temporal delay and only undergo modification subsequent to considerable tissue damage. This severely restricts the timeframe for early detection and timely therapeutic intervention. Furthermore, standard markers fail to provide specific biological information regarding the underlying cellular injury mechanisms. The utilisation of advanced probe technologies in molecular imaging offers a robust alternative to overcome these inherent diagnostic limitations.This comprehensive review systematically evaluates recent progress in the design and application of two primary categories of molecular imaging tools for acute kidney disease, specifically reactive probes and enzyme-activated probes. Reactive probes are engineered to specifically interact with redox-active chemical species, including hydrogen peroxide, peroxynitrite, hypochlorous acid, and sulfur dioxide. Because oxidative stress constitutes a primary early event in acute renal tubular damage, these probes enable researchers and clinicians to visualize early cellular injury and radical accumulation well before global renal functional decline becomes evident. We discuss the application of these reactive probes across multiple imaging modalities including fluorescence imaging, magnetic resonance imaging (MRI), positron emission tomography (PET), and photoacoustic techniques. Photoacoustic imaging combines high spatial resolution with deep tissue penetration and has successfully demonstrated the ability to provide diagnostic alerts up to 12 h before any detectable rise in serum creatinine levels. Additionally, specific reactive probes have shown promising translational potential when tested by high-throughput screening in clinical human urine samples. Enzyme-activated probes target the specific catalytic activity of disease-relevant enzymes. These include well-documented renal tubular structural biomarkers such as NAG, GGT, and ALP, along with apoptosis-related caspases and specific nitroreductases. By responding only to enzymatic cleavage, these tools provide highly specific and pathology-directed imaging readouts. Recent structural design strategies in this field have advanced significantly beyond single-enzyme detection. Researchers are now focusing on sophisticated dual-target recognition to minimize background noise, multimodal integration to cross-validate imaging signals, and theranostic applications where probes simultaneously deliver diagnostic feedback and therapeutic agents to injured tissues. Nanotechnology serves as a fundamental enabler for realizing these advanced probe functions. By precisely optimizing nanoparticle parameters such as hydrodynamic size, surface charge, and targeting ligands, researchers can achieve amplified signal output, highly precise kidney delivery, and protection against premature degradation in the systemic circulation. For example, modifying surface charges can significantly enhance the active uptake of nanoprobes by damaged renal tubular epithelial cells.While preclinical probe development has progressed rapidly, moving these technologies into routine clinical practice remains a major challenge. We analyze the translational feasibility and current obstacles from biological, technological, and regulatory perspectives. Although biological targets such as KIM-1, FAP, and ALP have been validated in extensive patient cohorts, practical barriers severely limit their immediate clinical application. These obstacles involve complex changes in in vivo pharmacokinetics. During an acute injury episode, the extreme drop in the glomerular filtration rate alters probe clearance and can cause unwanted systemic accumulation or confusing background imaging signals. Other major hurdles include a lack of comprehensive long-term toxicity data and the absence of standardized manufacturing protocols to ensure batch-to-batch consistency. Future successful translation will require rigorous multi-center clinical studies to confirm the true diagnostic value of these probes over traditional markers. Researchers must also establish strict standardization of imaging procedures and comprehensive safety evaluations. Ultimately, this review provides a thorough reference framework for designing clinically translatable molecular probes and building a precision diagnostic imaging system for acute kidney injury.

Objective To analyze the status of teaching occupational health and occupational medicine course under the background of new medical science, and to construct a semantic knowledge graph to realize the digital teaching reform of the course. Methods i) The literature on teaching research of occupational health and occupational medicine courses published between January 1, 2005 to December 31, 2025 was retrieved through the China National Knowledge Infrastructure. CiteSpace 6.4.R2 and VOSviewer 1.6.20 were used for bibliometric visualization. ii) A knowledge graph system based on Web front-end was constructed using the textbook of Occupational Health and Occupational Medicine (9th ed.), published by People's Medicine Publishing House, as the core data source. Results i) A total of 240 publications related to the teaching in occupational health and occupational medicine courses were included. The overall number of publications showed an upward trend. The research focused on curriculum teaching reform, curriculum-based political education, and digital technology-empowered teaching, forming an interdisciplinary and multi-dimensional research system. The evolution of keywords included three stages: the foundation period (2005-2015), the growth period (2016-2020), and the innovation period (2021-2025). ii) The constructed semantic knowledge graph realizes structural visualization and a dual-mode intelligent question answering agent. A total of four independent navigation modules, including chapter overview, core concept exploration, learning progress details, and relationship network visualization, were used to achieve multidimensional learning pathways. The system requires no installation and supports cross-platform operation, meeting the needs of both teachers and students. It effectively helps students establish systematic knowledge frameworks and enhances interdisciplinary integration ability and learning initiative. Conclusion In the context of new medical science, research on teaching in occupational health and occupational medicine has evolved from a niche field into a research hotspot and entered a stage of high-quality development. The constructed semantic knowledge graph for the Occupational Health and Occupational Medicine course facilitates digital teaching reform in this field and lays a solid foundation for cultivating high-level interdisciplinary occupational health professionals.

BACKGROUND:High-frequency repetitive transcranial magnetic stimulation has garnered significant attention due to its potential non-invasive benefits in modulating brain function.However,no studies have comprehensively analyzed the current research landscape and development trends of this field from a macroscopic perspective.OBJECTIVE:To explore research hotspots,current trends,and emerging frontiers in the field of high-frequency repetitive transcranial magnetic stimulation through visualized analysis.METHODS:Data were collected from the Web of Science Core Collection database from January 1,2014 to November 15,2024.CiteSpace was used for analyzing publication volume,collaborations among countries/regions,institutions and authors,citation analysis of journals and co-cited literature,as well as disciplinary distribution.Additionally,keyword co-occurrence,clustering,and burst analyses were conducted,and visualized knowledge maps were generated.RESULTS AND CONCLUSION:A total of 860 articles were included.The publication volume of high-frequency repetitive transcranial magnetic stimulation showed an overall upward trend from 2014 to 2022,followed by a decline from 2022 to 2024.China had the highest publication volume,while Ghent University ranked as the most productive institution.Universities acted as the most high-output institutions.Chris Baeken from Ghent University was identified as the most prolific author.Collaboration among leading authors and institutions worldwide remained limited.The main research hotspots in this field were associated with keywords such as depression,stroke,neuropathic pain,and Parkinson's disease.Burst keywords focused on mild cognitive impairment,reflecting a diversification in research directions.The overall research activity in high-frequency repetitive transcranial magnetic stimulation continues to rise,with primary focuses on its clinical applications for psychiatric and neurological disorders,as well as explorations of its underlying mechanisms.Future research may focus on optimizing treatment parameters for targeting different brain regions in clinical applications and expanding its applications and mechanisms across various domains.

BACKGROUND:High-frequency repetitive transcranial magnetic stimulation has garnered significant attention due to its potential non-invasive benefits in modulating brain function.However,no studies have comprehensively analyzed the current research landscape and development trends of this field from a macroscopic perspective.OBJECTIVE:To explore research hotspots,current trends,and emerging frontiers in the field of high-frequency repetitive transcranial magnetic stimulation through visualized analysis.METHODS:Data were collected from the Web of Science Core Collection database from January 1,2014 to November 15,2024.CiteSpace was used for analyzing publication volume,collaborations among countries/regions,institutions and authors,citation analysis of journals and co-cited literature,as well as disciplinary distribution.Additionally,keyword co-occurrence,clustering,and burst analyses were conducted,and visualized knowledge maps were generated.RESULTS AND CONCLUSION:A total of 860 articles were included.The publication volume of high-frequency repetitive transcranial magnetic stimulation showed an overall upward trend from 2014 to 2022,followed by a decline from 2022 to 2024.China had the highest publication volume,while Ghent University ranked as the most productive institution.Universities acted as the most high-output institutions.Chris Baeken from Ghent University was identified as the most prolific author.Collaboration among leading authors and institutions worldwide remained limited.The main research hotspots in this field were associated with keywords such as depression,stroke,neuropathic pain,and Parkinson's disease.Burst keywords focused on mild cognitive impairment,reflecting a diversification in research directions.The overall research activity in high-frequency repetitive transcranial magnetic stimulation continues to rise,with primary focuses on its clinical applications for psychiatric and neurological disorders,as well as explorations of its underlying mechanisms.Future research may focus on optimizing treatment parameters for targeting different brain regions in clinical applications and expanding its applications and mechanisms across various domains.

In recent years, cancer treatment methods and means are becoming more and more diversified, and single treatment methods often have limited efficacy, while the synergistic effect of immunity combined with chemotherapy can inhibit tumor growth more effectively. Based on this, we constructed a sodium alginate hydrogel composite system loaded with chemotherapeutic agents and tumor vaccines (named SA-DOX-NA) with a view to the combined use of chemotherapeutic agents and tumor vaccines. Firstly, the tumor vaccine (named NA) degradable under acidic conditions was constructed by in situ polymerization using chicken ovalbumin (OVA), acrylamide (AAM) and 2-(dimethylamino) ethyl methacrylate (DMAEMA) monomer. Then a hydrogel composite system SA-DOX-NA co-loaded with chemotherapeutic drug doxorubicin (DOX) and NA was prepared using sodium alginate as a matrix. The results showed that SA-DOX-NA had good in situ gel-forming ability and formed a mesh structure that could realize the co-loading of DOX and NA as well as the slow drug release. The electron microscopy results showed that SA-DOX-NA had good in situ gel-forming ability with good internal connectivity, and the three-dimensional mesh structure could realize the co-loading of DOX and NA as well as the slow drug release. The antitumor and immunomodulatory results showed that SA-DOX-NA both effectively inhibited the growth of tumor cells and efficiently promoted the proliferation and activation of DC2.4 dendritic cells without additional adjuvant. In summary, SA-DOX-NA exerts the dual efficacy of chemotherapy and immunotherapy for tumor treatment, and has a good application prospect in local tumor treatment.

Objective:To compare the safety and efficacy of 3D-printed porous bioceramic artificial bone and artificial bone substitutes in the treatment of limb bone defects.Methods:A total of 220 patients with post-traumatic limb bone defects admitted to Xijing Hospital Affiliated to Air Force Medical University of the Chinese People's Liberation Army (34 cases), the Third Hospital of Hebei Medical University (60 cases), Xi'an Honghui Hospital (28 cases), the Third Hospital of Southern Medical University (18 cases), Changsha Third Hospital (28 cases), Foshan Traditional Chinese Medicine Hospital (16 cases), Foshan Fuxing Chancheng Hospital (12 cases), and Henan Provincial Orthopaedic Hospital (24 cases) from May 2022 to October 2023 were included as research subjects. According to the manufacturing method of the bone graft material, the subjects were randomly divided into the 3D printed porous bioceramic artificial bone group (3D printing group) and the artificial bone substitute group (non-3D printing group) at a ratio of 1:1 by the envelope method. Adverse events that might be related to the surgery were selected through correlation evaluation and classified as abnormal laboratory indicators, systemic or other site symptoms and abnormalities, and local symptoms and abnormalities of the affected limb. The safety of the two groups was compared. The bone graft fusion rate, bone defect repair and healing rate, and short form 12 (SF-12) score of the two groups were calculated to evaluate the postoperative recovery.Results:Thirty-two cases were excluded (4 cases refused to use their data after reconsideration, 7 cases were not used after preoperative assessment, and 21 cases exceeded the standard for body mass index and laboratory indicators upon re-examination). A total of 188 cases were randomly divided into the 3D printing group and the non-3D printing group according to the random method, with 94 cases in each group. Among them, 11 cases in the 3D printing group and 9 cases in the non-3D printing group dropped out due to loss to follow-up. Finally, 168 cases completed the follow-up, including 83 cases in the 3D printing group and 85 cases in the non-3D printing group. In the 3D printing group, there were 53 males and 30 females, with an average age of 47.9±12.7 years; in the non-3D printing group, there were 53 males and 32 females, with an average age of 48.6±12.9 years. A total of 51 cases in the two groups experienced adverse events related to the surgery, including 13 cases of abnormal laboratory indicators (5 cases in the 3D printing group and 8 cases in the non-3D printing group), 15 cases of systemic or other site symptoms and abnormalities (9 cases in the 3D printing group and 6 cases in the non-3D printing group), and 23 cases of local symptoms and abnormalities of the affected limb (13 cases in the 3D printing group and 10 cases in the non-3D printing group). There was no statistically significant difference in the incidence of adverse events between the two groups ( P>0.05). The bone graft fusion rates of the 3D printing group and the non-3D printing group at 6 months after surgery were 99%(82/83) and 99%(84/85), respectively, and the bone defect repair and healing rates were 89%(74/83) and 89%(76/85), respectively. At the time of 12 months after surgery, the bone graft fusion rates were 99%(82/83) and 99%(84/85), respectively, and the bone defect repair and healing rates were 94%(78/83) and 92%(78/85), respectively. There was no statistically significant difference in the bone graft fusion rate and bone defect repair and healing rate between the two groups ( P>0.05). The SF-12 scores during the screening period were 27.82±2.96 points and 27.22±4.23 points in the 3D printing group and the non-3D printing group, respectively, and at 3 months after surgery were 28.08±3.13 points and 27.64±3.16 points, at 6 months after surgery were 29.42±3.10 points and 28.55±3.45 points, and at 12 months after surgery were 29.78±2.80 points and 29.58±2.94 points, respectively. There was no statistically significant difference between the groups ( P>0.05). Both groups of surgeries were successfully completed without any serious surgical or bone graft-related complications. Conclusion:The safety and efficacy of 3D-printed porous bioceramic artificial bone in the treatment of limb bone defects are not significantly different from those of currently clinically applied artificial bone substitutes.

Objective To comprehensively evaluate the multidimensional impact of the"Tianjin Experience"of Chest Pain Center(CPC)development on in-hospital mortality,optimization of treatment workflows,and regional coordination of care for patients with acute myocardial infarction(AMI),with the aim of providing scientific evidence to further improve the model and enhance AMI treatment outcomes.Methods This study analyzed data from the"Cardiovascular and Cerebrovascular Acute Events Surveillance System"maintained by the Tianjin Center for Disease Control and Prevention from 2013 to 2024.A segmented regression model was applied to assess the long-term trends in in-hospital mortality from acute myocardial infarction(AMI),with a particular focus on evaluating the impact of the chest pain center program on treatment outcomes.Additionally,supplementary analyses were conducted using surveillance data from the Tianjin Chest Pain Center Quality Control Team between 2017 and 2024.To verify the effectiveness of treatment process optimization,temporal trends in key time-based process indicators were assessed,including Door-in-Door-out(DIDO)time at non-PCI hospitals,Door-to-Wire(D-to-W)time,and First Medical Contact to Wire(FMC-to-W)to wire time.Results According to the data from the Tianjin Center for Disease Control and Prevention,the average 28-day AMI mortality rate in the overall patient population was 9.85％.Between 01/2013 and 12/2014,the mortality rate showed a significant upward trend(P＜0.01),followed by a downward trend from 01/2015 to 12/2024,although the latter did not reach statistical significance(P＞0.05).From 2013 to 2024,a total of 27 633 AMI cases with complete clinical records were collected from Tianjin Chest Hospital,with an average 28-day mortality rate of 4.55％.The mortality rate exhibited a decreasing trend from 01/2013 to 12/2016,with an annual percent change(APC)of-7.56(P＜0.05).From 01/2017 to 12/2024,the trend stabilized,with an APC of 0.39(P＞0.05).Conclusions The development of the CPC system in Tianjin significantly reduced key treatment times and improved the overall efficiency of AMI management.While population-level AMI mortality rates began to decline after 2015,the rate of improvement has slowed,indicating a continued need for optimizing the regional coordinated care system to further enhance patient outcomes.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

BACKGROUND: Death burden of stroke is severe with over one-third rural residents in China, but there is still a lack of specific national and high-quality reports on the urban-rural differences in stroke burden, especially for subtypes. We aimed to update the understanding of urban-rural differences in stroke deaths. METHODS: This is a descriptive observational study. Data from the national mortality surveillance system, which covers 323.8 million with 605 disease surveillance points (DSPs) across all 31 provinces, municipalities, and autonomous regions in China. All deaths from stroke as the underlying cause from 2015 to 2020 according to DSPs. Crude mortality rate and age-standardized mortality rate (ASMR) were estimated through DSPs. Average annual percentage change was used to explain the change in mortality rate. RESULTS: From 2015 to 2020, the majority of deaths from all stroke subtypes occurred in rural areas. There were significant differences between the changes of urban and rural ASMRs. On the whole, the changes in urban areas were evidently better, and the ASMR differences were basically expanding. Stroke ASMR in urban China decreased by 15.5%. The rural ASMR of ischemic stroke increased by 12.9%. The rural and urban ASMRs of intracerebral hemorrhage decreased by 24.9% and 27.4%, and those of subarachnoid hemorrhage decreased by 29.5% and 40.4%, respectively. The highest ASMRs of all stroke subtypes and the increasing trend of ischemic stroke ASMR make rural males the focus of stroke management. CONCLUSIONS The death burden of stroke varies greatly between urban and rural China. Rural residents face unique challenges.
Humans ; China/epidemiology* ; Stroke/mortality* ; Rural Population/statistics & numerical data* ; Male ; Female ; Urban Population/statistics & numerical data* ; Middle Aged ; Aged ; Aged, 80 and over ; Adult

Objective This study aimed to investigate natural infection of rodents with Ehrlichia and Neoehrlichia at major Chinese land-border ports along the"Belt and Road".Methods In 2022,rodents were monitored in 10 ports in northern and southern China and identified based on diagnostic morphological characteristics.The 16S rRNA genes of Ehrlichia and Neoehrlichia were detected by PCR using universal primers from rodent samples and phylogenetic analysis was performed based on the sequences of the detected positive pathogens.Results A total of 356 rodents were sampled,including 2 orders,5 families,15 genera,and 20 species.Predominantly,73,61,56,and 58 were Meriones unguiculatus(20.51%),Rattus norvegicus(17.13%),Apodemus agrarius(15.73%),and Microtus gregalis(16.29%).Only one Microtus fortis from Suifenghe Port was infected with Ehrlichia sp.Moreover,12 rodents were infected with Neoehrlichia spp.(overall positivity rate:3.37%).Conclusions Natural infections with Ehrlichia spp.and Neoehrlichia spp.were demonstrated in rodents at important Chinese land-border ports.The positivity rate of Neoehrlichia spp.was high in some ports,indicating that surveillance for ticks and their prevention and control measures should be intensified in these regions.