Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

Abstract The health literacy level among the elderly in China remains at a low level. The 14th Five-Year Plan for Healthy Aging clearly points out that health literacy promotion projects should be implemented to improve the health literacy level among the elderly. The health literacy promotion strategies for the elderly require individual, social, policy and environmental supports. This article reviewed four types of health literacy promotion strategies for the elderly, including social strategies, lecture-based health education strategies, new media-based health communication strategies and environmental strategies. It also proposed that health education institutions, communities and other parties should work together, take advantage of digital technology and internet, and take various measures simultaneously to improve the health literacy of the elderly.

Electroencephalogram (EEG) is a non-invasive, high temporal-resolution technique for monitoring brain activity. However, affected by the volume conduction effect, EEG has a low spatial resolution and is difficult to locate brain neuronal activity precisely. The surface Laplacian (SL) technique obtains the Laplacian EEG (LEEG) by estimating the second-order spatial derivative of the scalp potential. LEEG can reflect the radial current activity under the scalp, with positive values indicating current flow from the brain to the scalp (“source”) and negative values indicating current flow from the scalp to the brain (“sink”). It attenuates signals from volume conduction, effectively improving the spatial resolution of EEG, and is expected to contribute to breakthroughs in neural engineering. This paper provides a systematic overview of the principles and development of SL technology. Currently, there are two implementation paths for SL technology: current source density algorithms (CSD) and concentric ring electrodes (CRE). CSD performs the Laplace transform of the EEG signals acquired by conventional disc electrodes to indirectly estimate the LEEG. It can be mainly classified into local methods, global methods, and realistic Laplacian methods. The global method is the most commonly used approach in CSD, which can achieve more accurate estimation compared with the local method, and it does not require additional imaging equipment compared with the realistic Laplacian method. CRE employs new concentric ring electrodes instead of the traditional disc electrodes, and measures the LEEG directly by differential acquisition of the multi-ring signals. Depending on the structure, it can be divided into bipolar CRE, quasi-bipolar CRE, tripolar CRE, and multi-pole CRE. The tripolar CRE is widely used due to its optimal detection performance. While ensuring the quality of signal acquisition, the complexity of its preamplifier is relatively acceptable. Here, this paper introduces the study of the SL technique in resting rhythms, visual-related potentials, movement-related potentials, and sensorimotor rhythms. These studies demonstrate that SL technology can improve signal quality and enhance signal characteristics, confirming its potential applications in neuroscientific research, disease diagnosis, visual pathway detection, and brain-computer interfaces. CSD is frequently utilized in applications such as neuroscientific research and disease detection, where high-precision estimation of LEEG is required. And CRE tends to be used in brain-computer interfaces, that have stringent requirements for real-time data processing. Finally, this paper summarizes the strengths and weaknesses of SL technology and envisages its future development. SL technology boasts advantages such as reference independence, high spatial resolution, high temporal resolution, enhanced source connectivity analysis, and noise suppression. However, it also has shortcomings that can be further improved. Theoretically, simulation experiments should be conducted to investigate the theoretical characteristics of SL technology. For CSD methods, the algorithm needs to be optimized to improve the precision of LEEG estimation, reduce dependence on the number of channels, and decrease computational complexity and time consumption. For CRE methods, the electrodes need to be designed with appropriate structures and sizes, and the low-noise, high common-mode rejection ratio preamplifier should be developed. We hope that this paper can promote the in-depth research and wide application of SL technology.

OBJECTIVE: To investigate hypertension (HTN) trends, key risk factors, and gender disparities in rural China, and to propose targeted strategies for improving HTN control in resource-limited settings. METHODS: This longitudinal study used data from the Henan Rural Cohort Study, including baseline (2015-2017; n = 39,224) and follow-up (2018-2022; n = 28,621) participants. HTN was defined as systolic/diastolic blood pressure ≥ 140/90 mmHg, self-reported diagnosis, or use of antihypertensive medication. Severity was classified using a 7-tier blood pressure (BP) staging system (optimal, normal, high normal, and HTN stages 1-4). A generalized linear mixed-effects model (GLMM) identified associated risk factors. RESULTS: HTN prevalence increased modestly from 32.7% (95% CI: 32.2-33.2) to 33.9% (95% CI: 33.3%-34.4%). Awareness and treatment improved from 20.1% to 25.3%, and from 18.8% to 24.4%, respectively, but control rates remained low (6.2% to 12.3%). After adjustment, women had a 1.53-fold higher HTN risk than men ( OR = 1.53, 95% CI: 1.43-1.63), revealing gender-specific trends. Key risk factors included alcohol use ( OR = 1.37, 95% CI: 1.27-1.47) and overweight status ( OR = 1.76, 95% CI: 1.66-1.86). BP staging showed an increase in optimal BP (42.3% to 45.8%), but stagnant management of advanced HTN stages. CONCLUSION Hypertension in rural China is shaped by behavioral risk factors and healthcare access gaps. Gender-sensitive, community-based interventions, including task-shifting models, are necessary to mitigate the growing burden of hypertension.
Humans ; Hypertension/etiology* ; China/epidemiology* ; Female ; Male ; Rural Population/statistics & numerical data* ; Prevalence ; Risk Factors ; Middle Aged ; Adult ; Aged ; Longitudinal Studies ; Sex Factors ; Cohort Studies ; East Asian People

Objective: To investigate the seroepidemiological characteristics of hepatitis B among outpatients in medical institutions in Jiaxing City, Zhejiang Province, so as to provide a reference for formulating region-specific hepatitis B prevention and control strategies. Methods: From April to June 2024, outpatients were selected as study subjects from sentinel medical institutions in Jiaxing City. Information such as gender and age was collected. Venous blood samples were obtained and serological markers including hepatitis B surface antigen (HBsAg), hepatitis B surface antibody (HBsAb), hepatitis B e antigen (HBeAg), hepatitis B e antibody (HBeAb), and hepatitis B core antibody (HBcAb) were tested. Positive rates of hepatitis B virus (HBV) serological markers were analyzed by genders and ages. Results: A total of 1 468 outpatients were included, among whom 721 were males (49.11%) and 747 were females (50.89%). The mean age was (46.41±19.66) years. The positive rates of HBsAg, HBsAb, HBeAg, HBeAb, and HBcAb were 7.29%, 44.75%, 1.84%, 23.50%, and 42.03%, respectively. The HBcAb positive rate in males was significantly higher than in females (46.05% vs. 38.15%, P<0.05), while no statistically significant gender differences were observed in the positive rates of other four HBV serological markers (all P>0.05). Except for HBsAb, the positive rates of the other four HBV serological markers showed statistically significant differences across different age groups (all P<0.05). Pairwise comparisons results showed that the HBsAg positive rates in age groups of 20-<40 years and 40-<60 years were 9.48% and 9.57%, respectively, which were higher than those in age groups of <20 years (1.43%) and ≥60 years (2.75%) (all P<0.05). A total of 17 HBV serological marker patterns were observed, among which the proportion of all markers negative was the highest, at 39.65%. The proportions of "small three positive" (HBsAg+, HBeAb+, HBcAb+) and "large three positive" (HBsAg+, HBeAg+, HBcAb+) patterns were 4.77% and 1.50%, respectively. Among HBsAg-positive individuals, the proportions of the "small three positive" pattern across age groups were 0, 45.45%, 90.00%, and 81.82%, while those of the "large three positive" were 0, 36.36%, 5.00%, and 0, with statistically significant differences across age groups (both P<0.05). Conclusions The positive rate of HBsAg among outpatients in medical institutions in Jiaxing City is relatively high, with a notable proportion of individuals showing either no immunity or non-response to vaccination. It is recommended to strengthen hepatitis B immunization efforts among the population aged 20-<60 years, and to enhance monitoring and interventional treatment for "small three positive" and "large three positive" patterns.

Objective:To analyze the characteristics of non-seroconverted cases after rabies vaccination and observe the effect of booster vaccination.Methods:A retrospective collection of data was conducted from March 2022 to March 2023 across 409 rabies vaccination clinics in 27 provinces in China, focusing on cases with rabies virus neutralizing antibody (RVNA) levels less than 0.5 IU/ml after vaccination.Results:A total of 77 cases were identified in whom seroconversion was not observed within 30 days post-vaccination with the rabies vaccine. The gender distribution was 51.9% male and 48.1% female, with ages ranging from 2 to 83 years old. Delayed vaccination was observed in 11 cases (14.3%), and 63 cases (81.8%) received human rabies immunoglobulin (HRIG) injections. None of the cases had a confirmed immunosuppressive disease or taking immunosuppressive drugs, and the body mass index (BMI) distribution ranged from 14.37 to 34.74 kg/m 2. Seventy-six cases seroconverted after 1 to 3 doses of rabies vaccines as a booster vaccination. One case that did not seroconvert after the initial booster vaccination seroconverted after receiving additional 2 doses of vaccine. All patients were followed up for one year, with no cases of rabies reported. Conclusions:The characteristics of cases that failed to seroconvert after the full course of rabies vaccination lacked specificity, and booster vaccination could lead to seroconversion.

Hand degloving injury represents one of the most severe forms of hand trauma, characterised by challenging treatment and a complex prognostic outcome. It is crucial to effectively utilise the degloved tissues in emergency or primary repair of a hand degloving injury. This consensus provides a comprehensive review of the existing literature on definition, classification, emergency assessment, debridement, judgment of skin viability, in situ repair of the degloved skin, and adjunctive treatment for degloving injury of hand. Based on conclusion of both domestic and international experiences, this expert consensus on the classification of hand degloving injury and the emergency repair with the avulsed skin is established, aiming to provide a guidance to surgeons on standardised treatment strategy and improve the management of hand degloving injury.

Objective:To explore the differences between the Phoenix sepsis scoring system including Phoenix sepsis score (PSS) and Phoenix-8 organ dysfunction score (hereinafter referred to as Phoenix-8) and the commonly used pediatric sepsis scores in evaluating clinical characteristics and prognostic analysis of pediatric patients with severe sepsis diagnosed under traditional standards, namely the diagnostic criteria from the 2005 International Pediatric Sepsis Consensus Conference.Methods:This study was a retrospective observational study. From December 2020 to March 2023, 202 pediatric patients with severe sepsis meeting the inclusion criteria were admitted to the Children's Hospital of Nanjing Medical University. Based on the sepsis diagnostic criteria outlined in the International Consensus Criteria for Pediatric Sepsis and Septic Shock (2024), the pediatric patients were categorized into a sepsis group and a non-sepsis group. Sepsis group was further subdivided into a death subgroup and a survival subgroup based on the outcomes. The age, hospitalization costs, disease outcome indicators (e.g., mortality rate and incidence of septic shock), major organ (e.g., heart, liver, lungs, and kidneys) damage and their correlations, as well as PSS, Phoenix-8 and commonly used pediatric sepsis scores (e.g., pediatric sequential organ failure assessment (pSOFA), pediatric risk of mortality score Ⅲ (PRISM Ⅲ), pediatric logistic organ dysfunction-2 score (PELOD-2), pediatric multiple organ dysfunction score (P-MODS), pediatric critical illness score (PCIS), and pediatric early warning score (PEWS)) were collected and compared. Receiver operating characteristic (ROC) curve and precision-recall curve were plotted to evaluate the predictive ability of PSS, Phoenix-8, and commonly used pediatric sepsis scores for mortality risk in pediatric patients with severe sepsis under traditional standards. Predictive performance was quantified using the area under the ROC curve (AUROC). Univariate logistic regression analysis was employed to quantify the odds ratios of PSS and Phoenix-8 for predicting mortality risk. Patients with severe sepsis under traditional standards were further stratified into subgroups based on complications and comorbidities, including central nervous system (CNS) diseases, multiple infections, cardiovascular system diseases, shock, and malignancies. The Hosmer-Lemeshow goodness-of-fit test was used to assess calibration of PSS and Phoenix-8, and the DeLong test was used to compare whether there were statistically significant differences in the AUROC of PSS and Phoenix-8 for predicting mortality risk among different subgroups of pediatric patients. Results:Compared with those in non-sepsis group, pediatric patients in sepsis group were significantly older ( Z=-2.92, P<0.05) with higher incidences of septic shock and mortality, hospitalization costs, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, PSS, and Phoenix-8 (with χ2 values of 21.28 and 13.64, respectively, Z values of -1.99, -5.33, -5.10, -8.55, -6.91, -10.98, and -9.93, respectively, P<0.05), and lower PCIS ( Z=-3.34, P<0.05). Compared with those in survival subgroup, hospitalization costs, PSS, Phoenix-8, PRISM Ⅲ, PEWS, pSOFA, PELOD-2, and P-MODS of pediatric patients in death subgroup was significantly higher (with Z values of -2.50, -3.50, -2.47, -5.11, -3.84, -2.94, -3.61, and -3.04, respectively, P<0.05). Compared with those in survival subgroup, the incidences of lung damage and liver damage of pediatric patients in death subgroup were also significantly higher (with χ2 values of 6.20 and 10.94, respectively, P<0.05), and 64.7% (97/150) of patients exhibited two or more concurrent organ damage. For predicting mortality risk in pediatric patients with severe sepsis under traditional standards, the AUROC values for PRISM Ⅲ, PCIS, PEWS, pSOFA, PELOD-2, P-MODS, PSS, and Phoenix-8 were approximately 0.70, with optimal cutoff values of 17.5, 91.0, 5.5, 4.5, 2.5, 4.5, 3.5, and 4.5, respectively; PELOD-2 demonstrated the highest sensitivity (0.83); while PRISM Ⅲ, PSS, and Phoenix-8 showed high specificity (>0.80). Univariate logistic regression analysis showed that for every 1-point increase in the PSS within 24 hours of pediatric intensive care unit admission, the relative risk of mortality increased by 63.7% (with odds ratio of 1.64, 95% confidence interval of 1.34-1.99, P<0.05). Similarly, for every 1-point increase in the Phoenix-8, the relative risk of mortality increased by 37.5% (with odds ratio of 1.38, 95% confidence interval of 1.18-1.60, P<0.05). The AUROC values (around 0.80) of PSS and Phoenix-8 for predicting mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases were relatively high. In contrast, the AUROC values (0.60-0.80) for predicting mortality risk in pediatric patients with severe sepsis combined with shock or malignant tumors were moderate. All models passed the Hosmer-Lemeshow goodness-of-fit test ( P>0.05). The DeLong test indicated no statistically significant differences in predictive ability between PSS and Phoenix-8 across subgroups of pediatric patients ( P>0.05). Conclusions:PSS and Phoenix-8 exhibited higher specificity than most of the commonly used pediatric sepsis scores in predicting mortality risk under traditional standards. Both scores performed much better in predicting the mortality risk in pediatric patients with severe sepsis combined with CNS diseases, multiple infections, and cardiovascular system diseases.