ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

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OBJECTIVE: To explore the early changes in various liver function indicators in critically injured trauma patients assessed by intelligent calculation method, aiming to develop more advantageous diagnostic and treatment strategies for traumatic liver injury. METHODS: A retrospective study was conducted. Critically injured trauma patients [injury severity score (ISS) ≥ 16, age > 18 years old] admitted to the Emergency Medical Center of Tianjin Fifth Central Hospital from January 1, 2022, to December 1, 2023 were enrolled. ISS score and acute physiology and chronic health evaluation II (APACHE II) assessed by intelligent calculation method were collected upon patient admission to the emergency medical center. Trends in liver function indicators in fasting venous serum were analyzed at 6, 24 and 72 hours after admission, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), γ-glutamyl transferase (GGT), lactate dehydrogenase (LDH), albumin (ALB), total bilirubin (TBil), prothrombin time (PT). Patients were grouped based on APACHE II scores into those with APACHE II < 15 and APACHE II ≤ 15, and liver function indicators within 6 hours of admission were compared between the two groups. RESULTS: A total of 112 critically injured trauma patients were included, with 83 males and 29 females, an average age of (47.78±14.84) years old. The median ISS score was 21.0 (18.0, 26.0). The most common cause of injury for critically injured trauma patients was road traffic accidents (68 cases, accounting for 60.71%), followed by falls from heights, compression injuries, heavy object injuries, knife stabs, and explosion injuries. The most common injured areas was the limbs and pelvis (97 cases, accounting for 86.61%), followed by chest injuries, surface skin and soft tissue injuries, abdominal and pelvic organ injuries, head injuries, and facial injuries. The proportion of elevated LDH, AST, and ALT within 6 hours of admission was 77.68%, 79.46%, and 52.68%, respectively, while the proportion of decreased ALB was 75.89%, the abnormal rates of ALP, GGT, TBil, and PT were all below 50%. The ALT and AST levels of patients at 24 hours and 72 hours after admission were significantly lower than those at 6 hours after admission [ALT (U/L): 37.0 (22.0, 66.0), 31.0 (21.2, 52.0) vs. 41.0 (25.0, 71.0), AST (U/L): 55.5 (30.0, 93.5), 40.0 (27.0, 63.2) vs. 69.5 (39.0, 130.8), all P < 0.05]. There was no statistically significant difference in ISS score between APACHE II > 15 group (45 cases) and APACHE II ≤ 15 group [67 cases; 21.0 (18.5, 26.5) vs. 20.0 (17.0, 22.0), P > 0.05]. Nevertheless, compared with patients with APACHE II ≤ 15, patients with APACHE II > 15 have a higher abnormality rate of ALT and AST within 6 hours of admission [ALT abnormal rate: 66.44% (29/45) vs. 44.78% (30/67), AST abnormal rate: 93.33% (42/45) vs. 70.15% (47/67), both P < 0.05], and the levels of ALT and AST were higher [ALT (U/L): 56.0 (30.0, 121.0) vs. 35.0 (21.0, 69.0), AST (U/L): 87.0 (48.0, 233.0) vs. 52.0 (31.0, 117.0), both P < 0.05]. CONCLUSIONS Severe trauma patients frequently exhibit a high incidence of reversible early liver function impairment. Based on intelligent calculation method, the utilization of both the ISS and APACHE II scores demonstrates a distinct advantage in the assessment of their early liver injury.
Humans ; Retrospective Studies ; Liver/physiopathology* ; Risk Assessment ; APACHE ; Wounds and Injuries ; Adult ; Injury Severity Score ; Male ; Middle Aged ; Female ; Liver Function Tests ; Alanine Transaminase/blood* ; Young Adult ; Aspartate Aminotransferases/blood*

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

OBJECTIVE: The study aim was to investigate the effects of exposure to multiple environmental organic pollutants on cardiopulmonary health with a focus on the potential mediating role of oxidative stress. METHODS: A repeated-measures randomized crossover study involving healthy college students in Beijing was conducted. Biological samples, including morning urine and venous blood, were collected to measure concentrations of 29 typical organic pollutants, including hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), bisphenol A and its substitutes, phthalates and their metabolites, parabens, and five biomarkers of oxidative stress. Health assessments included blood pressure measurements and lung function indicators. RESULTS: Urinary concentrations of 2-hydroxyphenanthrene (2-OH-PHE) ( β = 4.35% [95% confidence interval ( CI): 0.85%, 7.97%]), 3-hydroxyphenanthrene ( β = 3.44% [95% CI: 0.19%, 6.79%]), and 4-hydroxyphenanthrene (4-OH-PHE) ( β = 5.78% [95% CI: 1.27%, 10.5%]) were significantly and positively associated with systolic blood pressure. Exposures to 1-hydroxypyrene (1-OH-PYR) ( β = 3.05% [95% CI: -4.66%, -1.41%]), 2-OH-PHE ( β = 2.68% [95% CI: -4%, -1.34%]), and 4-OH-PHE ( β = 3% [95% CI: -4.68%, -1.29%]) were negatively associated with the ratio of forced expiratory volume in the first second to forced vital capacity. These findings highlight the adverse effects of exposure to multiple pollutants on cardiopulmonary health. Biomarkers of oxidative stress, including 8-hydroxy-2'-deoxyguanosine and extracellular superoxide dismutase, mediated the effects of multiple OH-PAHs on blood pressure and lung function. CONCLUSION Exposure to multiple organic pollutants can adversely affect cardiopulmonary health. Oxidative stress is a key mediator of the effects of OH-PAHs on blood pressure and lung function.
Humans ; Oxidative Stress/drug effects* ; Male ; Cross-Over Studies ; Female ; Young Adult ; Environmental Pollutants/toxicity* ; Environmental Exposure/adverse effects* ; Biomarkers/blood* ; Adult ; Blood Pressure/drug effects* ; Polycyclic Aromatic Hydrocarbons/urine* ; Beijing

ObjectiveFat infiltration has been shown to be closely related to muscle mass loss and a variety of muscle diseases. This study proposes a method based on phase-angle electrical impedance tomography (ΦEIT) to visualize the electrical characteristic response caused by muscle fat infiltration, aiming to provide a new technical means for early non-invasive detection of muscle mass deterioration. MethodsThis study was divided into two parts. First, a laboratory pork model was constructed to simulate different degrees of fat infiltration by injecting1 ml or 2 ml of emulsified fat solution into different muscle compartments, and the phase angle images were reconstructed using ΦEIT. Second, a human experiment was conducted to recruit healthy subjects (n=8) from two age groups (20-25 years old and 26-30 years old). The fat content percentage η_fat of the left and right legs was measured by bioelectrical impedance analysis (BIA), and the phase angle images of the left and right calves were reconstructed using ΦEIT. The relationship between the global average phase angle Φ_M and the spatial average phase angle Φ_Mi of each muscle compartment and fat infiltration was further analyzed. ResultsIn the laboratory pork model, the grayscale value of the image increased with the increase of η_fat and Φ_M showed a downward trend. The results of human experiments showed that at the same fat content percentage, the Φ_M of the 26-30-year-old group was about 20%-35% lower than that of the 20-25-year-old group. The fat content percentage was significantly negatively correlated with Φ_M. In addition, the M₂ (soleus) compartment was most sensitive to fat infiltration, and the spatial average phase angles of the M₂ (soleus), M₃ (tibialis posterior and flexor digitorum longus), and M₄ (tibialis anterior, extensor digitorum longus, and peroneus longus) compartments all showed significant inter-group differences. ConclusionΦEIT imaging can effectively distinguish different degrees of fat infiltration, especially in deep, small or specially located muscles, showing high sensitivity, demonstrating the potential application of this method in local muscle mass monitoring and early non-invasive diagnosis.

OBJECTIVE: To analyze the demographic and clinical characteristics of inpatients with osteoporotic vertebral compression fractures (OVCF) and provide a basis for clinical prevention and treatment. METHODS: A retrospective analysis was performed on the clinical data of 744 inpatients diagnosed with OVCF between January 2017 and December 2021 who met the inclusion criteria. Among them, 146 were male and 598 were female, with age ranging from 50 to 95 years (mean, 69.37 years). The demographic characteristics (gender, age, ethnicity, occupation, regional distribution, urban-rural distribution, and seasonal incidence) and clinical features [causes of injury, history of vertebral fractures, smoking and drinking history in males, comorbidities (hypertension, diabetes, coronary atherosclerotic heart disease, cerebral infarction), body mass index (BMI), blood lipid levels, menopausal age in females, vertebral bone mineral density T-value, number of vertebral fractures, and fracture segment distribution] of OVCF patients were analyzed. Multiple linear regression was used to analyze the independent risk factors of vertebral osteoporosis. RESULTS: The demographic analysis indicated that female patients with OVCF were significantly younger than male patients ( P<0.05). Significant differences were observed in the age distribution of OVCF between males and females ( P<0.05), with the highest proportion of male patients in the 70-79 years group (37.0%) and the highest proportion of female patients in the 60-69 years group (40.0%). From 2017 to 2021, the age of onset for OVCF gradually increased, with a similar trend observed for both genders. The distribution of occupations between genders also showed significant differences ( P<0.05); with the top three occupations for males being farmers (48.6%), retirees (24.7%), and workers (13.7%), while for females, the leading occupations were farmers (51.5%), retirees (19.4%), and service workers (10.0%). Female OVCF patients had higher BMI, vertebral bone mineral density T-value, history of vertebral fractures, hypertension prevalence, and blood lipid levels compared to male patients ( P<0.05). No significant difference between the males and the females was found in ethnicity, seasonal distribution, regional distribution, urban-rural distribution, causes of injury, number of vertebral fractures, or prevalence of comorbidities (except hypertension) ( P>0.05). Among the 744 OVCF patients, a total of 1 309 vertebrae were involved, with 628 thoracic vertebrae (48.0%) and 681 lumbar vertebrae (52.0%). The most common fracture segments were L ₁ (22.5%), T ₁₂ (21.2%), followed by L ₂ (12.2%) and T ₁₁ (10.2%). No significant gender difference was observed in the distribution of fracture segments ( P>0.05). Multiple linear regression analysis indicated that older age, female, and lower BMI were independent risk factors for vertebral osteoporosis ( P<0.05). CONCLUSION The age of onset of OVCF patients is increasing year by year. The number of fractured vertebral bodies, age distribution of morbidity, occupational distribution, BMI, history of vertebral fracture, hypertension, and blood lipid levels are related to gender. The occurrence of OVCF is mainly in the thoracolumbar segment. The female, older age, and lower BMI are independent risk factors of osteoporosis.
Humans ; Male ; Female ; Aged ; Middle Aged ; Retrospective Studies ; Spinal Fractures/etiology* ; Aged, 80 and over ; Osteoporotic Fractures/etiology* ; Fractures, Compression/etiology* ; Risk Factors ; Bone Density ; China/epidemiology* ; Osteoporosis/epidemiology* ; Comorbidity ; Inpatients ; Sex Factors ; Age Factors

PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

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.