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.

According to General Chapter 1145 of Division IV in the Chinese Pharmacopoeia (2020 Edition), the test for depressor substances is a common method for drug testing. It determines whether the level of depressor substances in a test sample complies with the specified standards by comparing the extent of blood pressure reduction in anesthetized cats induced by the histamine reference substance and the test sample. If an out-of-specification (OOS) result occurs in the test for depressor substances, it may be caused by inherent quality issues of the drug or errors in the testing process. Therefore, analyzing the causes of OOS is particularly important for confirming the test results and evaluating drug quality. Cats are used as experimental animals in the test for depressor substances. Compared with conventional laboratory animals, they are less stable, surgery procedures are more challenging, and the testing process is more complex. These factors make it more difficult to investigate the causes of OOS in this test. Based on a review of the literature and practical work experience, this article analyzes the causes of OOS in the test for depressor substances from the following five aspects: (1) an analysis of the impact of drug standards on OOS from three aspects: standard determination, standard content, and standard drafting; (2) personnel qualifications, including pre-employment training, compliance with standard operating procedures during experimental operations, and the ability to operate instruments; (3) factors related to cats, used as experimental animals in the test for depressor substances, including physiological characteristics, genetic background, and abnormal conditions during the experiment; (4) reference substances, reagents, test samples, and key instruments such as the multi-channel physiological signal instrument; (5) experimental operations including animal anesthesia, arterial and venous catheterization, drug administration, and data processing. This article aims to provide reference approaches for professionals engaged in the testing of pharmaceuticals and biological products when analyzing the causes of OOS in the test for depressor substances.

According to General Chapter 1145 of Division IV in the Chinese Pharmacopoeia (2020 Edition), the test for depressor substances is a common method for drug testing. It determines whether the level of depressor substances in a test sample complies with the specified standards by comparing the extent of blood pressure reduction in anesthetized cats induced by the histamine reference substance and the test sample. If an out-of-specification (OOS) result occurs in the test for depressor substances, it may be caused by inherent quality issues of the drug or errors in the testing process. Therefore, analyzing the causes of OOS is particularly important for confirming the test results and evaluating drug quality. Cats are used as experimental animals in the test for depressor substances. Compared with conventional laboratory animals, they are less stable, surgery procedures are more challenging, and the testing process is more complex. These factors make it more difficult to investigate the causes of OOS in this test. Based on a review of the literature and practical work experience, this article analyzes the causes of OOS in the test for depressor substances from the following five aspects: (1) an analysis of the impact of drug standards on OOS from three aspects: standard determination, standard content, and standard drafting; (2) personnel qualifications, including pre-employment training, compliance with standard operating procedures during experimental operations, and the ability to operate instruments; (3) factors related to cats, used as experimental animals in the test for depressor substances, including physiological characteristics, genetic background, and abnormal conditions during the experiment; (4) reference substances, reagents, test samples, and key instruments such as the multi-channel physiological signal instrument; (5) experimental operations including animal anesthesia, arterial and venous catheterization, drug administration, and data processing. This article aims to provide reference approaches for professionals engaged in the testing of pharmaceuticals and biological products when analyzing the causes of OOS in the test for depressor substances.

Objective: Traumatic brain injury (TBI) patients often experience massive bleeding and require blood transfusion. However, the storage duration of the transfused blood may affect the prognosis of these patients. This study explored the influence of exosomes derived from fresh and aged blood on the prognosis of rats with TBI, so as to provide theoretical support for the blood transfusion management of TBI patients. Methods: Exosomes were isolated from red blood cell (RBC) suspensions stored for 1 week and 5 weeks using ultracentrifugation method. The size, morphology and surface markers of the exosomes were identified by nanoparticle flow cytometry, transmission electron microscopy and Western blotting, respectively. A rat model of TBI was constructed using a mechanical impactor for brain injury. After the successful establishment of the model, exosomes from RBC suspensions stored for 1 week and 5 weeks were injected into the extracellular space of rat brain cells using a stereotactic syringe. Cerebral edema at day 1, 3, 7 and 14 were recorded through cranial magnetic resonance imaging (MRI) scans. Magnetic tracing technology (the tracer was Gd-DTPA solution) was used to evaluate the drug metabolism level in the extracellular space of brain cells of TBI rats. The cranial magnetic resonance imaging was scanned every 15 or 30 minutes, and the recording lasted for a total of 240 minutes. The magnetic images were imported into the 3D-Slicer software in Dicom data format for analysis. Mass spectrometry technology was used to analyze the differential proteins of exosomes from RBC suspensions stored for 1 week and 5 weeks, and functional prediction was carried out to explore the possible mechanisms by which exosomes affect the prognosis of TBI. Results: After injection of exosomes into TBI rats, the areas of cerebral edema on the day 1, 3, 7, and 14 were all significantly higher in the rats treated with exosomes from 5-week-stored RBC suspensions, with peak cerebral edema occurring at day 3. The diffusion volume of the tracer was significantly higher in TBI rats than in normal rats, which implied there was a disorder in the structure of the traumatic brain tissue in TBI rats. Compared with the rats injected with exosomes from 1-week-stored RBC suspensions, those treated with exosomes from 5-week-stored RBC suspensions showed increased tracer diffusion volume within 120 minutes. Mass spectrometry analysis identified 81 differentially expressed proteins between exosomes from RBC suspensions stored for 5 weeks vs 1 week. Among them, 93.83% (76/81) proteins had increased expression levels. The neurodegeneration-related pathways were among the most enriched pathways for upregulated proteins. Conclusion: The exosomes from aged RBC suspensions can lead to exacerbated cerebral edema, disrupted extracellular space, and suppressed metabolic rate in TBI rats, suggesting that transfusion of aged RBC suspensions may have adverse effects on TBI patients.

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.

To investigate the effects of phosphorus fertilizer on the morphological traits, active ingredients and rhizosphere soil microbial community of Polygala tenuifolia. The phosphorus fertilizer was calculated in terms of P_2O_5. Five treatments were set up: 0(CK), 17(P1), 34(P2), 51(P3), and 68(P4) kg per Mu(1 Mu≈667 m~2). A randomized block design was adopted. Samples of P. tenuifolia and its rhizosphere soil were collected under different superphosphate fertilizer treatments. Illumina high-throughput sequencing was used to analyze the rhizosphere soil microbial community, 9 morphological traits were measured and the content of 11 active ingredients were determined. The results showed that the whole plant weight, shoot fresh weight, root weight, and root peel thickness were the highest under P1 treatment, increasing by 34.41%, 38.80%, 39.21%, and 3.17% respectively compared to CK. Under P2 treatment, the plant height, stem diameter, root thickness, and core thickness were significantly higher than CK. Phosphorus fertilizer had a significant impact on the content of tenuifolin, sibiricose A5, sibiricose A6, arillanin A, 3,6'-disinapoyl sucrose, and polygalaxanthone Ⅲ. Correlation analysis results showed that the relative abundance of Arthrobacter, Bacillus, norank＿f＿Vicinamibacteraceae, norank＿o＿Vicinamibacterales, MND1 and other bacteria, as well as the relative abundance of Neocosmospora, Paraphoma and other fungi were positively correlated with root diameter, wood core diameter, the whole plant weight, root weight, shoot fresh weight of P. tenuifolia. Bacillus, Neocosmospora, Subulicystidium were significantly positively correlated with oligosaccharides such as 3,6'-disinapoyl sucrose, sibiricose A5、sibiricose A6、glomeratose A、arillanin A and tenuifoliside C. Arthrobacter, Humicola, Aspergillus, Paraphoma were positively correlated with tenuifolin and norank＿f＿Vicinamibacteraceae, norank＿o＿Vicinamibacterales, Fusarium were positively correlated with polygalaxanthone Ⅲ. Evidently, appropriate phosphorus application is conducive to the growth and quality improvement of P. tenuifolia, and can increase the abundance of beneficial microorganisms in the soil.
Rhizosphere ; Phosphorus/pharmacology* ; Soil Microbiology ; Polygala/anatomy & histology* ; Fertilizers/analysis* ; Bacteria/metabolism* ; Soil/chemistry* ; Microbiota/drug effects* ; Plant Roots/metabolism*

Microbial detection and control of traditional Chinese medicine(TCM) decoction pieces are crucial for the quality control of TCM preparations. It is also a key area of research in the measurement technology and equipment development for TCM manufacturing. Guided by TCM manufacturing measurement methodologies, this study presented a design of a novel portable microbial detection device, using Atractylodis Macrocephalae Rhizoma decoction pieces as a demonstration. Immunomagnetic separation technology was employed for specific isolation and labeling of target microorganisms. Enzymatic signal amplification was utilized to convert weak biological signals into colorimetric signals, constructing an optical biosensor. A self-developed smartphone APP was further applied to analyze the colorimetric signals and quantify target concentrations. A portable and automated detection system based on Arduino microcontroller was developed to automatically perform target microbial separation/extraction, as well as mimetic enzyme labeling and catalytic reactions. The developed equipment specifically focuses on the rapid and quantitative microbial analysis of TCM active pharmaceutical ingredients, intermediates in TCM manufacturing, and final TCM products. Experimental results demonstrate that the equipment could detect Salmonella in samples within 2 h, with a detection limit as low as 5.1 × 10~3 CFU·mL~(-1). The equipment enables the rapid detection of microorganisms in TCM decoction pieces, providing a potential technical solution for on-site rapid screening of microbial contamination indicators in TCM. It has broad application prospects in measurement technology for TCM manufacturing and offers strong technical support for the modernization, industrialization, and intelligent development of TCM.
Drugs, Chinese Herbal/analysis* ; Atractylodes/microbiology* ; Rhizome/microbiology* ; Biosensing Techniques/methods* ; Medicine, Chinese Traditional ; Colorimetry/instrumentation* ; Quality Control

OBJECTIVES: To investigate the association between maternal depressive symptoms and adolescent suicidal ideation, and to examine the chain mediating roles of childhood trauma and ineffectiveness. METHODS: A cross-sectional online survey was administered by school psychologists to 4 157 mother-adolescent pairs from middle schools in Shanghai and Henan, China. Measures included the Center for Epidemiological Studies Depression Scale, the Childhood Trauma Questionnaire, and the Children's Depression Inventory. Using Bootstrap method to examine the chain mediating effect of childhood trauma and ineffectiveness on the relationship between maternal depression symptoms and adolescent suicidal ideation. RESULTS: The prevalence of maternal depressive symptoms was 17.68% (735/4 157); among adolescents, the prevalence of depressive symptoms was 15.49% (644/4 157), and suicidal ideation was 28.19% (1 172/4 157). Adolescent depressive symptoms and suicidal ideation were positively correlated with maternal depressive symptoms, childhood trauma, and ineffectiveness (all P<0.01). Childhood trauma significantly mediated the association between maternal and adolescent depressive symptoms (95%CI: 0.046 9-0.077 2). The chain mediation of childhood trauma and ineffectiveness in the association between maternal depressive symptoms and adolescent suicidal ideation was also significant (95%CI: 0.000 7-0.001 3). CONCLUSIONS Higher maternal depressive symptom levels are associated with a greater likelihood of adolescents' exposure to childhood trauma, which increases adolescents' ineffectiveness and, in turn, is associated with suicidal ideation. This chain effect has important implications for social interventions targeting adolescent depression.
Humans ; Suicidal Ideation ; Adolescent ; Female ; Depression/etiology* ; Cross-Sectional Studies ; Mothers/psychology* ; Male ; Child ; Adult

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.