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.

Biliary tract cancers (BTC), a heterogeneous disease with poor prognosis, including gallbladder cancer (GBC), intrahepatic cholangiocarcinoma (ICC), and extrahepatic cholangiocarcinoma (ECC). Although surgery is currently the primary regimen to treat BTC, most BTC patients are diagnosed at an advanced stage and miss the opportunity of surgical eradication. As a result, non-surgical therapy serves as the main intervention for advanced BTC. In recent years, immunotherapy has emerged as one of the most promising therapies in a number of solid cancers, and it includes immune checkpoint inhibitors (ICIs) monotherapy or combined therapy, tumor vaccines, oncolytic virus immunotherapy, adoptive cell therapy (ACT), and cytokine therapy. However, these therapies have been practiced in limited clinical settings in patients with BTC. In this review, we focus on the discussion of latest advances of immunotherapy in BTC and update the progress of multiple current clinical trials with different immunotherapies.

Objective:To explore the understanding on health-related quality of life(HRQoL)among the Chinese populations and to develop a HRQoL conceptual framework that can be used to guide the development of Chinese HRQoL instruments.Methods:Respondents of Chinese general population and patients populations were recruited from 31 provinces in China.One-to-one semi-structured qualitative interviews were conducted to collect the views and perceptions on HRQoL.Based on the grounded theory,multi-level coding of qualitative interviews was carried out,and the framework method was used to sort out and summarize the coding to develop the HRQoL conceptual framework in China.Results:A total of 68 respondents were included in the study.The study extracted 1 558 open coding from the qualitative interview,which were analyzed and sorted into 180 axial coding and 31 selective coding(dimensions).The HRQoL conceptual framework for the Chinese population with 6 themes was finally summarized.Conclusions:The HRQoL conceptual framework based on the health concepts and preferences of the Chinese population contains 6 themes,refers to symptoms,physical function,emotion,cognition,activities and social function.In particular,the items of appetite,sleep and fatigue identifies may reflect Chinese cultural specific perceptions on important aspects of HRQoL.

Spinocerebellar ataxia (SCA) is a group of progressively aggravated neurodegenerative disease with autosomal dominant inheritance. Cerebellar ataxia is the core symptom, which may be accompanied by pyramidal tract signs, extrapyramidal signs, cognitive dysfunction and peripheral neuropathy. Although SCA can be accurately diagnosed by genetic testing, treatment is still difficult. We review the pathogenesis and therapeutic targets of SCA in recent years, in terms of genetic or gene regulation abnormalities, disruption of protein quality control (PQC) network, disruption of energy homeostasis, stability maintenance of PQC system, maintenance of cerebellar Purkinje cell function, and regulation of neuroinflammation, so as to promote the transformation of preclinical research into human therapy.

The global morbidity and mortality of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection are gradually decreasing,but the elderly people are still at higher risk of death than the general population,especially for those with Alzheimer's disease(AD).AD is a slowly progressing degenerative disease of the nervous system,and is the most common type of dementia.Its neuropathological features include overproduction and clea-rance imbalance of amyloid β-protein and overphosphorylated tau protein leading to neurofibrillary tangle.People with AD are more susceptible to be infected with SARS-CoV-2,likewise,the virus can also cause AD in those who are infected.After SARS-CoV-2 infection,it affects AD through immune response,inflammatory response,cell aging,DNA damage reaction,autophagy disorder,choroidal homeostasis disorder,over-activation of renin-angio-tensin system,and oxidative stress.This article mainly reviews the research progress in the effect of SARS-CoV-2 infection on AD.

Objective To explore the value of blood inflammatory load in predicting overall survival of elderly patients with epithelial ovarian cancer(EOC).Methods Elderly patients with EOC were selected,and their clinical data and peripheral blood parameters were collected.We constructed an inflammation-related blood scoring system using univariate and multivariate Cox regression analysis.The Kaplan-Meier method was used for survival analysis.We used Cox proportional hazards analysis to identify the independent prognostic factors.A nomogram model was constructed based on independent prognostic factors,and the receiver operating characteristic curve,C-index,and calibration curve were used to evaluate the model.Results Patients with high blood inflammatory load had worse prognosis(P=0.002).Compared with the low inflammatory load group,patients with high inflammatory load had later clinical stages and larger ascites volume(P<0.05).Cox regression analysis showed that ACCI,CA125,residual lesions,and blood score were independent factors affecting overall survival(P<0.05).Conclusion The blood inflammatory load is the biomarker for the prognosis of elderly patients with EOC.Scoring the inflammatory load in the blood can assist in efficacy monitoring and treatment intervention of ovarian cancer patients.