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.

ObjectiveTo evaluate the clinical efficacy and safety of Huaban Jiedu Formulation （化斑解毒方， HJF） in treating psoriasis vulgaris with blood-heat syndrome. MethodsA randomized， double-blind， placebo-controlled study was conducted with 60 patients diagnosed with psoriasis vulgaris of blood-heat syndrome. Patients were randomly assigned to either a treatment group or a control group， with 30 cases in each. The treatment group received HJF granules orally， one dose a day， combined with topical Qingshi Zhiyang Ointment （青石止痒软膏）， while the control group received placebo granules， one dose a day， combined with the same topical ointment. Both groups were topically treated twice daily of 28 days treatment cours. Psoriasis area and severity index （PASI）， visual analogue scale for pruritus （VAS）， traditional Chinese medicine （TCM） syndrome scores， dermatology life quality index （DLQI）， and psoriasis life stress inventory （PLSI） were assessed before treatment and on day 14 and day 28. Response rates for PASI 50 （≥50% reduction） and PASI 75 （≥75% reduction）， as well as overall clinical efficacy， were compared between groups. Serum levels of interleukin-6 （IL-6） and interleukin-17 （IL-17） were measured before and after 28 days of treatment. Adverse reactions during treatment were recorded. ResultsAfter 28 days of treatment， both groups showed significant reductions in PASI total score， lesion area score， erythema， scaling， and infiltration scores， pruritus VAS score， TCM syndrome score， DLQI， PLSI， and serum IL-6 and IL-17 levels （P＜0.05）. Compared to the control group， the treatment group had significantly greater improvements in PASI total score and erythema score， TCM syndrome score， serum IL-6 and IL-17 levels， and PASI 50 response rate after 28 days （P＜0.05）. Between-group comparisons of score differences before and after 28-day treatment revealed that the treatment group showed significantly better improvements in PASI total， lesion area score， erythema score， TCM syndrome score， DLQI， PLSI， and inflammatory markers （P＜0.05 or P＜0.01）. The total effective rate on day 14 and day 28 was 40.00% （12/30） and 83.33% （25/30） in the treatment group， versus 6.90% （2/29） and 41.38% （12/29） in the control group， respectively. The clinical efficacy in the treatment group was significantly superior to that in the control group （P＜0.05）. Mild gastric discomfort occurred in 3 patients in the treatment group and 1 in the control group. ConclusionHJF can effectively improve skin lesions and TCM symptoms relieve pruritus， enhance quality of life， and reduce inflammatory markers IL-6 and IL-17， in patients with blood-heat syndrome of psoriasis vulgaris， with a good safety profile.

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.

Di-(2-ethylhexyl) phthalate (DEHP) is currently one of the most widely used plasticizers, widely found in all kinds of items, such as children’s toys and food packaging materials, but also added to wallpaper, cable protective agents and other building decoration materials. DEHP is toxic and absorbed by the human body through respiratory tract, digestive tract and skin contact, which can cause damage to multiple systems, especially the male reproductive system, and testis is an important target organ. Oxidative stress injury is the core mechanism of spermatogenesis disorder caused by DEHP. DEHP exposure can cause oxidative stress or reactive oxygen species (ROS) increase in germ cells, and on this basis, promote cell apoptosis or cause excessive autophagy. The toxicity of DEHP to Leydig cells is mainly to interfere with the synthesis of steroid hormones. For Sertoli cells, ferroptosis and destruction of the blood-testis barrier are common injury mechanisms. In addition, gene methylation caused by DEHP not only affects the spermatogenic process, but also has epigenetic effects on offspring. In this paper, we reviewed the pathological damage, germ cell toxicity and epigenetic effects of DEHP on testis, and focused on the damage and molecular mechanism on testicular spermatogenic cells, Leydig cells and Sertoli cells. Future research is required to elucidate the body’s clearance mechanism and treatment plan after exposure to DEHP and whether DEHP will damage the function of myoid cells. It is hoped that this can provide new ideas for prevention and treatment of male reproductive disorders resulting from long-term exposure to plastic products.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.

Objective To analyze the competition status and spatial autocorrelation of Beijing medical market from 2015 to 2019.Methods The Herfindahl-Hirschman Index(HHI)was used to calculate the degree of market competi-tion in 16 districts of Beijing,and the Moran index was used to calculate the spatial autocorrelation of market compe-tition.Results Except for the number of discharged patients,the average HHI of the number of health technicians,the number of beds and the total number of medical visits in 16 medical markets in Beijing from 2015 to 2019 showed a downward trend between 0.2 and 0.4,and the spatial global Moran index of the HHI index was all less than 0,showing a spatial negative correlation with the degree of competition in the medical market.Conclusion The medical market competition in Beijing is strengthened,the competition gap between urban and rural areas is large,and the competition in adjacent markets is mutually exclusive.It is suggested to strengthen the differentiated develop-ment of hospitals,strengthen the balanced layout between regions,and promote the low-competitive market with cross-regional medical association,forming a positive spillover effect.

Objective Space radiation is an important environmental factor affecting the health and efficiency of astronauts.To explore the effects of radiation on electroencephalogram(EEG)signal,and to provide references for further study of the effects of radiation on Central Nervous System(brain)injury.Methods The resting state EEG of radiotherapy volunteers were collected before and after X-ray exposure.The effects of radiation on EEG was studied by means of spectral analysis,nonlinear dynamic characteristic analysis,correlation coefficient analysis and microstate analysis.Results The results show that radiation induced a"slow wave"phenomenon in the EEG spectrum,with a decrease in Gravity Frequency,Sample Entropy,and Lempel-Ziv Complexity,and an increase in Fatigue Index.The average duration and frequency of EEG microstate C both significantly decreased,and the proportion of time for microstate D decreased,while the average correlation coefficient between microstates A and C increased.Conclusion A decrease was induced by radiation in neuronal excitability,which may affect cognitive brain networks and brain attention.This study can provide reference for the study of radiation damage to the Central Nervous System(brain).

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Objective This study aims at establishing a teaching catalog and content for breast rare dis-eases and developing the syllabus for the breast rare disease using integrated multimodality of case-/problem-/resource-based learning(CBL+PBL+RBL).Methods By conducting bibliometrics co-occurrence analysis,we collected 6291 articles on breast rare disease published from January,1975 to June,2024.Additionally,we re-trieved the Textbook on Rare Diseases,the Catalog of Chinese Rare Disease,and Second Batch of Rare Dis-ease Catalog and then decided the teaching content.Results From 16,387 keywords,1000(6.1％)keywords were identified through co-occurrence analysis,including 50(0.3％)candidate diseases.These were classified into three categories:rare primary breast diseases,rare genetic mutation-related diseases associated with breast cancer,and rare systemic multi-system diseases involving the breast.From the candidate list,20(0.1％)rare primary breast diseases were further selected for their notable clinical teaching significance,and significant multi-systemic diseases affecting the breast,whether related to gene mutations or not.Teaching plans were draf-ted using a diversified parallel teaching approaches,taking into account the characteristics of different diseases and the focus of different teaching methods.Conclusions This study initiated the development of the teaching content for breast rare diseases and developed the teaching syllabus using the CBL+PBL+RBL integrated multi teaching model and targeting each rare breast disease for the critical point for teaching.

Lactic acid produced by muscles during exercise training is transported to the liver for metabolism through the bloodstream.In this process,the lactate acid level increases with the increase of exercise intensity,and the concentration of lactate acid in interstitial matrix of muscle tissues increases subsequently,leading to muscle fatigue.Transcutaneous electrical nerve stimulation(TENS)is a widely used medical method for muscle relaxation and improving peripheral blood circulation.To monitor the potential of TENS to alleviate muscle fatigue,this study adopted electrical impedance tomography(EIT)method to visualize the alleviating effect of TENS on muscle fatigue by detecting the tissue electrical characteristics response caused by the changes in blood lactate concentration,a biomarker of muscle fatigue.An experimental platform was thus constructed to mimic the changes of blood lactate concentration(Cbl)in the muscle tissue model,and to measure the trend of the spatial-mean conductivity((σ))in the mimic model during the Cbl change.The blood flow velocity was closely related to the metabolic rate of the lactate in the blood.TENS could speed up blood flow and effectively reduced the lactate accumulation in muscle tissue.However,too fast blood flow velocity was prone to cause secondary ventricular fibrillation disease,which threatened the safety of human life.To avoid this threat,a real-time blood flow velocity mimic platform was developed in this study to monitor the(σ)changes caused by the changes in blood flow velocity(vph)in the vicinity of mimic blood vessels.The correlations between Cbl vs(σ),and vph vs(σ)in the mimic muscle tissue were verified by Pearson test.Pearson correlation analysis results showed a positive correlation between Cbl and(σ)(r=0.9113,p<0.05),and betweenvph and(σ)(r=0.9782,p<0.001).The approach presented here quantitatively assessed the potential of TENS stimulation-induced changes in lactate concentration and blood flow velocity for alleviating muscle fatigue through(σ).