Objective To investigate the impact of intraoperative red blood cell (RBC) transfusion volume on the postoperative oxygenation index in lung transplant recipients. Methods This retrospective study analyzed the clinical data of patients who underwent lung transplantation at Wuxi People's Hospital Affiliated to Nanjing Medical University from 2021 to 2023. Patients were divided into a non-severe primary graft dysfunction (PGD) group and a severe PGD group based on whether their postoperative oxygenation index was>200 mm Hg at 0, 24, and 48 h. General patient data and intraoperative RBC transfusion volumes were compared between the two groups. A binary logistic regression model was constructed to explore the effect size (OR and its 95%CI) of RBC transfusion volume on postoperative oxygenation status at different time points (0, 24, and 48 h). The area under the receiver operating characteristic curve was calculated to evaluate the model's diagnostic performance. Results A total of 351 patients were included (260 males, 91 females), with ages ranging from 20 to 77 years. The OR for the effect of intraoperative RBC transfusion on poor oxygenation was 1.486 (95%CI 0.982 to 2.248, P=0.061) at 0 h postoperatively, 3.111 (95%CI 1.793 to 5.399, P<0.001) at 24 h, and 1.583 (95%CI 1.026 to 2.442, P=0.038) at 48 h. This indicated that as time progressed, the postoperative oxygenation status of lung transplant recipients was affected by the intraoperative transfusion volume. Furthermore, an RBC transfusion volume>975 mLhad a significant impact on patient oxygenation at 24 and 48 h postoperatively. Conclusion The volume of intraoperative RBC transfusion has a significant impact on the oxygenation status at 24 and 48 h postoperatively. Intraoperative RBC transfusion volume is associated with the occurrence of severe PGD after lung transplantation. Controlling the volume of RBC transfusion during lung transplantation may help reduce the incidence of severe PGD.

With the development of artificial intelligence， machine learning has shown great potential in the field of medical health. Machine learning conducts a comprehensive analysis of patient data including clinical features， blood tests， and imaging examinations and establishes corresponding mathematical models to achieve the diagnosis and treatment of diseases and the prediction of disease conditions， thereby guiding disease management. With reference to the latest research findings， this article reviews the application of machine learning in chronic hepatitis C and related research advances.

[Objective] To retrospectively analyze the detection results of alanine aminotransferase (ALT) unqualified repeat blood donors in Guangzhou, so as to provide evidence for further expanding the repeat blood donor pool, reducing the rate of blood discarding and improving the qualified rate of blood test. [Methods] Blood donors with unqualified ALT in Guangzhou Blood Center from January 2018 to April 2024 were selected as the research objects. The past blood donation and population characteristics were analyzed according to the number of blood donations and ALT unqualified times. [Results] Among repeat blood donors with previous ALT disqualification, 99.5% to 99.7% did not have reactive markers for transfusion-transmitted diseases (TTD), which was higher than the rate among first-time blood donors with unqualified ALT (95.8%) (P<0.05). The rate of single-item ALT disqualification in repeat blood donors was higher in males than in females (P<0.05); it also varied by age (18-25 years > 26-35 years > 36-45 years > over 45 years) (P<0.05); and by quarter (third and fourth quarters > first and second quarters) (P<0.05). The ALT unqualified rate was significantly higher whole blood donors than that of platelet donors and returning blood donors (P<0.05). The overall ALT level (51.0 U/L), individual ALT level (56.0 U/L) and individual ALT unqualified rate (66.7%) of repeat blood donors with multiple ALT disqualifications were higher than those of repeat blood donors with single-item ALT disqualifications (26.0 U/L, 38.5 U/L, and 33.3%, respectively) (P<0.05). Moreover, as the number of ALT disqualifications increased, the overall level of ALT in repeat blood donors also increased (P<0.05), and the average level of individual ALT and individual ALT unqualified ratio tended to increase. Repeat blood donors with frequent ALT disqualifications had higher ALT levels (69.0 U/L). [Conclusion] The ALT unqualified rates of repeat blood donors were mostly non-specific elevation without TTD. Repeat blood donors with multiple ALT disqualifications tend to have continuous high ALT. Moreover, and with the increase of ALT disqualifications times, the overall ALT levels the average individual ALT levels and individual ALT unqualified rates showed an increasing trend.

In 2025， Severe Liver Disease and Artificial Liver Group and Nutrition and Regeneration in End-Stage Liver Disease Group of Chinese Society of Hepatology， Chinese Medical Association， convened a panel of national experts to jointly develop China’s first guideline for the diagnosis and treatment of acute-on-chronic liver failure （ACLF）. Based on the latest research findings and clinical practice in China and globally， this guideline establishes a standardized definition of ACLF and provide recommendations for its diagnosis， treatment， and clinical management. This article gives an interpretation of the key points in the guideline， in order to provide a reference for standardized diagnosis and treatment of ACLF.

ObjectiveTo establish and validate a new prediction model for the risk of death in patients with acute-on-chronic liver failure （ACLF） based on sarcopenia and other clinical indicators， and to improve the accuracy of prognostic assessment for ACLF patients. MethodsA total of 380 patients with ACLF who were admitted to Beijing YouAn Hospital， Capital Medical University， from January 2019 to January 2022 were enrolled， and they were divided into training group with 228 patients and testing group with 152 patients in a ratio of 6∶4 using the stratified random sampling method. For the training group， CT images were used to measure the cross-sectional area of the skeletal muscle at the third lumbar vertebra （L3）， and L3 skeletal muscle index （L3-SMI） was calculated. Sarcopenia was diagnosed based on the previously established L3-SMI reference values for healthy adults in northern China. Univariate and multivariable Cox regression analyses were used to establish a sarcopenia-ACLF model which integrated sarcopenia and clinical risk factors， and a nomogram was developed for presentation. The area under the ROC curve （AUC） was used to assess the predictive performance of the model， the calibration curve was used to assess the degree of calibration， and a decision curve analysis was used to investigate the clinical application value of the model. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. The Kaplan-Meier method was used to plot survival curves， and the Log-rank test was used for comparison between groups. The DeLong test was used for comparison of AUC between different models. ResultsThe multivariate Cox regression analysis showed that sarcopenia （hazard ratio ［HR］=1.962， 95% confidence interval ［CI］： 1.185‍ ‍—‍ ‍3.250， P=0.009）， total bilirubin （HR=1.003， 95%CI： 1.002‍ ‍—‍ ‍1.005， P<0.001）， international normalized ratio （HR=1.997， 95%CI： 1.674‍ ‍—‍ ‍2.382， P<0.001）， and lactic acid （HR=1.382， 95%CI： 1.170‍ ‍—‍ ‍1.632， P<0.001） were included in the sarcopenia-ACLF model. In the training cohort， the sarcopenia-ACLF model had a larger AUC than MELD-Na score in predicting 90-day mortality in patients with ACLF （0.80 vs 0.73， Z=1.97， P=0.049）. In the test cohort， the sarcopenia-ACLF model had a significantly larger AUC than MELD score （0.79 vs 0.69， Z=2.70， P=0.007） and MELD-Na score （0.79 vs 0.68， Z=2.92， P=0.004）. The calibration curve showed that the model had good calibration ability， with a relatively good consistency between the predicted risk of mortality and the observed results. The DCA results showed that within a reasonable range of threshold probabilities， the sarcopenia-ACLF model showed a greater net benefit than MELD and MELD-Na scores in both the training cohort and the test cohort. ConclusionThe sarcopenia-ACLF model developed in this study provides a more accurate tool for predicting the risk of 90-day mortality in ACLF patients， which provides support for clinical decision-making and helps to optimize treatment strategies.

Objective To explore the application effect of prone position ventilation combined with veno-venous extracorporeal membrane oxygenation (VV-ECMO) in the treatment of severe primary graft dysfunction (PGD) after lung transplantation. Methods The clinical data of 75 lung transplant recipients who developed severe PGD after lung transplantation and were treated with VV-ECMO from January 2021 to June 2024 at Wuxi People's Hospital Affiliated to Nanjing Medical University were collected. The patients with severe graft dysfunction after lung transplantation were divided into VV-ECMO group (control group, 45 cases) and prone position ventilation combined with VV-ECMO group (treatment group, 30 cases). The general data of the two groups of patients were compared, including the donors' clinical data (age, gender and oxygenation index, etc) and the recipients' clinical data [gender, age and body mass index (BMI), etc]. Cox regression analysis was used to analyze the influencing factors of the recipients' 30-day, 90-day and 180-day survival after surgery. The survival curves of the two groups of recipients were drawn using Kaplan-Meier method and compared using the log-rank test. Results The intensive care unit (ICU) stay time, ECMO application time and ventilator use time of control group were longer than those of treatment group. The proportion of male recipients and the BMI of control group were lower than those of treatment group. The 30-day, 90-day and 180-day survival of control group was worse than that of treatment group, and the differences were statistically significant (all P<0.05). The univariate Cox regression analysis of the recipients' 30-day survival after surgery showed that the recipients' BMI, history of diabetes, enlargement of the right atrium and right ventricle, intraoperative blood transfusion volume and intraoperative red blood cell transfusion volume were statistically significant (all P<0.05). The multivariate Cox regression analysis showed that the history of diabetes and enlargement of the right atrium and right ventricle were risk factors affecting the 30-day survival of lung transplant recipients (all P<0.05). The univariate Cox regression analysis of the recipients' 90-day survival after surgery showed that the recipients' BMI, history of diabetes, enlargement of the right atrium and right ventricle, intraoperative blood transfusion volume, intraoperative red blood cell transfusion volume and group variable were statistically significant (all P<0.05). The multivariate Cox regression analysis showed that the history of diabetes, enlargement of the right atrium and right ventricle and group variable were risk factors affecting the 90-day survival of lung transplant recipients (all P<0.05). The univariate Cox regression analysis of the recipients' 180-day survival after surgery showed that the recipients' BMI, history of diabetes, right atrium and right ventricle enlargement, intraoperative blood transfusion volume, intraoperative red blood cell transfusion volume and group variable were statistically significant (all P<0.05). The multivariate Cox regression analysis showed that the history of diabetes, enlargement of the right atrium and right ventricle and group variable were risk factors affecting the 180-day survival of lung transplant recipients (all P<0.05). The 30-day, 90-day and 180-day survival rates of control group were lower, and the differences between the two groups were statistically significant (all P<0.05), with a median survival time of 100 days in control group. Conclusions In the clinical treatment of severe PGD after lung transplantation, prone position ventilation combined with VV-ECMO may shorten ECMO application time, invasive ventilation time and ICU stay time, and improve the short-term prognosis of lung transplantation.

In order to accurately capture the respiratory muscle movement and extract the synchronization signals corresponding to the breathing phases, a comprehensive signal sensing system for sensing the movement of the respiratory muscle was developed with applying the thin-film varistor FSR402 IMS-C07A in this paper. The system integrated a sensor, a signal processing circuit, and an application program to collect, amplify and denoise electronic signals. Based on the respiratory muscle movement sensor and a STM32F107 development board, an experimental platform was designed to conduct experiments. The respiratory muscle movement data and respiratory airflow data were collected from 3 healthy adults for comparative analysis. In this paper, the results demonstrated that the method for determining respiratory phase based on the sensing the respiratory muscle movement exhibited strong real-time performance. Compared to traditional airflow-based respiratory phase detection, the proposed method showed a lead times ranging from 33 to 210 ms [(88.3 ± 47.9) ms] for expiration switched into inspiration and 17 to 222 ms [(92.9 ± 63.8) ms] for inspiration switched into expiration, respectively. When this system is applied to trigger the output of the ventilator, it will effectively improve the patient-ventilator synchrony and facilitate the ventilation treatment for patients with respiratory diseases.
Humans ; Respiratory Muscles/physiology* ; Signal Processing, Computer-Assisted ; Movement/physiology* ; Respiration ; Monitoring, Physiologic/methods* ; Adult

In the century-long evolution of insulin pharmaceuticals, each transformative advancement in this drug class has been closely tied to the ability to obtain new insulin isoforms for research. Despite this, the recently discovered naturally occurring isoforms of glycosylated human insulin have remained largely unattainable for proper characterization. Herein, we demonstrate for the first time that total chemical synthesis can be used to generate all isoforms. This achievement required maintaining the correct positions of the interchain disulfide bonds while effectively removing protecting groups on complex glycans. Notably, the availability of seven glycoforms reveals the important effects of natural sialylated glycans in suppressing insulin self-association and enhancing its solubility, surpassing the performance of currently employed rapid-acting insulin drugs. This work not only offers a readily adaptable platform for exploring natural O-glycosylation in other therapeutic proteins and peptides but also lays the groundwork for further research into harnessing natural glycosylation for therapeutic applications.

Objective Electrocardiogram(ECG)signal quality degrades when the level of activity is high and motion artifacts are severe.Poor quality signals may result in false alarms,poor patient monitoring,imprecise measurement,and misleading diagnosis.The quantitative assessment of ECG signal quality forms the basis of automatic ECG noise reduction and heart disease diagnosis.Methods The ECG signal quality index(SQI)was obtained by statistically analyzing the heartbeat similarity and the slope character,respectively,namely rSQI and kSQI.Results Using MIT-BIH Noise Stress Test Database to test,both rSQI and kSQI decreased when the Signal Noise Ratio(SNR)decreased,which revealed the ECG signal quality.Based on the quasiperiodic property,the waveform similarity,as a beat-to-beat index,is obtained by cross correlation between two ECG cycles with high precision but heavy computation.Slope-based method dispenses with QRS detection and is very simple and real-time,but its sensitivity is lower than similarity-based method and it only get statistical data.Conclusion Both morphology similarity and slope character algorithms could provide objective estimation of ECG quality.Slope-based method is an attractive measure due to its simplicity and mathematical convenience,while similarity-based method is more accurate and robust for ECG quality assessment.

Objective To explore the role in sleep staging from blood volume pulse(BVP)and triaxial acceleration(ACC)of body movement obtained by wristband.Methods The BVP and ACC obtained by Empatica E4 wristband were used from all 100 cases of sleep disorder subjects in the DREAMT public database.Two frequency domain characteristics(eS,LF/HF)and one time domain characteristic(vA)of the BVP baseline and the activity counts(CS)of the ACC were used for sleep-awakening classification based on random forest.Results The results of sleep-awakening classification of all 100 cases of sleep disorder subjects were obtained by leaving-one-out strategy.The accuracy is 79.8%and the Kappa coefficient is 0.56 by 4 features from BVP and ACC;the accuracy is 70.4%and the Kappa coefficient is 0.36 by 3 features of BVP;the accuracy is 75.1%and the Kappa coefficient is 0.47 based on activity counts.Conclusion The BVP and ACC obtained by the wristband can be used for the rough estimation of sleep and awakening for sleep disorder subjects,among which the importance of ACC is higher than that of BVP.