The development of organ transplantation has brought new hope to many patients with organ failure and their families， but it has also raised numerous ethical issues. How to balance the rights and interests between organ donors and recipients， as well as ensure the fairness and transparency of the transplantation process has become an urgent problem to be solved. Based on the latest Regulations on Organ Donation and Transplantation and the Working Rules of the Ethics Committee for Human Organ Transplantation， the current difficulties and challenges in organ transplantation ethics were deeply analyzed. Taking the ethical review practice of Shenzhen Third People’s Hospital as an example， this paper explored issues such as full informed consent of both donors and recipients， risk assessment of marginal donors， and the review of relationships between donors and recipients. It also explored and constructed a set of complete ethical review models for organ transplantation through refined management. This model improved the efficiency and quality of ethical review as well as enriched the related knowledge system. It is expected that the implementation of this model can provide a reference for promoting effective ethical review nationwide， advancing the improvement and development of ethical review work in organ transplantation. Meanwhile， more medical ethics experts and practitioners are called upon to focus on and engage in the research and practice of ethical review in organ transplantation， jointly promoting progress in this field.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

The AP2/ERF transcription factor family is a class of transcription factors widely present in plants, playing a crucial role in regulating flowering, flower development, flower opening, and flower senescence. Based on transcriptome data from flower, leaf, and stem samples of two Lonicera macranthoides varieties, 117 L. macranthoides AP2/ERF family members were identified, including 14 AP2 subfamily members, 61 ERF subfamily members, 40 DREB subfamily members, and 2 RAV subfamily members. Bioinformatics and differential gene expression analyses were performed using NCBI, ExPASy, SOMPA, and other platforms, and the expression patterns of L. macranthoides AP2/ERF transcription factors were validated via qRT-PCR. The results indicated that the 117 LmAP2/ERF members exhibited both similarities and variations in protein physicochemical properties, AP2 domains, family evolution, and protein functions. Differential gene expression analysis revealed that AP2/ERF transcription factors were primarily differentially expressed in the flowers of the two L. macranthoides varieties, with the differentially expressed genes mainly belonging to the ERF and DREB subfamilies. Further analysis identified three AP2 subfamily genes and two ERF subfamily genes as potential regulators of flower development, two ERF subfamily genes involved in flower opening, and two ERF subfamily genes along with one DREB subfamily gene involved in flower senescence. Based on family evolution and expression analyses, it is speculated that AP2/ERF transcription factors can regulate flower development, opening, and senescence in L. macranthoides, with ERF subfamily genes potentially serving as key regulators of flowering duration. These findings provide a theoretical foundation for further research into the specific functions of the AP2/ERF transcription factor family in L. macranthoides and offer important theoretical insights into the molecular mechanisms underlying floral phenotypic differences among its varieties.
Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Transcription Factors/chemistry* ; Lonicera/classification* ; Flowers/metabolism* ; Phylogeny ; Gene Expression Profiling ; Multigene Family

This article reports a child with cardioaciocutaneous syndrome (CFCS) caused by a rare microdeletion of chromosome 19p13.3, and a literature review is conducted. The child had unusual facies, short stature, delayed mental and motor development, macrocephaly, and cardiac abnormalities. Whole-exome sequencing identified a 1 040 kb heterozygous deletion in the 19p13.3 region of the child, which was rated as a "pathogenic variant". This is the first case of CFCS caused by a loss-of-function mutation reported in China, which enriches the genotype characteristics of CFCS. It is imperative to enhance the understanding of CFCS in children. Early identification based on its clinical manifestations should be pursued, and genetic testing should be performed to facilitate diagnosis.
Humans ; Chromosome Deletion ; Chromosomes, Human, Pair 19/genetics* ; Ectodermal Dysplasia/genetics* ; Facies ; Failure to Thrive/genetics* ; Heart Defects, Congenital/genetics*

AIM: To evaluate the performance of three distinct large language models(LLM), including GPT-3.5, GPT-4, and PaLM2, in responding to queries within the field of ophthalmology, and to compare their performance with three different levels of medical professionals: medical undergraduates, master of medicine, and attending physicians.METHODS: A total of 100 ophthalmic multiple-choice tests, which covered ophthalmic basic knowledge, clinical knowledge, ophthalmic examination and diagnostic methods, and treatment for ocular disease, were conducted on three different kinds of LLM and three different levels of medical professionals(9 undergraduates, 6 postgraduates and 3 attending physicians), respectively. The performance of LLM was comprehensively evaluated from the aspects of mean scores, consistency and confidence of response, and it was compared with human.RESULTS: Notably, each LLM surpassed the average performance of undergraduate medical students(GPT-4:56, GPT-3.5:42, PaLM2:47, undergraduate students:40). Specifically, performance of GPT-3.5 and PaLM2 was slightly lower than those of master's students(51), while GPT-4 exhibited a performance comparable to attending physicians(62). Furthermore, GPT-4 showed significantly higher response consistency and self-confidence compared with GPT-3.5 and PaLM2.CONCLUSION: LLM represented by GPT-4 performs well in the field of ophthalmology, and the LLM model can provide clinical decision-making and teaching aids for clinicians and medical education.

Objective:To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application.Methods:This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis.Results:The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group ( χ2=5.560, P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group ( χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion:SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.

Objective:To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application.Methods:This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis.Results:The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group ( χ2=5.560, P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group ( χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion:SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.

Objective:To explore the causes of platelet aggregation in version 6.4 Trima Accel automated blood collection system and the effect of 2 intervention measures.Methods:The data on platelet aggregation(n=61)and non-aggregation(n=323)of 61 donors in 2020 were collected and the causes of aggregation were analyzed.Then the 72 donors with platelet aggregation in 2021 were randomized into intervention group A(increasing the anticoagulant-to-blood ratio)and intervention group B(wrapping the donor's arm with an electric blanket to keep warm and improve the blood flow speed).The collection time,average blood flow speed,number of machine alarms,anticoagulant usage,deaggregation and citrate reaction of the two groups were compared.Results:Platelet aggregation was negatively correlated with the average blood flow speed(r=-0.394)and positively correlated with the collection time(r=0.458).The equations for predicting aggregation and non-aggregation were constructed based on Bayesian and Fisher discriminant analysis,and the predicted accuracy was 77.1％.The comparison of the effects of two intervention measures showed that the average blood flow speed in group B was higher than that in group A;the collection time,number of machine alarms,anticoagulant usage and proportion of citrate reaction in blood donors in group B were all lower than those in Group A,all these differences were significant(P＜0.05).In the entire cohort in 2021,90.28％of the products were immediately deaggregated after collection,and 9.72％of the products were deaggregated within 4 hours.There was no statistically significant difference in deaggregation between the two intervention groups(P＞0.05).Conclusion:During apheresis platelet collection,the predictive equations for aggregation and non-aggregation can be used to predict the occurrence probability of aggregation,and the intervention can be made in advance.Both intervention measures are effective in reducing platelet aggregation,however,measure B has the advantages of improving the speed of blood collection,shortening the collection time,reducing the alarm frequency and the anticoagulant usage,and reducing the incidence of citrate reaction in blood donors.

Objective:To investigate the evaluation efficacy and predictive prognostic value of alpha-fetoprotein (AFP) response in tyrosine kinase inhibitors (TKIs) in combination with PD-1 inhibitors (α-PD-1) for intermediate-to-advanced hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 205 patients with intermediate-to-advanced HCC who were admitted to 9 medical centers, including Mengchao Hepatobiliary Hospital of Fujian Medical University et al, from March 2020 to July 2022 were collected. There were 178 males and 27 females, aged (52±12)years. Based on AFP response at 6-8 weeks after treatment, patients were divided into the AFP response group (AFP level decreased by ≥50% compared to baseline) and the AFP no response group (AFP level decreased by <50% compared to baseline). Observation indicators: (1) AFP response evaluation of anti-tumor efficacy; (2) comparison of patient prognosis; (3) analysis of factors affecting patient prognosis. Measurement data with normal distrubution were represented as Mean± SD, and measurement data with skewed distribution were represented as M(range) and M( Q1, Q3). Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. The Kaplan-Meier method was used to draw survival curve and calculate survival rate, and the Log-Rank test was used for survival analysis. The COX proportional risk model was used for univariate analysis and the COX stepwise regression model was used for multivariate analysis. Results:(1) AFP response evaluation of anti-tumor efficacy. Before treatment, all 205 patients were positive of AFP, with a baseline AFP level of 1 560(219,3 400)μg/L. All 205 patients were treated with TKIs in combination with α-PD-1, and the AFP level was 776(66,2 000)μg/L after 6 to 8 weeks of treatment. Of the 205 patients, 88 cases were classified as AFP response and 117 cases were classified as AFP no response. According to the response evaluation criteria in solid tumors version 1.1, the objective response rate (ORR) and disease control rate (DCR) were 42.05%(37/88) and 94.32%(83/88) in patients of the AFP response group and 16.24% (19/117) and 64.10% (75/117) in patients of the AFP no response group, showing significant differences between them ( χ2=16.846, 25.950, P<0.05). According to the modified response evaluation criteria in solid tumors, the ORR and DCR were 69.32% (61/88) and 94.32% (83/88) in patients of the AFP response group and 33.33% (39/117) and 64.10% (75/117) in patients of the AFP no response group, showing significant differences between them ( χ2=26.030, 25.950, P<0.05). (2) Comparison of patient prognosis. All 205 patients were followed up for 12.4(range, 2.4-34.0)months after treatment. The median progression free survival time and total survival time were 5.5 months and 17.8 months, respectively. The 1-year, 2-year progression free survival rates were 20.8% and 7.2%, and the 1-year, 2-year overall survival rates were 68.7% and 31.5%, respectively. The median progression free survival time, 1-year and 2-year progression free survival rates were 9.7 months, 39.6% and 14.2% in patients of the AFP response group and 3.7 months, 7.8% and 2.0% in patients of the AFP no response group, showing a significant difference in progression free survival between them ( χ2=43.154, P<0.05). The median overall survival time, 1-year and 2-year overall survival rates were not reached, 85.2% and 56.3% in patients of the AFP response group and 14.6 months, 56.3% and 14.5% in patients of the AFP no response group, showing a significant difference in overall survival between them ( χ2=33.899, P<0.05). (3) Analysis of factors affecting patient prognosis. Results of multivariate analysis showed that invasion of large blood vessels, extrahepatic metastasis, combined hepatic artery intervention therapy, and AFP response were independent factors influencing progression free survival in patients with intermediate-to-advanced HCC who were treated with TKIs in combination with α-PD-1 ( hazard ratio=1.474, 1.584, 0.631, 0.367, 95% confidence interval as 1.069-2.033, 1.159-2.167, 0.446-0.893, 0.261-0.516, P<0.05), and Eastern Cooperative Oncology Group score, invasion of large blood vessels, extrahepatic metastasis, and AFP response were independent factors influencing overall survival in patients with intermediate-to-advanced HCC who were treated with TKIs in combination with α-PD-1 ( hazard ratio= 1.347, 1.914, 1.673, 0.312, 95% confidence interval as 1.041-1.742, 1.293-2.833, 1.141-2.454, 0.197-0.492, P<0.05). Conclusions:AFP response at 6-8 weeks after treatment can effectively evaluate anti-tumor efficacy of TKIs in combination with α-PD-1 for intermediate-to-advanced HCC. AFP response is the independent factor influencing progression free survival and overall survival in patients with intermediate-to-advanced HCC who were treated with TKIs in combination with α-PD-1.