OBJECTIVE: To investigate the clinical features and risk factors associated with cutaneous chronic graft-versus-host disease (cGVHD) after allogeneic hematopoietic stem cell transplantation (allo-HSCT) in children. METHODS: A retrospective analysis was conducted on the clinical data of children who underwent allo-HSCT in the Wuhan Children's Hospital from August 1, 2016, to December 31, 2023, and were regularly followed up for 1 year or more. The differences in clinical features between children with and without cutaneous cGVHD were compared, and the risk factors affecting the occurrence of cutaneous cGVHD were analyzed. RESULTS: During the study period, 296 children received allo-HSCT. Until December 31, 2024, follow-up showed that 20 children (6.8%) developed cutaneous cGVHD, which manifested as cutaneous lichenification, hyperpigmentation, keratosis pilaris, sclerotic changes, and hair or nail involvement. According to their skin lesion area and degree of grading, 5 cases were mild, 10 cases were moderate, and 5 cases were severe. Multivariate logistic regression analysis revealed that female donors and previous acute GVHD were risk factors for the development of cutaneous cGVHD after allo-HSCT. All 20 children were treated with glucocorticoid ± calcineurin inhibitors (tacrolimus/cyclosporine) as first-line therapeutic agents. Only 1 child improved after first-line treatment. The remaining 19 children treated with a second-line regimen of combination interventions based on individualized status, including 10 children who could not tolerate hormonotherapy or first-line treatment, and showed no significant improvement after 3 months, as well as 9 children with multi-organ cGVHD. After comprehensive second-line treatment, 17 children showed improvement in cutaneous symptoms. There were 3 deaths, including 1 due to primary disease recurrence and 2 due to pulmonary infections. CONCLUSION The skin is the first manifestation and most common organ involved in cGVHD in children. Cutaneous cGVHD severely affects the daily activities of transplanted children and requires prolonged immunosuppressive therapy, but has a favorable prognosis. First-line treatments for adults are not applicable to children who usually require a combination treatment with multiple drugs.
Humans ; Graft vs Host Disease/etiology* ; Hematopoietic Stem Cell Transplantation/adverse effects* ; Retrospective Studies ; Risk Factors ; Female ; Child ; Skin Diseases/etiology* ; Chronic Disease ; Transplantation, Homologous ; Male ; Child, Preschool ; Adolescent

Fusion variations of neurotrophic receptor tyrosine kinase (NTRK) are oncogenic drivers in various solid tumors such as breast cancer, salivary gland carcinoma, infant fibrosarcoma, etc. Gene rearrangements involving NTRK1/2/3 lead to constitutive activation of the tropomyosin receptor kinase (TRK) domain, and the expressed fusion proteins drive tumor growth and survival. NTRK fusions are estimated to occur at a frequency of approximately 0.1% to 1% in non-small cell lung cancer (NSCLC). Epidermal growth factor receptor (EGFR) mutations are prevalent in NSCLC, but the frequency of EGFR G719A mutation is relatively low (about 2%), and EGFR mutations are typically mutually exclusive with NTRK fusion variants. The study presented the first documented case of lung adenocarcinoma harboring both EGFR G719A mutation and LMNA-NTRK1 fusion. A review of the literature was conducted to elucidate the role of NTRK fusion mutations in NSCLC and their relationship with EGFR mutations, aiming to enhance the understanding of NTRK fusion mutations in NSCLC.
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Humans ; Adenocarcinoma/genetics* ; Adenocarcinoma of Lung ; ErbB Receptors/genetics* ; Lamin Type A/genetics* ; Lung Neoplasms/genetics* ; Mutation ; Oncogene Proteins, Fusion/genetics* ; Receptor, trkA/metabolism*

eIF3a is a N ⁶-methyladenosine (m⁶A) reader that regulates mRNA translation by recognizing m⁶A modifications of these mRNAs. It has been suggested that eIF3a may play an important role in regulating translation initiation via m⁶A during infection when canonical cap-dependent initiation is inhibited. However, the death of animal model studies impedes our understanding of the functional significance of eIF3a in immunity and regulation in vivo. In this study, we investigated the in vivo function of eIF3a using eIF3a knockout and knockdown mouse models and found that eIF3a deficiency resulted in splenic tissue structural disruption and multi-organ damage, which contributed to severe sepsis induced by Lipopolysaccharide (LPS). Ectopic eIF3a overexpression in the eIF3a knockdown mice rescued mice from LPS-induced severe sepsis. We further showed that eIF3a maintains a functional and healthy immune system by regulating B cell function and quantity through m⁶A modification of mRNAs. These findings unveil a novel mechanism underlying sepsis, implicating the pivotal role of B cells in this complex disease process regulated by eIF3a. Furthermore, eIF3a may be used to develop a potential strategy for treating sepsis.

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

Xiaoaiping (XAP) Injection demonstrates the anti-prostate cancer (PCa) effects, yet the underlying mechanism remains unclear. This study aims to investigate the impact of XAP on PCa and elucidate its mechanism of action. PCa cell proliferation was evaluated using a cell counting kit-8 (CCK-8) assay. Cell apoptosis was assessed through Hoechst staining and Western blotting assays. Proteomics technology was employed to identify key molecules and significant signaling pathways modulated by XAP in PCa cells. To further validate potential key genes and important pathways, a series of assays were conducted, including acridine orange (AO) staining, transmission electron microscopy, and immunofluorescence assays. The molecular mechanism of XAP against PCa in vivo was examined using a PC3 xenograft mouse model. Results demonstrated that XAP significantly inhibited cell proliferation in multiple PCa cell lines. In C4-2 and prostate cancer cell line-3 (PC3) cells, XAP induced cellular apoptosis, evidenced by reduced B-cell lymphoma 2 (Bcl-2) levels and elevated Bcl-2-associated X (Bax) levels. Proteomic, immunofluorescence, and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) investigations revealed a strong correlation between forkhead box O3a (FoxO3a) autophagic degradation and the anti-PCa action of XAP. XAP hindered autophagy by reducing the expression levels of autophagy-related protein 5 (Atg5)/autophagy-related protein 12 (Atg12) and enhancing FoxO3a expression and nuclear translocation. Furthermore, XAP exhibited potent anti-PCa action in PC3 xenograft mice and triggered FoxO3a nuclear translocation in tumor tissue. These findings suggest that XAP induces PCa apoptosis via inhibition of FoxO3a autophagic degradation, potentially offering a novel perspective on XAP injection as an effective anticancer therapy for PCa.
Male ; Humans ; Prostatic Neoplasms/physiopathology* ; Autophagy/drug effects* ; Animals ; Drugs, Chinese Herbal/pharmacology* ; Proteomics ; Mice ; Apoptosis/drug effects* ; Cell Line, Tumor ; Cell Proliferation/drug effects* ; Forkhead Box Protein O3/genetics* ; Xenograft Model Antitumor Assays ; Mice, Nude ; Mice, Inbred BALB C

Background::In vitro fertilization (IVF) has emerged as a transformative solution for infertility. However, achieving favorable live-birth outcomes remains challenging. Current clinical IVF practices in IVF involve the collection of heterogeneous embryo data through diverse methods, including static images and temporal videos. However, traditional embryo selection methods, primarily reliant on visual inspection of morphology, exhibit variability and are contingent on the experience of practitioners. Therefore, an automated system that can evaluate heterogeneous embryo data to predict the final outcomes of live births is highly desirable. Methods::We employed artificial intelligence (AI) for embryo morphological grading, blastocyst embryo selection, aneuploidy prediction, and final live-birth outcome prediction. We developed and validated the AI models using multitask learning for embryo morphological assessment, including pronucleus type on day 1 and the number of blastomeres, asymmetry, and fragmentation of blastomeres on day 3, using 19,201 embryo photographs from 8271 patients. A neural network was trained on embryo and clinical metadata to identify good-quality embryos for implantation on day 3 or day 5, and predict live-birth outcomes. Additionally, a 3D convolutional neural network was trained on 418 time-lapse videos of preimplantation genetic testing (PGT)-based ploidy outcomes for the prediction of aneuploidy and consequent live-birth outcomes.Results::These two approaches enabled us to automatically assess the implantation potential. By combining embryo and maternal metrics in an ensemble AI model, we evaluated live-birth outcomes in a prospective cohort that achieved higher accuracy than experienced embryologists (46.1% vs. 30.7% on day 3, 55.0% vs. 40.7% on day 5). Our results demonstrate the potential for AI-based selection of embryos based on characteristics beyond the observational abilities of human clinicians (area under the curve: 0.769, 95% confidence interval: 0.709–0.820). These findings could potentially provide a noninvasive, high-throughput, and low-cost screening tool to facilitate embryo selection and achieve better outcomes. Conclusions::Our study underscores the AI model’s ability to provide interpretable evidence for clinicians in assisted reproduction, highlighting its potential as a noninvasive, efficient, and cost-effective tool for improved embryo selection and enhanced IVF outcomes. The convergence of cutting-edge technology and reproductive medicine has opened new avenues for addressing infertility challenges and optimizing IVF success rates.

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.

The immune microenvironment plays a key role in the development and progression of tumors.In recent years,with the rapid advancement of high-throughput sequencing technologies,researchers have gained a deeper under-standing of the composition and function of immune cells in the tumor microenvironment.However,traditional bulk sequenc-ing technologies are limited in resolving heterogeneity at the single-cell level,constraining a comprehensive understanding of the complexity of the tumor microenvironment.The advent of single-cell RNA sequencing technology has brought new opportunities to uncover the heterogeneity of the immune microenvironment in lung cancer.Currently,T-cell-centered im-munotherapy in clinical settings is prone to side effects affecting prognosis,such as immunogenic drug resistance or immune-related pneumonia,with the key factor being changes in the interactions between immune cells and tumor cells in the tumor microenvironment.Single-cell RNA sequencing technology can reveal the origins and functions of different subgroups within the tumor microenvironment from perspectives such as intercellular interactions and pseudotime analysis,thereby discovering new cell subgroups or novel biomarkers,providing new avenues for uncovering resistance to immunotherapy and monitoring therapeutic efficacy.This review comprehensively discusses the newest research techniques and advancements in single-cell RNA sequencing technology for unveiling the heterogeneity of the tumor micro environment after lung cancer immunotherapy,offering insights for enhancing the precision and personalization of immunotherapy.

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 influencing factors of depressive symptoms and to construct and verify the prediction model of depressive symptoms in middle school students, so as to provide risk assessment tools for effectively screening depressive symptom. Methods: Physical examination and questionnaire survey were conducted among middle school students in one city in Guangdong Province from September to October in 2021 ( n =2 376) and from September to October in 2022 ( n =4 344) by a multistage cluster sampling method, and a nomographic prediction model of depressive symptoms in middle school student was constructed. The questionnaire survey was conducted using the student health status and influencing factors questionnaire (secondary school version) and the Center for Epidemiological Studies Depression Scale (CES-D) to measure the lifestyle and depressive symptom of middle school students. Results: The detection rate of depressive symptoms in 2021 was 23.3%. Multivariate Logistic regression analysis showed that irregular breakfast ( OR =2.64), school bullying ( OR =4.28), being beaten by parents ( OR =2.86), using mobile devices for a long time ( OR =1.08) and sitting for a long time ( OR =1.05) were positively related to depressive symptoms in middle school students ( P <0.05). Long sleep duration ( OR =0.78) and outdoor activity durations of 1-<2, 2-<3 and ≥3 h/d (compared with <1 h/d, OR =0.63, 0.61, 0.49) were negatively related to depressive symptoms in middle school students ( P < 0.05 ). Multivariate Logistic regression analysis showed that 7 statistically signifucant predictive factors constructed a nomogram, and the AUC of the nomogram was 0.77, which had been verified internally and externally with good differentiation and reliability. Conclusions The nomogram prediction model of depressive symptoms provides a convenient and effective risk assessment tool for depressive symptoms among middle school students. The life behavior, diet behavior and injury behavior of middle school students play an important role in the formation of depressive symptoms. It should pay attention to the impact of the behavioral factors on the mental health of middle school students.