Objective: To explore the impact of sleep quality, experience of childhood maltreatment, and their interaction on depressive symptoms among middle school students, so as to provide the reference for early intervention of depressive symptoms among middle school students. Methods: From September to December 2023, a questionnaire survey was conducted among 1 231 students from two secondary schools in Harbin, Heilongjiang Province by a convenient sampling method. The survey included general demographic information, Childhood Trauma Questionnaire Short Form, Pittsburgh Sleep Quality Index and Short Version of Center for Epidemiological Studies Depression Scale. The Chi square test was used to analyze the differences in depressive symptom, sleep quality and childhood maltreatment among students with different demographic characteristics. Correlation analysis was conducted using Logistic regression, and interaction analysis was performed by both additive and multiplicative interaction models. Results: The detection rate of depressive symptoms among middle school students was 22.7%, and the rate for high school students (35.2%) was significantly higher than that for middle school students (17.0%) ( χ 2=50.35, P <0.01). The detection rates of depressive symptoms among middle school students with a history of childhood maltreatment and poor sleep quality were 45.8% and 44.0%, respectively. Multivariate Logistic regression analysis showed that compared to students without a history of childhood maltreatment, students with a history of childhood maltreatment had a higher risk of depressive symptoms ( OR =4.49，95% CI =3.31~ 6.09 , P <0.01);students with poor sleep quality had a higher risk of depressive symptoms than students with good sleep quality ( OR = 5.99，95% CI =4.37~8.22, P <0.01).The interaction results showed that the presence of childhood maltreatment and poor sleep quality had an additive interaction on the occurrence of depression in middle school students. Compared with students without childhood maltreatment and having good sleep quality, students with childhood maltreatment and poor sleep quality had a 22.49 times higher risk of developing depression ( OR =22.49，95% CI =14.22~35.59, P <0.01). Conclusion Depressive symptoms among middle school students are associated with childhood maltreatment and poor sleep quality, and there is an additive interaction between childhood maltreatment and poor sleep quality on the impact of depressive symptoms.

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.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Alzheimer's disease (AD) is the major form of dementia in the elderly and is closely related to the toxic effects of microglia sustained activation. In AD, sustained microglial activation triggers impaired synaptic pruning, neuroinflammation, neurotoxicity, and cognitive deficits. Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with regulating microglia function. Here, we use RNA sequencing to identify a deubiquitinase YOD1 as a regulator of microglial function and AD pathology. Further study showed that YOD1 knockout significantly improved the migration, phagocytosis, and inflammatory response of microglia, thereby improving the cognitive impairment of AD model mice. Through LC-MS/MS analysis combined with Co-IP, we found that Myosin heavy chain 9 (MYH9), a key regulator maintaining microglia homeostasis, is an interacting protein of YOD1. Mechanistically, YOD1 binds to MYH9 and maintains its stability by removing the K48 ubiquitin chain from MYH9, thereby mediating the microglia polarization signaling pathway to mediate microglia homeostasis. Taken together, our study reveals a specific role of microglial YOD1 in mediating microglia homeostasis and AD pathology, which provides a potential strategy for targeting microglia to treat AD.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract, which increases the incidence of colorectal cancer (CRC). In the pathophysiology of IBD, ubiquitination/deubiquitination plays a critical regulatory function. Josephin domain containing 2 (JOSD2), a deubiquitinating enzyme, controls cell proliferation and carcinogenesis. However, its role in IBD remains unknown. Colitis mice model developed by dextran sodium sulfate (DSS) or colon tissues from individuals with ulcerative colitis and Crohn's disease showed a significant upregulation of JOSD2 expression in the macrophages. JOSD2 deficiency exacerbated the phenotypes of DSS-induced colitis by enhancing colon inflammation. DSS-challenged mice with myeloid-specific JOSD2 deletion developed severe colitis after bone marrow transplantation. Mechanistically, JOSD2 binds to the C-terminal of inosine-5'-monophosphate dehydrogenase 2 (IMPDH2) and preferentially cleaves K63-linked polyubiquitin chains at the K134 site, suppressing IMPDH2 activity and preventing activation of nuclear factor kappa B (NF-κB) and inflammation in macrophages. It was also shown that JOSD2 knockout significantly exacerbated increased azoxymethane (AOM)/DSS-induced CRC, and AAV6-mediated JOSD2 overexpression in macrophages prevented the development of colitis in mice. These outcomes reveal a novel role for JOSD2 in colitis through deubiquitinating IMPDH2, suggesting that targeting JOSD2 is a potential strategy for treating IBD.

Long-term hypertension causes excessive vascular remodeling and leads to adverse cardiovascular events. Balance of ubiquitination and deubiquitination has been linked to several chronic conditions, including pathological vascular remodeling. In this study, we discovered that the expression of ubiquitin-specific protease 25 (USP25) is significantly up-regulated in angiotensin II (Ang II)-challenged mouse aorta. Knockout of Usp25 augments Ang II-induced vascular injury such as fibrosis and endothelial to mesenchymal transition (EndMT). Mechanistically, we found that USP25 interacts directly with Forkhead box O3 (FOXO3) and removes the K63-linked ubiquitin chain on the K258 site of FOXO3. We also showed that this USP25-mediated deubiquitination of FOXO3 increases its binding to light chain 3 beta isoform and autophagosomic-lysosomal degradation of FOXO3. In addition, we further validated the biological function of USP25 by overexpressing USP25 in the mouse aorta with AAV9 vectors. Our studies identified FOXO3 as a new substrate of USP25 and showed that USP25 may be a potential therapeutic target for excessive vascular remodeling-associated diseases.

Acetaminophen (APAP) is the primary cause of drug-induced acute liver failure. Ovarian tumor deubiquitinase 6A (OTUD6A), a recently discovered deubiquitinase of the OTU family, has been primarily studied in tumor contexts. However, its role in APAP-induced liver injury (AILI) remains unclear. Therefore, this study aimed to investigate the involvement of OTUD6A in the pathogenesis of AILI. Our findings demonstrated a substantial upregulation of OTUD6A in both the liver tissue and isolated hepatocytes of mice following APAP stimulation. OTUD6A knockout exacerbated APAP-induced inflammation, hepatocyte necrosis, and liver injury, whereas OTUD6A overexpression alleviated these pathologies. Mechanistically, OTUD6A directly interacted with the enhancer of zeste homolog 2 (EZH2) and selectively removed K48-linked polyubiquitin chains from EZH2, enhancing its stability. This resulted in increased protein levels of EZH2 and H3K27me3, as well as reduced endoplasmic reticulum (ER) stress and cell death in hepatocytes. Collectively, our research uncovers a novel role for OTUD6A in mitigating APAP-induced liver injury by promoting EZH2 stabilization.

Objective:To analyze the immune reconstitution after BTKi treatment in patients with chronic lymphocytic leukemia(CLL).Methods:The clinical and laboratorial data of 59 CLL patients admitted from January 2017 to March 2022 in Fujian Medical University Union Hospital were collected and analyzed retrospectively.Results:The median age of 59 CLL patients was 60.5(36-78).After one year of BTKi treatment,the CLL clones(CD5+/CD19+)of 51 cases(86.4％)were significantly reduced,in which the number of cloned-B cells decreased significantly from(46±6.1)× 109/L to(2.3±0.4)× 109/L(P=0.0013).But there was no significant change in the number of non-cloned B cells(CD19+minus CD5+/CD19+).After BTKi treatment,IgA increased significantly from(0.75±0.09)g/L to(1.31±0.1)g/L(P＜0.001),while IgG and IgM decreased from(8.1±0.2)g/L and(0.52±0.6)g/L to(7.1±0.1)g/L and(0.47±0.1)g/L,respectively(P＜0.001,P=0.002).BTKi treatment resulted in a significant change in T cell subpopulation of CLL patients,which manifested as both a decrease in total number of T cells from(2.1±0.1)× 109/L to(1.6±0.4)× 109/L and NK/T cells from(0.11±0.1)× 109/L to(0.07±0.01)× 109/L(P=0.042,P=0.038),both an increase in number of CD4+cells from(0.15±6.1)× 109/L to(0.19±0.4)× 109/L and CD8+cells from(0.27±0.01)× 109/L to(0.41±0.08)× 109/L(both P＜0.001).BTKi treatment also up-regulated the expression of interleukin(IL)-2 while down-regulated IL-4 and interferon(IFN)-γ.However,the expression of IL-6,IL-10,and tumor necrosis factor(TNF)-α did not change significantly.BTKi treatment could also restored the diversity of TCR and BCR in CLL patients,especially obviously in those patients with complete remission(CR)than those with partial remission(PR).Before and after BTKi treatment,Shannon index of TCR in patients with CR was 0.02±0.008 and 0.14±0.001(P＜0.001),while in patients with PR was 0.01±0.03 and 0.05±0.02(P＞0.05),respectively.Shannon index of BCR in patients with CR was 0.19±0.003 and 0.33±0.15(P＜0.001),while in patients with PR was 0.15±0.009 and 0.23±0.18(P＜0.05),respectively.Conclusions:BTKi treatment can shrink the clone size in CLL patients,promote the expression of IgA,increase the number of functional T cells,and regulate the secretion of cytokines such as IL-2,IL-4,and IFN-γ.BTKi also promote the recovery of diversity of TCR and BCR.BTKi treatment contributes to the reconstitution of immune function in CLL patients.

Objective:To explore the genotypes and frequency distribution of thalassemia in Lingui District,Guilin City,and provide reference for the prevention and control of thalassemia in this area. Methods:The results of genetic testing for thalassemia in 1501 suspected cases at the Second Affiliated Hospital of Guilin Medical University were analyzed retrospectively. The deletional mutations of α-thalassemia were detected by gap-PCR,the non-deletional mutations of α-thalassemia and β-thalassemia mutations were detected by PCR-reverse dot blot (PCR-RDB). Results:In 1501 samples,a total of 678 cases of thalassemia carriers were detected,with a detection rate of 45.17％. Among them,379 cases were α-thalassemia (including deletional α-thalassemia and non-deletional α-thalassemia),with a detection rate of 25.25％,the most common genotype was--SEA/αα (227 cases,15.12％),followed by-α3.7/αα (53 cases,3.53％). 270 cases of β-thalassemia were detected,with a detction rate of 17.99％,and βCD41-42/βN (144 cases,9.59％) was the main genotypes,followed by βCD17/βN (66 cases,4.40％) . In addition,there were 29 cases of αβ compound thalassemia,accounting for 1.93％,and the most common genotype was--SEA/αα complex βCD41-42/βN (5 cases,0.33％). Conclusion:Lingui District in Guilin City is a high-incidence area of thalassemia,and the genotypes of carriers are complex and diverse,with genetic heterogeneity. The results of this study provide a scientific basis for genetic counseling and prenatal diagnosis in this area.

Objective To investigate the effect of Anlotinib on proliferation and apoptosis in non-small cell lung cancer(NSCLC)cells and its molecular mechanism.Methods Non-small cell lung cancer cell lines A549 and H1299 were incubated with Anlotinib,miR-16-5p agonist and/or PD-1 overexpression vector respectively.CCK-8 assay and EDU assay were applied to detect the proliferation.Flow cytometry was performed to detect the cell apop-tosis.The relative expression of miR-16-5 p in A549 and H1299 was detected by real-time quantitative polymerase chain reaction(RT-qPCR).The relative protein expression of PD-1 in A549 and H1299 was detected by Western blot assay.The interaction between miR-16-5p and PD-1 was determined by dual luciferase reporter assay.Finally,A549 cell xenograft model was established to assess the effect of Anlotinib on tumor growth in vivo.Results Anlotinib significantly increased miR-16-5p expression and decreased PD-1 expression in A549 cells and H1299 cells,inhibited cell proliferation and promoted apoptosis in a dose-dependent manner(P＜0.05).The highly-expressed miR-16-5p inhibited proliferation and promoted cell apoptosis(P＜0.05).Also,miR-16-5p targeted at PD-1 and negatively regulated PD-1 expression.Knockdown of PD-1 inhibited proliferation and pro-moted cell apoptosis(P＜0.05).PD-1 over-expression reversed the Anlotinib-mediated pro-proliferation and anti-apoptosis of miR-16-5p in A549 cells and H1299 cells(P＜0.05).Anlotinib significantly reduced tumor growth in vivo(P＜0.05).Conclusions Anlotinib may inhibit cell proliferation,anti-apoptosis,and reduce tumor growth for NSCLC,which is involved in miR-16-5p/PD-1 axis.