SUN5 interacts with nuclear membrane LaminB1 and cytoskeletal GTPase Septin12 mediating the sperm head-and-tail junction.

Acephalic spermatozoa syndrome (ASS) is a severe teratospermia with decaudated, decapitated, and malformed sperm, resulting in male infertility. Nuclear envelope protein SUN5 localizes to the junction between the sperm head and tail. Mutations in the SUN5 gene have been identified most frequently (33-47%) in ASS cases, and its molecular mechanism of action is yet to be explored. In the present study, we generated Sun5 knockout mice, which presented the phenotype of ASS. Nuclear membrane protein LaminB1 and cytoskeletal GTPases Septin12 and Septin2 were identified as potential partners for interacting with SUN5 by immunoprecipitation-mass spectrometry in mouse testis. Further studies demonstrated that SUN5 connected the nucleus by interacting with LaminB1 and connected the proximal centriole by interacting with Septin12. The binding between SUN5 and Septin12 promoted their aggregation together in the sperm neck. The disruption of the LaminB1/SUN5/Septin12 complex by Sun5 deficiency caused separation of the Septin12-proximal centriole from the nucleus, leading to the breakage of the head-to-tail junction. Collectively, these data provide new insights into the pathogenesis of ASS caused by SUN5 deficiency.

Artificial intelligence model system for bone age assessment of preschool children.

BACKGROUD: Our study aimed to assess the impact of inter- and intra-observer variations when utilizing an artificial intelligence (AI) system for bone age assessment (BAA) of preschool children. METHODS: A retrospective study was conducted involving a total sample of 53 female individuals and 41 male individuals aged 3-6 years in China. Radiographs were assessed by four mid-level radiology reviewers using the TW3 and RUS-CHN methods. Bone age (BA) was analyzed in two separate situations, with/without the assistance of AI. Following a 4-week wash-out period, radiographs were reevaluated in the same manner. Accuracy metrics, the correlation coefficient (ICC)and Bland-Altman plots were employed. RESULTS: The accuracy of BAA by the reviewers was significantly improved with AI. The results of RMSE and MAE decreased in both methods (p < 0.001). When comparing inter-observer agreement in both methods and intra-observer reproducibility in two interpretations, the ICC results were improved with AI. The ICC values increased in both two interpretations for both methods and exceeded 0.99 with AI. CONCLUSION: In the assessment of BA for preschool children, AI was found to be capable of reducing inter-observer variability and enhancing intra-observer reproducibility, which can be considered an important tool for clinical work by radiologists. IMPACT: The RUS-CHN method is a special bone age method devised to be suitable for Chinese children. The preschool stage is a critical phase for children, marked by a high degree of variability that renders BA prediction challenging. The accuracy of BAA by the reviewers can be significantly improved with the aid of an AI model system. This study is the first to assess the impact of inter- and intra-observer variations when utilizing an AI model system for BAA of preschool children using both the TW3 and RUS-CHN methods.

SUN5, a testis-specific nuclear membrane protein, participates in recruitment and export of nuclear mRNA in spermatogenesis.

SUN5, a testis-specific gene, is associated with acephalic spermatozoa syndrome (ASS). Here, we demonstrate that Sun5 is involved in mRNA export. In Sun5-knockout mice ( Sun5 -/-), poly(A) + RNA accumulates in the nuclei of germ cells, leading to reduced sperm counts, decreased sperm motility and disrupted sperm head-to-tail junctions. Additionally, in the GC-2 germ cell line with RNA interference of Sun5, heterogeneous nuclear ribonucleoproteins (hnRNPs) and poly (A) + RNA (mainly mRNA) are retained in the nucleus. Further mechanistic studies reveal that Sun5 interacts with Nxf1 (nuclear RNA export factor 1) and nucleoporin 93 (Nup93). Interference with Nup93 inhibits mRNA export. Treatment with leptomycin B to block the CRM1 pathway indicates that Sun5 regulates mRNA export through an Nxf1-dependent pathway. In Sun5 -/- mice, the binding of Nxf1 and Nup93 decreases due to loss of Sun5 function, and the process of submitting Nxf1-binding mRNPs to Nup93 is inhibited, resulting in abnormal spermatogenesis. Together, these data may elucidate a novel pathway for mRNA export in male germ cells.

A combination of radiomic features, clinic characteristics, and serum tumor biomarkers to predict the possibility of the micropapillary/solid component of lung adenocarcinoma.

BACKGROUND: Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment. OBJECTIVE: This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers. DESIGN: A retrospective case control, diagnostic accuracy study. METHODS: This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21-83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines. RESULTS: The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively. CONCLUSION: This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

A new tool to predict aggressive lung cancer types before surgeryWe developed a tool to help doctors determine whether lung cancer is one of the more dangerous types, called micropapillary (MPP) or solid (SOL) patterns, before surgery. These patterns can be more harmful and spread quickly, so knowing they are there can help doctors plan the best treatment. We looked at the cases of 273 lung cancer patients who had surgery and found that 61 of them had these aggressive cancer types. To predict these patterns, we used a computer process known as logistic regression, analyzing CT scan details, health information, and blood tests for cancer markers. Based on CT scans, our tool was very good at predicting whether these patterns were present in two patient groups. However, predictions using only basic health information like the size of the tumor and whether the patient smoked needed to be more accurate. We found a way to make our predictions even better. Combining all information into one chart, known as a nomogram, significantly improved our ability to predict these dangerous cancer patterns. This combined chart could be a big help for doctors. It gives them a clearer picture of the cancer's aggressiveness before surgery, which can guide them to choose the best treatment options. This approach aims to offer a better understanding of the tumor, leading to more tailored and effective treatments for patients facing lung cancer.

A combinatorial MRI sequence-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer.

This study aimed to develop an optimal radiomics model for preoperatively predicting microsatellite instability (MSI) in patients with rectal cancer (RC) based on multiparametric magnetic resonance imaging. The retrospective study included 308 RC patients who did not receive preoperative antitumor therapy, among whom 51 had MSI. Radiomics features were extracted and dimensionally reduced from T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), diffusion-weighted imaging (DWI), and T1-weighted contrast enhanced (T1CE) images for each patient, and the features of each sequence were combined. Multifactor logistic regression was used to screen the optimal feature set for each combination. Different machine learning methods were applied to construct predictive MSI status models. Relative standard deviation values were determined to evaluate model performance and select the optimal model. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses were performed to evaluate model performance. The model constructed using the k-nearest neighbor (KNN) method combined with T2WI and T1CE images performed best. The area under the curve values for prediction of MSI with this model were 0.849 (0.804-0.887), with a sensitivity of 0.784 and specificity of 0.805. The Delong test showed no significant difference in diagnostic efficacy between the KNN-derived model and the traditional logistic regression model constructed using T1WI + DWI + T1CE and T2WI + T1WI + DWI + T1CE data (P > 0.05) and the diagnostic efficiency of the KNN-derived model was slightly better than that of the traditional model. From ROC curve analysis, the KNN-derived model significantly distinguished patients at low- and high-risk of MSI with the optimal threshold of 0.2, supporting the clinical applicability of the model. The model constructed using the KNN method can be applied to noninvasively predict MSI status in RC patients before surgery based on radiomics features from T2WI and T1CE images. Thus, this method may provide a convenient and practical tool for formulating treatment strategies and optimizing individual clinical decision-making for patients with RC.

Hsa_circ_0081065 exacerbates IH-induced EndMT via regulating miR-665/HIF-1α signal axis and HIF-1α nuclear translocation.

CircRNAs play an important role in various physiological and pathological biological processes. Despite their widespread involvement, the function of circRNAs in intermittent hypoxia (IH) remain incompletely understood. This study aims to clarify the molecular mechanism of it in IH. Differentially expressed circRNAs were identified by transcriptome sequencing analysis in intermittent hypoxia (IH) model. GO and KEGG enrichment analys were performed on the identified differentially expressed circRNAs. The circular characteristics of hsa_circ_0081065 in human umbilical vein endothelial cells (HUVECs) were detected by RT-qPCR. The sublocalization of hsa_circ_0081065 was examined by FISH. The effect of hsa_circ_0081065 on endothelial to mesenchymal transition (EndMT) was estimated by detecting the expression of EndMT related markers. Various techniques, including RNA-pull down, RIP, EMSA, dual-luciferase reporter assay and immunofluorescence staining were used to investigate the relationship among hsa_circ_0081065, miR-665 and HIF-1α. A total of 13,304 circRNAs were identified in HUVECs treatment with IH, among which 73 were differentially expressed, including 24 upregulated circRNAs and 49 downregulated circRNAs. Notably, hsa_circ_0081065 demonstrated a significantly upregulation. Hsa_circ_0081065 exhibited the circular characteristics of circRNA and was predominantly localized in the cytoplasm. Knockdown of hsa_circ_0081065 inhibited EndMT. Mechanically, we demonstrated that hsa_circ_0081065 acts as a sponge for miR-665 to up-regulate HIF-1α and exacerbate HIF-1α nuclear translocation in HUVECs. We have demonstrated that hsa_circ_0081065 is significantly upregulated in HUVECs treated with IH. Our findings indicate that hsa_circ_0081065 exacerbates IH-induced EndMT through the regulation of the miR-665/HIF-1α signal axis and facilitating HIF-1α nuclear translocation. These results provide a theoretical basis for considering of EndMT as a potential therapeutic target for OSAHS intervention.

Deep-learning-based 3D super-resolution CT radiomics model: Predict the possibility of the micropapillary/solid component of lung adenocarcinoma.

Objective: Invasive lung adenocarcinoma（ILA） with micropapillary (MPP)/solid (SOL) components has a poor prognosis. Preoperative identification is essential for decision-making for subsequent treatment. This study aims to construct and evaluate a super-resolution（SR） enhanced radiomics model designed to predict the presence of MPP/SOL components preoperatively to provide more accurate and individualized treatment planning. Methods: Between March 2018 and November 2023, patients who underwent curative intent ILA resection were included in the study. We implemented a deep transfer learning network on CT images to improve their resolution, resulting in the acquisition of preoperative super-resolution CT (SR-CT) images. Models were developed using radiomic features extracted from CT and SR-CT images. These models employed a range of classifiers, including Logistic Regression (LR), Support Vector Machines (SVM), k-Nearest Neighbors (KNN), Random Forest, Extra Trees, Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Multilayer Perceptron (MLP). The diagnostic performance of the models was assessed by measuring the area under the curve (AUC). Result: A total of 245 patients were recruited, of which 109 (44.5 %) were diagnosed with ILA with MPP/SOL components. In the analysis of CT images, the SVM model exhibited outstanding effectiveness, recording AUC scores of 0.864 in the training group and 0.761 in the testing group. When this SVM approach was used to develop a radiomics model with SR-CT images, it recorded AUCs of 0.904 in the training and 0.819 in the test cohorts. The calibration curves indicated a high goodness of fit, while decision curve analysis (DCA) highlighted the model's clinical utility. Conclusion: The study successfully constructed and evaluated a deep learning（DL）-enhanced SR-CT radiomics model. This model outperformed conventional CT radiomics models in predicting MPP/SOL patterns in ILA. Continued research and broader validation are necessary to fully harness and refine the clinical potential of radiomics when combined with SR reconstruction technology.

miR-26a-5p protects against myocardial ischemia/reperfusion injury by regulating the PTEN/PI3K/AKT signaling pathway

Reperfusion strategies in acute myocardial infarction (AMI) can cause a series of additional clinical damage, defined as myocardial ischemia/reperfusion (I/R) injury, and thus there is a need for effective therapeutic methods to attenuate I/R injury. miR-26a-5p has been proven to be an essential regulator for biological processes in different cell types. Nevertheless, the role of miR-26a-5p in myocardial I/R injury has not yet been reported. We established an I/R injury model in vitro and in vivo. In vitro, we used cardiomyocytes to simulate I/R injury using hypoxia/reoxygenation (H/R) assay. In vivo, we used C57BL/6 mice to construct I/R injury model. The infarct area was examined by TTC staining. The level of miR-26a-5p and PTEN was determined by bioinformatics methods, qRT-PCR, and western blot. In addition, the viability and apoptosis of cardiomyocytes were separately detected by MTT and flow cytometry. The targeting relationship between miR-26a-5p and PTEN was analyzed by the TargetScan website and luciferase reporter assay. I/R and H/R treatment induced myocardial tissue injury and cardiomyocyte apoptosis, respectively. The results showed that miR-26a-5p was down-regulated in myocardial I/R injury. PTEN was found to be a direct target of miR-26a-5p. Furthermore, miR-26a-5p effectively improved viability and inhibited apoptosis in cardiomyocytes upon I/R injury by inhibiting PTEN expression to activate the PI3K/AKT signaling pathway. miR-26a-5p could protect cardiomyocytes against I/R injury by regulating the PTEN/PI3K/AKT pathway, which offers a potential approach for myocardial I/R injury treatment.