ObjectivePreeclampsia is a common and serious complication of pregnancy, posing a threat to maternal and fetal safety due to the lack of effective biomarkers and treatment strategies. This study aimed to identify potential biomarkers that can be used to predict preeclampsia and identify the molecular mechanisms of preeclampsia pathogenesis and drug prediction at the transcriptome level.MethodsWe analyzed differential expression genes (DEGs) in preeclampsia and non-preeclampsia groups in the GSE75010 dataset, cross-linking with extracted inflammatory response-related genes to obtain differentially expressed inflammation-related genes (DINRGs). Enrichment analysis and protein-protein interaction (PPI) networks were constructed to understand the functions and enrichment pathways. Machine learning models were used to identify key genes associated with preeclampsia and build a nomogram in the training set, which was validated in the validation set. The R package RcisTarget was used to predict transcription factors, and Cytoscape was used to construct miRNA-mRNA pathways, which could identify the molecular mechanisms. Then, we conducted molecular docking of the obtained key genes INHBA (inhibin subunit beta A), OPRK1 (opioid receptor kappa 1), and TPBG (trophoblast glycoprotein), as well as predicted transcription factors with drug molecules. Additionally, the CIBERSORT method explored the differences in immune cell infiltration between preeclampsia and non-preeclampsia samples based on the GSE75010 dataset.ResultsA total of 69 DINRGs associated with preeclampsia patients were screened. INHBA, OPRK1, and TPBG were the key genes based on machine learning models. A nomogram for prediction was further constructed, and the receiver operating curves (ROCs) showed good performance. Based on the transcriptome level of key genes, we proposed that RELA-miR-548K/miR-1206-TPBG may be a potential RNA regulatory pathway regulating the progression of early preeclampsia. Molecular docking suggested the effectiveness of curcumin in the treatment of preeclampsia. Additionally, regulatory T cells (Tregs) and resting mast cells were significantly different between the two groups.ConclusionIn summary, we identified three key inflammation-associated genes, namely INHBA, OPRK1, and TPBG, which can be used as potential genetic biomarkers for preeclampsia prediction and treatment, and established a nomogram as a predictive model. Additionally, we provided insights into the mechanisms of preeclampsia development at the transcriptome level and performed corresponding drug predictions.

Background: T-cell immunoglobulin and mucin domain-containing molecule-3 (TIM-3) was originally found to negatively regulate immune response and mediate immune escape in tumors. Subsequently, an increasing body of evidence has shown that TIM-3 exerts positive functions in the development and progression of several tumors. However, the role of TIM-3 in nasopharyngeal carcinoma (NPC) remains unknown. Methods: Data from the Cancer Genome Atlas-head and neck squamous cell carcinoma and immunohistochemistry were analyzed to compare the expression of TIM-3 in NPC and noncancerous nasopharyngitis tissues. Cell proliferation was evaluated using the Cell counting kit-8 in vitro and xenograft experiment in nude mice in vivo. Flow cytometry was used to evaluate the cell cycle. The migration and invasion of NPC cells were assessed through wound healing and Transwell assays. In addition, Western blotting was used to analyze the expression of specific proteins. Results: Higher expression of TIM-3 was detected in NPC tissues than normal nasopharyngeal tissues and positively correlated with the clinical stage and T classification; however, it was not correlated with gender, age, and N classification. Furthermore, overexpression of TIM-3 using lentiviral vectors increased the malignancy of 6-10B and CNE-2 cell lines that lowly express TIM-3, by promoting cell proliferation, migration, and invasion in vitro and in vivo. In addition, overexpression of TIM-3 was associated with upregulation of matrix metalloproteinase 9 (MMP9) and MMP2, and led to epithelial-mesenchymal transition (EMT) by increasing the levels of mesenchymal markers (ie, N-cadherin, Vimentin) and decreasing those of the epithelial marker E-cadherin. Further study showed that SMAD7 was downregulated in the TIM-3 overexpression group. Relatively, phosphorylated SMAD2 and downstream molecule SNAIL1 were also upregulated in this group. Conclusion: TIM-3 exerts a tumor-promoting function in NPC by mediating changes in the SMAD7/SMAD2/SNAIL1 axis. These findings provide a new idea for the study of invasion, metastasis, and treatment of NPC.

BackgroundMalignant transformation of deep infiltrating endometriosis (DIE) invading the cervix and rectum is quite rare, especially in patients combined with Lynch syndrome (LS). We report a rare case of a 49-year-old perimenopausal woman with endometrioid carcinoma arising from the pouch of Douglas, invading the cervix and rectum 1 year after a unilateral salpingo-oophorectomy treatment for ovarian endometriosis. The genetic testing of the patient showed germline mutations in MSH2, which combined with the special family history of colorectal cancer of the patient, was also thought to be associated with LS. We have analyzed the reported cases of DIE malignant transformation over the last 10 years, and reviewed the relevant literature, in order to strengthen the clinical management of patients with endometriosis, particularly patients with DIE, and reveal a possible correlation between malignant transformation of endometriosis and LS.Case PresentationA 49-year-old perimenopausal woman presented with hypogastralgia, diarrhea, and intermittent fever for more than 1 month. A Transvaginal ultrasound (TVS) showed a cervix isthmus mass, and a magnetic resonance imaging (MRI) showed a mass in pouch of Douglas with high suspicion of malignancy, possibly invading the anterior wall of the rectum. Prior to surgery, the patient performed the ultrasound guided pelvic mass biopsy through the vagina, and the pathology of the mass showed endometrioid carcinoma. The patient received a gynecological–surgical laparotomy and enterostomy, and a histopathology revealed endometrioid carcinoma infiltrating the cervical wall and rectal wall. In the family genetic history of the patient, her mother and two sisters suffered from colorectal cancer, so lesion tissue and blood were taken for genetic testing, which showed a germline mutation in MSH2, with LS being considered. After the surgical treatment, the patient received six courses of paclitaxel–carboplatin chemotherapy. During the course of treatment, bone marrow suppression occurred, but was healed after symptomatic treatment. To date, the patient is generally in good health, and imaging examination showed no evidence of recurrence.ConclusionThe risk of malignant transformation of endometriosis is increased in perimenopause and postmenopause, as DIE is a rare malignant transformation of endometriosis. DIE can invade other adjacent organs and cause poor prognosis, thus, comprehensive gynecological–surgical treatment should be necessary. In addition, if histopathology showed endometrioid carcinoma, the possibility of LS should be considered, and if necessary, immunohistochemical staining and gene detection should be improved to provide follow-up targeted therapy and immunotherapy.

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Unlike optical satellites, synthetic aperture radar (SAR) satellites can operate all day and in all weather conditions, so they have a broad range of applications in the field of ocean monitoring. The ship targets’ contour information from SAR images is often unclear, and the background is complicated due to the influence of sea clutter and proximity to land, leading to the accuracy problem of ship monitoring. Compared with traditional methods, deep learning has powerful data processing ability and feature extraction ability, but its complex model and calculations lead to a certain degree of difficulty. To solve this problem, we propose a lightweight YOLOV5-MNE, which significantly improves the training speed and reduces the running memory and number of model parameters and maintains a certain accuracy on a lager dataset. By redesigning the MNEBlock module and using CBR standard convolution to reduce computation, we integrated the CA (coordinate attention) mechanism to ensure better detection performance. We achieved 94.7% precision, a 2.2 M model size, and a 0.91 M parameter quantity on the SSDD dataset.

BackgroundGiven the increasing number and survival rates of reproductive-age patients with chronic myeloid leukemia (CML), several studies aimed to elucidate optimum disease management in pregnancy. This study aimed to use bibliometric analysis to assess focus and reported insights, as well as future trends, in CML and pregnancy research.MethodsWe extracted all studies related to CML and pregnancy from the Web of Science database from 2001 to 2020. VOS Viewer, CiteSpace, Python, and R-bibliometrix were used for bibliometric analysis, revealing the leading research countries, institutions, and authors, as well as distribution of keywords (frequency greater than five).ResultsA total of 196 records, published in 137 journals by 1,105 authors from 421 research institutes in 50 countries, were identified for analysis. The United States was the leader in the number of publications. Imperial College London and National Research Center for Hematology were the most influential institutions. In addition, Apperley J, Cortes J, Abruzzese E and Kantarjian H were the leading authors in the field. Keyword analysis identified four research hotspot clusters.ConclusionsThis study systematically analyzed the progress in CML and pregnancy research in the last 20 years. The present findings suggest that the management of planned and unplanned pregnancies in patients with CML will remain a research focus, as further evidence is required for the development of treatment guidelines.

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