Discovery medicine最新文献

Correction of Discovery Medicine 2023, 35 (179) https://www.discovmed.com/EN/10.24976/Discov.Med.202335179.90 The authors wish to make the following correction to this paper [1]: The authors would like to correct the name of their affiliated institution, the corrected author's affiliation is provided below: 1Department of Emergency Medicine, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, 210002 Nanjing, Jiangsu, China.

Background: High-mobility group box 1 (HMGB1) participates in the progression of osteosarcoma (OS) through the p38 mitogen-activated protein kinase (MAPK) signaling pathway. Corylin, one of the active components of Psoralea corylifolia L., has anti-oxidant, anti-inflammatory, and anti-tumor effects. This study investigates the association between corylin and HMGB1, and their impact and mechanism of action on OS.

Methods: OS cells and osteoblasts were transfected with/without HMGB1 overexpression plasmid and siHMGB1. Cell viability was examined using the Cell Counting Kit-8 (CCK-8) assay after treatment with corylin (0, 2.5, 5, 10, 30 μM). The effects of corylin on cell malignant behaviors were examined by cell function assays. The mRNA expression level of high-mobility group box 1 (HMGB1) was determined by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The protein levels of HMGB1, matrix metalloproteinase-2 (MMP-2), MMP-9, and alpha-smooth muscle actin (α-SMA) were measured by western blotting. The effects of corylin and HMGB1 on the expression of p38 MAPK signaling pathway-related proteins were also assessed.

Results: Corylin decreased OS cell viability, proliferation, migration, and invasion but increased apoptosis in a concentration-dependent manner. Corylin concentration-dependently suppressed the levels of HMGB1, MMP-2, MMP-9, and α-SMA. Overexpression of HMGB1 was partially reversed, while knockdown of HMGB1 enhanced the above effects of corylin.

Conclusion: Corylin inhibits OS cell migration and invasion through regulation of the HMGB1-mediated p38 MAPK signaling pathway.

Background: Lung cancer is one of the leading causes of cancer-related deaths worldwide, with treatment failure resulting from metastasis. C-X-C chemokine receptor type 4 (CXCR4) plays a crucial role in tumor cell migration and metastasis. Recent studies have suggested that the commonly used antiepileptic drug, carbamazepine (CBZ), may impede tumor metastasis; however, its specific mechanism remains unclear.

Methods: In this study, we evaluated the effects of CBZ on the migration and invasion of lung cancer cells through in vitro cell cultures and in vivo animal models. The regulatory effect of CBZ on CXCR4 expression was analyzed using western blot and reverse transcription-quantitative polymerase chain reaction techniques. To further validate whether CBZ's anti-metastatic effect is mediated through CXCR4, we used the CXCR4 agonist NUCC-390 and overexpression of the CXCR4 gene in lung cancer cell lines.

Results: The results demonstrated that CBZ significantly inhibited the migration and invasion of lung cancer cells (*p < 0.001). In animal experiments, CBZ treatment significantly reduced the extent of metastasis in the lungs (*p < 0.01). Moreover, CBZ downregulated the expression of CXCR4 (*p < 0.001). When NUCC-390 was used or CXCR4 was overexpressed, the anticancer effect of CBZ was reversed, indicating the anti-metastatic effect of CBZ is closely associated with its inhibition of CXCR4 expression.

Conclusion: This study reveals, for the first time, a novel mechanism by which CBZ inhibits lung cancer metastasis through the suppression of CXCR4 expression. These findings offer a new avenue for the treatment of lung cancer using CBZ as a potential agent against lung cancer metastasis. Further research is warranted to explore the clinical potential of CBZ and to offer more treatment options for lung cancer patients.

Background: Acute pancreatitis (AP) is a prevalent pathological condition of abdomen characterized by sudden onset, high incidence and complex progression. Timely assessment of AP severity is crucial for informing intervention decisions so as to delay deterioration and reduce mortality rates. Existing AP-related scoring systems can only assess current condition of patients and utilize only a single type of clinical data, which is of great limitation. Therefore, it is imperative to establish more accurate and data-compatible methods for predicting the severity of AP. The artificial intelligence (AI) algorithm based on artificial neural network (ANN) allow for the adaptive feature extraction for objective task through its internal complex network, instead of the hand-crafted methods commonly used in traditional machine learning (ML) algorithms. In this study, we delve into the final severity classification prediction of newly admitted AP patients, using deep learning (DL) algorithm to develop multi-view models, incorporated with patients' demographic information, vital signs, AP-related laboratory indexes and admission computed tomography (CT) images.

Methods: The pancreatitis database in the platform of Clinical Data Research Center of Acute Abdominal Surgery at the First Affiliated Hospital of Dalian Medical University was used to gather AP cases. Deep neural network (DNN) and convolutional neural network (CNN) were utilized to construct models. The DNN prediction models with clinical data as input, the CNN prediction models with admission CT as input, and the multi-view models combining the two inputs were respectively established to predict the severity of AP.

Results: DL models for AP severity classification based on clinical indexes, imaging data and merged data were constructed. The multi-view model based on merged data offered more accurate prediction of the final severity classification of AP, with an overall accuracy rate of 80.26% (95% confidence interval (CI): 79.58%-80.94%). The constituent accuracy rates for mild acute pancreatitis, moderately severe acute pancreatitis, and severe acute pancreatitis were 91.69% (95% CI: 87.80%-95.57%), 64.90% (95% CI: 58.85%-70.95%), and 75.56% (95% CI: 68.58%-82.53%), respectively.

Conclusion: The multi-view models using clinical indexes and imaging data as input outperform single-view models in AP severity prediction.

Background: Osteoporotic fractures (OPF) pose a public health issue, imposing significant burdens on families and societies worldwide. Currently, there is a lack of comprehensive and validated risk assessment models for OPF. This study aims to develop a model to assess and predict the risk of OPF in Qingdao City, China.

Methods: From January 2021 to January 2023, we recruited 84 osteoporotic patients diagnosed with fractures from Qingdao University Affiliated Hospital, Qingdao Municipal Hospital, Qingdao Hiser Hospital Affiliated of Qingdao University, and Qingdao Central Hospital as the experimental group. In addition, 112 osteoporotic patients without fractures were recruited as the control group. In this study, we employed seven machine learning models, namely Adaboost, random forest (RF), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Logistic Regression (LR), Naive Bayes (NB), and Gradient Boosting Decision Trees (GBDT), to analyze the risk factors influencing the occurrence of OPF. Next, we plotted receiver operating characteristic (ROC), Precision-Recall (PR), and calibration curves to evaluate the predictive values of the different risk assessment models for OPF.

Results: Among the seven models built based on the training set data, the Adaboost model showed area under the curve (AUC), sensitivity, and specificity values close to 1, indicating the best classification performance. In the test set, the AUC values for the RF, SVM, LR, KNN, NB, AdaBoost, and GBDT models were 0.936, 0.905, 0.88, 0.93, 0.862, 0.939, and 0.859, respectively (p < 0.001). All sensitivity and specificity values for these models were higher than 0.8, with sensitivity and specificity values of the Adaboost model closest to 1. Additionally, six models had an area under the Precision-Recall curve (prAUC) values higher than 0.9, except KNN at 0.284 (p < 0.001). The calibration curves of the seven models did not significantly deviate from the ideal curve, indicating acceptable discriminative ability and predictive performance of the predictive model. All results showed that trabecular bone score (TBS) was the most important variable affecting the model, followed by osteocalcin (OST) and hunchback.

Conclusions: Given the various clinical data from patients with OPF, we assessed and demonstrated the good predictive performance of our risk predictive models. This model will enable us to take timely intervention measures to reduce the incidence of OPF and improve patient prognosis.

Background: Angiotensin II, is critical in regulating the sympathetic and neuroendocrine systems through angiotensin II type 1 receptors (AT₁-R). Angiotensin II intracerebral administration increases water and sodium intake, as well as renal sodium excretion. Previously, our group has shown that AT₁-R is involved in behavioral and neurochemical sensitization induced by amphetamine. We aimed to assess the physiological output, behavioral, and neurochemical responses to intracerebral angiotensin II administration, via the AT₁-R, twenty-one days after amphetamine administration.

Material and methods: Male Wistar rats received daily vehicle or AT₁-R antagonist (oral) for 10 days, and amphetamine or saline intraperitoneal (i.p.) from day 6 to 10. On day 25 they were implanted with an intracerebral cannula. On day 32, the animals received intracerebral angiotensin II. First group: the animals were tested in a free choice paradigm for 2% NaCl and water intake, and sacrificed for neuronal activity assessment via c-Fos immunohistochemistry. Second group: urine samples were collected for electrolyte determination. Third group: the animals were tested in the plus maze or the hole board for anxiety and working memory evaluation, respectively, and sacrificed for c-Fos immunohistochemistry.

Results: Amphetamine exposure blunted the increase in sodium intake (p = 0.0022), and potentiated the natriuretic (p = 0.0043) and kaliuretic effect (p = 0.0002) induced by angiotensin II. Moreover, amphetamine exposure prevented the expression of the anxiogenic effect (drug effect p < 0.0001) and the memory deficit (p = 0.1314) induced by cerebral angiotensin II administration. Amph decreased c-Fos immunoreactivity in nucleus tractus solitarii (NTS) p = 0.0037; paraventricular nucleus (PVN) p = 0.0047; Central amygdala (CeA) p = 0.0008; Basolateral amygdala (BLA) p = 0.0018; increased in hippocampus region CA1 p = 0.0043; CA3 p = 0.026; and dentate gyrus (DG) p = 0.0057. The blockade of AT₁-R prevented these alterations (sodium intake p = 0.0421 natriuresis p = 0.019; kaliuresis p = 0.196; working memory (p < 0.0001); but no the anxiogenic response to angiotensin II (drug effect p < 0.0001); as well as the c-Fos changes (NTS p = 0.0052; PVN p = 0.029; CeA p = 0.0002; BLA p = 0.0021; CA1 p = 0.0026; CA3 p = 0.022; and DG p = 0.0016).

Conclusion: Most of the long-lasting AT₁-R altered responses to brain angiotensin II administration induced by repeated amphetamine exposure could be prevented by AT₁-R blockade.

Background: Diabetes mellitus is a common metabolic disorder, and diabetic erectile dysfunction (DMED) is one of its common complications. The differentiation of the types of erectile dysfunction (ED) is fundamental to treatment, yet there is a lack of simple and efficacious tools for this purpose in clinical practice. In this study, we endeavor to predict ED types using commonly available clinical data from diabetic patients, aiming to develop and assess a risk prediction model for organic erectile dysfunction in individuals with type 2 diabetes.

Methods: The study was a retrospective analysis. Data were obtained from the hospital's internal medical record system. We selected and analyzed the clinical data of 250 patients with type 2 diabetes. Lasso regression was used for risk factor selection, and the selected variables were included in a multivariate logistic regression analysis to establish the risk prediction model. Internal validation was performed using the bootstrap method, and the discrimination, calibration, and clinical effectiveness of the model were evaluated using the C-index, calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve.

Results: Among the 250 patients, 168 (67.2%) were diagnosed with organic ED. The risk factors included in the logistic regression analysis were the duration of diabetes, low-density lipoprotein cholesterol (LDL-C), red blood cell distribution width (RDW), intima-media thickness of the carotid artery, diabetic retinopathy, diabetic nephropathy, and peripheral neuropathy. The C-index was 0.827 (95% confidence interval (CI) = 0.772-0.882). The distribution curve of the predicted values and the calibration curve of the model were well fitted. The decision curve analysis (DCA) suggested that using the model could be clinically beneficial when the threshold probability was between 28% and 100%.

Conclusion: By combining the duration of diabetes, carotid artery intima-media thickness, diabetic retinopathy, diabetic nephropathy, peripheral neuropathy, RDW, and LDL-C, this study preliminarily establishes a risk prediction model for organic ED in patients with type 2 diabetes mellitus. The model demonstrates good predictive performance.

Background: Bladder cancer (BC) is a malignant tumor that begins in the cells of the bladder, characterized by poor cell differentiation and strong invasion capacity, with a high incidence rate. Identifying key molecules that enhance BC cells' cisplatin sensitivity can help improve the clinical efficacy of BC treatment. Hence, this study aimed to determine the expression level of long non-coding RNA (lncRNA) ADAM Metallopeptidase with Thrombospondin Type 1 Motif 9 Antisense RNA 1 (ADAMTS9-AS1) in BC and explore its related mechanism underlying the amplification of cisplatin sensitivity.

Methods: Cancer tissues and para-cancerous tissues of 10 BC patients treated in The 908th Hospital of Joint Logistic Support Force of PLA were collected retrospectively and analyzed for the expression of the lncRNA ADAMTS9-AS1 and fused in sarcoma (FUS) in this tissue. Normal bladder epithelial cell line SV-HUC1, and BC cell lines such as T24, J82, 5637, KU-19-19, and EJ were cultured for in vitro experimentation. Then, the expression levels of ADAMTS9-AS1, FUS mRNA, and FUS protein were detected by means of reverse-transcription quantitative polymerase chain reaction (RT-qPCR), Western blotting, and immunohistochemistry. pcDNA3.1 vector, pcDNA3.1-ADAMTS9-AS1, or pcDNA3.1-ADAMTS9-AS1 and FUS overexpression plasmid was transfected into the cultured T24 and 5637 cells. A series of tests were performed to detect cell proliferation, migration capacity, apoptosis, and cisplatin half-effective concentration (IC50) values of BC cells using Cell Counting Kit-8 (CCK-8) assay, colony formation assay, wound healing assay, flow cytometry, and gradient cisplatin culturation.

Results: Compared with SV-HUC1 cell line and adjacent normal tissues, ADAMTS9-AS1 levels were significantly decreased in T24, J82, 5637, KU-19-19, EJ cell lines, and BC tissues, while FUS mRNA and protein expression levels were up-regulated (p < 0.05). After transfection with pcDNA3.1-ADAMTS9-AS1, the colony number, cell viability, wound healing ratio, and cisplatin IC50 value, were remarkably reduced (p < 0.05), but apoptosis ratio, cleaved-caspase3 and cleaved-poly-ADP-ribose polymerases (PARP) expressions were increased (p < 0.05). ADAMTS9-AS1 was found to directly target FUS, and overexpression of FUS reversed ADAMTS9-AS1 effects on BC cells.

Conclusions: ASAMTS9-AS1 can inhibit the proliferation and migration, and promote apoptosis and cisplatin sensitivity of BC cells through regulating FUS, thus providing a theoretical basis for ADAMTS9-AS1 as a potential therapeutic target in BC treatment.

The immune and musculoskeletal systems closely interplay in bone repair and regeneration. After bone injury, the body produces high levels of cytokines and signaling molecules to balance bone formation and resorption. Interleukin (IL)-17A, a cytokine expressed early in the inflammatory process, profoundly influences osteoprogenitor cell fate, thereby contributing to bone homeostasis. In addition, mesenchymal stromal/stem cells (MSCs) can differentiate into osteoblasts, contributing to bone repair and regeneration. Although IL-17A can influence MSCs to become early osteoprogenitor cells, it also can inhibit bone formation. However, the reasons for these dual roles are not yet fully understood. This review overviews IL-17A signaling and the mechanisms that govern MSCs' osteogenic differentiation and summarizes relevant data from the literature on IL-17A's pro- and anti-osteogenic roles.

Invasive alien plant species (IAPS) are well known to disrupt biodiversity, natural ecosystems, and infrastructures, resulting in a significant worldwide economic cost. However, the impact of IAPS on human health has been generally disregarded, despite a significant potential risk. Currently, due to new evidence and the concept of One Health, this concern is gaining strength. The spread of invasive plants at a global scale can profoundly affect human health through pollen and toxin production. Allergic respiratory diseases caused by pollen are likely the primary risks posed by IAPS. Because of the frequent invasion of populated areas and their different pollination period throughout the year, IAPS might further contribute to the current striking increase in allergies. Respiratory allergies significantly affect the quality of life of patients, along with associated economic impacts. In this study, we focus on a paradigmatic IAPS that is invading considerable areas of the globe, Cortaderia selloana (Pampas grass), to illustrate the increasing and widely disregarded human health risk posed by IAPS. Our aim is to raise awareness of the IAPS concern among the medical community and health policymakers, suggesting rapid action to address associated concerns.