Epithelial-mesenchymal plasticity in cancer: signaling pathways and therapeutic targets.

Currently, cancer is still a leading cause of human death globally. Tumor deterioration comprises multiple events including metastasis, therapeutic resistance and immune evasion, all of which are tightly related to the phenotypic plasticity especially epithelial-mesenchymal plasticity (EMP). Tumor cells with EMP are manifest in three states as epithelial-mesenchymal transition (EMT), partial EMT, and mesenchymal-epithelial transition, which orchestrate the phenotypic switch and heterogeneity of tumor cells via transcriptional regulation and a series of signaling pathways, including transforming growth factor-ß, Wnt/ß-catenin, and Notch. However, due to the complicated nature of EMP, the diverse process of EMP is still not fully understood. In this review, we systematically conclude the biological background, regulating mechanisms of EMP as well as the role of EMP in therapy response. We also summarize a range of small molecule inhibitors, immune-related therapeutic approaches, and combination therapies that have been developed to target EMP for the outstanding role of EMP-driven tumor deterioration. Additionally, we explore the potential technique for EMP-based tumor mechanistic investigation and therapeutic research, which may burst vigorous prospects. Overall, we elucidate the multifaceted aspects of EMP in tumor progression and suggest a promising direction of cancer treatment based on targeting EMP.

An exosomal strategy for targeting cancer-associated fibroblasts mediated tumors desmoplastic microenvironments.

Tumors desmoplastic microenvironments are characterized by abundant stromal cells and extracellular matrix (ECM) deposition. Cancer-associated fibroblasts (CAFs), as the most abundant of all stromal cells, play significant role in mediating microenvironments, which not only remodel ECM to establish unique pathological barriers to hinder drug delivery in desmoplastic tumors, but also talk with immune cells and cancer cells to promote immunosuppression and cancer stem cells-mediated drug resistance. Thus, CAFs mediated desmoplastic microenvironments will be emerging as promising strategy to treat desmoplastic tumors. However, due to the complexity of microenvironments and the heterogeneity of CAFs in such tumors, an effective deliver system should be fully considered when designing the strategy of targeting CAFs mediated microenvironments. Engineered exosomes own powerful intercellular communication, cargoes delivery, penetration and targeted property of desired sites, which endow them with powerful theranostic potential in desmoplastic tumors. Here, we illustrate the significance of CAFs in tumors desmoplastic microenvironments and the theranostic potential of engineered exosomes targeting CAFs mediated desmoplastic microenvironments in next generation personalized nano-drugs development.

Engineered Exosomes Carrying miR-588 for Treatment of Triple Negative Breast Cancer Through Remodeling the Immunosuppressive Microenvironment.

Background: The morbidity and mortality of triple-negative breast cancer (TNBC) are still high, causing a heavy medical burden. CCL5, as a chemokine, can be involved in altering the composition of the tumor microenvironment (TME) as well as the immunosuppressive degree, and has become a very promising target for the treatment of TNBC. Dysregulation of microRNAs (miRNAs) in tumor tissues is closely related to tumor progression, and its utilization can be used to achieve therapeutic purposes. Engineered exosomes can avoid the shortcomings of miRNAs and also enhance their targeting and anti-tumor effects through engineering. Therefore, we aimed to create a cRGD-modified exosome for targeted delivery of miR-588 and to investigate its effect in remodeling immunosuppressive TME by anchoring CCL5 in TNBC. Methods: In this study, we loaded miR-588 into exosomes using electroporation and modified it with cRGD using post insertion to obtain cRGD-Exos/miR-588. Transmission electron microscopy (TEM), nanoparticle tracking assay technique (NTA), Western Blots, qPCR, and flow cytometry were applied for its characterization. CCK-8, qPCR and enzyme-linked immunosorbent assay (ELISA), in vivo fluorescence imaging system, immunohistochemistry and H&E staining were used to explore the efficacy as well as the mechanism at the cellular level as well as in subcutaneous graft-tumor nude mouse model. Results: The cRGD-Exos/miR-588 was successfully constructed and had strong TNBC tumor targeting in vitro and in vivo. Meanwhile, it has significant efficacy on TME components affected by CCL5 and the degree of immunosuppression, which can effectively control TNBC with good safety. Conclusion: In this experiment, cRGD-Exos/miR-588 was prepared to remodel immunosuppressive TME by anchoring CCL5, which is affected by the vicious cycle of immune escape. Overall, cRGD-Exos/miR-588 explored the feasibility of targeting TME for the TNBC treatment, and provided a competitive delivery system for the engineered exosomes to deliver miRNAs for antitumor therapy drug.

The integrative and conjugative element ICECiPOL15 mediates horizontal transfer of ß-lactam resistance gene in Chryseobacterium indoltheticum POL15.

OBJECTIVES: The dissemination of antibiotic resistance genes (ARGs) from the environment, including agricultural sources, is of increasing concern. In this study, we examined the antibiotic resistance profile and genomic sequence of a strain of Chryseobacterium indoltheticum obtained from an agricultural location. METHODS: The multidrug-resistant bacterial strain POL15 was isolated from the wastewater of a livestock farm in China. Whole-genome sequencing was performed followed by bioinformatics analyses to identify integrative and conjugative elements (ICEs) and ARGs. Mating assays were performed to analyse ICE transferability. RESULTS: Whole-genome sequencing and annotation showed that the genome of POL15 encodes ARGs. Additionally, an ICE named ICECiPOL15, which carries a class C ß-lactamase-encoding gene blaAQU, was identified in the POL15 genome. Genes encoding an integrase, an excisionase, a relaxase, a type IV coupling protein and conjugative transposon proteins involved in a type IV secretion system were also identified in ICECiPOL15. Sequence alignment revealed that ICECiPOL15 might have evolved from other Chryseobacterium species. The horizontal transferability of ICECiPOL15 was demonstrated by mating experiments between C. indoltheticum POL15 and Escherichia coli DL21. CONCLUSIONS: This study represents the first characterization of a mobilizable antibiotic resistance ICE in a species of C. indoltheticum and provides evidence that C. indoltheticum strains could be important reservoirs and vehicles for ARGs on livestock farms.

Using an artificial intelligence model to detect and localize visible clinically significant prostate cancer in prostate magnetic resonance imaging: a multicenter external validation study.

Background: An increasing number of patients with suspected clinically significant prostate cancer (csPCa) are undergoing prostate multiparametric magnetic resonance imaging (mpMRI). The role of artificial intelligence (AI) algorithms in interpreting prostate mpMRI needs to be tested with multicenter external data. This study aimed to investigate the diagnostic efficacy of an AI model in detecting and localizing visible csPCa on mpMRI a multicenter external data set. Methods: The data of 2,105 patients suspected of having prostate cancer from four hospitals were retrospectively collected to develop an AI model to detect and localize suspicious csPCa. The lesions were annotated based on pathology records by two radiologists. Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values were used as the input for the three-dimensional U-Net framework. Subsequently, the model was validated using an external data set comprising the data of 557 patients from three hospitals. Sensitivity, specificity, and accuracy were employed to evaluate the diagnostic efficacy of the model. Results: At the lesion level, the model had a sensitivity of 0.654. At the overall sextant level, the model had a sensitivity, specificity, and accuracy of 0.846, 0.884, and 0.874, respectively. At the patient level, the model had a sensitivity, specificity, and accuracy of 0.943, 0.776, and 0.849, respectively. The AI-predicted accuracy for the csPCa patients (231/245, 0.943) was significantly higher than that for the non-csPCa patients (242/312, 0.776) (P<0.001). The lesion number and tumor volume were greater in the correctly diagnosed patients than the incorrectly diagnosed patients (both P<0.001). Among the positive patients, those with lower average ADC values had a higher rate of correct diagnosis than those with higher average ADC values (P=0.01). Conclusions: The AI model exhibited acceptable accuracy in detecting and localizing visible csPCa at the patient and sextant levels. However, further improvements need to be made to enhance the sensitivity of the model at the lesion level.

Pathological progress and remission strategies of osteoarthritic lesions caused by long-term joint immobilization.

OBJECTIVE: While joint immobilization is a useful repair method for intra-articular ligament injury and periarticular fracture, prolonged joint immobilization can cause multiple complications. A better understanding how joint immobilization and remobilization impact joint function and homeostasis will help clinicians develop novel strategies to reduce complications. DESIGN: We first determined the effects of long-term immobilization on joint pain and osteophyte formation in patients after an extraarticular fracture or ligament injury. We then developed a mouse model of joint immobilization and harvested the knee joint samples at 2, 4, and 8 weeks. We further determined the effects of remobilization on recovery of the osteoarthritis (OA) lesions induced by immobilization in mice. RESULTS: We found that the long-term (6 weeks) joint immobilization caused significant joint pain and osteophytes in patients. In mice, 2-week immobilization already induced moderate sensory innervation and increased pain sensitivity and infiltration in synovium without inducing marked osteophyte formation and cartilage loss. Long-term immobilization (4 and 8 weeks) induced more severe sensory innervation and inflammatory infiltration in synovium, massive osteophyte formation on both sides of the femoral condyle, and the edge of the tibial plateau and significant loss of the articular cartilage in mice. Remobilization, which ameliorates normal joint load and activity, restored to certain extent some of the OA lesions and joint function in mice. CONCLUSIONS: Joint immobilization caused multiple OA-like lesions in both mice and humans. Joint immobilization induced progressive sensory innervation, synovitis, osteophyte formation, and cartilage loss in mice, which can be partially ameliorated by remobilization.

Seroepidemiology study of rubella virus antibodies among neonates and pregnant women at hospitals in Henan province, China.

Rubella virus infection can cause vertical transmission to the fetus during pregnancy. In China's Henan province, rubella surveillance needs to be well-established. In this research, a total of 1933 neonates and 2502 pregnant women were enrolled, and their sera for IgG and IgM antibodies against rubella were tested by chemiluminescence assay. Of 1933 neonates' sera tested, the seropositive of rubella IgG was 68.7%. The seroprevalence of rubella IgM in neonates was 0.4%. 30.9% of neonates had negative results for IgG and IgM antibodies. Two thousand five hundred and two pregnant women participated in the serosurvey, and 79.3% were rubella IgG positive. Rubella IgG seropositivity in pregnant women differed by age and number of births. 0.8% of the pregnant women had positive results for IgM against the rubella virus. The seronegative of rubella IgG and IgM antibodies in pregnant women was 19.8%. Due to the negative rubella-specific IgG antibody, many neonates remain at risk of rubella virus infection. Rubella virus continues to spread since some neonates and pregnant women with rubella-specific IgM antibody positive have been detected. Rubella vaccination may be introduced for childbearing-age women to increase immunity levels against rubella with periodic sero-surveillance.

Apolipoproteins as potential communicators play an essential role in the pathogenesis and treatment of early atherosclerosis.

Atherosclerosis as the leading cause of the cardiovascular disease is closely related to cholesterol deposition within subendothelial areas of the arteries. Significantly, early atherosclerosis intervention is the critical phase for its reversal. As atherosclerosis progresses, early foam cells formation may evolve into fibrous plaques and atheromatous plaque, ulteriorly rupture of atheromatous plaque increases risks of myocardial infarction and ischemic stroke, resulting in high morbidity and mortality worldwide. Notably, amphiphilic apolipoproteins (Apos) can concomitantly combine with lipids to form soluble lipoproteins that have been demonstrated to associate with atherosclerosis. Apos act as crucial communicators of lipoproteins, which not only can mediate lipids metabolism, but also can involve in pro-atherogenic and anti-atherogenic processes of atherosclerosis via affecting subendothelial retention and aggregation of low-density lipoprotein (LDL), oxidative modification of LDL, foam cells formation and reverse cholesterol transport (RCT) in macrophage cells. Correspondingly, Apos can be used as endogenous and/or exogenous targeting agents to effectively attenuate the development of atherosclerosis. The article reviews the classification, structure, and relationship between Apos and lipids, how Apos serve as communicators of lipoproteins to participate in the pathogenesis progression of early atherosclerosis, as well as how Apos as the meaningful targeting mass is used in early atherosclerosis treatment.

[Cangxi Tongbi Capsules promote chondrocyte autophagy by regulating circRNA＿0008365/miR-1271/p38 MAPK pathway to inhibit development of knee osteoarthritis].

To investigate the mechanism by which Cangxi Tongbi Capsules promote chondrocyte autophagy to inhibit knee osteoarthritis(KOA) progression by regulating the circRNA＿0008365/miR-1271/p38 mitogen-activated protein kinase(MAPK) pathway. The cell and animal models of KOA were established and intervened with Cangxi Tongbi Capsules, si-circRNA＿0008365, si-NC, and Cangxi Tongbi Capsules combined with si-circRNA＿0008365. Flow cytometry and transmission electron microscopy were employed to determine the level of apoptosis and observe autophagosomes, respectively. Western blot was employed to reveal the changes in the protein levels of microtubule-associated protein light chain 3(LC3)Ⅱ/Ⅰ, Beclin-1, selective autophagy junction protein p62/sequestosome 1, collagen Ⅱ, a disintegrin and metalloproteinase with thrombospondin motifs 5(ADAMTS-5), and p38 MAPK. The mRNA levels of circRNA＿0008365, miR-1271, collagen Ⅱ, and ADAMTS-5 were determined by qRT-PCR. Hematoxylin-eosin staining was employed to reveal the pathological changes of the cartilage tissue of the knee, and enzyme-linked immunosorbent assay to measure the levels of interleukin-1ß(IL-1ß) and tumor necrosis factor-alpha(TNF-α). The chondrocytes treated with IL-1ß showed down-regulated expression of circRNA＿0008365, up-regulated expression of miR-1271 and p38 MAPK, lowered autophagy level, increased apoptosis rate, and accelerated catabolism of extracellular matrix. The intervention with Cangxi Tongbi Capsules up-regulated the expression of circRNA＿0008365, down-regulated the expression of miR-1271 and p38 MAPK, increased the autophagy level, decreased the apoptosis rate, and weakened the catabolism of extracellular matrix. However, the effect of Cangxi Tongbi Capsules was suppressed after interfering with circRNA＿0008365. The in vivo experiments showed that Cangxi Tongbi Capsules dose-dependently inhibited the p38 MAPK pathway, enhanced chondrocyte autophagy, and mitigated articular cartilage damage and inflammatory response, thereby inhibiting the progression of KOA in rats. This study indicated that Cangxi Tongbi Capsules promoted chondrocyte autophagy by regulating the circRNA＿0008365/miR-1271/p38 MAPK pathway to inhibit the development of KOA.

Case report of epileptic seizure during awake craniotomy of functional area glioma and literature study.

Intraoperative seizure is the most prevalent and serious complication of awake craniotomy in functional areas, which may not only trigger complications of the surgical procedure or even the failure of awake craniotomy but also may result in adverse consequences to patients. The influencing factors of intraoperative seizures are unclear, and only the possible influencing factors can be acquired from the examination and summary of existing cases to offer guidance for the seizure prevention of intraoperative epilepsy.

Artificial intelligence as diagnostic aiding tool in cases of Prostate Imaging Reporting and Data System category 3: the results of retrospective multi-center cohort study.

PURPOSE: To study the effect of artificial intelligence (AI) on the diagnostic performance of radiologists in interpreting prostate mpMRI images of the PI-RADS 3 category. METHODS: In this multicenter study, 16 radiologists were invited to interpret prostate mpMRI cases with and without AI. The study included a total of 87 cases initially diagnosed as PI-RADS 3 by radiologists without AI, with 28 cases being clinically significant cancers (csPCa) and 59 cases being non-csPCa. The study compared the diagnostic efficacy between readings without and with AI, the reading time, and confidence levels. RESULTS: AI changed the diagnosis in 65 out of 87 cases. Among the 59 non-csPCa cases, 41 were correctly downgraded to PI-RADS 1-2, and 9 were incorrectly upgraded to PI-RADS 4-5. For the 28 csPCa cases, 20 were correctly upgraded to PI-RADS 4-5, and 5 were incorrectly downgraded to PI-RADS 1-2. Radiologists assisted by AI achieved higher diagnostic specificity and accuracy than those without AI [0.695 vs 0.000 and 0.736 vs 0.322, both P < 0.001]. Sensitivity with AI was not significantly different from that without AI [0.821 vs 1.000, P = 1.000]. AI reduced reading time significantly compared to without AI (mean: 351 seconds, P < 0.001). The diagnostic confidence score with AI was significantly higher than that without AI (Cohen Kappa: -0.016). CONCLUSION: With the help of AI, there was an improvement in the diagnostic accuracy of PI-RADS category 3 cases by radiologists. There is also an increase in diagnostic efficiency and diagnostic confidence.

AI-predicted mpMRI image features for the prediction of clinically significant prostate cancer.

PURPOSE: To evaluate the feasibility of using mpMRI image features predicted by AI algorithms in the prediction of clinically significant prostate cancer (csPCa). MATERIALS AND METHODS: This study analyzed patients who underwent prostate mpMRI and radical prostatectomy (RP) at the Affiliated Hospital of Jiaxing University between November 2017 and December 2022. The clinical data collected included age, serum prostate-specific antigen (PSA), and biopsy pathology. The reference standard was the prostatectomy pathology, and a Gleason Score (GS) of 3 + 3 = 6 was considered non-clinically significant prostate cancer (non-csPCa), while a GS ≥ 3 + 4 was considered csPCa. A pre-trained AI algorithm was used to extract the lesion on mpMRI, and the image features of the lesion and the prostate gland were analyzed. Two logistic regression models were developed to predict csPCa: an MR model and a combined model. The MR model used age, PSA, PSA density (PSAD), and the AI-predicted MR image features as predictor variables. The combined model used biopsy pathology and the aforementioned variables as predictor variables. The model's effectiveness was evaluated by comparing it to biopsy pathology using the area under the curve (AUC) of receiver operation characteristic (ROC) analysis. RESULTS: A total of 315 eligible patients were enrolled with an average age of 70.8 ± 5.9. Based on RP pathology, 18 had non-csPCa, and 297 had csPCa. PSA, PSAD, biopsy pathology, and ADC value of the prostate outside the lesion (ADCprostate) varied significantly across different ISUP grade groups of RP pathology (P < 0.001). Other clinical variables and image features did not vary significantly across different ISUP grade groups (P > 0.05). The MR model included PSAD, the ratio of ADC value between the lesion and the prostate outside the lesion (ADClesion/prostate), the signal intensity ratio of DWI between the lesion and the prostate outside the lesion (DWIlesion/prostate), and the ratio of DWIlesion/prostate to ADClesion/prostate. The combined model included biopsy pathology, ADClesion/prostate, mean signal intensity of the lesion on DWI (DWIlesion), DWI signal intensity of the prostate outside the lesion (DWIprostate), and signal intensity ratio of DWI between the lesion and the prostate outside the lesion (DWIlesion/prostate). The AUC of the MR model (0.830, 95% CI 0.743, 0.916) was not significantly different from that of biopsy pathology (0.820, 95% CI 0.728, 0.912, P = 0.884). The AUC of the combined model (0.915, 95% CI 0.849, 0.980) was higher than that of the biopsy pathology (P = 0.042) and MR model (P = 0.031). CONCLUSION: The aggressiveness of prostate cancer can be effectively predicted using AI-extracted image features from mpMRI images, similar to biopsy pathology. The prediction accuracy was improved by combining the AI-extracted mpMRI image features with biopsy pathology, surpassing the performance of biopsy pathology alone.

Clinical study of multifactorial diagnosis in prostate biopsy.

PURPOSE: To study the feasibility of using an artificial intelligence (AI) algorithm for the diagnosis of clinically significant prostate cancer (csPCa) on multiparametric MRI (mpMRI) in combination with conventional clinical information. METHODS: A retrospective study cohort with 505 patients was collected, with complete information on age (≤60, 60-80, and >80 years), PSA (≤4, 4-10, and >10 ng/dL), and pathology results. The patients with ISUP group >2 were classified as csPCa, and the patients with ISUP = 1 or no evidence of prostate cancer were classified as non-csPCa. The diagnosis of mpMRI was made by experienced radiologists following the prostate imaging reporting and data system (PIRADS ≤ 2, PIRADS = 3, and PIRADS > 3). The mpMRI images were processed by a homemade AI algorithm, and the AI results were obtained as positive or negative for csPCa. Two logistic regression models were fitted, with pathological findings as the dependent variable, that is, a conventional model and an AI model. The conventional model used age, PSA, and PIRADS as the independent variables. The AI model took the AI result and the abovementioned clinical information as the independent variables. The predicted probability of the patients from the conventional model and the AI model were used to test the prediction efficacy of the models. The DeLong test was performed to compare differences in the area under the receiver operating characteristic (ROC) area under the curve (AUC) between the conventional model and the AI model. RESULTS: In total, 505 patients were included in the study; 280 were diagnosed with csPCa, and 225 were non-csPCa. The median age was 72.0 (67.0, 76.0) years, with a median PSA value of 13.0 (7.46, 27.5) ng/dL. Statically significant differences were found in age, PSA, PIRADS score and AI results between the csPCa and non-csPCa groups (all p < 0.001). In the multivariable regression models, all the variables were independently associated with csPCa. The conventional model (R2 = 0.361) and the AI model (R2 = 0.474) were compared with analysis of variance (ANOVA) and showed statistically significant differences (χ2 = 63.695, p < 0.001). The AUC of the ROC curve for the conventional model was 0.782 (95% confidence interval [CI]: 0.742-0.823), which was less than the AUC of the AI model with statistical significance (0.849 [95% CI: 0.815-0.883], p < 0.001). CONCLUSION: In combination with routine clinical information, such as age, PSA, and PIRADS category, adding information from the AI algorithm based on mpMRI could improve the diagnosis of csPCa.

The critical role of osteopontin (OPN) in fibrotic diseases.

Fibrosis is a pathological condition characterized by the excessive deposition of extracellular matrix components in tissues and organs, leading to progressive architectural remodelling and contributing to the development of various diseases. Osteopontin (OPN), a highly phosphorylated glycoprotein, has been increasingly recognized for its involvement in the progression of tissue fibrosis. This review provides a comprehensive overview of the genetic and protein structure of OPN and focuses on our current understanding of the role of OPN in the development of fibrosis in the lungs and other tissues. Additionally, special attention is given to the potential of OPN as a biomarker and a novel therapeutic target in the treatment of fibrosis.

Co-Delivery of Hesperetin and Cisplatin via Hyaluronic Acid-Modified Liposome for Targeted Inhibition of Aggression and Metastasis of Triple-Negative Breast Cancer.

Having no specific therapy for triple-negative breast cancer (TNBC), this subtype has the lowest survival rate and highest metastatic risk of breast cancer since the tumor inflammatory microenvironment mainly accounts for heterogeneity-induced insensitivity to chemotherapy and epithelial-mesenchymal transition (EMT). This study reports hyaluronic acid (HA)-modified liposomes loaded with cisplatin (CDDP) and hesperetin (Hes) (CDDP-HA-Lip/Hes) for active targeting to relieve systematic toxicity and effective anti-tumor/anti-metastasis ability of TNBC. Our results revealed that HA modification promoted the cellular uptake of the synthesized CDDP-HA-Lip/Hes nanoparticles in MDA-MB-231 cells and accumulation in tumor sites in vivo, indicating deeper tumor penetration. Importantly, CDDP-HA-Lip/Hes inhibited the PI3K/Akt/mTOR pathway to alleviate the inflammation in the tumor and with a crosstalk to suppress the process of the EMT, increasing the chemosensitivity and inhibiting tumor metastasis. Meanwhile, CDDP-HA-Lip/Hes could significantly inhibit the aggression and metastasis of TNBC with less side effects on normal tissues. Overall, this study provides a tumor-targeting drug delivery system with great potential for treating TNBC and its lung metastasis robustly.

Genetically predicted hypertension, antihypertensive drugs, and risk of erectile dysfunction: a Mendelian randomization study.

Background: The causal relationship between hypertension, antihypertensive drugs and the risk of erectile dysfunction is still uncertain. We performed a univariable and multivariable Mendelian randomization study to investigate whether they are causally related to erectile dysfunction. Methods: Genetic variants associated with blood pressure were derived from the genome-wide association study meta-analysis of the UK Biobank and International Consortium of Blood Pressure (N = 757,601). Summary association data for hypertension were obtained from the UK Biobank (N = 463,010) and the FinnGen study (N = 356,077). The summary statistics of erectile dysfunction were obtained from the European ancestry with 223,805 subjects. The SNP instruments used to assess the effect of the protein targets of antihypertensive drugs on erectile dysfunction were obtained from previous studys. Causal effects were estimated using the univariate Mendelian randomization method (inverse variance weighted, MR-Egger, weighted median, MR-PRESSO and Wald ratios) and the multivariate Mendelian randomization method. Sensitivity analyses were implemented with the Cochran's Q-test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. Results: Univariate MR found that elevated diastolic blood pressure may increase the occurrence of erectile dysfunction (odds ratio [OR] = 1.012; 95% confidence interval [CI]: 1.000-1.024; P = 0.047). Genetically predicted hypertension is also associated with ED (For the FinnGen, OR = 1.106; 95% CI: 1.027-1.191; P = 0.008. For the UK Biobank, OR = 3.832; 95% CI: 1.410-10.414; P = 0.008). However, after adjusting for systolic blood pressure, diastolic blood pressure and hypertension using multivariate Mendelian randomization, only hypertension was causally associated with ED occurrence (For the FinnGen, OR = 1.103; 95% CI: 1.018-1.195; P = 0.017. For the UK Biobank, OR = 5.037; 95% CI: 1.601-15.846; P = 0.006). We found no evidence that the use of angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and thiazide diuretic increased the risk of erectile dysfunction. Conclusions: Genetically predicted hypertension increases the risk of erectile dysfunction, but we found no causal relationship between elevated systolic/diastolic blood pressure and erectile dysfunction. We speculate that the relationship between elevated blood pressure and erectile dysfunction risk may be nonlinear. We found little evidence that antihypertensive drugs increase the risk of erectile dysfunction.

A multicenter study of artificial intelligence-aided software for detecting visible clinically significant prostate cancer on mpMRI.

BACKGROUND: AI-based software may improve the performance of radiologists when detecting clinically significant prostate cancer (csPCa). This study aims to compare the performance of radiologists in detecting MRI-visible csPCa on MRI with and without AI-based software. MATERIALS AND METHODS: In total, 480 multiparametric MRI (mpMRI) images were retrospectively collected from eleven different MR devices, with 349 csPCa lesions in 180 (37.5%) cases. The csPCa areas were annotated based on pathology. Sixteen radiologists from four hospitals participated in reading. Each radiologist was randomly assigned to 30 cases and diagnosed twice. Half cases were interpreted without AI, and the other half were interpreted with AI. After four weeks, the cases were read again in switched mode. The mean diagnostic performance was compared using sensitivity and specificity on lesion level and patient level. The median reading time and diagnostic confidence were assessed. RESULTS: On lesion level, AI-aided improved the sensitivity from 40.1% to 59.0% (18.9% increased; 95% confidence interval (CI) [11.5, 26.1]; p < .001). On patient level, AI-aided improved the specificity from 57.7 to 71.7% (14.0% increase, 95% CI [6.4, 21.4]; p < .001) while preserving the sensitivity (88.3% vs. 93.9%, p = 0.06). AI-aided reduced the median reading time of one case by 56.3% from 423 to 185 s (238-s decrease, 95% CI [219, 260]; p < .001), and the median diagnostic confidence score was increased by 10.3% from 3.9 to 4.3 (0.4-score increase, 95% CI [0.3, 0.5]; p < .001). CONCLUSIONS: AI software improves the performance of radiologists by reducing false positive detection of prostate cancer patients and also improving reading times and diagnostic confidence. CLINICAL RELEVANCE STATEMENT: This study involves the process of data collection, randomization and crossover reading procedure.

GALNT2 sustains glioma stem cells by promoting CD44 expression.

Glioblastoma (GBM) is the most prevalent and malignant brain tumor and is highly resistant to currently available treatment. In this study, we reveal that polypeptide N-acetylgalactosaminyltransferase 5 (GALNT2) expression level was elevated in GBM, IDH1 wildtype glioma, and GBM stem cells (GSCs). GALNT2 increased expression correlated with GBM patients' unfavorable clinical outcomes. Functionally, targeting GALNT2 blocks GSCs cell proliferation, self-renewal, and malignant invasion through repressing CD44 expression. Most importantly, we first provide evidence suggesting that STAT3 activates GALNT2 expression at the transcriptional level by directly binding to the GALNT2 promoter. Through a rational screening, we found a GALNT2 inhibitor that dramatically suppresses GSCs self-maintenance in vitro and in vivo. Collectively, we uncovered the critical function of GALNT2 in promoting GSCs self-maintenance and GBM progression and may provide a new potential drug for GBM clinical therapy.

Achyranthoside D attenuates chondrocyte loss and inflammation in osteoarthritis via targeted regulation of Wnt3a.

BACKGROUND: Achyranthes bidentata Blume (A. bidentata) is a common Chinese herb used to treat osteoarthritis (OA). Achyranthoside D (Ach-D) is a glucuronide saponin isolated from A. bidentata. PURPOSE: To assess the mechanisms of action of Ach-D and its effects on OA. METHODS: The effects of Ach-D were evaluated in rats underwent anterior cruciate ligament transection (ACLT) with medial meniscectomy (MMx) and in interleukin (IL)-1ß-induced chondrocytes. Histological changes in rat cartilage tissues were detected using Safranin O-Fast green and haematoxylin-eosin staining. Immunohistochemical staining, qRT-PCR, ELISA, immunoblotting, and immunofluorescence were conducted to examine cartilage degeneration-related and inflammation-related factor expression. CCK-8, LDH assay, and EdU staining were performed to detect chondrocyte death. RESULTS: Ach-D dose-dependently reduced the Osteoarthritis Research Society International (OARSI) scores, alleviated cartilage injury, and decreased the serum concentrations of CTX-II and COMP in ACLT-MMx models. Ach-D increased the expression levels of collagen II and aggrecan and decreased the levels of cartilage degeneration-related proteins, ADAMTS-5, MMP13, and MMP3, in rat cartilage tissues. Additionally, nod-like receptor protein 3 (NLRP3)-related inflammation was reduced by Ach-D, as shown by the significantly inhibited expression levels of NLRP3, ASC, GSDMD, IL-6, TNF-α, IL-1ß, and IL-18 in rat cartilage tissues. In primary rat chondrocytes, Ach-D protected against IL-1ß-induced viability loss and LDH release. Wnt3a is the target protein of Ach-D. Mechanistically, Ach-D alleviated OA by inhibiting Wnt signalling. CONCLUSION: ACH-D may reduce inflammation and cartilage degeneration by inhibiting the Wnt signalling pathway, thereby reducing OA.

Semiautomated pelvic lymph node treatment response evaluation for patients with advanced prostate cancer: based on MET-RADS-P guidelines.

BACKGROUND: The evaluation of treatment response according to METastasis Reporting and Data System for Prostate Cancer (MET-RADS-P) criteria is an important but time-consuming task for patients with advanced prostate cancer (APC). A deep learning-based algorithm has the potential to assist with this assessment. OBJECTIVE: To develop and evaluate a deep learning-based algorithm for semiautomated treatment response assessment of pelvic lymph nodes. METHODS: A total of 162 patients who had undergone at least two scans for follow-up assessment after APC metastasis treatment were enrolled. A previously reported deep learning model was used to perform automated segmentation of pelvic lymph nodes. The performance of the deep learning algorithm was evaluated using the Dice similarity coefficient (DSC) and volumetric similarity (VS). The consistency of the short diameter measurement with the radiologist was evaluated using Bland-Altman plotting. Based on the segmentation of lymph nodes, the treatment response was assessed automatically with a rule-based program according to the MET-RADS-P criteria. Kappa statistics were used to assess the accuracy and consistency of the treatment response assessment by the deep learning model and two radiologists [attending radiologist (R1) and fellow radiologist (R2)]. RESULTS: The mean DSC and VS of the pelvic lymph node segmentation were 0.82 ± 0.09 and 0.88 ± 0.12, respectively. Bland-Altman plotting showed that most of the lymph node measurements were within the upper and lower limits of agreement (LOA). The accuracies of automated segmentation-based assessment were 0.92 (95% CI: 0.85-0.96), 0.91 (95% CI: 0.86-0.95) and 75% (95% CI: 0.46-0.92) for target lesions, nontarget lesions and nonpathological lesions, respectively. The consistency of treatment response assessment based on automated segmentation and manual segmentation was excellent for target lesions [K value: 0.92 (0.86-0.98)], good for nontarget lesions [0.82 (0.74-0.90)] and moderate for nonpathological lesions [0.71 (0.50-0.92)]. CONCLUSION: The deep learning-based semiautomated algorithm showed high accuracy for the treatment response assessment of pelvic lymph nodes and demonstrated comparable performance with radiologists.