Fluorescence polarization assay for screening FANCM-RMI inhibitors to target the alternative lengthening of telomeres.

Alternative Lengthening of Telomeres (ALT) is a mechanism used by 10-15% of all cancers to achieve replicative immortality, bypassing the DNA damage checkpoint associated with short telomeres that leads to cellular senescence or apoptosis. ALT does not occur in non-cancerous cells, presenting a potential therapeutic window for cancers where this mechanism is active. Disrupting the FANCM-RMI interaction has emerged as a promising therapeutic strategy that induces synthetic ALT lethality in genetic studies on cancer cell lines. There are currently no chemical inhibitors reported in the literature, in part due to the lack of reliable biophysical or biochemical assays to screen for FANCM-RMI disruption. Here we describe the development of a robust competitive fluorescence polarization (FP) assay that quantifies target binding at the FANCM-RMI interface. The assay employs a labeled peptide tracer TMR-RaMM2 derived from the native MM2 binding motif, which binds to recombinant RMI1-RMI2 and can be displaced by competitive inhibitors. We report the methods for recombinant production of RMI1-RMI2, design and evaluation of the tracer TMR-RaMM2, along with unlabeled peptide inhibitor controls to enable ALT-targeted drug discovery.

Comparison of Simple Ultrasound Rules by International Ovarian Tumor Analysis (IOTA) with RMI-1 and RMI-4 (Risk of Malignancy Index) in Preoperative Differentiation of Benign and Malignant Adnexal Masses.

Background: IOTA proposed Simple Ultrasound Rules in 2009 for preoperative diagnosis of ovarian masses based on ultrasound only. It is an accurate, simple and inexpensive method. RMI, however, requires CA125 level. While RMI-4 is the latest, RMI-1 is still the most widely used method. The present study was done to compare IOTA Rules with RMI-1 and RMI-4. Purpose: To differentiate benign and malignant adnexal masses preoperatively using IOTA simple rules and compare its accuracy with RMI-1 and RMI-4. Methods: A prospective observational study was performed from 1st November 2019 to 31st March 2021 in the Department of Obstetrics and Gynaecology, ABVIMS and Dr. RML Hospital, New Delhi. This study was conducted on 70 patients with adnexal masses who underwent pre-operative evaluation using IOTA Simple Rules, RMI-1 and RMI-4. Histopathology was used to compare the results. Results: Out of 70 patients, 59 (84.3%) cases were benign and 11 (15.7%) were malignant. The IOTA Rules were applicable to 60 cases (85.7%), and the results were inconclusive in 10 cases (14.3%). Where applicable, the sensitivity and specificity of the IOTA Rules (88.9% and 94.1%, respectively) were significantly higher than RMI-1 (45.5% and 93.2%, respectively) and RMI-4 (45.5% and 89.8%, respectively). When inconclusive results were included as malignant, the sensitivity of the IOTA Rules increased (88.9% vs 90.9%); however, the specificity decreased (94.1% vs 81.4%). Conclusion: IOTA Simple Rules were more accurate at diagnosing benign from malignant adnexal masses than RMI-1 and RMI-4. However, the rules were not applicable to 14% of the cases.

A combined bioinformatics and experimental approach identifies RMI2 as a Wnt/ß-catenin signaling target gene related to hepatocellular carcinoma.

BACKGROUND: The Wnt/ß-catenin signaling pathway plays an important role in embryogenesis and tumorigenesis. In human cancer, abnormal activity of Wnt/ß-catenin signaling pathway induces overexpressed of downstream genes, and initiate oncogene. There are several target genes known to be key players in tumorigenesis, such as c-myc, cyclin D1, MMPs or survivin. Therefore, identifying the target genes of Wnt/ß-catenin signaling pathway is important to understanding Wnt/ß-catenin-mediated carcinogenesis. In this study, we developed a combined bioinformatics and experimental approach to find potential target genes. METHODS: Luciferase reporter assay was used to analyze the promoter activity of RMI2. WST1 cell proliferation assays and transwell assays were performed to determine the proliferation and migration capacities of RMI2 overexpressing or knockdown stable hepatic cells. Finally, xenograft experiments were performed to measure the tumor formation capacity in vivo. RESULTS: The results showed that RMI2 mRNA was upregulated after LiCl treatment and Wnt3a-conditioned medium in a culture of SK-hep-1 cell lines. A chromatin immunoprecipitation (ChIP) assay showed that the ß-catenin/T cell-specific factor (TCF) complex binds to the putative TCF binding site of the RMI2 promoter. We then found a TCF binding site at - 333/- 326 of the RMI2 promoter, which is crucial for ß-catenin responsiveness in liver cell lines. RMI2 was overexpressed in hepatoma tissue and cell lines, and it promoted the migration and invasion of HCC cells. Moreover, RMI2 upregulated the expression of epithelial-mesenchymal transition (EMT) markers and the Wnt3a/ß-catenin-related genes, but silencing RMI2 had the opposite effects. Notably, the expression of RMI2 was positively correlated with the clinical data of HCC patients who had significantly shorter overall survival (OS) and disease-free survival (DFS) (Both: P < 0.05). In addition, a total of 373 HCC patients' data from the Caner Genome Atlas project (TCGA) were used to validate our findings. CONCLUSIONS: Taking all these findings together, we determined that RMI2 was a new target gene of the Wnt/ß-catenin signaling pathway. We also found that RMI2 promotes EMT markers, HCC cell invasion, and metastasis, which indicated that RMI2 is a potential target for preventing or at least mitigating the progression of HCC.

[Cardiac sarcoidosis revealed by recurrent ventricular tachycardia]. / Tachycardie ventriculaire récidivante révélant une sarcoïdose cardiaque.

Sarcoidosis is an inflammatory disease whose diagnosis is suggested by clinical and paraclinical signs and confirmed by histological evidence showing granulomatosis without caseous necrosis. The clinical presentation is sometimes misleading and the diagnosis difficult to confirm. We report here the case of a young woman with cardiac sarcoidosis of difficult diagnosis, revealed by a myocardial infarction with normal coronary angiography and recurrent ventricular tachycardia. Multimodal imaging, combined with left ventricular endomyocardial biopsies guided by electrophysiological analysis and endocavitary mapping, finally confirmed the diagnosis, and allowed effective medical treatment.

Structural characterization of human RPA70N association with DNA damage response proteins.

The heterotrimeric Replication protein A (RPA) is the ubiquitous eukaryotic single-stranded DNA (ssDNA) binding protein and participates in nearly all aspects of DNA metabolism, especially DNA damage response. The N-terminal OB domain of the RPA70 subunit (RPA70N) is a major protein-protein interaction element for RPA and binds to more than 20 partner proteins. Previous crystallography studies of RPA70N with p53, DNA2 and PrimPol fragments revealed that RPA70N binds to amphipathic peptides that mimic ssDNA. NMR chemical-shift studies also provided valuable information on the interaction of RPA70N residues with target sequences. However, it is still unclear how RPA70N recognizes and distinguishes such a diverse group of target proteins. Here, we present high-resolution crystal structures of RPA70N in complex with peptides from eight DNA damage response proteins. The structures show that, in addition to the ssDNA mimicry mode of interaction, RPA70N employs multiple ways to bind its partners. Our results advance the mechanistic understanding of RPA70N-mediated recruitment of DNA damage response proteins.

Comparison of Four Risk of Malignancy Indices for Preoperative Evaluation of Ovarian Masses: A Prospective Observational Study.

BACKGROUND: Ovarian cancer imposes a significant health burden worldwide. Although various tumor markers are available to diagnose ovarian cancer, low-resource countries like India require a humble marker or index. The Risk of Malignancy Index (RMI) has been found to be a simple yet promising tool that can be used for this purpose. In this study, we attempted to validate various RMIs with the help of menopausal status, ultrasonogram score, cancer antigen (CA) 125 value and compare all four RMIs, which would be useful to differentiate benign and malignant ovarian masses. This could be an essential tool, especially in low-resource settings. METHOD: This prospective study was conducted at Kalinga Institute of Medical Sciences in Odisha, India, from September 2020 to September 2022 involving 191 patients with ovarian mass with histopathology, which was deemed the "gold standard" diagnostic tool. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of RMI 1, 2, 3, and 4 were calculated and compared.  Results: Out of 191 patients, 32 (16%) had malignancy and 159 (83.2%) had benign pathology. It was apparent that RMI 4 was a better tool for the initial assessment of patients with ovarian masses with a sensitivity of 80.6%, specificity of 96.2%, PPV of 81%, NPV of 96% at a cutoff of 334, and an area under the curve value of 0.939. CONCLUSION: RMI 4 followed by RMI 3 were relatively better indices than RMI 1 and RMI 2 for identifying benign and malignant ovarian masses. RMI 4 was a valuable and applicable method in diagnosing pelvic masses with a high risk of malignancy.

Dual Deep CNN for Tumor Brain Classification.

Brain tumor (BT) is a serious issue and potentially deadly disease that receives much attention. However, early detection and identification of tumor type and location are crucial for effective treatment and saving lives. Manual diagnoses are time-consuming and depend on radiologist experts; the increasing number of new cases of brain tumors makes it difficult to process massive and large amounts of data rapidly, as time is a critical factor in patients' lives. Hence, artificial intelligence (AI) is vital for understanding disease and its various types. Several studies proposed different techniques for BT detection and classification. These studies are on machine learning (ML) and deep learning (DL). The ML-based method requires handcrafted or automatic feature extraction algorithms; however, DL becomes superior in self-learning and robust in classification and recognition tasks. This research focuses on classifying three types of tumors using MRI imaging: meningioma, glioma, and pituitary tumors. The proposed DCTN model depends on dual convolutional neural networks with VGG-16 architecture concatenated with custom CNN (convolutional neural networks) architecture. After conducting approximately 22 experiments with different architectures and models, our model reached 100% accuracy during training and 99% during testing. The proposed methodology obtained the highest possible improvement over existing research studies. The solution provides a revolution for healthcare providers that can be used as a different disease classification in the future and save human lives.

Accuracy of the risk of malignancy index-I in diagnosing ovarian malignancy in menopausal women.

Introduction: To detect the accuracy of the risk of malignancy index-I (RMI-I) in diagnosing ovarian malignancy in menopausal women. Material and methods: Eighty-two menopausal women with suspected ovarian masses (OMs) scheduled for surgery were included in this study. Blood samples were preoperatively collected from participants to measure the CA-125, followed by transvaginal sonography to evaluate the suspected OMs regarding the consistency, whether the OMs were unilateral or bilateral, unilocular or multilocular, and for extra-ovarian metastasis. The preoperative RMIs were compared to the postoperative histology of the excised OMs to detect the accuracy of RMI-I at a cut-off value of 200 in diagnosing ovarian malignancy. The receiver operating characteristic curve was also used to detect the cut-off value of RMI-I with the highest sensitivity and specificity in diagnosing ovarian malignancy in menopausal women. Results: The incidence of benign and malignant OMs in the studied menopausal women was 59.8% and 40.2%, respectively. The risk of malignancy index-I at a cut-off value 200 in this study had 75.8% sensitivity, 91.8% specificity, 86.2% positive predictive value (PPV), and 84.9% negative predictive value (NPV) in diagnosing ovarian malignancy in menopausal women. The receiver operating characteristic curve showed that the RMI-I at a cut-off value of > 241.5 had 96% sensitivity and 94.74% specificity in diagnosing ovarian malignancy in menopausal women (AUC 0.98, 95% CI: 0.92-0.99, p < 0.001). Conclusions: The risk of malignancy index I at a cut-off value of 200 had 75.8% sensitivity, 91.8% specificity, 86.2% PPV, and 84.9% NPV in diagnosing ovarian malignancy in menopausal women. The receiver operating characteristic curve showed that the RMI-I at a cut-off value > 241.5 had 96% sensitivity and 94.74% specificity in diagnosing ovarian malignancy in menopausal women.

Broadness and specificity: ArdB, ArdA, and Ocr against various restriction-modification systems.

ArdB, ArdA, and Ocr proteins inhibit the endonuclease activity of the type I restriction-modification enzymes (RMI). In this study, we evaluated the ability of ArdB, ArdA, and Ocr to inhibit different subtypes of Escherichia coli RMI systems (IA, IB, and IC) as well as two Bacillus licheniformis RMI systems. Furthermore we explored, the antirestriction activity of ArdA, ArdB, and Ocr against a type III restriction-modification system (RMIII) EcoPI and BREX. We found that DNA-mimic proteins, ArdA and Ocr exhibit different inhibition activity, depending on which RM system tested. This effect might be linked to the DNA mimicry nature of these proteins. In theory, DNA-mimic might competitively inhibit any DNA-binding proteins; however, the efficiency of inhibition depend on the ability to imitate the recognition site in DNA or its preferred conformation. In contrast, ArdB protein with an undescribed mechanism of action, demonstrated greater versatility against various RMI systems and provided similar antirestriction efficiency regardless of the recognition site. However, ArdB protein could not affect restriction systems that are radically different from the RMI such as BREX or RMIII. Thus, we assume that the structure of DNA-mimic proteins allows for selective inhibition of any DNA-binding proteins depending on the recognition site. In contrast, ArdB-like proteins inhibit RMI systems independently of the DNA recognition site.

[Anti-Restriction Activity of ArdB Protein against EcoAI Endonuclease].

ArdB proteins are known to inhibit the activity of the type I restriction-modification (RM-I) system, in particular EcoKI (IA family). The mechanism of ArdB's activity still remains unknown; the spectrum of targets inhibited has been poorly studied. In this work, it was shown that the presence of the ardB gene from the R64 plasmid could suppress the activity of EcoAI endonuclease (IB family) in Escherichia coli TG1 cells. Due to the absence of specificity of ArdB to a certain RM-I system (it inhibits both the IA- and IB-family), it can be assumed that the mechanism of the anti-restriction activity of this protein does not depend on the sequence DNA at the recognition site nor the structure of the restriction enzyme of the RM-I systems.

Evaluating the risk of malignancy in adnexal masses: validation of O-RADS and comparison with ADNEX model, SA, and RMI.

OBJECTIVES: To evaluate the diagnostic value of Ovarian-adnexal Reporting and Data System (O-RADS), and to compare it with Assessment of Different NEoplasias in the adnexa (ADNEX) model, Subjective Assessment (SA), and Risk of Malignancy Index (RMI) in differentiating benign and malignant adnexal masses (AMs). MATERIAL AND METHODS: Ultrasound characteristics of 445 patients included in the study were retrospectively analyzed and evaluated using diagnostic models. The diagnostic performances of ultrasound diagnostic models were measured by assessing, receiver-operating characteristic curves, sensitivities, positive predictive values, positive likelihood ratios, specificities, negative predictive values, and negative likelihood ratios. Kappa values were used to evaluate inter-reviewer agreement (IRA). RESULTS: Of the 445 AMs, 265 were benign and 180 were malignant. The area under the curve (AUC) of O-RADS (0.941), ADNEX model (0.925), and SA (0.931) were higher than RMI (0.815) (all p < 0.05). The sensitivity of O-RADS (93.3%), ADNEX model (94.4%), and SA (96.1%) were higher than RMI (70.6%) (p > 0.05), and there was no statistical significance among them (p > 0.05). The specificity of O-RADS, ADNEX model, SA, and RMI was 90.2%, 90.6%, 90.2%, and 92.5%, respectively, with no statistical significance (p > 0.05). All four ultrasound diagnostic methods showed better IRA. CONCLUSIONS: O-RADS, ADNEX model and SA have better diagnostic value in differentiating benign and malignant AMs than RMI.

RMI2 is a novel prognostic and predictive biomarker for breast cancer.

BACKGROUND: RecQ-mediated genome instability 2 (RMI2) maintains genome stability by promoting DNA damage repair. It has been reported to accelerate the progression of several tumors. However, the functional mechanism of RMI2 in breast cancer remains unclear. METHODS: Gene expression profiles were obtained from TCGA, GTEx, and GEO databases. The expression of RMI2 and its prognostic value in breast cancer was explored. In addition, we calculated pooled standardized mean deviation (SMD) and performed a summary receiver operating characteristic (sROC) curve analysis to further determine RMI2 expression status and diagnostic significance. The functions and related signaling pathways were investigated based on GO and KEGG analyses. The PPI network was constructed by combining the STRING database and Cytoscape software. Subsequently, in vitro assays were conducted to detect the effect of RMI2 on the proliferation and migration of breast cancer cells. RESULTS: The expression of RMI2 was markedly upregulated in breast cancer tissues relative to that in normal tissues. Moreover, pooled SMD further confirmed the overexpression of RMI2 in breast cancer (SMD = 1.29, 95% confidence interval (CI): 1.18-1.41, p = 0.000). The sROC curve analysis result suggested that RMI2 had a relatively high diagnostic ability in breast cancer (AUC = 0.87, 95% CI: 0.84-0.90). High RMI2 expression was associated with poor prognosis. GO and KEGG analyses revealed that RMI2 was closely related to cell adhesion, various enzyme activities, and PI3K/AKT signaling pathway. PPI analysis showed that RMI2 had interactions with proteins involved in DNA damage repair. knockdown of RMI2 remarkably inhibited the proliferation and migration of breast cancer cells, while overexpression of RMI2 exerted the opposite effects. Furthermore, we identified that RMI2 accelerates the proliferation and migration of breast cancer cells via activation of the PI3K/AKT pathway. CONCLUSION: The results suggest that RMI2 is a potential diagnostic and prognostic biomarker associated with cell proliferation and migration, and may be used as a novel therapeutic target for breast cancer in the future.

Morphological parameters of ovarian masses and accuracy of the risk of malignancy index in diagnosing ovarian malignancy.

Introduction: To detect the morphological parameters of ovarian masses and the accuracy of the risk of mali-gnancy index (RMI) in diagnosing ovarian malignancy. Material and methods: 264 women in 3 groups (reproductive, premenopausal, and postmenopausal) presented with ovarian masses and scheduled for surgery were included in this study. The participants' preoperative RMI was compared to the postoperative histology (gold standard) to detect the accuracy of RMI in diagnosing ovarian malignancy. Results: The incidence of malignant and benign ovarian tumours in the reproductive group was 9.1% and 90.9%, respectively, while it was 35.2% and 64.8%, respectively, in the premenopausal group, and 35.2%, and 64.8%, respectively, in the postmenopausal group. The incidence of malignant ovarian tumours was significantly higher in the premenopausal (35.2%) and postmenopausal (35.2%) groups compared to the reproductive group (9.1%), (p = 0.0008, and p = 0.0008, respectively).The receiver operating characteristic curve showed that RMI at cut-off value > 247.5 had 82.9% sensitivity, 100% specificity, 100% positive predictive value (PPV), and 98.1% negative predictive value (NPV) in diagnosing ovarian malignancy in the 3 studied groups (AUC 0.955, p < 0.001). There was significant positive correlation between the participants' age, and RMI (p = 0.001), and between participants' cancer antigen-125 (CA-125) and RMI (p < 0.0001) in the ovarian malignancy group. Conclusions: The multimodal RMI is an effective tool for primary evaluation of suspected ovarian masses. Risk malignancy index at cut-off value > 247.5 had the best performance (82.9% sensitivity, 100% specificity, 100% PPV, and 98.1% NPV) in diagnosing ovarian malignancy in the 3 studied groups. There was significant positive correlation between participants' age, and RMI, and between participants' CA-125 and RMI, in the studied malignant ovarian tumours.

Molecular Biomarkers for the Early Detection of Ovarian Cancer.

Ovarian cancer is the deadliest gynecological cancer, leading to over 152,000 deaths each year. A late diagnosis is the primary factor causing a poor prognosis of ovarian cancer and often occurs due to a lack of specific symptoms and effective biomarkers for an early detection. Currently, cancer antigen 125 (CA125) is the most widely used biomarker for ovarian cancer detection, but this approach is limited by a low specificity. In recent years, multimarker panels have been developed by combining molecular biomarkers such as human epididymis secretory protein 4 (HE4), ultrasound results, or menopausal status to improve the diagnostic efficacy. The risk of ovarian malignancy algorithm (ROMA), the risk of malignancy index (RMI), and OVA1 assays have also been clinically used with improved sensitivity and specificity. Ongoing investigations into novel biomarkers such as autoantibodies, ctDNAs, miRNAs, and DNA methylation signatures continue to aim to provide earlier detection methods for ovarian cancer. This paper reviews recent advancements in molecular biomarkers for the early detection of ovarian cancer.

Blockchain Socket Factories with RMI-Enabled Framework for Fine-Grained Healthcare Applications.

The usage of digital and intelligent healthcare applications on mobile devices has grown progressively. These applications are generally distributed and access remote healthcare services on the user's applications from different hospital sources. These applications are designed based on client-server architecture and different paradigms such as socket, remote procedure call, and remote method invocation (RMI). However, these existing paradigms do not offer a security mechanism for healthcare applications in distributed mobile-fog-cloud networks. This paper devises a blockchain-socket-RMI-based framework for fine-grained healthcare applications in the mobile-fog-cloud network. This study introduces a new open healthcare framework for applied research purposes and has blockchain-socket-RMI abstraction level classes for healthcare applications. The goal is to meet the security and deadline requirements of fine-grained healthcare tasks and minimize execution and data validation costs during processing applications in the system. This study introduces a partial proof of validation (PPoV) scheme that converts the workload into the hash and validates it among mobile, fog, and cloud nodes during offloading, execution, and storing data in the secure form. Simulation discussions illustrate that the proposed blockchain-socket-RMI minimizes the processing and blockchain costs and meets the security and deadline requirements of fine-grained healthcare tasks of applications as compared to existing frameworks in work.

Diagnostic Models Combining Clinical Information, Ultrasound and Biochemical Markers for Ovarian Cancer: Cochrane Systematic Review and Meta-Analysis.

Background: Ovarian cancer (OC) is a diagnostic challenge, with the majority diagnosed at late stages. Existing systematic reviews of diagnostic models either use inappropriate meta-analytic methods or do not conduct statistical comparisons of models or stratify test performance by menopausal status. Methods: We searched CENTRAL, MEDLINE, EMBASE, CINAHL, CDSR, DARE, Health Technology Assessment Database and SCI Science Citation Index, trials registers, conference proceedings from 1991 to June 2019. Cochrane collaboration review methods included QUADAS-2 quality assessment and meta-analysis using hierarchical modelling. RMI, ROMA or ADNEX at any test positivity threshold were investigated. Histology or clinical follow-up was the reference standard. We excluded screening studies, studies restricted to pregnancy, recurrent or metastatic OC. 2 × 2 diagnostic tables were extracted separately for pre- and post-menopausal women. Results: We included 58 studies (30,121 patients, 9061 cases of ovarian cancer). Prevalence of OC ranged from 16 to 55% in studies. For premenopausal women, ROMA at a threshold of 13.1 (+/−2) and ADNEX at a threshold of 10% demonstrated significantly higher sensitivity compared to RMI I at 200 (p < 0.0001) 77.8 (72.5, 82.4), 94.9 (92.5, 96.6), and 57.1% (50.6 to 63.4) but lower specificity (p < 0.002), 92.5 (90.0, 94.4), 84.3 (81.3, 86.8), and 78.2 (75.8, 80.4). For postmenopausal women, ROMA at a threshold of 27.7 (+/−2) and AdNEX at a threshold of 10% demonstrated significantly higher sensitivity compared to RMI I at a threshold of 200 (p < 0.001) 90.4 (87.4, 92.7), 97.6 (96.2, 98.5), and 78.7 (74.3, 82.5), specificity of ROMA was comparable, whilst ADneX was lower, 85.5 (81.3, 88.9), 81.3 (76.9, 85.0) (p = 0.155), compared to RMI 55.2 (51.2, 59.1) (p < 0.001). Conclusions: In pre-menopausal women, ROMA and ADNEX offer significantly higher sensitivity but significantly decreased specificity. In post-menopausal women, ROMA demonstrates significantly higher sensitivity and comparable specificity to RMI I, ADNEX has the highest sensitivity of all models, but with significantly reduced specificity. RMI I has poor sensitivity compared to ROMA or ADNEX. Choice between ROMA and ADNEX as a replacement test will depend on cost effectiveness and resource implications.

Can serum human epididymis protein 4 (HE4) support the decision to refer a patient with an ovarian mass to an oncology hospital?

INTRODUCTION: The value of serum human epididymis protein 4 (HE4) in guiding referral decisions in patients with an ovarian mass remains unclear, because the majority of studies investigating HE4 were performed in oncology hospitals. However, the decision to refer is made at general hospitals with a low ovarian cancer prevalence. We assessed accuracies of HE4 in differentiating benign or borderline from malignant tumors in patients presenting with an ovarian mass at general hospitals. METHOD: Patients with an ovarian mass were prospectively included between 2017 and 2021 in nine general hospitals. HE4 and CA125 were preoperatively measured and the risk of malignancy index (RMI) was calculated. Histological diagnosis was the reference standard. RESULTS: We included 316 patients, of whom 195 had a benign, 39 had a borderline and 82 had a malignant ovarian mass. HE4 had the highest AUC of 0.80 (95%CI 0.74-0.86), followed by RMI (0.71, 95%CI 0.64-0.78) and CA125 (0.69, 95%CI 0.62-0.75). Clinical setting significantly influenced biomarker performances. Applying age-dependent cut-off values for HE4 resulted in a better performance than one cut-off. Addition of HE4 to RMI resulted in a 32% decrease of unnecessary referred patients, while the number of correctly referred patients remained the same. CONCLUSION: HE4 is superior to RMI in predicting malignancy in patients with an ovarian mass from general hospitals. The addition of HE4 to the RMI improved HE4 alone. Although, there is still room for improvement, HE4 can guide referral decisions in patients with an ovarian mass to an oncology hospital.

Multifaceted regulation of the sumoylation of the Sgs1 DNA helicase.

Homologous recombination repairs DNA breaks and sequence gaps via the production of joint DNA intermediates such as Holliday junctions. Dissolving Holliday junctions into linear DNA repair products requires the activity of the Sgs1 helicase in yeast and of its homologs in other organisms. Recent studies suggest that the functions of these conserved helicases are regulated by sumoylation; however, the mechanisms that promote their sumoylation are not well understood. Here, we employed in vitro sumoylation systems and cellular assays to determine the roles of DNA and the scaffold protein Esc2 in Sgs1 sumoylation. We show that DNA binding enhances Sgs1 sumoylation in vitro. In addition, we demonstrate the Esc2's midregion (MR) with DNA-binding activity is required for Sgs1 sumoylation. Unexpectedly, we found that the sumoylation-promoting effect of Esc2-MR is DNA independent, suggesting a second function for this domain. In agreement with our biochemical data, we found the Esc2-MR domain, like its SUMO E2-binding C-terminal domain characterized in previous studies, is required for proficient sumoylation of Sgs1 and its cofactors, Top3 and Rmi1, in cells. Taken together, these findings provide evidence that while DNA binding enhances Sgs1 sumoylation, Esc2-based stimulation of this modification is mediated by two distinct domains.

Potent Blockchain-Enabled Socket RPC Internet of Healthcare Things (IoHT) Framework for Medical Enterprises.

Present-day intelligent healthcare applications offer digital healthcare services to users in a distributed manner. The Internet of Healthcare Things (IoHT) is the mechanism of the Internet of Things (IoT) found in different healthcare applications, with devices that are attached to external fog cloud networks. Using different mobile applications connecting to cloud computing, the applications of the IoHT are remote healthcare monitoring systems, high blood pressure monitoring, online medical counseling, and others. These applications are designed based on a client-server architecture based on various standards such as the common object request broker (CORBA), a service-oriented architecture (SOA), remote method invocation (RMI), and others. However, these applications do not directly support the many healthcare nodes and blockchain technology in the current standard. Thus, this study devises a potent blockchain-enabled socket RPC IoHT framework for medical enterprises (e.g., healthcare applications). The goal is to minimize service costs, blockchain security costs, and data storage costs in distributed mobile cloud networks. Simulation results show that the proposed blockchain-enabled socket RPC minimized the service cost by 40%, the blockchain cost by 49%, and the storage cost by 23% for healthcare applications.

Biomarkers for Early Diagnosis of Ovarian Carcinoma.

The leading cause of gynecological cancer-related morbidity and mortality is ovarian cancer (OC), which is dubbed a silent killer. Currently, OC is a target of intense biomarker research, because it is often not discovered until the disease is advanced. The goal of OC research is to develop effective tests using biomarkers that can detect the disease at the earliest stages, which would eventually decrease the mortality, thereby preventing recurrence. Therefore, there is a pressing need to revisit the existing biomarkers to recognize the potential biomarkers that can lead to efficient predictors for the OC diagnosis. This Perspective covers an update on the currently available biomarkers used in the triaging of OC to gain certain insights into the potential role of these biomarkers and their estimation that are crucial to the understanding of neoplasm progression, diagnostics, and therapy.