Enhancing gastric cancer early detection: A multi-verse optimized feature selection model with crossover-information feedback.

Gastric cancer (GC), an acknowledged malignant neoplasm, threatens life and digestive system functionality if not detected and addressed promptly in its nascent stages. The indispensability of early detection for GC to augment treatment efficacy and survival prospects forms the crux of this investigation. Our study introduces an innovative wrapper-based feature selection methodology, referred to as bCIFMVO-FKNN-FS, which integrates a crossover-information feedback multi-verse optimizer (CIFMVO) with the fuzzy k-nearest neighbors (FKNN) classifier. The primary goal of this initiative is to develop an advanced screening model designed to accelerate the identification of patients with early-stage GC. Initially, the capability of CIFMVO is validated through its application to the IEEE CEC benchmark functions, during which its optimization efficiency is measured against eleven cutting-edge algorithms across various dimensionalities-10, 30, 50, and 100. Subsequent application of the bCIFMVO-FKNN-FS model to the clinical data of 1632 individuals from Wenzhou Central Hospital-diagnosed with either early-stage GC or chronic gastritis-demonstrates the model's formidable predictive accuracy (83.395%) and sensitivity (87.538%). Concurrently, this investigation delineates age, gender, serum gastrin-17, serum pepsinogen I, and the serum pepsinogen I to serum pepsinogen II ratio as parameters significantly associated with early-stage GC. These insights not only validate the efficacy of our proposed model in the early screening of GC but also contribute substantively to the corpus of knowledge facilitating early diagnosis.

Predictive modeling of deep vein thrombosis risk in hospitalized patients: A Q-learning enhanced feature selection model.

Deep vein thrombosis (DVT) represents a critical health concern due to its potential to lead to pulmonary embolism, a life-threatening complication. Early identification and prediction of DVT are crucial to prevent thromboembolic events and implement timely prophylactic measures in high-risk individuals. This study aims to examine the risk determinants associated with acute lower extremity DVT in hospitalized individuals. Additionally, it introduces an innovative approach by integrating Q-learning augmented colony predation search ant colony optimizer (QL-CPSACO) into the analysis. This algorithm, then combined with support vector machines (SVM), forms a bQL-CPSACO-SVM feature selection model dedicated to crafting a clinical risk prognostication model for DVT. The effectiveness of the proposed algorithm's optimization and the model's accuracy are assessed through experiments utilizing the CEC 2017 benchmark functions and predictive analyses on the DVT dataset. The experimental results reveal that the proposed model achieves an outstanding accuracy of 95.90% in predicting DVT. Key parameters such as D-dimer, normal plasma prothrombin time, prothrombin percentage activity, age, previously documented DVT, leukocyte count, and thrombocyte count demonstrate significant value in the prognostication of DVT. The proposed method provides a basis for risk assessment at the time of patient admission and offers substantial guidance to physicians in making therapeutic decisions.

Performance optimization of support vector machine with oppositional grasshopper optimization for acute appendicitis diagnosis.

Preoperative differentiation of complicated and uncomplicated appendicitis is challenging. The research goal was to construct a new intelligent diagnostic rule that is accurate, fast, noninvasive, and cost-effective, distinguishing between complicated and uncomplicated appendicitis. Overall, 298 patients with acute appendicitis from the Wenzhou Central Hospital were recruited, and information on their demographic characteristics, clinical findings, and laboratory data was retrospectively reviewed and applied in this study. First, the most significant variables, including C-reactive protein (CRP), heart rate, body temperature, and neutrophils discriminating complicated from uncomplicated appendicitis, were identified using random forest analysis. Second, an improved grasshopper optimization algorithm-based support vector machine was used to construct the diagnostic model to discriminate complicated appendicitis (CAP) from uncomplicated appendicitis (UAP). The resultant optimal model can produce an average of 83.56% accuracy, 81.71% sensitivity, 85.33% specificity, and 0.6732 Matthews correlation coefficients. Based on existing routinely available markers, the proposed intelligent diagnosis model is highly reliable. Thus, the model can potentially be used to assist doctors in making correct clinical decisions.

Evolving fuzzy k-nearest neighbors using an enhanced sine cosine algorithm: Case study of lupus nephritis.

Because of its simplicity and effectiveness, fuzzy K-nearest neighbors (FKNN) is widely used in literature. The parameters have an essential impact on the performance of FKNN. Hence, the parameters need to be attuned to suit different problems. Also, choosing more representative features can enhance the performance of FKNN. This research proposes an improved optimization technique based on the sine cosine algorithm (LSCA), which introduces a linear population size reduction mechanism for enhancing the original algorithm's performance. Moreover, we developed an FKNN model based on the LSCA, it simultaneously performs feature selection and parameter optimization. Firstly, the search performance of LSCA is verified on the IEEE CEC2017 benchmark test function compared to the classical and improved algorithms. Secondly, the validity of the LSCA-FKNN model is verified on three medical datasets. Finally, we used the proposed LSCA-FKNN to predict lupus nephritis classes, and the model showed competitive results. The paper will be supported by an online web service for any question at https://aliasgharheidari.com.

Long Noncoding RNA PCAT18 Upregulates SPRR3 to Promote Colorectal Cancer Progression by Binding to miR-759.

BACKGROUND: Long noncoding RNAs (lncRNAs) play essential functions in the development of several cancers, including colorectal cancer (CRC). Nevertheless, how PCAT18 regulates CRC tumorigenesis remains unclear. In this research, we aimed to investigate the roles of PCAT18 in CRC. MATERIALS AND METHODS: qRT-PCR and Western blot were used to analyze RNA and protein levels. CCK8, colony formation, transwell and wound healing assays were utilized to analyze proliferation, migration and invasion. Luciferase reporter assay was used to analyze RNA interactions. RESULTS: PCAT18 was found to be highly expressed in CRC tissues and cells. PCAT18 level was positively correlated with lymph node metastasis and TNM stage. Functionally, PCAT18 silencing induced impairment of CRC proliferation, migration and invasion. Besides, PCAT18 was identified to inhibit miR-759. PCAT18 promotes SPRR3 expression through binding to miR-759. Furthermore, miR-759 inhibitors or SPRR3 ectopic expression partially rescued the abilities of proliferation, migration and invasion in CRC cells transfected with sh-PCAT18. CONCLUSION: Therefore, our study demonstrated that PCAT18 contributes to CRC progression through regulating miR-759/SPRR3 axis, which provides a new theoretical basis of explaining CRC tumorigenesis.

Circular RNA hsa_circRNA_102958 promotes tumorigenesis of colorectal cancer via miR-585/CDC25B axis.

Purpose: Circular RNAs (circRNAs) are recently identified new noncoding RNAs and play an important role in tumorigenesis. Previous studies have indicated that hsa_circRNA_102958 is a potential diagnostic indicator in gastric cancer. However, its role in colorectal cancer (CRC) is poorly understood. Methods: qRT-PCR and ISH were used to test gene expression in tissues. Survival rate was analzyed by Kaplan-Meier curve. Luciferase reporter assay was used to determine the interaction between circRNA and miRNA or between miRNA and mRNA. Western blotting was used to test protein expression. CCK8 and colony formation assay was used to analyze proliferation. Transwell assay was used for migration and invasion determination. Results: In our research, we found that hsa_circRNA_102958 expression was significantly increased in CRC tissues, compared to adjacent normal controls. Increased hsa_circRNA_102958 levels in CRC patients indicated a poor prognosis. The effects of hsa_circRNA_102958 on CRC cell proliferation, migration and invasion were then determined by CCK8, colony formation and Transwell assays. We showed that hsa_circRNA_102958 silencing markedly suppressed CRC growth, migration and invasion. Furthermore, hsa_circRNA_102958 was identified as a sponge for miR-585. We demonstrated that hsa_circRNA_102958 promoted CDC25B expression through inhibiting miR-585 in CRC. Rescue assays illustrated that CDC25B overexpression reversed the suppressive effects of hsa_circRNA_102958 silencing on CRC. Conclusion: Taken together, our findings revealed the novel oncogenic roles of hsa_circRNA_102958 in CRC through miR-585/CDC25B axis.

A novel lncRNA LOC101927746 accelerates progression of colorectal cancer via inhibiting miR-584-3p and activating SSRP1.

An increasing number of reports have indicated that long noncoding RNAs (lncRNAs) are involved in the pathogenesis of colorectal cancer (CRC). However, many lncRNAs remain unidentified in CRC, and their functions are yet to be elucidated. In this study, we investigated the function of lncRNA LOC101927746 in CRC progression. We found that LOC101927746 expression was significantly increased in CRC tissues according to the GEO dataset. Moreover, LOC101927746 expression was positively correlated with tumor stage and metastasis. Additionally, the high expression of LOC101927746 predicted poor prognosis in CRC patients. Functionally, we demonstrated that LOC101927746 silencing significantly suppressed the proliferation, migration, and invasion of CRC cells. In terms of its mechanism, LOC101927746 could serve as a competing endogenous RNA to inhibit miR-584-3p and activate its target gene SSRP1. The expression of miR-584-3p was inversely correlated with either LOC101927746 or SSRP1 in CRC tissues. The overexpression of SSRP1 or inhibition of miR-584-3p could reverse the effects of LOC101927746 knockdown in CRC cells. Taken together, our results suggest that the LOC101927746/miR-584-3p/SSRP1 axis modulates CRC progression.

Long noncoding RNA lncBRM promotes proliferation and invasion of colorectal cancer by sponging miR-204-3p and upregulating TPT1.

Long noncoding RNAs (lncRNAs) are characterized as a type of noncoding RNAs over 200 nucleotides with little or none protein-coding potential. In the past years, lncRNAs have been proved to participant in many physiological and pathological processes. However, the role of lncRNAs in colorectal cancer (CRC) still needs more attentions. In our study, we found that lncBRM was highly expressed in CRC samples and the expression level of lncBRM was correlated with metastasis and advanced stage in CRC patients. And also, we showed that high expression of lncBRM predicted poor prognosis. Furthermore, we found that knockdown of lncBRM impaired the proliferation, migration and invasion of CRC cells while overexpressing of lncBRM promotes the proliferation, migration and invasion of CRC cells. Mechanically, we found that lncBRM served as a sponge of miR-204-3p that targeted TPT1. Highly expressed TPT1 can promote the proliferation, migration and invasion of CRC cells. In conclusion, we found that lncBRM was highly expressed in CRC and sponged miR-204-3p to modulate the expression of TPT1.

miR­3666 suppresses cellular proliferation and invasion in colorectal cancer by targeting SATB2.

MicroRNA­3666 (miR­3666) acts as a tumor suppressor in cervical cancer, non­small cell lung cancer and thyroid carcinoma; however, the function of miR­3666 in colorectal cancer (CRC) remains largely unknown. In the present study, was demonstrated that miR­3666 was significantly downregulated in CRC tissues compared with in adjacent normal tissues by reverse transcription­quantitative polymerase chain reaction. Additionally, miR­3666 may serve as a prognostic biomarker for patients with CRC. Via functional experiments, the present study reported that miR­3666 overexpression significantly inhibited the proliferation, migration and invasion of CRC cells as determined by Cell Counting Kit­8 and Transwell assays, and vice versa. In addition, miR­3666 was reported to directly target special AT­rich sequence binding protein 2 (SATB2) in CRC cells; overexpression of miR­3666 significantly suppressed the expression of SATB2 in CRC cells as determined by western blotting. Furthermore, an inverse correlation was observed between the expression levels of miR­3666 and SATB2 in CRC tissues. Restoration of SATB1 expression significantly reversed the effects of miR­3666 mimic on CRC cells. In summary, the results of the present study indicated that miR­3666 may serve as a tumor suppressor in CRC by targeting SATB2.

Preoperative serum visfatin levels and prognosis of breast cancer among Chinese women.

Visfatin is identified a pro-inflammatory cytokine and its serum level is increased in various cancers. This study aimed to evaluate the prognostic value of preoperative serum visfatin level in breast cancers. Preoperative serum visfatin levels of 248 patients with breast cancer and serum visfatin levels of 100 healthy individuals and 100 benign women controls were determined using enzyme-linked immunosorbent assay. Unfavorable outcome was defined as first local recurrence, distant metastasis, second primary cancer of another organ, or death from any cause. Disease-free survival was defined as the time between surgery and the date of unfavorable outcome whichever appeared first. Overall survival was defined from surgery to death for any cause. The association of serum visfatin level with outcomes including mortality, unfavorable outcome, disease-free survival and overall survival was investigated by univariate and multivariate analyses. Preoperative serum visfatin level was substantially higher in patients than in healthy subjects and benign controls respectively. Elevated preoperative serum level of visfatin was identified an independent predictor of mortality, unfavorable outcome, disease-free survival and overall survival. Receiver operating characteristic curve analysis showed that serum level visfatin had high predictive value for mortality and unfavorable outcome. Thus, our results suggest that high preoperative serum visfatin level is associated with poor patient outcomes as well as may play a role as prognostic biomarker in breast cancer survival.