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Defect prediction is crucial for software quality assurance and has been extensively researched over recent decades. However, prior studies rarely focus on data complexity in defect prediction tasks, and even less on understanding the difficulties of these tasks from the perspective of data complexity. In this article, we conduct an empirical study to estimate the hardness of over 33,000 instances, employing a set of measures to characterize the inherent difficulty of instances and the characteristics of defect datasets. Our findings indicate that: (1) instance hardness in both classes displays a right-skewed distribution, with the defective class exhibiting a more scattered distribution; (2) class overlap is the primary factor influencing instance hardness and can be characterized through feature, structural, and instance-level overlap; (3) no universal preprocessing technique is applicable to all datasets, and it may not consistently reduce data complexity, fortunately, dataset complexity measures can help identify suitable techniques for specific datasets; (4) integrating data complexity information into the learning process can enhance an algorithm's learning capacity. In summary, this empirical study highlights the crucial role of data complexity in defect prediction tasks, and provides a novel perspective for advancing research in defect prediction techniques. [ABSTRACT FROM AUTHOR]

Herein, we used DIANA TOOLS, gene expression profiling interactive analysis and other bioinformatics databases to predict regulatory pathways in breast cancer. Accordingly, we clarified the regulatory mechanism of eyes absent family of protein (EYA2) on miR-93 expression to aggravate breast cancer, which was involved with the STING signaling pathway. Cholecystokinin octapeptide assay, scratch test, Transwell assay and flow cytometry were applied to detect cell viability, migration, invasion and apoptosis. The experimental data found that EYA2 was highly expressed in breast cancer tissues and cells and associated with poor prognosis. Overexpression of miR-93 in breast cancer was positively correlated with EYA2. EYA2 promoted miR-93 expression, advanced breast cancer cell proliferation and inhibited their apoptosis. Results of luciferase assay showed that miR-93 was enriched in the STING 3'UTR (untranslated region). Furthermore, knockdown of EYA2 inhibited the expression of miR-93, promoted the expression of STING and inhibited the tumor growth. In response to EYA2 knockdown, the expression of IFN-β and interferon-stimulated gene was increased, and PD-L1 was decreased. In addition, the phosphorylation level of TANK-binding kinase 1 and interferon regulatory factor 3 was enhanced, the percentage of myeloid-derived suppressor cells in blood was reduced, and secretion of IFN-β and IL-12 was enhanced. In conclusion, EYA2 upregulates miR-93 expression and promotes malignancy of breast cancer by targeting and inhibiting the STING signaling pathway. [ABSTRACT FROM AUTHOR]

Software defect prediction aims to predict defect-prone code regions automatically before defects are discovered. Accurate prediction helps software practitioners to prioritize their testing efforts. In recent decades, dozens of approaches have been put forward and acquired good results in this field. However, in practical scenarios, many projects have limited labeled instances; more than that, most of these labeled instances are nondefective. The lack of training data and class imbalance problem together bring serious challenges to software defect prediction tasks. So far, few of prevailing approaches can well handle these two difficulties simultaneously. One important reason is that they do not pay adequate attention to several key instances, which are difficult to classify in a small imbalanced dataset. This article introduces the concept of “instance hardness” to integrate various difficulties of imbalance classification tasks. Based on it, a novel imbalance learning framework named self-paced ensemble of ensembles (SPE $^{2}$) is proposed to perform software defect prediction. SPE $^{2}$ aims to generate a strong ensemble of ensembles by self-paced harmonizing instance hardness via undersampling. Finally, SPE $^{2}$ is extensively compared with eight imbalance learning approaches on ten open-source defect datasets. Experiments indicate that SPE $^{2}$ improves the performance and achieves better and more significant F-measure values than its existing counterparts, based on Brunner’s statistical significance test and Cliff’s effect sizes. [ABSTRACT FROM AUTHOR]

Introduction: This real-world study evaluated the efficacy, safety, and operative parameters of two perfluoropropane (C3F8) tamponade methods combined with pars plana vitrectomy (PPV) for retinal detachment (RD). Methods: A retrospective study of 132 patients (132 eyes) with RD (pure C3F8 in 38 eyes, mixed C3F8 in 94 eyes). All eyes underwent PPV with C3F8 tamponade and were followed up for at least 3 months. Retinal reattachment rate, time of gas configuration and injection, C3F8 dosage, intraocular pressure (IOP), best corrected visual acuity, postoperative ocular inflammation, and patients’ complaints were evaluated. Results: The single-surgery retinal reattachment rates of the pure C3F8 group and mixed C3F8 group were 97.4% and 96.8%, respectively, with no significant difference (p = 1.00). The final retinal reattachment rates of the two groups were 100% and 97.2%, respectively, with no significant difference (p = 1.00). The gas configuration time, gas injection time, and C3F8 dosage were significantly less in the pure C3F8 group (all p < 0.001). Time, but not group, was the influencing factor of postoperative IOP changes in the two groups (p < 0.001, p = 0.547, respectively). Compared with the baseline, the IOP estimates of the pure C3F8 group showed a significant increase immediately after surgery (p < 0.001), and the mixed C3F8 group showed a significant increase immediately and 1–2 days after surgery (all p < 0.05). There was no statistical difference in ocular inflammation (p = 0.339) and patients’ complaints of discomfort (p = 0.175) between the two groups. Conclusion: Both the two methods of C3F8 tamponade combined with PPV in RD patients showed good efficacy and safety, but the clinical operation of pure C3F8 tamponade was more convenient and eco-friendly. [ABSTRACT FROM AUTHOR]

In this work, we report the synthesis of Cu-Ag bimetallic nanopartiles and g-C 3 N 4 nanosheets decorated on zeolitic imidazolate framework-8 (ZIF-8) to form a Cu-Ag/g-C 3 N 4 /ZIF hybrid. The hybrid was synthesized and characterized by Transmission electron microscopy (TEM), Fourier transformed infrared (FTIR), the X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). The Cu-Ag/g-C 3 N 4 /ZIF hybrid has intrinsic peroxidaselike catalytic activity towards the oxidation of TMB in the presence of H 2 O 2 . The situ synthesis of Cu-Ag bimetallic nanopartiles on 2D support such as g-C 3 N 4 nanosheets would significantly enhance the peroxidaselike catalytic properties of individual Cu-Ag bimetallic nanopartiles and the g-C 3 N 4 nanosheets. After loading of Cu-Ag bimetallic nanopartiles and g-C 3 N 4 nanosheets on the ZIF-8, the hybrids exhibited superior peroxidaselike catalytic activity and good recyclability. Then, this method was applied for detecting glucose in human serum, owing the significant potential for detection of metabolites with H 2 O 2 -generation reactions.

Pancreatic cancer (PC) is a lethal cancer in the digestive system. microRNAs (miRNAs) have been demonstrated to participate in PC progression. In this context, we, thus, aimed to explore the mechanism of miR-382 in epithelial mesenchymal transition (EMT) and lymph node metastasis in PC in relation to Anxa3 and the PI3K/Akt signaling pathway. Gene expression data sets GSE16515, GSE71989, and GSE32676 were screened out, with the findings showing the significance of miR-382 and annexin A3 (Anxa3) in PC. A total of 115 PC patients were selected for determination of miR-382 and Anxa3 expression with lowly expressed miR-382 and highly expressed Anxa3 found via RT-quantitative PCR and Western blot analysis. Additionally, negative correlation was found between miR-382 and Anxa3 in PC. Dual-luciferase reporter gene assay and in situ hybridization results confirmed that miR-382 negatively regulated Anxa3. miR-382 targeted Anxa3 and suppressed PC progression by blocking the PI3K/Akt signaling pathway. After a series of gain- and loss-of function approaches, upregulation of miR-382 or silencing of Anxa3 inhibited the EMT and lymph node metastasis, as evidenced by increased level of E-cadherin and decreased level of N-cadherin, vimentin, vascular endothelial growth factor(VEGFR)-3, VEGF-C, and VEGF-D. Overexpression of miR-382 or downregulation of Anxa3 was shown to inhibit colony formation, migration, and invasion abilities of PC cells. Further, tumor xenograft in nude mice in vivo also confirmed the inhibitory role of miR-382 and silenced Anxa3 in lymph node metastasis in PC. Thus, this study provides promising therapeutic targets for PC treatment. NEW & NOTEWORTHY This study focused on the mechanism of miR-382 in epithelial mesenchymal transition and lymph node metastasis in PC in relation to Anxa3 and the PI3K/Akt signaling pathway. We found the inhibitory role of miR-382 in PC in vitro and in vivo.