Multi-Strategy Improved Dung Beetle Optimization Algorithm and Its Applications.

The dung beetle optimization (DBO) algorithm, a swarm intelligence-based metaheuristic, is renowned for its robust optimization capability and fast convergence speed. However, it also suffers from low population diversity, susceptibility to local optima solutions, and unsatisfactory convergence speed when facing complex optimization problems. In response, this paper proposes the multi-strategy improved dung beetle optimization algorithm (MDBO). The core improvements include using Latin hypercube sampling for better population initialization and the introduction of a novel differential variation strategy, termed "Mean Differential Variation", to enhance the algorithm's ability to evade local optima. Moreover, a strategy combining lens imaging reverse learning and dimension-by-dimension optimization was proposed and applied to the current optimal solution. Through comprehensive performance testing on standard benchmark functions from CEC2017 and CEC2020, MDBO demonstrates superior performance in terms of optimization accuracy, stability, and convergence speed compared with other classical metaheuristic optimization algorithms. Additionally, the efficacy of MDBO in addressing complex real-world engineering problems is validated through three representative engineering application scenarios namely extension/compression spring design problems, reducer design problems, and welded beam design problems.

Identification of Three Novel Linear B-Cell Epitopes in Non-Structural Protein 3 of Porcine Epidemic Diarrhea Virus Using Monoclonal Antibodies.

Porcine epidemic diarrhea virus (PEDV) is a highly pathogenic swine coronavirus that causes diarrhea and high mortality in piglets, resulting in significant economic losses within the global swine industry. Nonstructural protein 3 (Nsp3) is the largest in coronavirus, playing critical roles in viral replication, such as the processing of polyproteins and the formation of replication-transcription complexes (RTCs). In this study, three monoclonal antibodies (mAbs), 7G4, 5A3, and 2D7, targeting PEDV Nsp3 were successfully generated, and three distinct linear B-cell epitopes were identified within these mAbs by using Western blotting analysis with 24 truncations of Nsp3. The epitope against 7G4 was located on amino acids 31-TISQDLLDVE-40, the epitope against 5A3 was found on amino acids 141-LGIVDDPAMG-150, and the epitope against 2D7 was situated on amino acids 282-FYDAAMAIDG-291. Intriguingly, the epitope 31-TISQDLLDVE-40 recognized by the mAb 7G4 appears to be a critical B-cell linear epitope due to its high antigenic index and exposed location on the surface of Nsp3 protein. In addition, bioinformatics analysis unveiled that these three epitopes were highly conserved in most genotypes of PEDV. These findings present the first characterization of three novel linear B-cell epitopes in the Nsp3 protein of PEDV and provide potential tools of mAbs for identifying host proteins that may facilitate viral infection.

A retrospective study of dynamic navigation system-assisted implant placement.

BACKGROUND: To evaluate the accuracy of implant placement assisted by a dynamic navigation system, as well as its influencing factors and learning curve. METHODS: At Macao We Care Dental Center, 55 cases of implant placement using dynamic navigation were retrospectively evaluated. To evaluate their accuracy, the apex, tip, and angle deviations of preoperatively planned and postoperatively placed implants were measured. The effects of the upper and lower jaws, different sites or lateral locations of dental implants, and the length and diameter of the implants on accuracy were analyzed, as well as the variation in accuracy with the increase in the number of surgical procedures performed by dentists. RESULTS: The implant had an apex deviation of 1.60 ± 0.94 mm, a tip deviation of 1.83 ± 1.03 mm, and an angle deviation of 3.80 ± 2.09 mm. Statistical differences were observed in the tip deviation of implants at different positions based on three factors: jaw position, lateral location, and tooth position (P < 0.05). The tip deviation of the anterior teeth area was significantly greater than those of the premolar and molar areas. There were no statistically significant differences in apex deviation, tip deviation, or angle deviation between the implants of different diameters and lengths (P > 0.05). There were significant differences in the angle deviation between the final 27 implants and the first 28 implants. Learning curve analysis revealed that angle deviation was negatively correlated with the number of surgical procedures, whereas the regression of apex deviation and tip deviation did not differ statistically. CONCLUSIONS: The accuracy of dynamic navigation-assisted dental implants meets the clinical needs and is higher than that of traditional implants. Different jaw positions, lateral locations, and implant diameters and lengths had no effect on the accuracy of the dental implants guided by the dynamic navigation system. The anterior teeth area had a larger tip deviation than the posterior teeth area did. As the number of dynamic implantation procedures performed by the same implant doctor increased, the angle deviation gradually decreased.

Serum metabolomics analysis reveals metabolite profile and key biomarkers of idiopathic membranous nephropathy.

Background: Idiopathic membranous nephropathy (IMN) is an organ-specific autoimmune disease with multiple and complex pathogenic mechanisms. Currently, renal biopsy is considered the gold standard for diagnosing membranous nephropathy. However, there were limitations to the renal puncture biopsy, such as the relatively high cost, longer time consuming, and the risk of invasive procedures. We investigated the profile of serum metabolites in IMN patients based on the UHPLC-QE-MS metabolomics technique for exploring the potential disease biomarkers and clinical implementation. Methods: In our research, we collected serum samples from healthy control (n = 15) and IMN patients (n = 25) to perform metabolomics analysis based on the UHPLC-QE-MS technique. Result: We identified 215 differentially expressed metabolites (DEMs) between the IMN and healthy control (HC) groups. Furthermore, these DEMs were significantly identified in histidine metabolism, arginine and proline metabolism, pyrimidine metabolism, purine metabolism, and steroid hormone biosynthesis. Several key DEMs were significantly correlated with the level of clinical parameters, such as serum albumin, IgG, UTP, and cholesterol. Among them, dehydroepiandrosterone sulfate (DHEAS) was considered the reliable diagnostic biomarker in the IMN group. There was an increased abundance of actinobacteria, phylum proteobacteria, and class gammaproteobacterial in IMN patients for host-microbiome origin analysis. Conclusion: Our study revealed the profiles of DEMs from the IMN and HC groups. The result demonstrated that there were disorders of amino acids, nucleotides, and steroids hormones metabolism in IMN patients. The down-regulation of DHEAS may be associated with the imbalance of the immune environment in IMN patients. In host-microbiome origin analysis, the gut microbiota and metabolite disturbances were present in IMN patients.

MRI and DC/TMD Methods Analyze the Diagnostic Accuracy of the Change in Articular Disc of Temporomandibular Joint.

METHODS: DC/TMD clinical questionnaire diagnosis was conducted for 30 patients with temporomandibular disorder (TMD) and 11 asymptomatic volunteers who were admitted to the Department of Oral Medicine of the First Hospital affiliated with Jinan University from June 2020 to June 2021. At the same time, MRI scanned the opening and closed positions to obtain the image information of the articular disc and compared the diagnostic difference between MRI and DC/TMD to the position of the articular disc through statistical analysis. RESULTS: The probability of DC/TMD's diagnosis of reusable/nonreusable anterior disc displacement (ADD) was 80.1% and 62.7%, respectively. CONCLUSION: DC/TMD's diagnosis of abnormal articular disc position is less accurate than MRI testing. Therefore, the diagnosis of these two diseases for DC/TMD examination is of little significance, and MRI examination is required at the same time. It can improve diagnosis specificity and sensitivity, reduce missed diagnosis and misdiagnosis rates to ensure that true positive patients can be detected in time, and establish a basis for clinical diagnosis and treatment.

Robust Glycogene-Based Prognostic Signature for Proficient Mismatch Repair Colorectal Adenocarcinoma.

BACKGROUND: Proficient mismatch repair (pMMR) colorectal adenocarcinoma (CRAC) metastasizes to a greater extent than MMR-deficient CRAC. Prognostic biomarkers are preferred in clinical practice. However, traditional biomarkers screened directly from sequencing are often not robust and thus cannot be confidently utilized. METHODS: To circumvent the drawbacks of blind screening, we established a new strategy to identify prognostic biomarkers in the conserved and specific oncogenic pathway and its regulatory RNA network. We performed RNA sequencing (RNA-seq) for messenger RNA (mRNA) and noncoding RNA in six pMMR CRAC patients and constructed a glycosylation-related RNA regulatory network. Biomarkers were selected based on the network and their correlation with the clinicopathologic information and were validated in multiple centers (n = 775). RESULTS: We constructed a competing endogenous RNA (ceRNA) regulatory network using RNA-seq. Genes associated with glycosylation pathways were embedded within this scale-free network. Moreover, we further developed and validated a seven-glycogene prognosis signature, GlycoSig (B3GNT6, GALNT3, GALNT8, ALG8, STT3B, SRD5A3, and ALG6) that prognosticate poor-prognostic subtype for pMMR CRAC patients. This biomarker set was validated in multicenter datasets, demonstrating its robustness and wide applicability. We constructed a simple-to-use nomogram that integrated the risk score of GlycoSig and clinicopathological features of pMMR CRAC patients. CONCLUSIONS: The seven-glycogene signature served as a novel and robust prognostic biomarker set for pMMR CRAC, highlighting the role of a dysregulated glycosylation network in poor prognosis.