Search Results (1,169)

In this research, we assess the feasibility of employing hybrid friction stir channeling (HFSC) to produce composite panels that combined an 8 mm thick AA6082-T6 aluminum alloy and 5 mm thick glass-fiber-reinforced Noryl GFN2. HFSC is an innovative solid-state technology that combines both friction stir joining and channeling characteristics, which enable the generation of integral internal channels while joining different components. A parametric study was outlined to explore the effects of the travel speed, probe length, and tool plunging on the resulting composite panels. The resulting composite panels were subsequently subjected to a comprehensive analysis encompassing exterior ceiling quality, internal channel, and joining interface morphology. Depending on the processing parameters, the geometry of the channels was found to be quasi-rectangular or quasi-trapezoidal, with significant variability on cross-sectional area, resulting in hydraulic diameters ranging from 1.2 to 2.9 mm. The joining interface was characterized by a concavity of aluminum that was extruded downwards into the polymeric molten pool, which was clinched after polymeric re-solidification. The experimental results prove the ability to join metals and polymers while creating an integral channel in a single process step using HFSC. Despite the positive effect of irregular shaped channels on heat exchange, the numerical models evidenced a detrimental effect of 14.3 and 16.3% on ultimate tensile and flexural loads, respectively. This way, this fabrication technology evidenced promising characteristics that are suitable for manufacturing thermal management systems such as conformal cooling for plastic injection molding or battery trays for EVs. Full article

Background/Objectives: The PB family of “cut-and-paste” DNA transposons shows great promise as genetic manipulation tools while significantly impacting eukaryotic genome evolution. However, their evolutionary profile in beetles (Coleoptera), the most species-rich animal order, remains poorly characterized. Methods: A local tBLASTN search was conducted to mine PiggyBac (PB) transposons across 136 coleopteran insect genomes, using the DDE domain of the PB transposase as the query. Multiple sequence alignment was performed with MAFFT, and a maximum likelihood phylogenetic tree of the transposase DDE domains was constructed using IQ-TREE. Evolutionary dynamics were analyzed by means of K-divergence. Results: Our study reveals PB transposons are widely distributed, highly diverse, and remarkably active across beetles. We detected PB elements in 62 of 136 examined species (45%), classifying them into six distinct clades. A total of 62 PB-containing species harbored intact copies, with most showing recent insertions (K divergence ≈ 0), indicating ongoing transpositional activity. Notably, PB elements from Harmonia axyridis, Apoderus coryli, and Diabrotica balteata exhibit exceptional potential for genetic tool development. Structurally, intact PB elements ranged from 2074 to 3465 bp, each containing a single transposase ORF (500–725 aa). All were flanked by terminal inverted repeats and generated TTAA target site duplications. Conclusions: These findings demonstrate PB transposons have not only shaped historical beetle genome evolution but continue to drive genomic diversification, underscoring their dual significance as natural genome architects and promising biotechnological tools. Full article

Myeloproliferative neoplasms (MPNs) are clonal hematopoietic disorders characterized by the abnormal proliferation of myeloid cells. In addition to the main driver mutations in JAK2, MPL, and CALR, the transcription factor nuclear factor erythroid 2 (NFE2) has emerged as a key contributor to MPN pathophysiology. NFE2 expression is elevated in the majority of MPN patients, and augmented NFE2 activity in hematopoietic stem cells is sufficient to induce an MPN phenotype with spontaneous leukemic transformation in murine models. Moreover, NFE2 mutations, found in a subset of MPN patients, augment NFE2 activity and are associated with a markedly increased risk of progression to acute myeloid leukemia (AML). However, the molecular mechanism by which NFE2 mutations cause leukemogenesis is not understood. Here, we demonstrate that the E3 ubiquitin ligase ITCH mediates proteasomal degradation of wild-type (wt) NFE2 in HEK-293T cells. A gain-of-function truncation mutant, NFE2-226aa, retains the capacity to interact with ITCH but is no longer degraded. Rather, NFE2-226aa protects wt NFE2 from ITCH-dependent degradation, resulting in enhanced NFE2 activity. Full article

This paper is the first to reveal that the conventionally built aluminium alloy (AA) 7085-T7452 has mechanical properties, viz: a yield stress, ultimate strength, and an elongation to failure, that are similar to that of laser powder bed fusion (LPBF) built Scalmalloy^®. Following this observation, the growth of cracks that nucleated from corrosion pits in AA7085-T7452 specimens that had been exposed to a 5 wt% NaCl salt fog environment at 35 °C according to ASTM B117-19 standard for fourteen days is then studied. The specimen geometries were chosen to be identical to those associated with a similar study on Boeing Space, Intelligence, and Weapon Systems (BSI&WS) LPBF built Scalmalloy^®. This level of prior exposure led to pits in AA7085-T7452 that were approximately 0.5 mm deep with a surface width/diameter of up to approximately 1.5 mm. These pit sizes are broadly consistent with those leading to fatigue crack growth (FCG) in AA 7050-T7451 structural parts on the RAAF F/A-18 Classic Hornet fleet operating in a highly corrosive environment. Fatigue tests on these AA7085-T7452 specimens, under the same spectrum as used in the BSI&WS LPBF Scalmalloy^® study, reveals that AA7085-T7452 and Scalmalloy^® have similar crack growth histories. This, in turn, leads to the discovery that the growth of naturally occurring three-dimensional (3D) cracks in AA 7085-T7452 could be predicted using the crack growth equation developed for BSI&WS LPBF Scalmalloy^®, albeit with allowance made for their different fracture toughness’s. These findings suggest that Scalmalloy^® may be suitable for printing parts for both current and future attritable aircraft. Full article

This study explores Friction Stir Spot Welding (FSSW), a well-established solid-state joining technique, for high-strength aluminum alloys like AA2024-T4, which present significant challenges for conventional welding techniques. This research focuses on the impact of relatively low rotational speeds, specifically within a range of 700 to 1300 rpm, on the mechanical and microstructural properties of the welded joints. By employing a short dwell time of 3 s, this study aims to enhance productivity in the automotive and aerospace industries. The experimental work evaluated the joints’ thermal cycles, macrostructure, microstructure, hardness and load-carrying capacity. Results indicated a linear relationship between rotational speed and heat input. Although all welds exhibited a significant grain size reduction in the stir zone (SZ) compared to the base material (29.7 ± 6.1 μm), the SZ grain size increased with rotational speed, ranging from 4.7 ± 1.4 to 8.3 ± 1.3 μm. This study identified 900 rpm as the optimal parameter, achieving the highest load-carrying capacity (7.35 ± 0.4 kN) and a high SZ hardness (99 ± 1.5 HV). These findings confirm that joint strength is a balance between grain refinement and thermal softening. The presence of precipitates and the fractography of the tensile–shear tested specimens were also investigated and discussed. Full article

Background and Objectives: Pelvic organ prolapse (POP) is a prevalent pelvic floor disorder affecting a large proportion of parous and aging women worldwide. While surgical intervention is generally reserved for advanced prolapse, conservative approaches remain essential for the management of early-stage disease. Flat magnetic stimulation (FMS), a novel non-invasive modality, has shown promising results in pelvic floor rehabilitation for urinary incontinence, but its role in prolapse treatment remains insufficiently investigated. This study aimed to evaluate anatomical and patient-reported outcomes in women with mild POP undergoing FMS therapy. Materials and Methods: This retrospective observational study included 87 women with stage ≤ 2 POP, classified according to the Pelvic Organ Prolapse Quantification (POP-Q) system. Participants underwent eight FMS sessions, each lasting 25 min, over four weeks using the Dr. Arnold device (DEKA, Calenzano, Italy). Pre- and post-treatment evaluations included standardized POP-Q measurements and the Patient Global Impression of Improvement (PGI-I) questionnaire. Statistical analyses were performed using paired t-tests, with significance set at p < 0.05. Results: Statistically significant improvements were observed in the anterior vaginal compartment, with mean Aa values improving from −0.3 ± 1.2 to −0.7 ± 1.3 (mean difference −0.4 cm; 95% CI −0.8 to −0.03; p = 0.03; Cohen’s d = 0.31) and mean Ba values from −0.3 ± 1.3 to −0.7 ± 1.3 (mean difference −0.4 cm; 95% CI −0.8 to −0.02; p = 0.04; Cohen’s d = 0.30). No significant changes were found at other POP-Q landmarks. According to PGI-I results, 90.8% of participants reported symptom improvements, and 37.9% described their condition as “very much improved” or “much improved.” No adverse events occurred, and treatment compliance was 100%. Conclusions: FMS seems to be a safe, well-tolerated, and potentially effective conservative therapy strategy for mild POP, offering both objective anatomical benefits and high subjective satisfaction. Further randomized controlled trials with longer follow-up are required to validate these findings and clarify the long-term role of FMS in the management of pelvic floor dysfunction. Full article

Background: Individual differences in immune responses to African swine fever virus (ASFV), whether induced by vaccination or natural infection, may be linked to genetic variation in the genes involved in antigen presentation. Methods: A total of nine pigs from the 112-population were selected for RNA-seq analysis. To pinpoint key transcription factors (TFs) regulating gene expression in the lymph nodes, weighted Kendall’s Tau rank correlation analysis was performed to link the TF binding potential with the extent of differential expression of target genes. Results: CD8⁺ T cells expressing a specific epitope of the ASFV p72 protein (ACD8⁺) accounted for 41% of the total CD8⁺ T cells in peripheral blood. A total of 2062 transcripts were identified as differentially expressed across the nine pigs (q-value < 1 × 10⁻⁸). Differential expression levels of the target genes for MECP2, ETS1, ZBTB33, ELK4, and E2F4 were significantly correlated with their TF binding potential (p < 0.05). Six SNPs were identified in the promoter region of ELK4. Analysis of the 112-pig population revealed that SNPs at S.-404A>G and S.-668C>T loci were significantly associated with ACD8⁺ levels (q-value < 0.01). Individuals with the AA genotype at S.-404A>G had significantly higher ACD8⁺ counts compared to those with AG and GG genotypes (q-value < 0.05). At the S.-668C>T locus, ACD8⁺ levels were highest in the CC genotype, followed by CT and TT genotypes, with CC showing notably higher ACD8⁺ counts (q-value < 0.05). Notably, the S.-404A>G site overlaps with potential binding sites for TFs FOXA2, GATAs, and TRPS1, while the S.-668C>T site lies within the binding regions for NR1H3, RARA, VDR, and NR1I3. Conclusion: These mutations may disrupt TFs binding to the ELK4 promoter, potentially reducing ELK4 expression and impairing antigen processing and presentation. Full article

Alopecia areata (AA) is a chronic autoimmune disease characterized by non-scarring hair loss, where pathogenesis is closely linked to the collapse of hair follicle immune privilege and dysregulated T-cell responses. Increasing evidence suggests that gut dysbiosis may contribute to systemic immune alterations relevant to autoimmune disorders, yet its role in AA remains largely unexplored. In this study, we aimed to characterize the gut microbiota composition of AA patients and evaluate its potential as a biomarker for disease discrimination. Fecal samples from patients with AA and healthy controls were analyzed by 16S rRNA sequencing and processed through QIIME2 and MicrobiomeAnalyst platforms. Diversity metrics, differential abundance, and microbial network correlations were assessed, and supervised machine learning models were developed to classify AA versus control profiles. Our results revealed distinct microbial signatures in AA, with enrichment of pro-inflammatory genera such as Methanobrevibacter, Collinsella, and Ruminococcus gnavus, and depletion of immunoregulatory commensals, including Faecalibacterium and Eubacterium eligens group. Network analyses showed more complex microbial interactions in AA, and Random Forest models achieved 92% accuracy in discriminating AA from controls. These findings indicate that gut dysbiosis may play a role in AA pathogenesis, providing potential diagnostic biomarkers and supporting microbiota-targeted interventions as future therapeutic strategies. Full article

Introduction: The proteasome is a multicatalytic complex responsible for protein degradation and regulation of immune responses, and has been implicated in type 1 diabetes mellitus (T1DM) pathogenesis. Zinc (Zn²⁺) is essential for insulin granule biogenesis and modulates proteasomal activity. This study investigated associations between single-nucleotide polymorphisms (SNPs) in proteasomal subunits predicted to bind Zn²⁺ and T1DM susceptibility or related traits. Methods: This case–control study included 654 patients with T1DM and 573 subjects without DM from Southern Brazil. SNPs were selected through in silico analysis using MIB docking platform to identify Zn²⁺-interacting residues in proteasomal subunits. Five SNPs in proteasomal subunit genes—PSMA6 (rs1048990), PSMB6 (rs2304975), PSMB9 (rs17587), PSMC6 (rs2295825), and PSMD3 (rs3087852)—were genotyped using TaqMan assays. Results: The PSMC6 rs2295825C allele was associated with lower T1DM (OR = 0.77, 95% CI 0.61–0.97; p = 0.028) and diabetic retinopathy (DR; OR = 0.65; 95% CI 0.42–0.99; p = 0.048) risk, and a more favorable lipid profile (higher HDL-C, lower triglycerides) compared to the G/G genotype. The PSMB9 rs17587A/A genotype was linked to higher total cholesterol and HbA1c levels. The PSMA6 rs1048990G allele was linked to increased prevalence of diabetic kidney disease (DKD; OR = 1.75, 95% CI 1.02–2.99; p = 0.042), and the PSMD3 rs3087852A allele was associated with lower urinary albumin excretion. No significant associations were observed for the PSMB6 rs2304975 SNP. Conclusions: The PSMC6 rs2295825 SNP may confer protection against T1DM. The PSMC6 rs2295825, PSMB9 rs17587, PSMA6 rs1048990, and PSMD3 rs3087852 SNPs appear to influence lipid metabolism and diabetic microvascular complications. Full article

Diabetic nephropathy (DN) remains the leading cause of end-stage renal disease (ESRD) worldwide, primarily affecting individuals with Type 2 Diabetes Mellitus (T2DM). While traditional risk factors—such as hypertension, poor glycemic control, and dyslipidemia—are well known, recent research has illuminated the pivotal role of inflammation in DN pathogenesis. Inflammatory processes involving chemokines, cytokines, immune cell infiltration, and pro-fibrotic signaling pathways (e.g., NFκB, JAK/STAT) contribute significantly to glomerular and tubulointerstitial damage. Key immune players include macrophages and T lymphocytes, particularly CD4⁺ T cells, which correlate with disease severity and progression. Serum Amyloid A (SAA), an acute-phase reactant traditionally associated with Serum Amyloid A Amyloidosis (AA amyloidosis), has emerged as both a biomarker and active mediator of renal inflammation in DN. SAA promotes cytokine release, leukocyte recruitment, and extracellular matrix remodeling, contributing to glomerular and tubular injury. Elevated Saa3 expression in experimental models correlates with DN progression, while activation of the advanced glycation end products and the receptors for advanced glycation end products (AGE–RAGE) axis in podocytes enhances SAA upregulation and inflammatory signaling. Increasing evidence now indicates that SAA functions, not only as a marker of systemic inflammation, but also as a mechanistically significant driver of intrarenal injury, bridging metabolic dysregulation with sustained inflammatory and fibrotic signaling. Emerging therapeutic approaches—including interleukin 6 (IL-6) blockade, inhibition of AGE formation, targeted anti-fibrotic agents, and recently developed SAA-directed RNA or peptide therapeutics—underscore the therapeutic potential of modulating SAA activity in DN. Preclinical evidence further supports the efficacy of monoclonal antibodies, signaling inhibitors, and dietary anti-inflammatory compounds in mitigating renal injury. Collectively, these developments position SAA as a central mediator at the intersection of metabolic, inflammatory, and fibrotic pathways, highlighting its promise as both a diagnostic biomarker and a therapeutic target for early intervention in diabetic kidney disease. Full article

Refill friction stir spot welding (refill FSSW) is a solid-state joining technique that enables dissimilar welding between aluminum and steel alloys with minimal intermetallic compound (IMC) formation. Previous studies have focused on the interfacial mechanical performance of such joints, limited attention has been given to the localized corrosion behavior of the aluminum surface after welding, particularly in relation to microstructural evolution. This study investigates the effect of refill FSSW on the localized corrosion resistance of the aluminum surface in dissimilar joints with DP600 steel, since the Al side is typically the exposed surface in automotive service conditions. Emphasis is placed on the correlation between microstructural changes induced by the welding thermal cycle, such as grain refinement and precipitate coarsening, and localized corrosion behavior. The welded samples were characterized by optical and scanning electron microscopy, Vickers hardness measurements and potentiodynamic polarization techniques. Corrosion tests revealed a slight reduction in corrosion resistance in the stir zone compared to the base metal, mainly attributed to Mg₂Si coarsening. Pit initiation sites were associated with Al(Fe, Mn)Si and Mg₂Si precipitates. These findings offer new insights into the corrosion mechanisms acting on the aluminum surface of refill FSSW joints, supporting the development of more corrosion-resistant dissimilar structures. Full article

This study fabricated AA2024-T4 aluminum alloy components using Additive Friction Stir Deposition (AFSD) to systematically investigate the effects of tool rotational speed (100–400 rpm) on the macroscopic morphology, microstructure, and mechanical properties of the deposited layers. The results demonstrate that defect-free, fully dense deposits with good surface quality were successfully achieved across the entire speed range under a constant traverse speed. The deposition zone exhibited a homogeneous, fine equiaxed grain structure with an average grain size of 2.01 μm. As the rotational speed decreased from 400 rpm to 200 rpm, the ultimate tensile strength in the longitudinal direction increased from 340 MPa to 390 MPa, indicating that a moderate reduction in rotational speed enhances both the strength and ductility of AFSD-fabricated AA2024. This research provides the first revelation of the bidirectional material flow behavior and the mechanisms underlying regional property variations in AA2024 during AFSD. Furthermore, the contributions of different strengthening mechanisms were quantified using a multi-mechanism strength model. These findings offer a significant foundation and theoretical support for the solid-state additive manufacturing of high-performance Al-Cu alloy components. Full article

Doped perovskites are widely studied in the domain of perovskite material design. However, due to the limited data available for the target materials, machine learning methods based on small datasets become particularly important. In this study, we propose a transfer learning strategy aimed at predicting doped perovskites on limited data samples. This strategy first utilizes the ABO₃-type perovskite dataset to develop a deep learning source model based on its formation energies. Then, fine-tuning is performed on the doped perovskite structure dataset to obtain a model with good transferability, applicable to the doped perovskite oxide target domain. Based on the transfer learning model, we further predict the formation energies of 12,897 A₂BB′O₆ compounds, 10,401 AA′B₂O₆ compounds, and 49,723 AA′BB′O₆ compounds. With the tolerance factor $\mathrm{t} \in [0.7–1.1]$, octahedral factor $\mathsf{\mu } \in [0.45–0.7]$, and the modified tolerance factor $\mathsf{\tau } \in [0, 4.18]$ for screening, we successfully predict 3389 A₂B′BO₆, 3002 AA′B₂O₆, and 13,563 AA′BB′O₆ structures as potential stable doped perovskite candidates. Among these filtered results, 821 A₂B′BO₆, 69 AA′B₂O₆, and 6 AA′BB′O₆ compounds have been reported in the OQMD database. For each doped perovskite, we select the candidate with the lowest formation energy and perform DFT validation. This resulted in three newly reported stable doped perovskite materials: CaSrHfScO₆, BaSrHf₂O₆, and Ba₂HfNdO₆. The transfer learning-based perovskite material design method proposed in this study not only effectively addresses the challenges of model training on small datasets but also significantly improves the accuracy and stability of doped perovskite material predictions. Through transfer learning, the model can fully leverage the data and knowledge from the ABO₃-type perovskite, effectively overcoming the problem of limited data. This strategy provides a new approach for efficient perovskite material design, enabling broader structural and performance predictions under limited experimental data conditions, and offering a powerful tool for the development of novel functional materials. Full article

Body temperature serves as a crucial indicator of dairy cow health. Traditional rectal temperature (RT) measurement often induces stress responses in animals. Body temperature detection based on infrared thermography (IRT) offers non-invasive and timely advantages, contributing to welfare-oriented farming practices. However, automated detection and temperature extraction from critical cow regions are susceptible to complex illumination, black-and-white fur texture interference, and region of interest (ROI) deformation, resulting in low detection accuracy and poor robustness. To address this, this paper proposes the EDC-YOLO-World-DB framework to enhance detection and temperature extraction performance under complex illumination conditions. First, URetinex-Net and CLAHE methods are employed to enhance low light and overexposed images, respectively, improving structural information and boundary contour clarity. Subsequently, spatial relationship constraints between LU and AA are established using five-class text priors—lower udder (LU), around the anus (AA), rear udder, hind legs, and hind quarters—to strengthen the spatial localisation capability of the model for ROIs. Subsequently, a Dual Bidirectional Feature Pyramid Network architecture incorporating EfficientDynamicConv was introduced at the neck of the model to achieve dynamic weight allocation across modalities, levels, and scales. Task Alignment Metric, Gaussian soft-constrained centroid sampling, and combined IoU (C_IoU + G_IoU) loss were introduced to enhance sample matching quality and regression stability. Results demonstrate detection confidence improvements by 0.08 and 0.02 in low light and overexposed conditions, respectively; compared to two-text input, five-text input increases P, R, and mAP50 by 3.61%, 3.81%, and 1.67%, respectively; Comprehensive improvements yielded P = 88.65%, R = 85.77%, and mAP50 = 89.33%—further surpassing the baseline by 2.79%, 3.01%, and 1.92%, respectively. Temperature extraction experiments demonstrated significantly reduced errors for $T_{Max}$, $T_{Min}$, and $T_{avg}$. Specifically, for the mean error of LU, $T_{Max}$, $T_{Min}$, and $T_{avg}$ were reduced by 66.6%, 33.5%, and 4.27%, respectively; for AA, $T_{Max}$, $T_{Min}$, and $T_{avg}$ were reduced by 66.6%, 25.4%, and 11.3%, respectively. This study achieves robust detection of LU and AA alongside precise temperature extraction under complex lighting and deformation conditions, providing a viable solution for non-contact, low-interference dairy cow health monitoring. Full article

Auditory stimuli are known to enhance visual target recognition in rapid serial visual presentation (RSVP) tasks, yet the robustness and potential trade-offs of this audiovisual integration (AVI) effect remain debated. Attribute amnesia (AA) refers to the phenomenon in which individuals successfully identify a stimulus for a task, but fail to recall its basic attributes when unexpectedly tested. The present study investigates whether improvements in visual recognition through AVI occur at the expense of auditory information loss, as predicted by the AA framework. Across two RSVP experiments, participants were presented with letter targets embedded among digit distractors. In Experiment 1, an auditory pitch (bass, alto, treble) accompanied the second target (T2); in Experiment 2, an auditory syllable either matched or mismatched the semantic identity of T2. A surprise-test paradigm was used to assess participants’ ability to recall auditory stimuli. The results show that both pitch and semantic attributes were subject to AA, with semantic stimuli recalled more accurately than pitch. Moreover, semantic congruency enhanced T2 identification, highlighting the automatic processing advantage of semantic cues. Post-surprise trials revealed the improved recall of auditory attributes, consistent with the working memory reselection model. Together, these findings suggest that AVI enhances visual recognition by reallocating cognitive resources, but at the cost of a partial loss of irrelevant auditory information. Full article