Search Results (637)

Nomex honeycomb composites (NHCs) are highly sensitive to the abnormal wear state of disc tools during cutting, leading to poor product quality. This paper proposes a real-time anomaly detection method combining a novel CNN–GRU–Attention (CGA) deep learning model with an Exponentially Weighted Moving Average (EWMA) control chart to monitor sensor data from the disc tool. The CGA model integrates an improved CNN layer to extract multidimensional local features, a GRU layer to capture long-term temporal dependencies, and a multi-head attention mechanism to highlight key information and reduce error accumulation. Trained solely on normal operation data to address the scarcity of abnormal samples, the model predicts cutting force time series with an RMSE of 0.5012, MAE of 0.3942, and R² of 0.9128, outperforming mainstream time series data prediction models. The EWMA control chart applied to the prediction residuals detects abnormal tool wear trends promptly and accurately. Experiments on real NHC cutting datasets demonstrate that the proposed method effectively identifies abnormal machining conditions, enabling timely tool replacement and significantly enhancing product quality assurance. Full article

Background: Upper limb loss significantly impacts quality of life, and whereas myoelectric prostheses restore some function, conventional surface electromyography (sEMG) systems face challenges like poor signal quality, high cognitive burden, and suboptimal control. Phantom X, a novel implantable electrode-array-based system leveraging machine learning (ML), aims to overcome these limitations. This feasibility study assessed Phantom X’s performance using non-invasive surface EMG electrodes to approximate implantable system behavior. Methods: This single-arm, non-randomized study included 11 participants (9 able-bodied, 2 with transradial amputation) fitted with a 32-electrode cutaneous array around the forearm. EMG signals were processed through an ML algorithm to control a desk-mounted prosthesis. Performance was evaluated via gesture accuracy (GA), modified gesture accuracy (MGA), and classifier gesture accuracy (CGA) across 11 hand gestures in three arm postures. User satisfaction was also assessed among the two participants with transradial amputation. Results: Phantom X achieved an average GA of 89.0% ± 6.8%, MGA of 96.8% ± 2.0%, and CGA of 93.6% ± 4.1%. Gesture accuracy was the highest in the Arm Parallel posture and the lowest in the Arm Perpendicular posture. Thumbs Up had the highest accuracy (100%), while Index Point and Index Tap gestures showed lower performance (70% and 79% GA, respectively). The mean latency between EMG onset and gesture detection was 250.5 ± 145.9 ms, with 91% of gestures executed within 500 ms. The amputee participants reported high satisfaction. Conclusions: This study demonstrates Phantom X’s potential to enhance prosthesis control through multi-electrode EMG sensing and ML-based gesture decoding. The non-invasive evaluation suggests high accuracy and responsiveness, warranting further studies with the implantable system to assess long-term usability and real-world performance. Phantom X may offer a superior alternative to conventional sEMG-based control, potentially reducing cognitive burden and improving functional outcomes for upper limb amputees. Full article

The induction of type I interferon (IFN) via intracellular nucleic acid sensors may be useful in preventing viral infections. However, little is known about the effect of natural plant materials on sensor responses. We previously found that cardamom (Elettaria cardamomum (L.) Maton) seed extract (CSWE) enhanced type I IFN expression and prevented influenza virus infection. In this study, we investigated the effect of CSWE on type I IFN responses using intracellular nucleic acid sensor molecules. Human lung epithelial A549 cells were treated with CSWE and transfected with poly(dA:dT) or poly(I:C) using lipofection. CSWE and 1,8-cineole, the major CSWE components, dose-dependently induced type I IFNs and IFN-stimulated genes in both poly(dA:dT)- and poly(I:C)-transfected A549 cells. The type I IFN-enhancing effect of CSWE was dependent on the stimulator of interferon genes (STING), whereas the effect of 1,8-cineole was independent of STING and mediated by the down-regulation of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-inducible poly-ADP-ribose polymerase expression. Our study suggests that CSWE has the potential to act as a beneficial antiviral agent by enhancing homeostatic type I IFN production. Full article

The effect of ultrasonic frequencies of 40 kHz/300 W (U-40) and 120 kHz/300 W (U-120) on the aqueous extraction of bioactive compounds from dried whole-fruit powders (DPs) of red-peel/white-flesh (WFP) and red-peel/red-flesh (RFP) pitayas was investigated, and shaking at 120 rpm (S-120) was used for a comparison. The effects of temperature and the solid-to-liquid ratio on the extraction efficiencies of the total phenolic content (TPC) and ferric-reducing antioxidant power (FRAP) of WFP and RFP were evaluated. The impact of extraction time on the aqueous extraction of specific compounds, namely, chlorogenic acid (CGA) and quercetin, from WFP and RFP was assessed with extraction modes of U-40, U-120, and S-120. At 40 °C and a 1/20 (g DP/mL) solid-to-liquid ratio, the use of U-40 achieved higher TPC and FRAP values at 15 min than U-120 and S-120 for WFP. The use of U-40 and U-120 extracted higher amounts of free CGA and free quercetin from WFP and RFP at 15 and 60 min than S-120 but showed different extraction efficiencies for free CGA and free quercetin. This study demonstrates that different ultrasonic frequencies can be applied in the green extraction of target bioactive compounds for use in nutraceutical foods. Full article

African ground squirrels (Xerus spp.), the inhabitants of African arid zones, face extreme heat and water scarcity driving selection for metabolic optimization. We assembled and annotated the first mitogenomes of Xerus inauris and Xerus rutilus (16,525–16,517 bp), revealing conserved vertebrate architecture with genus-specific traits. Key features include Xerus rutilus’s elongated ATP6 (680 vs. 605 bp), truncated ATP8–ATP6 spacers (4 vs. 43 bp), and tRNA-Pro control regions with 78.1–78.3% AT content. Their nucleotide composition diverged from that of related sciurids, marked by reduced T (25.78–26.9%) and extreme GC skew (−0.361 to −0.376). Codon usage showed strong Arg-CGA bias (RSCU = 3.78–3.88) and species-specific elevations in Xerus rutilus’s UGC-Cys (RSCU = 1.83 vs. 1.17). Phylogenetics positioned Xerus as sister to Ratufa bicolor (Bayesian PP = 0.928; ML = 1.0), aligning with African biogeographic isolation. Critically, we identified significant signatures of positive selection in key mitochondrial genes linked to arid adaptation. Positive selection signals in ND4 (ω = 1.8 × background), ND1, and ATP6 (p < 0.0033) correspond to enhanced proton gradient efficiency and ATP synthesis–molecular adaptations likely crucial for optimizing energy metabolism under chronic water scarcity and thermoregulatory stress in desert environments. Distinct evolutionary rates were observed across mitochondrial genes and complexes: Genes encoding Complex I subunits (ND2, ND6) and Complex III (Cytb) exhibited accelerated evolution in arid-adapted lineages, while genes encoding Complex IV subunits (COXI) and Complex V (ATP8) remained highly conserved. These findings resolve the Xerus mitogenomic diversity, demonstrating adaptive plasticity balancing arid-energy optimization and historical diversification while filling critical genomic gaps for this xeric-adapted lineage. Full article

Halictidae, as a major pollinator family in bees, has significant ecological value. However, the insufficient molecular data for this group has limited our understanding of the evolutionary history of this group. Herein, we newly sequenced and assembled four mitogenomes of Halictidae, including three species of Nomiinae and one species of Rophitinae. We analyzed the characters of the newly obtained mitogenomes, including nucleotide composition, sequence length, and gene rearrangements. The length of the newly sequenced mitogenomes ranged from 16,492 to 21,192 bp, and all newly obtained mitogenomes contained 22 tRNAs, 13 protein-coding genes, two rRNAs, and one control region. Their AT content (%) ranged from 82.55 to 86.44. Relative synonymous codon usage analysis showed that UUU, UUA, and AUU were the preferred codons. The relative synonymous codon usage > 2 of mostly newly sequenced species was as follows: UUA > UCA > CGA. All newly obtained mitogenomes show gene rearrangement; we found five gene rearrangement patterns in total. Notably, ND4-trnP-ND4L-trnT was the first reported gene rearrangement pattern in bees. In addition, we reconstructed the phylogenetic relationships of Halictidae based on 10 species (eight ingroups and two outgroups), using Bayesian Inference and Maximum Likelihood approaches. Phylogenetic analysis showed that Rophitinae was the basal group within Halictidae. Full article

Background: Comprehensive Geriatric Assessment (CGA) is essential for evaluating older cancer patients, but significant gaps persist in both research and clinical practice. This study aimed (I) to identify the CGA elements that most influence anti-cancer treatment decisions in older patients and (II) to explore the predictive value of CGA components for mortality. Methods: This observational study included older patients with newly diagnosed, histologically confirmed solid or hematological cancers, recruited consecutively from 2003 to 2023. Participants were followed for four years. The data collected included CGA measures of functional (Activities of Daily Living-ADL), cognitive (Mini-Mental State Examination-MMSE), and emotional (Geriatric Depression Scale-GDS) domains. Patients were categorized into frail, vulnerable, or fit groups based on Balducci’s criteria. Statistical analyses included decision tree modeling and Cox regression to identify predictors of mortality. Results: A total of 7022 patients (3222 females) were included, with a mean age of 78.3 ± 12.9 years. The key CGA factors influencing treatment decisions were ADL (first step), cohabitation status (second step), and age (last step). After four years, 21.9% patients had died. Higher GDS scores (OR 1.04, 95% CI 1.01–1.07, p = 0.04) were independently associated with survival in men and living with family members (OR 1.67, 95% CI 1.35–2.07, p < 0.001) in women. Younger patients (<77 years) showed both MMSE and GDS as significant risk factors for mortality. Conclusions: Functional capacity, cohabitation status, and GDS scores are crucial for guiding treatment decisions and predicting mortality in older cancer patients, emphasizing the need for a multidimensional geriatric assessment. Full article

Segregative phase separation technology demonstrates substantial potential for precise molecular fractionation in food and biomaterial applications. The investigation elucidates the causal relationship between viscosity variations and phase separation dynamics, which govern molecular fractionation in GA/HPMC composite systems. By conducting a comparative analysis of two GA subtypes (CGA and SGA) and three HPMC grades with controlled viscosity gradients, we utilized gel permeation chromatography-multi-angle laser light scattering (GPC-MALLS) coupled with rheological characterization to elucidate the critical relationship between continuous phase viscosity and fractionation efficiency. Notably, increasing HPMC viscosity significantly intensified phase separation, resulting in selective enrichment of arabinogalactan-protein complexes: from 6.3% to 8.5% in CGA/HPMC systems and from 27.3% to 36.5% in SGA/HPMC systems. Further mechanistic investigation revealed that elevated HPMC viscosity enhances thermodynamic incompatibility while slowing interfacial mass transfer, synergistically driving component redistribution. These findings establish a quantitative viscosity–fractionation relationship, offering theoretical insights for optimizing GA/HPMC systems in emulsion stabilization, microencapsulation, and functional biopolymer purification via viscosity-mediated phase engineering. Full article

Chronic high-fat diet (HFD) feeding in male rats causes significant metabolic as well as inflammatory disturbances, including obesity, insulin resistance, dyslipidemia, liver and kidney dysfunction, oxidative stress, and hypothalamic dysregulation. This study assessed the therapeutic effects of chlorogenic acid (CGA), a natural polyphenol, administered at 10 mg and 100 mg/kg/day for the last 4 weeks of a 12-week HFD protocol. Both CGA doses reduced body weight gain, abdominal circumference, and visceral fat accumulation, with the higher dose showing greater efficacy. CGA improved metabolic parameters by lowering fasting glucose and insulin and enhancing lipid profiles. CGA suppressed orexigenic genes (Agrp, NPY) and upregulated anorexigenic genes (POMC, CARTPT), suggesting appetite regulation in the hypothalamus. In abdominal white adipose tissue (WAT), CGA boosted antioxidant defenses (SOD, CAT, GPx, HO-1), reduced lipid peroxidation (MDA), and suppressed pro-inflammatory cytokines including TNF-α, IFN-γ, and IL-1β, while increasing the anti-inflammatory cytokine IL-10. CGA modulated inflammatory signaling via upregulation of miR-146a and inhibition of IRAK1, TRAF6, and NF-κB. It also reduced apoptosis by downregulating p53, Bax, and Caspase-3, and restoring Bcl-2. These findings demonstrate that short-term CGA administration effectively reverses multiple HFD-induced impairments, highlighting its potential as an effective therapeutic for obesity-related metabolic disorders. Full article

This study enhanced the self-healing performance of cherry wood furniture coatings by incorporating chitosan gum arabic-coated tung oil (CGA-T) microcapsules (types 1 and 2) into UV topcoats at 3%–15% concentrations. Multi-layer coated samples were systematically evaluated for optical, mechanical, and self-healing properties. Results demonstrated that microcapsules conferred self-healing ability, but concentrations >9% reduced reflectance (min 39.20%), increased color difference (max ΔE = 8.35), decreased gloss (max 35.25% loss at 60°), and raised roughness (max 1.79 μm). Mechanically, impact resistance improved (to grade 3), while adhesion declined (to grade 3) and hardness decreased (4H→2H). Self-healing performance peaked at 9% microcapsule 2 content (31.32% healing rate), with optimal overall performance at 6%. The 6% microcapsule 2 formulation (Sample 7) achieved the best overall balance among optical, mechanical, and self-healing properties, demonstrating its suitability for practical applications. Full article

Background: Reducing postprandial blood glucose (PBG) is a crucial strategy for treating diabetes and minimizing the risk of complications. Developing efficient and safe α-glycosidase inhibitors from natural products to lower PBG has attracted much attention. Silphium perfoliatum L. (SP), a traditional herbal medicine of North American Indigenous tribes, has efficacy of treating metabolic diseases, but its hypoglycemic activity and bioactive components have not been fully studied. Methods: In vitro α-glucosidase inhibition and in vivo sucrose/maltose/starch tolerance assays were performed to assess the hypoglycemic effects of SP extracts, and UPLC-Triple-TOF-MS/MS analysis was used to tentatively identify its chemical structure composition. In vitro enzyme inhibition and molecular docking were used to verify the effective ingredients. Results: In vitro hypoglycemic activities of four extracts of SP (SP-10/SP-40/SP-60/SP-C) showed that SP-10 exhibited strong α-glucosidase (sucrase and maltase) inhibitory effects with IC₅₀ of 67.81 μg/mL and 62.99 μg/mL, respectively. Carbohydrate tolerance assays demonstrated that SP-10 could significantly reduce the PBG levels of diabetic mice, with a significant hypoglycemic effect at a dosage of 20 mg/kg. A total of 26 constituents, including 11 caffeoylquinic acids (CQAs) and 15 flavonol glycosides, were tentatively identified by mainly analyzing secondary MS fragmentation. Moreover, three CQAs rich in SP-10, namely chlorogenic acid (CGA), neochlorogenic acid (NCGA), and cryptochlorogenic acid (CCGA), may be the main hypoglycemic substances, as evidenced by their inhibitory effects on sucrase and maltase. Conclusions: The α-glucosidase inhibitory effects of SP extract both in vitro and in vivo and its active ingredients were systematically studied for the first time. Results indicated that SP extract, rich in CQAs, had significant hypoglycemic activity, supporting the considerable potential of SP as hypoglycemic functional food or cost-effective therapeutic agents for diabetes treatment. Full article

The B-cell adapter for PI3K (BCAP) is a protein that connects membrane receptor signaling to the PI3K pathway. In fibroblasts or dendritic cells, priming the cGAS nucleic-acid-sensing pathway increases BCAP expression and enhances type I interferon (IFN-I) production upon lipopolysaccharide (LPS) stimulation. These findings corroborate the idea that BCAP may bias cytokine production toward IFN during inflammation, indicating its potential involvement in IFN-driven diseases like systemic lupus erythematosus (SLE). We investigate the role of BCAP in regulating the inflammatory response in SLE and its relationship with IFN-mediated inflammation. BCAP gene expression and IFN signature were analyzed in 36 subjects with SLE and 20 healthy controls. Two cellular models were used to assess BCAP’s role in LPS response and IFN signaling after cGAS stimulation. We found a correlation between BCAP and interferon-stimulated gene (ISG) expression in SLE. In a cellular model, tofacitinib and anifrolumab, acting as IFN signaling “inhibitors”, blocked BCAP overexpression triggered by cGAS, confirming BCAP as an ISG. Additional studies in BCAP^−/− cells revealed that, in the absence of BCAP, these cells exhibited diminished IFN production upon LPS stimulation following prior exposure to cGAMP. Overall, BCAP is an ISG that acts as a positive regulator of Toll-like receptor 4-mediated IFN production. We speculate that its increased expression in SLE may contribute to a positive feedback loop, enhancing IFN production during bacterial infections. Full article

Chemical products, including cleaning agents, disinfectants, stain removers, and cosmetics, release harmful chemicals that pose a risk to human health and the environment, necessitating alternative sources. The objective of this research was to identify the most effective phytoextract from food production waste for use in sustainable aerosol hygiene technology as an electrostatic bio-disinfectant. The investigation was performed through wipe tests and airborne microbial collection techniques. The upgraded coffee silverskin phytoextract demonstrated superior disinfection potential for various surfaces and airborne microbes compared to the hot trub phytoextract, with an industrial disinfectant serving as the control. Log reduction analyses revealed a more significant killing efficacy (p ≤ 0.05, using the ANOVA test) against Gram-positive organisms (Bacillus subtilis and Listeria monocytogenes) than against Gram-negative organisms (Escherichia coli and Vibrio parahaemolyticus), with the log reductions ranging from 3.08 to 5.56 and 3.72 to 5.81, respectively. Chemical characterization by LC-ESI-QTOF-MS, ¹H NMR, and FTIR showed that CGAs and chalcones are the most bioactive compounds in CSS and HT, respectively. The innovation in this work involves an integrated approach that combines waste-derived phytoextracts, advanced chemical profiling, and scalable aerosol disinfection. Furthermore, this research offers a greener, cost-effective, and industrially relevant alternative to synthetic chemical disinfectants. The interdisciplinary approach contributes to the development of bio-based disinfectants for use in the food industry, hospitals, and public health settings. This investigation supports a paradigm shift toward sustainable disinfection practices, thereby improving food and environmental safety. Full article

Background: Emotional dysregulation (ED) is a transdiagnostic feature of multiple adolescent psychiatric disorders and a predictor of functional impairment and self-harming behaviors. Despite its clinical relevance, pharmacological treatments targeting ED in youth remain underexplored. This retrospective study investigated the clinical effectiveness and tolerability of adjunctive lithium therapy in adolescents with severe ED, independent of specific diagnostic categories. Methods: A total of 35 inpatients (13–17 years) with significant ED were divided into two groups based on pharmacological treatment: lithium add-on therapy (Li group, n = 17) and standard therapy without lithium (Control group, n = 18). Clinical severity (CGI-S) and global functioning (C-GAS) were assessed at baseline (T0), 6 months (T1), and 12 months (T2). A mixed-design ANOVA was performed to assess group × time interactions. Adverse events and treatment adherence were also examined. Results: At T1, the Li group showed a significantly greater reduction in symptom severity (CGI-S) compared to the Control group (p = 0.029). Global functioning (C-GAS) improved over time in both groups (p < 0.001), with no significant interaction effects. Adverse effects, primarily metabolic and endocrine, were more frequent in the Li group but did not reduce adherence. Conclusions: Adjunctive lithium therapy may reduce symptom severity in adolescents with severe ED without negatively affecting treatment tolerability or adherence. These findings support the potential utility of lithium in complex adolescent cases and warrant further prospective research. Full article

With the development of industrialization, the demand for high-performance metal materials has increased, and copper and its alloys have been widely used. The microstructure of these materials significantly affects their performance. To address the issues of subjectivity, low efficiency, and limited quantitative capability in traditional metallographic analysis methods, this paper proposes a deep learning-based approach for segmenting the second phase in Cu-Fe alloys. The method is built upon the YOLO11 framework and incorporates a series of structural enhancements tailored to the characteristics of the secondary-phase microstructure, aiming to improve the model’s detection accuracy and segmentation performance. Specifically, the EIEM module enhances the C3K2 structure to improve edge perception; the CSPSA module is optimized into C2CGA to strengthen multi-scale feature representation; and the RepGFPN and DySample techniques are integrated to construct the GDFPN neck network. Experimental results on the Cu-Fe alloy metallographic image dataset demonstrate that YOLO11 outperforms mainstream semantic segmentation models such as U-Net and DeepLabV3+ in terms of mAP (85.5%), inference speed (208 FPS), and model complexity (10.2 GFLOPs). The improved YOLO11 model achieves an mAP of 89.0%, a precision of 84.6%, and a recall of 81.0% on this dataset, showing significant performance improvements while effectively balancing inference speed and model complexity. Additionally, a quantitative analysis software system for secondary phase uniformity based on this model provides strong technical support for automated metallographic image analysis and demonstrates broad application prospects in materials science research and industrial quality control. Full article