Browse Articles

Efficacy and safety of ultrasound-guided radiofrequency ablation versus laparoscopic cholecystectomy in gallbladder polyps: a bicentric study

Enhancing deep learning based multi-parameter fire detection by training on simulated and combustion experimental dataset

Analysis of the condition of thin-walled composite structures based on the results of experiments conducted at variable temperature by acoustic emission

Abstract This paper presents considerations for interpreting acoustic emission results in combination with equilibrium paths obtained from experiments conducted using a testing machine and a digital image correlation system. The experiments were performed on thin-walled carbon-epoxy composite profiles. Two types of samples with different shapes were tested at various temperatures. The samples had identical lay-up configurations. The primary objective of the research was to perform a quantitative and qualitative assessment of composite material damage using independent experimental testing techniques, including digital image correlation (DIC) and acoustic emission. An additional aspect was to assess the impact of temperature on the stability and load-bearing capacity of thin-walled composite structures under variable thermal conditions (negative and positive temperatures). The paper used experimental, non-destructive testing methods to evaluate how two types of composite structures behave under different conditions and under simultaneous temperature variations.

Dynamic quality aware path planning for 6 DoF robotic arms using BiRRT and metaheuristic optimization based on B spline paths

Abstract Industrial robotic arms utilized in contemporary industrial and collaborative environments must operate within increasingly congested and dynamically restricted workspaces while adhering to rigorous standards of safety, precision, and motion quality. This paper presents a two-stage framework for path planning and optimization of a 6-DOF industrial robotic arm navigating amid randomly distributed obstacles. A collision-free reference motion is initially created by integrating B-spline geometric interpolation with a bidirectional RRT-Connect planner, augmented by short-cutting and effective joint-space collision verification for a KUKA KR 4 R600 manipulator. The baseline trajectory is subsequently enhanced through two metaheuristic optimizers: a Whale Genetic hybrid algorithm (WGA) and the Grey Wolf Optimizer (GWO). These optimizers minimize a composite objective that incorporates end-effector trajectory length, joint-level energy consumption based on established motor characteristics, and trajectory smoothness measured by joint jerk. Simulation results indicate that, while the raw Bi-RRT trajectory is geometrically efficient and energy-efficient, it demonstrates excessively high jerk. The suggested enhancements based on WGA and GWO diminish the jerk index of the original Bi-RRT solution by roughly 94–96%, resulting in relatively slight increases in trajectory length and energy, while producing dynamically smooth, collision-free trajectories that adhere to all kinematic constraints. This work presents a comprehensive, implementation-ready methodology that compares sampling-based planning, and multi-objective metaheuristic optimization to produce executable, energy-efficient, and jerk-minimized motions for industrial manipulators in intricate environments.

Subtypes of adolescent major depressive disorder characterized by divergent information dynamics in sensory-association cortices

Mental and physical fatigue altered working memory consolidation and impaired gaze behavior and perceptual-cognitive skills using video-based and real-situation

Enhancing 5-fluorouracil efficacy in colorectal cancer by inhibiting glutathione antioxidant mechanisms with an xCT inhibitor

Effects of selected nuts on the biology of Trogoderma granarium Everts

Immunomediator expression in human periodontal ligament MSCs varies depending on surface CD146 expression

Abstract Isolating mesenchymal stromal cell (MSC) subpopulations with improved quality based on specific surface markers, such as CD146, is one approach to enhance their therapeutic potential. However, there is limited information on the cytokine-boosted immunomodulatory mechanisms between CD146-expressing and non-expressing MSCs across various inflammatory conditions. This study seeks to address this gap. MSCs from the human periodontal ligament (hPDL-MSCs) were treated with interleukin-(IL)-1β, interferon-(IFN)-γ, or tumor necrosis factor-(TNF)-α, investigating the expression of IDO-1, PD-L1, PTGS-2, and TSG-6 between CD146 + and CD146 − hPDL-MSCs. Additionally, the expression of the immunomediators was compared between CD146-depleted and -enriched populations, generated by magnetic-bead-sorting. CD146 + hPDL-MSCs exhibited a significantly higher proportion of IDO-1 + cells, enhanced expression levels in the presence of IL-1β or TNF-α, and higher IL-1β, IFN-γ, or TNF-α-induced PD-L1 protein expression. Conversely, the proportion of TSG-6 + hPDL-MSCs was significantly lower in CD146 + cells under basal conditions. In CD146-enriched hPDL-MSCs, the immunomediator expression was minimally elevated, with significant differences under specific conditions: a higher PD-L1 protein expression under basal conditions and in the presence of IFN-γ or TNF-α, as well as higher or lower PGE 2 levels with TNF-α or IL-1β, respectively. These results suggest that the immunomediator expression in hPDL-MSCs alters with different CD146 surface expression. CD146 + hPDL-MSCs do not always show higher levels of immunomediator expression. Further research is necessary to isolate hPDL-MSC subpopulations with optimal potential for therapeutic applications.

Life strategies in an upwelling world: distribution patterns and niche partitioning of Calanidae copepods in the Benguela Current

Abstract Climate change is expected to alter coastal upwelling systems, making it essential to understand their current ecological structure. This study investigates the distribution and niche partitioning of Calanidae copepods in relation to upwelling intensities during austral summer in the northern (nBUS) and southern (sBUS) Benguela Current upwelling subsystems, which differ in upwelling seasonality, oxygen minimum zones and fisheries production. The six occurring Calanidae species were separated into three size categories each with potentially similar prey-size spectra. Similar-sized species differed in at least one of their horizontal, vertical or trophic niches. The dominant copepod Calanoides natalis was associated with cold, chlorophyll  a -rich shelf waters and showed high levels of diatom fatty acid markers. Calanus agulhensis  peaked offshore in the sBUS, with copepodids C5 also found deeper than 200 m and, unexpectedly, offshore in the nBUS, likely transported there by aged Agulhas retroflection rings drifting towards the nBUS and mixing with Subantarctic Mode Water, indicated by co-occurrences with  Neocalanus tonsus . Copepodids C5 of C. agulhensis  had elevated amounts of wax esters, suggesting special life-cycle adaptations of potential energy storage. Nannocalanus minor and Mesocalanus tenuicornis were associated with warm, offshore waters, with N. minor being more abundant in the nBUS and M. tenuicornis in the sBUS. They co-occurred to some extent but showed differences in their vertical and trophic niches. Fine-scale niche partitioning among closely related, similar-sized species likely supports persistence and diversity in highly dynamic upwelling systems. It raises questions about winners or losers in response to severe environmental changes related to future climate scenarios and how these changes may propagate to commercially important fish populations.

Decoding the dark genome reveals its organisation into modular disease networks

Unsupervised learning reveals novel disease-associated proteins in high-dimensional human proteomic data

Abstract Modern advancements in precision medicine have led to the generation of vast proteomic datasets, capturing the concentrations of thousands of proteins across tens of thousands of participants. These datasets are traditionally processed using supervised learning methods due to their relative simplicity to implement and assess the output. However, this approach can sometimes overlook subtle patterns that might offer deeper insights. In contrast, unsupervised learning, while capable of revealing hidden relationships, struggles with the challenge of high dimensionality, meaning that brute-force analysis could take millennia to complete. In this study, we developed the Dimensionality Reduction with Avoidance of Missing/COmmunity Detection (DIRAM/COD) framework to address this problem by combining dimensionality reduction techniques with unsupervised learning to analyze the massive proteomic dataset of the UK Biobank, which includes the concentrations of 2,923 plasma proteins from 52,691 participants. By applying this novel approach, we not only confirmed well-established biomarkers for diseases such as hypertension (UBE2L6) and leukemia (LRCH4) but also identified novel protein candidates. For instance, we identified IGF2BP3 in connection with celiac disease, a protein previously linked to intestinal barrier function, along with several other proteins not yet associated with these diseases. This approach opens up exciting possibilities for future research and may pave the way for the discovery of new biomarkers and therapeutic targets.

sB7-H3 as a prognostic biomarker in osteosarcoma: insights into clinical outcomes

High sensitivity formalin detection in aqueous solutions using plasmonic multifunctional metal insulator metal nanoring based optical refractive index sensor platform

Association between the atherogenic index of plasma and cognitive impairment

Experimental verification of SAM-OAM coupling of tightly focused elliptically polarized light

Pseudolysogeny-mediated evolutionary trade-offs favor phage therapy by limiting antibiotic resistance and virulence in Cutibacterium acnes

Integrated physiological, biochemical and hormonal traits determine drought tolerance and yield stability in cashew (Anacardium occidentale L.)

Triggering anger using a virtual reality social scene

Abstract Virtual reality (VR) simulations may provide a safer way for people with high levels of anger to practise overcoming unhelpful reactions. The first step in such treatment development is to test whether anger can be caused by a simulation of a common triggering situation. The aim was to test whether an intimidating VR social environment raises anger in men and whether the effect is more pronounced in those with problematic anger. A mixed-design experimental study was conducted. Two hundred and sixty-five people were screened: 20 men were allocated to a high anger group based on the clinical cut-off of the Dimensions of Anger Reactions-5 (DAR-5) (> 12) and 22 men to a low anger group (DAR-5 score < 8). Anger was assessed pre- and post-exposure to an intimidating VR lift scenario featuring seven characters. Appraisals of the virtual characters were also assessed. Regression analyses were used to test the effects of anger group and appraisals on anger response whilst controlling for baseline anger. Across all participants, anger significantly increased from pre- to post-VR ( t (41) = 3.63, p  < .001, d = 0.56). There was a significant effect of group on the extent anger was triggered by the VR scenario (β = 0.277, t (df) = 2.443, p  = .019, SE = 2.098) with the high anger group showing a greater anger response. Hostile appraisal of virtual characters (β = 0.416, t (df) = 3.285, p  = .002, SE = 0.038) was associated with a greater anger response. The reactions to the virtual reality simulation mirrored what may be expected in the real world. A mildly stressful VR social situation raised anger in all but this was more pronounced in men who have difficulties with anger. VR has the potential to be used in the assessment and treatment of anger.

Responses of tree defoliators to traffic-derived particulate matter and trace elements along a roadside pollution gradient

Abstract Traffic-derived particulate matter (PM) and trace elements (TEs) are pervasive stressors in roadside habitats. Although some insects, including pest species, appear to thrive despite roadside pollution, such observations may risk overgeneralization. We examined the responses of Yponomeuta padella , as a model roadside defoliator, to PM and TE pollution by rearing larvae on two hosts— Crataegus monogyna and Prunus cerasifera —obtained along a real-world pollution gradient (control, sidewalk, roadside). Leaves were characterized for physical traits (SLA, toughness), PM load, and TE concentrations. PM pollution followed a consistent control < sidewalk < roadside pattern across categories and size fractions; Cu, Fe and Sr showed the same spatial trend, while As, Cd, and Pb were absent in most control samples. Choice tests revealed strong larval avoidance of contaminated foliage (roadside and sidewalk) irrespectively of host species. Emergence dynamics (logistic models) showed slower growth rates and later inflection points with increasing pollution, and eclosion success declined significantly from control (90.1%) to sidewalk (82.5%) and roadside (77.1%). Adult body mass was lowest for roadside diets. Host species differed in SLA, toughness, and several accumulation metrics, but site effects dominated developmental outcomes. The results demonstrate context-dependent susceptibility of moths to PM and link adult performance costs to larval diets on PM-contaminated foliage. We propose that co-occurring pollution and stress typical of road verges act as an ecological filter shaping insect survival, with implications for habitat degradation in roadside ecosystems.