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Systemic inflammation is a hallmark of diabetes mellitus and contributes to insulin resistance and disease progression. Emerging evidence suggests that gut microbiota and their metabolites, particularly short-chain fatty acids (SCFAs), play a crucial role in modulating immune responses. Probiotics and synbiotics are increasingly explored for their potential to mitigate inflammation via microbiota-targeted mechanisms. This study aims to evaluate the effects of probiotic and synbiotic supplementation on inflammatory markers and microbial metabolites in individuals with type 1 and type 2 diabetes through meta-analytical techniques. A total of 46 randomized controlled trials (RCTs) comprising 3,580 diabetic patients were included following PRISMA guidelines. Meta-analyses were performed using random-effects models to assess changes in inflammatory markers (CRP, IL-6, TNF-α, IL-10) and SCFA levels (butyrate, propionate, acetate). Subgroup analyses and meta-regressions were conducted to identify effect modifiers such as intervention duration, formulation type (probiotic vs. synbiotic), and SCFA concentrations. Probiotic/synbiotic interventions led to significant reductions in CRP (SMD = -0.54), IL-6 (SMD = -0.41), and TNF-α (SMD = -0.48), along with an increase in IL-10 (SMD = +0.38). SCFA levels rose significantly, with butyrate showing the strongest effect (SMD = +0.46). Meta-regression revealed that butyrate levels, synbiotic use, and intervention duration ≥8 weeks were strong predictors of anti-inflammatory efficacy. Multi-strain and synbiotic interventions were more effective than single-strain or probiotic-only formulations. Sensitivity analyses confirmed the robustness of findings, and publication bias was minimal. These findings support the adjunctive use of targeted, SCFA-oriented probiotic formulations (e.g., with inulin/FOS, ≥10^9-10^10 CFU/day) to mitigate metabolic inflammation alongside standard care. Strain- and dose-standardized RCTs should confirm impacts on glycemic and cardiometabolic outcomes.

Background Cognitive impairment is a core symptom of schizophrenia. Metabolic abnormalities impact cognition, and although the influence of blood lipids on cognition has been documented, it remains unclear. We conducted a small cross-sectional study to investigate the relationship between blood lipids and cognition in patients with stable-phase schizophrenia. Using Olink proteomics, we explored the potential mechanisms through which blood lipids might affect cognition from an inflammatory perspective. Methods A total of 107 patients with stable-phase schizophrenia and cognitive impairment were strictly included. Comprehensive data collection included basic patient information, blood glucose, blood lipids, and body mass index. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and the MATRICS Consensus Cognitive Battery (MCCB). After controlling for confounding factors, we identified differential metabolic indicators between patients with mild and severe cognitive impairment and conducted correlation and regression analyses. Furthermore, we matched two small sample groups of patients with lipid metabolism abnormalities and used Olink proteomics to analyze inflammation-related differential proteins, aiming to further explore the association between lipid metabolism abnormalities and cognition. Results The proportion of patients with severe cognitive impairment (SCI) was 34.58%. Compared to patients with mild cognitive impairment (MCI), those with SCI performed worse in the Attention/Alertness (t = 2.668, p  = 0.009) and Working Memory (t = 2.496, p  = 0.014) cognitive dimensions. Blood lipid metabolism indicators were correlated with cognitive function, specifically showing that higher levels of TG ( r  = -0.447, p  < 0.001), TC ( r  = -0.307, p  = 0.002), and LDL-C ( r  = -0.607, p  < 0.001) were associated with poorer overall cognitive function. Further regression analysis indicated that TG (OR = 5.578, P  = 0.003) and LDL-C (OR = 5.425, P  = 0.001) may be risk factors for exacerbating cognitive impairment in individuals with stable-phase schizophrenia. Proteomics analysis revealed that, compared to individuals with stable-phase schizophrenia and normal lipid metabolism, those with hyperlipidemia had elevated levels of 10 inflammatory proteins and decreased levels of 2 inflammatory proteins in plasma, with these changes correlating with cognitive function. The differential proteins were primarily involved in pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, and IL-17 signaling pathway. Conclusion Blood lipids are associated with cognitive function in individuals with stable-phase schizophrenia, with higher levels of TG, TC, and LDL-C correlating with poorer overall cognitive performance. TG and LDL-C may be risk factors for exacerbating cognitive impairment in these patients. From an inflammatory perspective, lipid metabolism abnormalities might influence cognition by activating or downregulating related proteins, or through pathways such as cytokine-cytokine receptor interaction, chemokine signaling pathway, and IL-17 signaling pathway.

Background Stroke’s prevalence and morbidity are increasing (Guano, et al. Neuro 89:53–61, 2017), and limb motor dysfunction is left in most patients (Gittler, et al. JAMA 319:820–821, 2018). Particularly, the rehabilitation of upper limbs is more difficult and time-consuming (Borges, et al. The Cochrane database of systematic reviews 10:CD011887, 2018). Methods A double-blind randomized controlled trial (RCT) will be conducted to investigate whether a new functional electrical stimulation (FES) combined with acupoint therapy is more effective in the rehabilitation of upper limb motor dysfunction after stroke. Patients who meet the inclusion criteria will be randomly divided into two groups: programmed flexor–extensor alternating electrical acupoint stimulation group (PES group) and conventional flexor–extensor alternating electrical acupoint stimulation group (CES group), which will be treated for 3 weeks. The primary outcome measures are electroencephalogram (EEG) and surface electromyogram (sEMG). The secondary outcome variables include MBI (modified Barthel index), China Stroke Scale (CSS), FMA-U (Fugl-Meyer assessment upper limb), MMT (manual muscle testing), and Brunnstrom. Discussion The results of this study are expected to verify the efficacy of PES therapy in the rehabilitation of upper limb motor function after stroke. This may promote the widespread use of the therapy in hospitals, communities, and homes for early and continuous treatment. Trial registration ClinicalTrials.gov NCT05333497. Registered on April 11, 2022.

Blazars are a sub-class of quasars with Doppler boosted jets oriented close to the line of sight, and thus efficient probes of supermassive black hole growth and their environment, especially at high redshifts. Here we report on Very Long Baseline Interferometry observations of a blazar J0906 + 6930 at z  = 5.47, which enabled the detection of polarised emission and measurement of jet proper motion at parsec scales. The observations suggest a less powerful jet compared with the general blazar population, including lower proper motion and bulk Lorentz factor. This coupled with a previously inferred high accretion rate indicate a transition from an accretion radiative power to a jet mechanical power based transfer of energy and momentum to the surrounding gas. While alternative scenarios could not be fully ruled out, our results indicate a possibly nascent jet embedded in and interacting with a dense medium resulting in a jet bending. High redshift blazars are efficient probes of supermassive black holes and their environment in the early Universe. Here the authors show measurements of polarised emission and proper motion in the blazar J0906+6930 (redshift of 5.47) characterised by a nascent jet embedded in and interacting with a dense medium.

Graphs have provided an expressive mathematical tool to model quantum-mechanical devices and systems. In particular, it has been recently discovered that graph theory can be used to describe and design quantum components, devices, setups and systems, based on the two-dimensional lattice of parametric nonlinear optical crystals and linear optical circuits, different to the standard quantum photonic framework. Realizing such graph-theoretical quantum photonic hardware, however, remains extremely challenging experimentally using conventional technologies. Here we demonstrate a graph-theoretical programmable quantum photonic device in very-large-scale integrated nanophotonic circuits. The device monolithically integrates about 2,500 components, constructing a synthetic lattice of nonlinear photon-pair waveguide sources and linear optical waveguide circuits, and it is fabricated on an eight-inch silicon-on-insulator wafer by complementary metal–oxide–semiconductor processes. We reconfigure the quantum device to realize and process complex-weighted graphs with different topologies and to implement different tasks associated with the perfect matching property of graphs. As two non-trivial examples, we show the generation of genuine multipartite multidimensional quantum entanglement with different entanglement structures, and the measurement of probability distributions proportional to the modulus-squared hafnian (permanent) of the graph’s adjacency matrices. This work realizes a prototype of graph-theoretical quantum photonic devices manufactured by very-large-scale integration technologies, featuring arbitrary programmability, high architectural modularity and massive manufacturing scalability.A graph-theoretical programmable quantum photonic device composed of about 2,500 components is fabricated on a silicon substrate within a 12 mm × 15 mm footprint. It shows the generation, manipulation and certification of genuine multiphoton multidimensional entanglement, as well as the implementations of scattershot and Gaussian boson sampling.

Highlights Aspartame additive in electrolyte enables the in situ formation of ZnO-based solid electrolyte interphase, enhancing Zn anode corrosion resistance and stability with excellent self-healing capabilities. Zn║Zn symmetric cells with APM-modified electrolyte operate stably for 6,400 h at − 5 °C, 10,330 h at 25 °C, and 2,250 h at 40 °C, with a high DOD of 85.2%. Achieves 99.59% Coulombic efficiency, suppresses dendrite growth, and maintains 150 mAh g −1 capacity after 1,750 cycles in NH 4+ -V 2 O 5 full cells. Metallic Zn anodes suffer from hydrogen evolution and dendritic deposition in aqueous electrolytes, resulting in low Coulombic efficiency and poor cyclic stability for aqueous Zn-ion batteries (AZIBs). Constructing stable solid electrolyte interphase (SEI) with strong affinity for Zn and exclusion of water corrosion of Zn metal anodes is a promising strategy to tackle these challenges. In this study, we develop a self-healing ZnO-based SEI film on the Zn electrode surface by employing an aspartame (APM) as a versatile electrolyte additive. The hydrophobic nature and strong Zn affinity of APM can facilitate the dynamic self-healing of ZnO-based SEI film during cyclic Zn plating/stripping process. Benefiting from the superior protection effect of self-healing ZnO-based SEI, the Zn║Cu cells possess an average coulombic efficiency more than 99.59% over 1,000 cycles even at a low current density of 1 mA cm −2  − 1 mAh cm −2 . Furthermore, the Zn║NH 4 + -V 2 O 5 full cells display a large specific capacity of 150 mAh g −1  and high cyclic stability with a capacity retention of 77.8% after 1,750 cycles. In addition, the Zn║Zn cell delivers high temperature adaptability at a wide-temperature range from − 5 to 40 °C even under a high DOD of 85.2%. The enhanced capability and durability originate from the self-healing SEI formation enabled by multifunctional APM additives mediating both corrosion suppression and interfacial stabilization. This work presents an inspired and straightforward approach to promote a dendrite-free and wide-temperature rechargeable AZIBs energy storage system.

Accurate characterization of soil dynamic response is paramount for geotechnical and protective engineering. However, the impact properties of unsaturated cohesive soil have not been well characterized due to lack of sufficient research. For this purpose, impact tests using the Split Hopkinson Pressure Bar (SHPB) were elaborately designed to investigate the dynamic stress–strain response of unsaturated clay with strain rates of 204~590 s−1. As the strain rate increased up to 500 s−1, a lock-up behavior was observed in the plastic flow stage, which can be explained as the breakage and rearrangement of soil gains under a high level of stress. Further, the strain rate dependency of the dynamic strength was quantitatively characterized by the Cowper Symonds (CS) model and the CS coefficients were determined to be the intercept of 55 and slope of 0.8 in the double logarithmic scale of Dynamic Increase Factor (DIF) and strain rate space. Furthermore, the SHPB test was reproduced using a modified Material Particle Method (MPM), which involves an improved dynamic constitutive model for unsaturated soil considering the strain rate effect. The simulated stress–strain curves basically agree with the experimental results, indicating the feasibility of MPM for investigating the dynamic properties of unsaturated soil under SHPB impact loading.

Our previous work identified a class of SDSS quasars exhibiting multiple Gaia detections, classifying them as candidates for various astrophysical systems such as quasar-star pairs, dual quasars, and gravitationally lensed quasars. In this paper, we present a pilot VLBI study targeting a radio-bright subsample and report the first high-resolution imaging results. By leveraging the milliarcsecond-scale resolution of VLBI and its precise astrometric coordination incorporating with Gaia, we aim to refine the classification of these multiple matched sources, search for potential dual AGNs, and assess the efficacy of the combined Gaia-VLBI approach in resolving ambiguous quasar systems. We cross-matched the SQUAB quasar sample with the FIRST and NVSS catalogs, identifying 18 radio-emitting sources. The three brightest were selected for dual-frequency (1.6 and 4.9 GHz) VLBA observations. We performed VLBI imaging at both Gaia positions, constructed spectral index maps, and estimated brightness temperatures to characterize the radio morphology and physical properties. For the three target sources, our VLBI observations reveal compact radio structures consistent with single AGN at the primary Gaia positions. No significant emission is detected at the secondary Gaia locations. These results support the interpretation of the sources as quasar\\(-\\)star pairs, in line with earlier studies. This pilot study demonstrates the value of radio-VLBI high-resolution follow-ups on Gaia-selected quasar systems with multiple counterparts, showing how they can unambiguously reveal the true nature of these systems and help remove contaminants from dual AGN candidate samples.

There are some strange quasars with multiple Gaia detections or observed with abnormal astrometric characteristics, such as with large proper motions or significant astrometric noises. Those strange quasars could be potential candidates of quasar-star pairs, dual quasars (DQs), or lensed quasars (LQs). Searching for both DQs and LQs is of great importance in many fields of astrophysics. Here in this work, we select 143 SDSS spectroscopically confirmed quasars that have multiple Gaia EDR3 detections within 1 arcsec of the SDSS quasar' position. We apply several optical identification methods to classify this sample. We firstly exclude 65 quasar-star pairs via their stellar features including their parallaxes and proper motions, stellar features in the SDSS spectra, or via the colour-colour diagram. Based on the spectral-fitting results, we find 2 DQ candidates, one of which presents a double-peaked [O III] emission line feature and the other shows a broad \\(H_{\\beta}\\) velocity offset (\\(\\sim\\) 870 \\( km s^{-1} \\)) relative to the [O III] \\(\\lambda\\)5007 line. Via the colour difference method, we further find 56 LQ candidates with similar colours in their multiple images. We also cross-match 143 objects with the HST archive and find 19 targets with archival HST images. Our classification results of those 19 targets are mainly consistent with previous works.

With the widespread adoption of pathology foundation models in both research and clinical decision support systems, exploring their security has become a critical concern. However, despite their growing impact, the vulnerability of these models to adversarial attacks remains largely unexplored. In this work, we present the first systematic investigation into the security of pathology foundation models for whole slide image~(WSI) analysis against adversarial attacks. Specifically, we introduce the principle of \\textit{local perturbation with global impact} and propose a label-free attack framework that operates without requiring access to downstream task labels. Under this attack framework, we revise four classical white-box attack methods and redefine the perturbation budget based on the characteristics of WSI. We conduct comprehensive experiments on three representative pathology foundation models across five datasets and six downstream tasks. Despite modifying only 0.1\\% of patches per slide with imperceptible noise, our attack leads to downstream accuracy degradation that can reach up to 20\\% in the worst cases. Furthermore, we analyze key factors that influence attack success, explore the relationship between patch-level vulnerability and semantic content, and conduct a preliminary investigation into potential defence strategies. These findings lay the groundwork for future research on the adversarial robustness and reliable deployment of pathology foundation models. Our code is publicly available at: https://github.com/Jiashuai-Liu-hmos/Attack-WSI-pathology-foundation-models.