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Gastric cancer is one of the leading causes of cancer-related death due to late diagnosis with high metastatic frequency. In this study, the impact of tumor secreted exosomes on immune function in the tumor environment was investigated using exosomes isolated from gastric cancer cell lines MKN-28, MKN-45, and SGC-7901. Results show that exosomes derived from all of these cell lines changed the gene expression and cytokine secretion levels of CD8 + T cells. They also block cell cycle progression, induced apoptosis in CD8 + T cells. Image analysis of fluorescent labeled exosomes derived from three cell lines injected systemically into C57BL/6 mice revealed these exosomes primarily localize to the lungs. We further showed exosomes were mainly taken up by natural killer cells and macrophages in the lung. After long-term exposure to inject exosomes from MKN-45 cells, mice developed an immunosuppressive tumor microenvironment in the lung with increased frequency of effector memory CD4 + T and MDSC, decreased CD8 + T cell and NK frequency. This immune suppressive environment promotes gastric cancer lung metastasis. Lung metastasis sites developed after mice were exposed to exosomes isolated from all three gastric cancer cell lines when the mice were injected with MFC cells. Results suggest that exosomes derived from gastric cancer cells (especially MKN-45 and MKN-28) changed CD8 + T cell gene expression and cytokine secretion patterns to create an immunosuppressive condition for metastatic niche formation in the lung. Overall, this study provides new insights into how gastric cancer derived exosomes modulate the immune response to promote lung tumor metastasis.

RSCD faces persistent challenges in high-resolution imagery due to complex spatial structures, temporal heterogeneity, and semantic ambiguity. While deep learning methods have significantly advanced the field, most existing models still rely on static and homogeneous processing, treating all channels and modalities equally, which limits their capacity to capture fine-grained semantic shifts or adapt to region-dependent variations. To address these issues, we propose SynerCD, a unified Siamese encoder–decoder framework that introduces dynamic, content-adaptive perception through channel decoupling, frequency-domain enhancement, and vision-language collaboration. The encoder employs a Tri-branch Synergistic Coupling (TSC) module that dynamically rebalances channel responses and captures multi-scale spatial-frequency dependencies via Mamba-based long-sequence modeling and wavelet decomposition. The decoder integrates a vision-aware language-guided attention (VAL-Att) module, which adaptively modulates visual-textual fusion using CLIP-based semantic prompts to guide attention toward meaningful change regions. Extensive experiments on four benchmark datasets verify that SynerCD achieves superior localization accuracy and semantic robustness, establishing a dynamic and adaptive paradigm for multimodal change detection.

The hermaphroditic Caenorhabditis elegans , with its fully mapped connectome of 302 neurons, offers a paradigmatic example of how a minimal nervous system governs biotic, adaptive, and context-dependent behaviors. In contrast, modern artificial intelligence systems achieve intelligence through scale rather than efficiency, relying instead on massive datasets and artificially engineered architectures. This mini-review explores how Caenorhabditis elegans neural circuits can inform the development of more efficient and flexible artificial neural networks. We highlight recent studies that translate the principles inherent to Caenorhabditis elegans neural circuits into artificial neural network architectures, with applications in machine control and image classification, resulting in enhanced robustness and improved performance. By distilling neural principles from the simplest known nervous system, this mini-review outlines a pathway toward compact, adaptive, and biologically inspired artificial intelligence systems.

Background The triglyceride–glucose (TyG) index has been linked to the occurrence of prediabetes, but there is limited evidence regarding its association with mortality in individuals with prediabetes. Thus, this study aimed to explore the association between TyG-related indices and all-cause and cause-specific mortality in individuals with prediabetes. Method Based on NHANES data from 1999 to 2018, the TyG index, TyG-waist circumference (TyG-WC), and TyG-waist-to-height ratio (TyG-WHtR) were calculated. Mortality data including all-cause mortality, cardiovascular disease (CVD) mortality, and cancer mortality were determined as of December 31, 2019. Kaplan-Meier curves, Cox regression analysis, and restricted cubic splines (RCS) were used to assess associations of TyG-related indices with all-cause and cause-specific mortality (CVD and cancer) in individuals with prediabetes. Subgroup and sensitivity analyses were used to confirm the robustness of the results. Results In total, 9,574 participants with prediabetes were included. Kaplan-Meier curves indicated that overall survival and cancer-specific survival were associated with different quartiles of the TyG index, with quartile 1 having the lowest all-cause mortality ( P  = 0.042 and P  = 0.008). TyG-WHtR was negatively correlated with overall survival and CVD-specific survival ( P  < 0.001 and P  = 0.012). Multivariate Cox regression analysis showed a significant positive correlation between the TyG index and cancer mortality (Q4: HR = 1.957, 95% CI: 1.126–3.402, P  = 0.017). High quartiles of TyG-WC were significantly associated with cancer mortality in participants with prediabetes (HR = 2.397, 95% CI, 1.062–5.409, P  = 0.035). Similarly, higher quartiles of TyG-WHtR were positively associated with all-cause, CVD, and cancer mortality. RCS analysis showed that TyG-WC and TyG-WHtR were nonlinearly correlated with cancer mortality ( P for nonlinear = 0.028 and 0.006). Conclusion Elevated TyG and TyG-WC levels were significantly associated with increased cancer mortality risk, while TyG-WHtR showed stronger associations with all-cause and cause-specific mortality in individuals with prediabetes. These indices could serve as surrogate biomarkers for follow-up and clinical management of individuals with prediabetes.

This study aims to investigate the effects of calcium on the migration of nitrogen in coal (coal-N) to N-containing gas species, particularly, NH 3 and HCN (volatile-N) in volatiles, as well as the chemical transformation of the N in char during coal pyrolysis under different temperatures. The pyrolysis experiments of Shengli brown coal and its derived coal samples loaded with different contents of calcium were conducted under 600–800 °C in a novel fluidized bed reactor. The experimental results showed that during coal pyrolysis, the generation of NH 3 is mainly derived from secondary reactions among volatiles, tar and char with the catalytic effect of mineral matter, especially calcium in coal. Increasing pyrolysis temperature from 600 to 800 °C could enhance the release of N in coal to volatiles. Meanwhile, the increased pyrolysis temperature could also inhibit the generation of NH 3 while facilitating the formation of HCN. The release of HCN is more sensitive to pyrolysis temperatures. Specifically, under higher pyrolysis temperatures, more N-containing structures in coal would become thermally unstable and crack into HCN; On the other hand, higher pyrolysis temperature could also enhance the decomposition of N in coal to N-containing species in tar or N 2 , thus reducing the release of HCN and NH 3 . Nitrogen in tar could either undergo secondary decomposition reactions, generating NH 3 , HCN, N 2 and other N-containing species in gas phase, or experience condensation polymerization by forming macromolecular structure and be retained in char at high pyrolysis temperatures. Calcium could significantly restrain the release of N from coal, thus reducing the yields of NH 3 and HCN. During coal pyrolysis, calcium catalytically enhances the fracture and combination of chemical bonds, generating abundant free radicals. These free radicals could continuously attack N-containing structures and consequently release the N-containing gaseous products, such as NH 3 , HCN, N 2 etc., resulting in the decrease of N in char. Calcium also plays important roles in nitrogen transformation in char during coal pyrolysis by catalytically intensifying the transformation of N in char from pyridinic nitrogen (N-6) and pyrrolic nitrogen (N-5) to quaternary type nitrogen (N-Q) during coal pyrolysis.

Background The incidence and mortality rates of patients with chronic lymphocytic leukemia (CLL) in China have recently increased. This study performed a long-term economic evaluation of the first-line treatment strategies ibrutinib (IB) or bendamustine (BE) plus rituximab (RI) for previously untreated older patients with CLL without the del(17p)/TP53 mutation in China. Methods Based on clinical data from large, randomized trials, a Markov model including four disease states (event-free survival, treatment failure, post-treatment failure, and death) was used to estimate the incremental costs per quality adjusted-life year (QALY) gained from the first-line IB strategy versus the BE plus RI strategy over a 10-year period. All costs were adjusted to 2022 values based on the Chinese Consumer Price Index, and all costs and health outcomes were discounted at an annual rate of 5%. Sensitivity analysis was performed to confirm the robustness of base-case results. Results Compared to the first-line BE plus RI strategy, first-line IB treatment achieved 1.17 additional QALYs, but was accompanied by $88,046.78 (estimated in 2022 US dollars) in decremental costs per patient over 10 years. Thus, first-line treatment with IB appeared to have absolute dominance compared to the BE plus RI strategy. Sensitivity analysis confirmed the robustness of these results. Conclusions The first-line treatment with IB is absolutely cost-effective compared to the first-line BE plus RI treatment strategy for 65 or older patients with CLL without the del (17p)/TP53 mutation from the Chinese payer perspective. Therefore, it is strongly recommended that Chinese health authorities select the former strategy for these CLL patients.

Encoder-like micro area-changed capacitive transducers are advantageous in terms of their better linearity and larger dynamic range compared to gap-changed capacitive transducers. Such transducers have been widely applied in rectilinear and rotational position sensors, lab-on-a-chip applications and bio-sensors. However, a complete model accounting for both the parasitic capacitance and fringe effect in area-changed capacitive transducers has not yet been developed. This paper presents a complete model for this type of transducer applied to a high-resolution micro accelerometer that was verified by both simulations and experiments. A novel optimization method involving the insertion of photosensitive polyimide was used to reduce the parasitic capacitance, and the capacitor spacing was decreased to overcome the fringe effect. The sensitivity of the optimized transducer was approximately 46 pF/mm, which was nearly 40 times higher than that of our previous transducer. The displacement detection resolution was measured as 50 pm/√Hz at 0.1 Hz using a precise capacitance detection circuit. Then, the transducer was applied to a sandwich in-plane micro accelerometer, and the measured level of the accelerometer was approximately 30 ng/√Hz at 1Hz. The earthquake that occurred in Taiwan was also detected during a continuous gravity measurement.

The paper aims at studying the influences of temperature on the suspended cables’ dynamical behaviors subjected to dual harmonic excitations in thermal environments. Significantly, the quadratic nonlinearity and the corresponding secondary resonances are considered. By introducing a tension variation factor, the nonlinear vibration equations of motion could be obtained based on the condensation model. By using Galerkin’s procedure, the continuous model of the nonlinear system is reduced to a set of infinite models with quadratic and cubic nonlinearities. By using the multiple scales method, the resultant reduced model is solved and the stability analysis is also presented in two simultaneous resonance cases. Nonlinear dynamical behaviors with thermal effects are presented using bifurcation diagrams, time-history curves, phase portraits, frequency spectrums, and Poincaré sections. The numerical results show that thermal effects induce different scenarios. The sensitivities of linear (natural frequency) and nonlinear (quadratic and cubic) coefficients to temperature variations are different. The temperature may increase or decrease the response amplitudes depending on the excitation amplitude and the sag-to-span ratio. The inflection point is shifted and exhibited at a smaller or larger excitation amplitude in thermal environments. The resonant range between two Pitchfork bifurcations seems to be reduced when the temperature is decreasing. The response amplitude is very sensitive to temperature, and even an opposite spring behavior may be exhibited due to warming/cooling conditions. However, the periodic motions seem independent of temperature variations.

The measurements of wafers’ surface profile are crucial for safeguarding the fabrication quality of integrated circuits and MEMS devices. The current techniques measure the profile mainly by moving a capacitive or optical spacing sensing probe along multiple lines, which is high-cost and inefficient. This paper presents the calculation, simulation and experiment of a method for measuring the surface profile with arrayed capacitive spacing transducers. The calculation agreed well with the simulation and experiment. Finally, the proposed method was utilized for measuring the profile of a silicon wafer. The result is consistent with that measured by a commercial instrument. As a movement system is not required, the proposed method is promising for industry applications with superior cost and efficiency to the existing technology.

This work evaluated the effects of inherent alkali and alkaline earth metals on nitrogen transformation during steam gasification of Shengli lignite at the temperature of 873–1173 K in a fluidized-bed/fixed-bed quartz reactor. The results indicated that the alkali metal Na and alkaline earth metals Ca, Mg in coal have different effects on inherent nitrogen transformation to NH 3 , HCN and char-N during the lignite steam gasification. Specifically during the steam gasification of Shengli lignite, Na and Ca, Mg not only catalyze the inherent nitrogen conversions to NH 3 , but also promote the secondary reactions of the nascent char-N as well as the generation of NH 3 from the generated HCN, meanwhile they also inhibited the inherent nitrogen conversion to HCN and char-N. The presence of Na, Ca and Mg hindered the formation of oxidized nitrogen (N-X) functional groups, but enhanced pyridinic nitrogen (N-6) and quaternary nitrogen’s (N-Q) formation in char.