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In this article, we consider the following fractional (p , q) -Laplacian problem (− Δ) p s 1 u + (− Δ) q s 2 u + V (x) (| u | p − 2 u + | u | q − 2 u) = f (u) + λ | u | r − 2 u , where x ∈ R N , (− Δ) p s 1 is the fractional p-Laplacian operator ( (− Δ) q s 2 is similar), 0 < s 1 < s 2 < 1 < p < q < N s 2 , q s 2 * = N q N − s 2 q , r ≥ q s 2 * , f is a C 1 real function and V is a coercive function. By using variational methods, we prove that the above problem admits a sign-changing solution if λ > 0 is small. [ABSTRACT FROM AUTHOR]

Syndecan-1 (SDC1) modified lipid bilayer (LB)-coated mesoporous silica nanoparticles (MSN) to co-deliver gemcitabine (GEM) and honokiol (HNK) were prepared for the targeting treatment of pancreatic cancer. The encapsulation efficiencies of GEM and HNK in SDC1-LB-MSN-GEM/HNK were determined to be 60.3 ± 3.2% and 73.0 ± 1.1%. The targeting efficiency of SDC1-LB-MSN-GEM/HNK was investigated in BxPC-3 cells in vitro. The fluorescence intensity in the cells treated with SDC1-LB-MSN-Cou6 was 2-fold of LB-MSN-Cou6-treated cells, which was caused by SDC1/IGF1R-mediated endocytosis. As anticipated, its cytotoxicity was significantly increased. Furthermore, the mechanism was verified that SDC1-LB-MSN-HNK induced tumor cell apoptosis through the mitochondrial apoptosis pathway. Finally, the biodistribution, tumor growth inhibition, and preliminary safety studies were performed on BALB/c nude mice bearing BxPC-3 tumor models. The tumor growth inhibition index of SDC1-LB-MSN-GEM/HNK was 56.19%, which was 1.45-fold and 1.33-fold higher than that of the free GEM/HNK and LB-MSN-GEM/HNK treatment groups, respectively. As a result, SDC1-LB-MSN-GEM/HNK combined advantages of both GEM and HNK and simultaneously targeted and eliminated pancreatic cancerous and cancer-associated stromal cells. In summary, the present study demonstrated a new strategy of synergistic GEM and HNK to enhance the therapeutic effect of pancreatic cancer via the targeting depletion of tumor stroma. [ABSTRACT FROM AUTHOR]

$ Seru $ Production is an innovative production mode frequently utilized in electronic assembly enterprises. Up to now, there is no exact algorithm for the bi-objective $ Seru $ Production. We develop an innovative exact method based on decomposition and cutting solution space to obtain the exact Pareto-optimal solutions for the first time. $ Seru $ Production is decomposed into two decision processes, i.e., $ seru $ formation and $ seru $ scheduling. We define dominated $ seru $ formations and cut 97% dominated $ seru $ formations based on the ideal point and Non-Dominated Incumbent Solutions (NDIS). Thus, the Pareto-optimal solutions is obtained by executing Non-dominant Sort ($ NS $) for all the non-dominated $ seru $ formations. The $ \varepsilon $-constraint method is applied in $ seru $ scheduling to obtain the Pareto-optimal schedules for a given $ seru $ formation. In addition, the current best algorithms for solving multi-objective $ Seru $ Production are used to ensure the initial NDIS high-quality. Finally, parallel programming is performed according to the characteristics of $ Seru $ Production. Test data verify that proposed exact method can find the Pareto-optimal solution set for all small-scale and most medium-scale instances of bi-objective $ Seru $ Production.Keywords: $ Seru $ Production, bi-objective programming, exact method, solution space cut, $ seru $ formation dominance, intelligent algorithm, parallel programming. [ABSTRACT FROM AUTHOR]

We studied the unique kinematic properties in massive filament G352.63-1.07 at 103 au spatial scale with the dense molecular tracers observed with the Atacama Large Millimeter/submillimeter Array. We find the central massive core M1 (12 M ⊙) being separated from the surrounding filament with a velocity difference of v − v ¯ sys = − 2 km s − 1 and a transverse separation within 3″. Meanwhile, as shown in multiple dense-gas tracers, M1 has a spatial extension closely aligned with the main filament and is connected to the filament toward both its ends. M1 thus represents a very beginning state for a massive, young star-forming core escaping from the parental filament, within a timescale of ∼4000 yr. Based on its kinetic energy (3.5 × 1044 erg), the core escape is unlikely solely due to the original filament motion or magnetic field but requires more energetic events such as a rapid intense anisotropic collapse. The released energy also seems to noticeably increase the environmental turbulence. This may help the filament to become stabilized again. [ABSTRACT FROM AUTHOR]

Immunotherapy is a promising cancer treatment strategy. In contrast, programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) inhibitors are associated with low response rates and are only useful in a small group of cancer patients. A combination of treatments may be effective for overcoming this clinical issue. Preladenant is an adenosine (ADO) receptor inhibitor that can block the ADO pathway and improve the tumor microenvironment (TME), thereby enhancing the immunotherapeutic effect of PD-1 inhibitors. However, its poor water solubility and low targeting limit its clinical applications. We designed a PEG-modified thermosensitive-liposome (pTSL) loaded with ADO small molecule inhibitor preladenant (P-pTSL) to overcome these problems and enhance the effect of PD-1 inhibitor on breast cancer immunotherapy. The prepared P-pTSL was round and uniformly distributed with a particle size of (138.9 ± 1.22) nm, PDI: 0.134 ± 0.031, and zeta potential (–10.1 ± 1.63) mV; preladenant was released slowly at 37 °C but released fast at 42 °C from P-pTSL, which was 76.52 ± 0.44%. P-pTSL has good long-term and serum stability and excellent tumor-targeting ability in mice. Moreover, the combination with PD-1 inhibitor significantly enhanced the anti-tumor effect, and the improvement of related factors in serum and lymph was more obvious under the condition of 42 °C thermotherapy in vitro. [ABSTRACT FROM AUTHOR]

Globally, everybody deals with poverty as a shared societal issue. It is still unclear how to investigate its causes and create new paradigms for policy, but it offers many promising directions for academic study. The use of technological innovation in this environment for social change to address poverty reduction is also an important issue. Consequently, this study investigates how effective poverty reduction may be accomplished in Asia through technological innovation and financial development. The super-efficiency data envelopment analysis model and system generalized method of moments were utilized in the present study together with data from 2010 to 2020 for an empirical estimate. The data show that different areas have effectively reduced poverty over time. However, Asia's overall effectiveness in reducing poverty is rather unevenly distributed geographically. The significance of poverty reduction in Asia is positively impacted by technical advancement and financial prosperity. The effects of globalization on the efficacy of poverty reduction are negligible. This study presents some policy insights for decision makers based on the empirical findings. [ABSTRACT FROM AUTHOR]