Bis(μ-2-phenyl­quinoline-4-carboxyl­ato)-κ3 O,O′:O;κ3 O:O,O′-bis­[(2,2′-bipyridine-κ2 N,N′)(2-phenyl­quinoline-4-carboxyl­ato-κ2 O,O′)cadmium(II)]

The neutral binuclear title complex, [Cd2(C16H10NO2)4(C10H8N2)2], is centrosymmetric, with the inversion center generating the central (μ-O)2Cd2 bridge. The CdII ion is in a strongly distorted CdN2O5 penta­gonal-bipyramidal geometry, defined by two N atoms from one 2,2′-bipyridine ligand and five O atoms from three 2-phenyl­quinoline-4-carboxyl­ate ligands, one monodentate, two bidentate. Weak inter­molecular π–π inter­actions [centroid–centroid distance = 3.712 (3) Å] help to establish the packing of the structure

Adaptive Resource Allocation Algorithm in Wireless Access Network

Wireless network state varies with the surrounding environment, however, the existing resource allocation algorithm cannot adapt to the varying network state, which results to the underutilization of frequency and power resource. Therefore, in this paper, we propose an adaptive resource allocation algorithm which can efficiently adapt to the varying network state by building an optimal mathematical model and then changing the weighted value of the objective function. Furthermore, the optimal allocation of subcarrier and power is derived by using the Lagrange dual decomposition and the subgradient method. Simulation results show that the proposed algorithm can adaptively allocate the resource to the users according to the varying user density which represents the network state

Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning

Large language models (LLMs) have shown remarkable capabilities in various natural language understanding tasks. With only a few demonstration examples, these LLMs can quickly adapt to target tasks without expensive gradient updates. Common strategies to boost such 'in-context' learning ability are to ensemble multiple model decoded results and require the model to generate an explanation along with the prediction. However, these models often treat different class predictions equally and neglect the potential discrepancy between the explanations and predictions. To fully unleash the power of explanations, we propose EASE, an Explanation-Aware Soft Ensemble framework to empower in-context learning with LLMs. We design two techniques, explanation-guided ensemble, and soft probability aggregation, to mitigate the effect of unreliable explanations and improve the consistency between explanations and final predictions. Experiments on seven natural language understanding tasks and four varying-size LLMs demonstrate the effectiveness of our proposed framework

Bis(μ-2-phenyl­quinoline-4-carboxyl­ato)bis­[aqua­(1,10-phenanthroline)(2-phenyl­quinoline-4-carboxyl­ato)manganese(II)] dihydrate

In the centrosymmetric dinuclear title complex, [Mn2(C16H10NO2)4(C12H8N2)2(H2O)2]·2H2O, the MnII cation is in a distorted octa­hedral coordination geometry defined by two N atoms from a 1,10-phenanthroline ligand, one water O atom and three O atoms from three 2-phenyl­quinoline-4-carboxyl­ate anions. A pair of 2-phenyl­quinoline-4-carboxyl­ate anions bridge two Mn cations, forming the dinuclear mol­ecule. An intra­moleculr O—H⋯O hydrogen bond occurs. Inter­molecular O—H⋯O and O—H⋯N hydrogen bonds are present in the crystal structure

Immune modulation of gut microbiota and its metabolites in chronic hepatitis B

The gut microbiota is a diverse ecosystem consisting of 100 trillion microbiomes. The interaction between the host’s gut and distal organs profoundly impacts various functions such as metabolism, immunity, neurology, and nutrition within the human body. The liver, as the primary immune organ, plays a crucial role in maintaining immune homeostasis by receiving a significant influx of gut-derived components and toxins. Perturbations in gut microbiota homeostasis have been linked to a range of liver diseases. The advancements in sequencing technologies, such as 16S rRNA and metagenomics, have opened up new avenues for comprehending the intricate physiological interplay between the liver and the intestine. Metabolites produced by the gut microbiota function as signaling molecules and substrates, influencing both pathological and physiological processes. Establishing a comprehensive host-bacterium-metabolism axis holds tremendous potential for investigating the mechanisms underlying liver diseases. In this review, we have provided a summary of the detrimental effects of the gut-liver axis in chronic liver diseases, primarily focusing on hepatitis B virus-related chronic liver diseases. Moreover, we have explored the potential mechanisms through which the gut microbiota and its derivatives interact with liver immunity, with implications for future clinical therapies

Abnormal expression of miRNA-122 in cerebral infarction and related mechanism of regulating vascular endothelial cell proliferation and apoptosis by targeting CCNG1

Objective: To analyze the value of serum miRNA-122 expression in the diagnosis, severity, and prognosis of Acute Cerebral Infarction (ACI) and the correlation mechanism of serum miRNA-122 on the proliferation and apoptosis of vascular endothelial cells in ACI. Method: A total of 60 patients with ACI who were admitted to the emergency department of the Taizhou People's Hospital from January 1, 2019, to December 30, 2019, and 30 healthy controls during the same period were selected. General clinical data of all patients at admission were collected. Including age, sex, medical history, and inflammatory factors (C-Reactive Protein [CRP], Interleukin-6 [IL-6], Procalcitonin [PCT], Neutrophil Gelatinase-Associated Lipid carrier protein [NGAL]). The National Institutes of Health Stroke Scale (NIHSS) score at admission and short-term prognosis (the Modified Rankin Score [mRS]) score at 3 months after onset were recorded. The expression level of miRNA-122 in the serum of patients with ACI and normal controls was detected by reverse-transcription quantitative Real-Time Polymerase Chain Reaction (RT-QPCR), and the correlation between the expression level of miRNA-122 in the serum of patients with ACI and the level of inflammatory factors, NIHSS and mRS scores were analyzed. The expression levels of miRNA-122 in the serum of patients with ACI, normal people, and Human Umbilical cord Endothelial Cells (HUVECs) cultured in a blank control group were detected by RT-QPCR and statistically analyzed. MTT and flow cytometry was used to compare the proliferation and apoptosis of vascular endothelial cells in the miRNA-122 mimics and inhibitors transfection groups and the corresponding negative control group. The mRNA and protein levels of apoptosis-related factors Bax, Bcl-2, Caspase-3, and angiogenesis-related proteins Hes1, Notch1, Vascular Endothelial Growth Factors (VEGF), and CCNG1 were detected by RT-QPCR and Western blot. Bioinformatics methods predicted CCNG1 to be the target of miRNA-122, and the direct targeting relationship between CCNG1 and miRNA-122 was verified by a dual-luciferase reporting assay. Result: Serum miRNA-122 expression in patients with ACI was significantly higher than that in healthy controls, with an area under the receiver operating characteristic curve of 0.929, 95% Confidence Interval of 0.875‒0.983, and an optimal cut-off value of 1.397. The expression levels of CRP, IL-6, and NGAL in patients with ACI were higher than those in healthy control groups, p < 0.05; miRNA-122 was positively correlated with CPR, IL-6, NIHSS score, and mRS score. At 48h and 72h, the proliferation rate of HUVECs cells in the miRNA-122 mimics group decreased and the apoptosis rate increased. Cell proliferation rate increased, and apoptosis rate decreased significantly in the groups transfected with miRNA-122 inhibitors. The mRNA and protein levels of pro-apoptotic factors Bax and caspase-3 were significantly increased in the miRNA-122 mimics transfection group, while those of anti-apoptotic factor Bcl-2 were significantly decreased compared to those of the control group. The expression of Bax and Caspase-3 decreased, and the expression of anti-apoptotic factor Bcl-2 increased in the transfected miRNA-122 inhibitors group. mRNA expression levels of Hes1, Notch1, VEGF, and CCNG1 in the miRNA-122 mimic transfected group were significantly decreased, while mRNA expression levels in the miRNA-122 inhibitors transfected group were significantly increased. Bioinformatics showed that there was a miRNA-122 binding site in the 3′UTR region of CCNG1, and dual luciferase assay confirmed that CCNG1 was the target of miRNA-122. Conclusion: Serum miRNA-122 increased significantly after ACI, which may be a diagnostic marker of ACI. miRNA-122 may be involved in the pathological process of ACI and is related to the degree of neurological impairment and short-term prognosis in patients with ACI. miRNA-122 may play a regulatory role in ACI by inhibiting cell proliferation, increasing apoptosis, and inhibiting vascular endothelial cell regeneration through the CCNG1 channel.

On What Basis? Predicting Text Preference Via Structured Comparative Reasoning

Comparative reasoning plays a crucial role in text preference prediction; however, large language models (LLMs) often demonstrate inconsistencies in their reasoning. While approaches like Chain-of-Thought improve accuracy in many other settings, they struggle to consistently distinguish the similarities and differences of complex texts. We introduce SC, a prompting approach that predicts text preferences by generating structured intermediate comparisons. SC begins by proposing aspects of comparison, followed by generating textual comparisons under each aspect. We select consistent comparisons with a pairwise consistency comparator that ensures each aspect's comparisons clearly distinguish differences between texts, significantly reducing hallucination and improving consistency. Our comprehensive evaluations across various NLP tasks, including summarization, retrieval, and automatic rating, demonstrate that SC equips LLMs to achieve state-of-the-art performance in text preference prediction

Regulatory roles of RpoS in the biosynthesis of antibiotics 2,4-diacetyphloroglucinol and pyoluteorin of Pseudomonas protegens FD6

The rhizosphere microbe Pseudomonas protegens FD6 possesses beneficial traits such as the production of antibiotics like pyoluteorin (Plt) and 2,4-diacetylphloroglucinol (2,4-DAPG). The alternative RpoS (σ38 factor), as a master regulator, activates or inhibits the transcription of stationary phase genes in several biocontrol organisms. Here, we investigated the complicated function and regulatory mechanism of RpoS in the biosynthesis of 2,4-DAPG and Plt in strain FD6. Phenotypic assays suggested that ΔrpoS was impaired in biofilm formation, swimming motility, swarming motility, and resistance to stress, such as heat, H2O2 and 12% ethanol. The RpoS mutation significantly increased both 2,4-DAPG and Plt production and altered the transcription and translation of the biosynthetic genes phlA and pltL, indicating that RpoS inhibited antibiotic production by FD6 at both the transcriptional and translational levels. RpoS negatively controlled 2,4-DAPG biosynthesis and transcription of the 2,4-DAPG operon phlACBD by directly interacting with the promoter sequences of phlG and phlA. In addition, RpoS significantly inhibited Plt production and the expression of its operon pltLABCDEFG by directly binding to the promoter regions of pltR, pltL and pltF. Further analyzes demonstrated that a putative R147 mutation in the RpoS binding domain abolished its inhibitory activity on the expression of pltL and phlA. Overall, our results reveal the pleiotropic regulatory function of RpoS in P. protegens FD6 and provide the basis for improving antibiotic biosynthesis by genetic engineering in biocontrol organisms

Genetic Variants at 1p11.2 and Breast Cancer Risk: A Two-Stage Study in Chinese Women

BACKGROUND: Genome-wide association studies (GWAS) have identified several breast cancer susceptibility loci, and one genetic variant, rs11249433, at 1p11.2 was reported to be associated with breast cancer in European populations. To explore the genetic variants in this region associated with breast cancer in Chinese women, we conducted a two-stage fine-mapping study with a total of 1792 breast cancer cases and 1867 controls. METHODOLOGY/PRINCIPAL FINDINGS: Seven single nucleotide polymorphisms (SNPs) including rs11249433 in a 277 kb region at 1p11.2 were selected and genotyping was performed by using TaqMan® OpenArray™ Genotyping System for stage 1 samples (878 cases and 900 controls). In stage 2 (914 cases and 967 controls), three SNPs (rs2580520, rs4844616 and rs11249433) were further selected and genotyped for validation. The results showed that one SNP (rs2580520) located at a predicted enhancer region of SRGAP2 was consistently associated with a significantly increased risk of breast cancer in a recessive genetic model [Odds Ratio (OR)  =  1.66, 95% confidence interval (CI)  =  1.16-2.36 for stage 2 samples; OR  =  1.51, 95% CI  =  1.16-1.97 for combined samples, respectively]. However, no significant association was observed between rs11249433 and breast cancer risk in this Chinese population (dominant genetic model in combined samples: OR  =  1.20, 95% CI  =  0.92-1.57). CONCLUSIONS/SIGNIFICANCE: Genotypes of rs2580520 at 1p11.2 suggest that Chinese women may have different breast cancer susceptibility loci, which may contribute to the development of breast cancer in this population