Fake Alignment: Are LLMs Really Aligned Well?

The growing awareness of safety concerns in large language models (LLMs) has sparked considerable interest in the evaluation of safety within current research endeavors. This study investigates an interesting issue pertaining to the evaluation of LLMs, namely the substantial discrepancy in performance between multiple-choice questions and open-ended questions. Inspired by research on jailbreak attack patterns, we argue this is caused by mismatched generalization. That is, the LLM does not have a comprehensive understanding of the complex concept of safety. Instead, it only remembers what to answer for open-ended safety questions, which makes it unable to solve other forms of safety tests. We refer to this phenomenon as fake alignment and construct a comparative benchmark to empirically verify its existence in LLMs. Such fake alignment renders previous evaluation protocols unreliable. To address this, we introduce the Fake alIgNment Evaluation (FINE) framework and two novel metrics--Consistency Score (CS) and Consistent Safety Score (CSS), which jointly assess two complementary forms of evaluation to quantify fake alignment and obtain corrected performance estimates. Applying FINE to 14 widely-used LLMs reveals several models with purported safety are poorly aligned in practice. Our work highlights potential limitations in prevailing alignment methodologies

CircGLIS3 promotes gastric cancer progression by regulating the miR-1343-3p/PGK1 pathway and inhibiting vimentin phosphorylation

Abstract Background Circular RNAs (circRNAs) have been proved to play crucial roles in the development of various cancers. However, the molecular mechanism of circGLIS3 involved in gastric cancer (GC) tumorigenesis has not been elucidated. Methods The higher expression level of circGLIS3 was identified in GC through RNA sequencing and subsequent tissue verification using Quantitative real-time PCR (qRT-PCR). A series of functional experiments in vitro and in vivo were performed to evaluated the effects of circGLIS3 on tumor growth and metastasis in GC. The interaction and regulation of circGLIS3/miR-1343-3p/PGK1 axis was confirmed by RNA pulldown, western blot, and rescue experiments. RIP and western blot were performed to demonstrate the role of circGLIS3 in regulating phosphorylation of VIMENTIN. We then used qRT-PCR and co culture system to trace circGLIS3 transmission via exosomal communication and identify the effect of exosomal circGLIS3 on gastric cancer and macrophages. Finally, RIP experiments were used to determine that EIF4A3 regulates circGLIS3 expression. Results CircGLIS3(hsa_circ_0002874) was significantly upregulated in GC tissues and high circGLIS3 expression was associated with advanced TNM stage and lymph node metastasis in GC patients. We discovered that overexpression of circGLIS3 promoted GC cell proliferation, migration, invasion in vitro and in vivo, while suppression of circGLIS3 exhibited the opposite effect. Mechanistically, circGLIS3 could sponge miR-1343-3p and up-regulate the expression of PGK1 to promote GC tumorigenesis. We also found that circGLIS3 reduced the phosphorylation of VIMENTIN at ser 83 site by binding with VIMENTIN. Moreover, it was proven that exosomal circGLIS3 could promote gastric cancer metastasis and the M2 type polarization of macrophages. In the final step, the mechanism of EIF4A3 regulating the generation of circGLIS3 was determined. Conclusion Our findings demonstrate that circGLIS3 promotes GC progression through sponging miR-1343-3p and regulating VIMENTIN phosphorylation. CircGLIS3 is a potential therapeutic target for GC patients

Downregulation of miRNA-214 in cancer-associated fibroblasts contributes to migration and invasion of gastric cancer cells through targeting FGF9 and inducing EMT

Abstract Background Cancer-associated fibroblasts (CAFs), one of the principal constituents of the tumor microenvironment, have a pivotal role in tumor progression. Dysregulation of microRNAs (miRNAs) in CAFs contributes to the tumor-promoting ability of CAFs. However, the mechanism underlying the involvement of miRNAs in CAFs of gastric cancer (GC) is not fully understood. This study aimed to explore the effects of miRNA-214 in CAFs on GC migration and invasion. Methods The primary CAFs and corresponding normal fibroblasts (NFs) were isolated. Cell counting kit-8, EdU cell proliferation staining and Transwell assays were used to determine the role of miRNA-214 in GC progression. Real-time polymerase chain reaction, Western blot analysis, and dual-luciferase reporter assay were performed to verify the target genes of miRNA-214. Immunofluorescence and Western blot analysis were applied to detect the expression of epithelial–mesenchymal transition (EMT) markers. Immunohistochemistry and in situ hybridization were implemented to analyze the fibroblast growth factor 9 (FGF9) and miRNA-214 expression in human GC tissues, respectively. Finally, to assess its prognostic relevance, Kaplan–Meier survival analysis was conducted. Results MiRNA-214 was significantly downregulated in CAFs of GC compared with NFs. The upregulation of miRNA-214 in CAFs inhibited GC cell migration and invasion in vitro but failed to affect proliferation. Moreover, GC cells cultured with conditioned medium from CAFs transfected with miR-214 mimic showed increased expression of E-cadherin and decreased expression of Vimentin, N-cadherin and Snail, indicating the suppression of EMT of GC cells. Furthermore, FGF9 was proved to be a direct target gene of miR-214. The expression of FGF9 was higher in CAFs than that in tumor cells not only in primary tumor but also in lymph node metastatic sites (30.0% vs 11.9%, P < 0.01 and 32.1% vs 12.3%, P < 0.01, respectively). Abnormal expression of FGF9 in CAFs of lymph node metastatic sites was significantly associated with poor prognosis in patients with GC (P < 0.05). Conclusions This study showed that miR-214 inhibited the tumor-promoting effect of CAFs on GC through targeting FGF9 in CAFs and regulating the EMT process in GC cells, suggesting miRNA-214/FGF9 in CAFs as a potential target for therapeutic approaches in GC

Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn

The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize

Phenotypes of hiPSCs and somatic cells (HSFs).

<p>White histograms represent the surface expression of MHC-I, MHC-II, HLA-G, HLA-E, CD40, CD80, and CD86, and gray histograms represent isotype controls. Data shown here are representative of three different experiments.</p

Characterization of hiPSCs.

<p>(A) Expression of human ES cell-specific cell surface markers on hiPSCs were analyzed by flow cytometry. Gray histograms: isotype controls; White histograms: positive staining of antigens. (B) Various tissues of all three germ layers present in teratomas derived from hiPSCs. Hematoxylin and eosin staining of teratoma sections. Scale bars, 500 µm.</p

Phenotypes of hiPSCs and somatic cells (HSFs).

<p>White histograms represent the surface expression of MHC-I, MHC-II, HLA-G, HLA-E, CD40, CD80, and CD86, and gray histograms represent isotype controls. Data shown here are representative of three different experiments.</p

Cytokine expression profile in MLR.

<p>Culture supernatants were collected from the MLR after 24 hours of culture and examined for expression of cytokines secreted by Th1 (A), Th2 (B), and Th17 (C) (n = 7). Data shown are single values for each point in the scatter plot. * <i>P<</i>0.05; ** P<0.01; *** P<0.001. The grey lines indicate the sensitivity of each cytokine.</p