Female Underrepresentation in STEM Subjects: A Study of Female High School Students in China

In Chinese education, there is a conflict between girls’ socialized gender norms and the values and pedagogies that are incorporated in the science curriculum. These are influenced at both the micro- and macro-level of institutions and often discourage female students from choosing science courses, pushing them into social science instead. In order to ensure that female students have the same opportunities to reach their potential in science areas, it is important to understand the factors that influence their choices. This study investigates the potential reasons why female high school students in China are less likely to choose STEM subjects and direction. By conducting qualitative interviews with six female students, in two Chinese high schools, who have been enrolled in social sciences courses, the study discovers several factors, including the influence of current sciences curriculum, teachers, labor market, parents, and peers, behind their decision-making behaviors. The findings of this study enrich existing research on gender equity in science community by exploring the gender issue in Chinese high school education and provide a direction for future research on this topic while informing policies that can address gender disparities in science programs

YAP and TAZ are transcriptional co-activators of AP-1 proteins and STAT3 during breast cellular transformation

The YAP and TAZ paralogs are transcriptional co-activators recruited to target sites by TEAD proteins. Here, we show that YAP and TAZ are also recruited by JUNB (a member of the AP-1 family) and STAT3, key transcription factors that mediate an epigenetic switch linking inflammation to cellular transformation. YAP and TAZ directly interact with JUNB and STAT3 via a WW domain important for transformation, and they stimulate transcriptional activation by AP-1 proteins. JUNB, STAT3, and TEAD co-localize at virtually all YAP/TAZ target sites, yet many target sites only contain individual AP-1, TEAD, or STAT3 motifs. This observation and differences in relative crosslinking efficiencies of JUNB, TEAD, and STAT3 at YAP/TAZ target sites suggest that YAP/TAZ is recruited by different forms of an AP-1/STAT3/TEAD complex depending on the recruiting motif. The different classes of YAP/TAZ target sites are associated with largely non-overlapping genes with distinct functions. A small minority of target sites are YAP- or TAZ-specific, and they are associated with different sequence motifs and gene classes from shared YAP/TAZ target sites. Genes containing either the AP-1 or TEAD class of YAP/TAZ sites are associated with poor survival of breast cancer patients with the triple-negative form of the disease

YAP and TAZ are transcriptional co-activators of AP-1 proteins and STAT3 during breast cellular transformation [preprint]

The YAP and TAZ paralogues are transcriptional co-activators recruited to target sites, primarily by TEAD proteins. Here, we show that YAP and TAZ are also recruited by JUNB and STAT3, key factors that mediate an epigenetic switch linking inflammation to cellular transformation. YAP and TAZ directly interact with JUNB and STAT3 via a WW domain important for transformation, co-occupy many target sites in vivo via AP-1 and (to a lesser extent) STAT3 sequence motifs, and stimulate transcriptional activation by AP-1 proteins. A few target sites are YAP- or TAZ-specific, and they are associated with different sequence motifs and gene classes. YAP/TAZ, JUNB, and STAT3 directly regulate a common set of target genes that overlap, but are distinct from, those regulated by YAP/TAZ and TEADs. The set of genes regulated by YAP/TAZ, STAT3, and JUNB is associated with poor survival in breast cancer patients with the triple-negative form of the disease

PsyBench: a balanced and in-depth Psychological Chinese Evaluation Benchmark for Foundation Models

As Large Language Models (LLMs) are becoming prevalent in various fields, there is an urgent need for improved NLP benchmarks that encompass all the necessary knowledge of individual discipline. Many contemporary benchmarks for foundational models emphasize a broad range of subjects but often fall short in presenting all the critical subjects and encompassing necessary professional knowledge of them. This shortfall has led to skewed results, given that LLMs exhibit varying performance across different subjects and knowledge areas. To address this issue, we present psybench, the first comprehensive Chinese evaluation suite that covers all the necessary knowledge required for graduate entrance exams. psybench offers a deep evaluation of a model's strengths and weaknesses in psychology through multiple-choice questions. Our findings show significant differences in performance across different sections of a subject, highlighting the risk of skewed results when the knowledge in test sets is not balanced. Notably, only the ChatGPT model reaches an average accuracy above $70\%$, indicating that there is still plenty of room for improvement. We expect that psybench will help to conduct thorough evaluations of base models' strengths and weaknesses and assist in practical application in the field of psychology

Understanding Client Reactions in Online Mental Health Counseling

Communication success relies heavily on reading participants' reactions. Such feedback is especially important for mental health counselors, who must carefully consider the client's progress and adjust their approach accordingly. However, previous NLP research on counseling has mainly focused on studying counselors' intervention strategies rather than their clients' reactions to the intervention. This work aims to fill this gap by developing a theoretically grounded annotation framework that encompasses counselors' strategies and client reaction behaviors. The framework has been tested against a large-scale, high-quality text-based counseling dataset we collected over the past two years from an online welfare counseling platform. Our study shows how clients react to counselors' strategies, how such reactions affect the final counseling outcomes, and how counselors can adjust their strategies in response to these reactions. We also demonstrate that this study can help counselors automatically predict their clients' states.Comment: Accept to ACL 2023, oral. For code and data, see https://github.com/dll-wu/Client-Reac

Inhibition of ERK activation enhances the repair of double-stranded breaks via non-homologous end joining by increasing DNA-PKcs activation

AbstractNon-homologous end joining (NHEJ) is one of the major pathways that repairs double-stranded DNA breaks (DSBs). Activation of DNA-PK is required for NHEJ. However, the mechanism leading to DNA-PKcs activation remains incompletely understood. We provide evidence here that the MEK–ERK pathway plays a role in DNA-PKcs-mediated NHEJ. In comparison to the vehicle control (DMSO), etoposide (ETOP)-induced DSBs in MCF7 cells were more rapidly repaired in the presence of U0126, a specific MEK inhibitor, based on the reduction of γH2AX and tail moments. Additionally, U0126 increased reactivation of luciferase activity, which resulted from the repair of restriction enzyme-cleaved DSBs. Furthermore, while inhibition of ERK activation using the dominant-negative MEK1K97M accelerated the repair of DSBs, enforcing ERK activation with the constitutively active MEK1Q56P reduced DSB repair. In line with MEK activating ERK1 and ERK2 kinases, knockdown of either ERK1 or ERK2 increased DSB repair. Consistent with the activation of DNA-PKcs being required for NHEJ, we demonstrated that inhibition of ERK activation using U0126, MEK1K97M, and knockdown of ERK1 or ERK2 enhanced ETOP-induced activation of DNA-PKcs. Conversely, enforcing ERK activation by MEK1Q56P reduced ETOP-initiated DNA-PKcs activation. Taken together, we demonstrate that ERK reduces NHEJ-mediated repair of DSBs via attenuation of DNA-PKcs activation

PTEN inhibits BMI1 function independently of its phosphatase activity

<p>Abstract</p> <p>Background</p> <p><it>PTEN </it>is the second most mutated tumor suppressor gene other than p53. It suppresses tumorigenesis by dephosphorylating phosphatidylinositol (3,4,5)-triphosphate (<b>PIP3</b>) to phosphatidylinositol (4,5)-biphosphate (<b>PIP2</b>), thereby directly inhibiting phosphatidylinositol 3 kinase (<b>PI3K</b>)-mediated tumorigenic activities. Consistent with this model of action, cytosolic PTEN is recruited to the plasma membrane to dephosphorylate PIP3. While nuclear PTEN has been shown to suppress tumorigenesis by governing genome integrity, additional mechanisms may also contribute to nuclear PTEN-mediated tumor suppression. The nuclear protein BMI1 promotes stem cell self-renewal and tumorigenesis and PTEN inhibits these events, suggesting that PTEN may suppress BMI1 function.</p> <p>Results</p> <p>We investigated whether PTEN inhibits BMI1 function during prostate tumorigenesis. PTEN binds to BMI1 exclusively in the nucleus. This interaction does not require PTEN's phosphatase activity, as phosphatase-deficient PTEN mutants, PTEN/C124S (CS), PTEN/G129E (GE), and a C-terminal PTEN fragment (C-PTEN) excluding the catalytic domain, all associate with BMI1. Furthermore, the residues 186-286 of C-PTEN are sufficient for binding to BMI1. This interaction reduces BMI1's function. BMI1 enhances hTERT activity and reduces p16^INK4Aand p14^ARFexpression. These effects were attenuated by PTEN, PTEN(CS), PTEN(GE), and C-PTEN. Furthermore, knockdown of PTEN in DU145 cells increased hTERT promoter activity, which was reversed when BMI1 was concomitantly knocked-down, indicating that PTEN reduces hTERT promoter activity via inhibiting BMI1 function. Conversely, BMI1 reduces PTEN's ability to inhibit AKT activation, which can be attributed to its interaction with PTEN in the nucleus, making PTEN unavailable to dephosphorylate membrane-bound PIP3. Furthermore, BMI1 appears to co-localize with PTEN more frequently in clinical prostate tissue samples from patients diagnosed with PIN (prostatic intraepithelial neoplasia) and carcinoma compared to normal prostate epithelium. While PTEN co-localized with BMI1 in 2.4% of normal prostate epithelial cells, co-localization was observed in 37.6% and 18.5% of cells in PIN and carcinoma, respectively. Collectively, we demonstrate that PTEN inhibits BMI1 function via binding to BMI1 in a phosphatase independent manner.</p> <p>Conclusion</p> <p>We demonstrate that nuclear PTEN reduces BMI1 function independently of its phosphatase activity. It was recently observed that nuclear PTEN also suppresses tumorigenesis. Our results, therefore, provide a plausible mechanism by which nuclear PTEN prevents tumorigenesis.</p

Common reduction of the Raf kinase inhibitory protein in clear cell renal cell carcinoma

Despite the recent progress in our understanding of clear cell renal cell carcinomas (ccRCCs), the etiology of ccRCC remains unclear. We reported here a prevailing reduction of the raf kinase inhibitory protein (RKIP) in ccRCC. In our examination of more than 600 ccRCC patients by western blot and immunohistochemistry, RKIP was significantly reduced in 80% of tumors. Inhibition of RKIP transcription in ccRCC occurs to greater levels than VHL transcription based on the quantification analysis of their transcripts in six large datasets of DNA microarray available in Oncomine™ with the median rank of suppression being 582 and 2343 for RKIP and VHL, respectively. Collectively, the magnitude of RKIP reduction and the levels of its downregulation match those of VHL. Furthermore, RKIP displays tumor suppressing activity in ccRCC. While modulation of RKIP expression did not affect the proliferation of A498 and 786-0 ccRCC cells and neither their ability to form xenograft tumors in NOD/SCID mice, ectopic expression or knockdown of RKIP inhibited or enhanced A498 and 786-0 ccRCC cell invasion, respectively. This was associated with robust changes in vimentin expression, a marker of EMT. Taken together, we demonstrate here that downregulation of RKIP occurs frequently at a rate that reaches that of VHL, suggesting RKIP being a critical tumor suppressor for ccRCC. This is consistent with RKIP being a tumor suppressor for other cancers

Accurate and Efficient Evaluation of Chebyshev Tensor Product Surface

A Chebyshev tensor product surface is widely used in image analysis and numerical approximation. This article illustrates an accurate evaluation for the surface in form of Chebyshev tensor product. This algorithm is based on the application of error-free transformations to improve the traditional Clenshaw Chebyshev tensor product algorithm. Our error analysis shows that the error bound is u+Ou2×condP,x,y in contrast to classic scheme u×cond(P,x,y), where u is working precision and condP,x,y is a condition number of bivariate polynomial P(x,y), which means that the accuracy of the computed result is similar to that produced by classical approach with twice working precision. Numerical experiments verify that the proposed algorithm is stable and efficient