G2T: A simple but versatile framework for topic modeling based on pretrained language model and community detection

It has been reported that clustering-based topic models, which cluster high-quality sentence embeddings with an appropriate word selection method, can generate better topics than generative probabilistic topic models. However, these approaches suffer from the inability to select appropriate parameters and incomplete models that overlook the quantitative relation between words with topics and topics with text. To solve these issues, we propose graph to topic (G2T), a simple but effective framework for topic modelling. The framework is composed of four modules. First, document representation is acquired using pretrained language models. Second, a semantic graph is constructed according to the similarity between document representations. Third, communities in document semantic graphs are identified, and the relationship between topics and documents is quantified accordingly. Fourth, the word--topic distribution is computed based on a variant of TFIDF. Automatic evaluation suggests that G2T achieved state-of-the-art performance on both English and Chinese documents with different lengths. Human judgements demonstrate that G2T can produce topics with better interpretability and coverage than baselines. In addition, G2T can not only determine the topic number automatically but also give the probabilistic distribution of words in topics and topics in documents. Finally, G2T is publicly available, and the distillation experiments provide instruction on how it works

MicroRNA-542 suppressed the proliferation of human glioma cells by targeting talin-2 (TLN2)

Purpose: To investigate the effect of miR-542 in the development of human glioma. Methods: The expressions of miR-542 and TLN2 in glioma cells and normal human astrocytes were determined using qRT-PCR, while MTT and colony formation assays were used to determine cell proliferation. Western blotting was used to determine protein expression. Results: It was revealed that miR-542 was significantly downregulated in glioma cells. Overexpression of miR-542 inhibited the proliferation and clonogenicity of glioma cells via induction of apoptosis. The percentage of apoptotic U87 cells increased from 5.32 in control to 26.76 upon miR-542 overexpression. Moreover, TLN2 was identified as the functional regulatory target of miR542 in glioma. The expression of TLN2 was markedly upregulated in human glioma cells. However, overexpression of miR-542 suppressed TLN2 expression. Silencing of TLN2 mimicked the tumor-suppressive effects of miR-542 in glioma cells, but this effect was blocked by TLN2 over-expression. Conclusion: These results suggest that miR-542 exerted glioma-suppressive effect, with TLN2 as its functional regulatory target. Keywords: Glioma; Proliferation; Micro-RNA; Tumorigenesis; MiR-542; Apoptosis; Prognosis; talin-2; Oncogen

Unifying Presampling via Concentration Bounds

Auxiliary-input (AI) idealized models, such as auxiliary-input random oracle model (AI-ROM) and auxiliary-input random permutation model (AI-PRM), play a critical role in assessing non-uniform security of symmetric key and hash function constructions. However, obtaining security bounds in these models is often much more challenging. The presampling technique, initially introduced by Unruh (CRYPTO\u27 07) for AI-ROM and later exported to several other models by Coretti et al. (EUROCRYPT\u27 18). It generically reduces security proofs in AI models to much simpler bit-fixing (BF) models, making it much easier to obtain concrete bounds in AI models. As a result, the presampling technique has leads to simpler proofs for many known bounds (e.g. one-way functions), and has been applied to many settings where the compression technique appears intractable (e.g., Merkle-Damgard hashing). We study the possibility of leveraging the presampling technique to the quantum world. To this end, * We show that such leveraging will resolve a major open problem in quantum computing, which is closely related to the famous Aaronson-Ambainis conjecture (ITCS\u27 11). * Faced with this barrier, we give a new but equivalent bit-fixing model and a simple proof of presampling techniques for arbitrary oracle distribution in the classical setting, including AI-ROM and AI-PRM. Our theorem matches the best-known security loss and unifies previous presampling techniques by Coretti et al. (EUROCRYPT\u27 18) and Coretti et al. (CRYPTO\u27 18). * Finally, we leverage our new classical presampling techniques to a novel ``quantum bit-fixing\u27\u27 version of presampling. It matches the optimal security loss of the classical presampling. Using our techniques, we give the first post-quantum non-uniform security for salted Merkle-Damgard hash functions and reprove the tight non-uniform security for function inversion by Chung et al. (FOCS\u27 20)

Developmental iodine deficiency and hypothyroidism impair neural development in rat hippocampus: involvement of doublecortin and NCAM-180

<p>Abstract</p> <p>Background</p> <p>Developmental iodine deficiency results in inadequate thyroid hormone (TH), which damages the hippocampus. Here, we explored the roles of hippocampal doublecortin and neural cell adhesion molecule (NCAM)-180 in developmental iodine deficiency and hypothyroidism.</p> <p>Methods</p> <p>Two developmental rat models were established with either an iodine-deficient diet, or propylthiouracil (PTU)-adulterated water (5 ppm or 15 ppm) to impair thyroid function, in pregnant rats from gestational day 6 until postnatal day (PN) 28. Silver-stained neurons and protein levels of doublecortin and NCAM-180 in several hippocampal subregions were assessed on PN14, PN21, PN28, and PN42.</p> <p>Results</p> <p>The results show that nerve fibers in iodine-deficient and 15 ppm PTU-treated rats were injured on PN28 and PN42. Downregulation of doublecortin and upregulation of NCAM-180 were observed in iodine-deficient and 15 ppm PTU-treated rats from PN14 on. These alterations were irreversible by the restoration of serum TH concentrations on PN42.</p> <p>Conclusion</p> <p>Developmental iodine deficiency and hypothyroidism impair the expression of doublecortin and NCAM-180, leading to nerve fiber malfunction and thus impairments in hippocampal development.</p