New gapped quantum phases for S=1 spin chain with D2h symmetry

We study different quantum phases in integer spin systems with on-site D2h=D2xZ2 and translation symmetry. We find four distinct non-trivial phases in S=1 spin chains despite they all have the same symmetry. All the four phases have gapped bulk excitations, doubly-degenerate end states and the doubly-degenerate entanglement spectrum. These non-trivial phases are examples of symmetry protected topological (SPT) phases introduced by Gu and Wen. One of the SPT phase correspond to the Haldane phase and the other three are new. These four SPT phases can be distinguished experimentally by their different response of the end states to weak external magnetic fields. According to Chen-Gu-Wen classification, the D2h symmetric spin chain can have totally 64 SPT phases that do not break any symmetry. Here we constructed seven nontrivial phases from the seven classes of nontrivial projective representations of D2h group. Four of these are found in S=1 spin chains and studied in this paper, and the other three may be realized in S=1 spin ladders or S=2 models.Comment: 15+ pages,5 figures, 9 table

MicroRNAs, an active and versatile group in cancers

microRNAs (miRNAs) are a class of non-coding RNAs that function as endogenous triggers of the RNA interference pathway. Studies have shown that thousands of human protein-coding genes are regulated by miRNAs, indicating that miRNAs are master regulators of many important biological processes, such as cancer development. miRNAs frequently have deregulated expression in many types of human cancers, and play critical roles in tumorigenesis, which functions either as tumor suppressors or as oncogenes. Recent studies have shown that miRNAs are highly related with cancer progression, including initiating, growth, apoptosis, invasion, and metastasis. Furthermore, miRNAs are shown to be responsible for the cancer-related inflammation, anti-cancer drug resistance, and regulation of cancer stem cells. Therefore, miRNAs have generated great interest as a novel strategy in cancer diagnosis and therapy. Here we review the versatile roles of miRNAs in cancers and their potential applications for diagnosis, prognosis, and treatment as biomarkers

Bs(d)−Bˉs(d)B_{s(d)}-\bar{B}_{s(d)} Mixing and Bs→μ+μ−B_s\to\mu^+\mu^- Decay in the NMSSM with the Flavour Expansion Theorem

In this paper, motivated by the observation that the Standard Model predictions are now above the experimental data for the mass difference $\Delta M_{s(d)}$, we perform a detailed study of $B_{s(d)}-\bar{B}_{s(d)}$ mixing and $B_s\to\mu^+\mu^-$ decay in the $\mathbb{Z}_3$-invariant NMSSM with non-minimal flavour violation, using the recently developed procedure based on the Flavour Expansion Theorem, with which one can perform a purely algebraic mass-insertion expansion of an amplitude written in the mass eigenstate basis without performing any diagrammatic calculations in the interaction/flavour basis. Specifically, we consider the finite orders of mass insertions for neutralinos but the general orders for squarks and charginos, under two sets of assumptions for the squark flavour structures (\textit{i.e.}, while the flavour-conserving off-diagonal element $\delta_{33}^\text{LR}$ is kept in both of these two sectors, only the flavour-violating off-diagonal elements $\delta_{23}^\text{LL}$ and $\delta_{i3}^\text{RR}$ ($i=1,2$) are kept in the \text{LL} and \text{RR} sectors, respectively). Our analytic results are then expressed directly in terms of the initial Lagrangian parameters in the interaction/flavour basis, making it easy to impose the experimental bounds on them. It is found numerically that the NMSSM effects with the above two assumptions for the squark flavour structures can accommodate the observed deviation for $\Delta M_{s(d)}$, while complying with the experimental constraints from the branching ratios of $B_s\to \mu^+ \mu^-$ and $B\to X_s\gamma$ decays.Comment: 48 pages, 7 figures, and 2 tables; More discussions and references added, final version to be published in JHE

Human Mitochondrial tRNA Mutations in Maternally Inherited Deafness

AbstractMutations in mitochondrial tRNA genes have been shown to be associated with maternally inherited syndromic and non-syndromic deafness. Among those, mutations such as tRNALeu(UUR)3243A>G associated with syndromic deafness are often present in heteroplasmy, and the non-syndromic deafness-associated tRNA mutations including tRNASer(UCN)7445A>G are often in homoplasmy or in high levels of heteroplasmy. These tRNA mutations are the primary factors underlying the development of hearing loss. However, other tRNA mutations such as tRNAThr15927G>A and tRNASer(UCN)7444G>A are insufficient to produce a deafness phenotype, but always act in synergy with the primary mitochondrial DNA mutations, and can modulate their phenotypic manifestation. These tRNA mutations may alter the structure and function of the corresponding mitochondrial tRNAs and cause failures in tRNAs metabolism. Thereby, the impairment of mitochondrial protein synthesis and subsequent defects in respiration caused by these tRNA mutations, results in mitochondrial dysfunctions and eventually leads to the development of hearing loss. Here, we summarized the deafness-associated mitochondrial tRNA mutations and discussed the pathophysiology of these mitochondrial tRNA mutations, and we hope these data will provide a foundation for the early diagnosis, management, and treatment of maternally inherited deafness

Clinicopathological and molecular markers associated with prognosis and treatment effectiveness of endometrial stromal sarcoma: a retrospective study in China

PURPOSE: To evaluate the clinicopathological and immunophenotypic characteristics of endometrial stromal sarcoma (ESS) in China. METHODS AND MATERIALS: Seventy-two consecutive ESS cases treated between 1995 and 2009 were retrospectively reviewed. RESULTS: Sixty-three patients received surgical treatment. Forty-one patients underwent pelvic lymphadenectomy. In paraffin-embedded specimens, expression of the following molecular markers was detected: CD10 (27/36), vimentin (37/38), HHF35 (3/32), S-100 (0/25), desmin (2/29), CD117 (0/23), CD34 (2/24), alpha-inhibin (0/17), CK (1/34), CD99 (4/9), smooth muscle actin (5/25), EMA (0/7), estrogen receptor (13/16) and progesterone receptor (13/16). CD10 and vimentin were expressed more frequently in these specimens. Tumor classification, CD10 and surgical procedures were significantly associated with disease-free survival (DFS). Surgical procedures were significantly associated with overall survival (OS). Tumor stage (P = 0.024) and surgical procedure (P = 0.042) were found to be significant independent prognostic factors for DFS. No complete or partial response was observed among patients who received radiotherapy or chemotherapy. CONCLUSIONS: Our results indicate that total hysterectomy with bilateral salpingo-oophorectomy followed by pelvic lymphadenectomy is associated with an improved treatment outcome. CD10-negative expression may contribute to the malignant characteristics and recurrence associated with ESS

AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration

Diffusion models are emerging expressive generative models, in which a large number of time steps (inference steps) are required for a single image generation. To accelerate such tedious process, reducing steps uniformly is considered as an undisputed principle of diffusion models. We consider that such a uniform assumption is not the optimal solution in practice; i.e., we can find different optimal time steps for different models. Therefore, we propose to search the optimal time steps sequence and compressed model architecture in a unified framework to achieve effective image generation for diffusion models without any further training. Specifically, we first design a unified search space that consists of all possible time steps and various architectures. Then, a two stage evolutionary algorithm is introduced to find the optimal solution in the designed search space. To further accelerate the search process, we employ FID score between generated and real samples to estimate the performance of the sampled examples. As a result, the proposed method is (i).training-free, obtaining the optimal time steps and model architecture without any training process; (ii). orthogonal to most advanced diffusion samplers and can be integrated to gain better sample quality. (iii). generalized, where the searched time steps and architectures can be directly applied on different diffusion models with the same guidance scale. Experimental results show that our method achieves excellent performance by using only a few time steps, e.g. 17.86 FID score on ImageNet 64 $\times$ 64 with only four steps, compared to 138.66 with DDIM. The code is available at https://github.com/lilijiangg/AutoDiffusion