High performance entanglement-assisted quantum LDPC codes need little entanglement

Though the entanglement-assisted formalism provides a universal connection between a classical linear code and an entanglement-assisted quantum error-correcting code (EAQECC), the issue of maintaining large amount of pure maximally entangled states in constructing EAQECCs is a practical obstacle to its use. It is also conjectured that the power of entanglement-assisted formalism to convert those good classical codes comes from massive consumption of maximally entangled states. We show that the above conjecture is wrong by providing families of EAQECCs with an entanglement consumption rate that diminishes linearly as a function of the code length. Notably, two families of EAQECCs constructed in the paper require only one copy of maximally entangled state no matter how large the code length is. These families of EAQECCs that are constructed from classical finite geometric LDPC codes perform very well according to our numerical simulations. Our work indicates that EAQECCs are not only theoretically interesting, but also physically implementable. Finally, these high performance entanglement-assisted LDPC codes with low entanglement consumption rates allow one to construct high-performance standard QECCs with very similar parameters.Comment: 8 pages, 5 figures. Published versio

PGT-Net: Progressive Guided Multi-task Neural Network for Small-area Wet Fingerprint Denoising and Recognition

Fingerprint recognition on mobile devices is an important method for identity verification. However, real fingerprints usually contain sweat and moisture which leads to poor recognition performance. In addition, for rolling out slimmer and thinner phones, technology companies reduce the size of recognition sensors by embedding them with the power button. Therefore, the limited size of fingerprint data also increases the difficulty of recognition. Denoising the small-area wet fingerprint images to clean ones becomes crucial to improve recognition performance. In this paper, we propose an end-to-end trainable progressive guided multi-task neural network (PGT-Net). The PGT-Net includes a shared stage and specific multi-task stages, enabling the network to train binary and non-binary fingerprints sequentially. The binary information is regarded as guidance for output enhancement which is enriched with the ridge and valley details. Moreover, a novel residual scaling mechanism is introduced to stabilize the training process. Experiment results on the FW9395 and FT-lightnoised dataset provided by FocalTech shows that PGT-Net has promising performance on the wet-fingerprint denoising and significantly improves the fingerprint recognition rate (FRR). On the FT-lightnoised dataset, the FRR of fingerprint recognition can be declined from 17.75% to 4.47%. On the FW9395 dataset, the FRR of fingerprint recognition can be declined from 9.45% to 1.09%

TOXICOLOGICAL EVALUATION OF LEPISTA NUDA (BULL. EX FR.) COOKE MYCELIUM PRODUCED BY AN IN VITRO CULTURE METHODOLOGY

Objective: Considering the interest in L. nuda as a source of ingredients for the development of functional food and nutraceuticals has increased, the objective of this study was to evaluate its general toxicity and possible genotoxic effects in rats to assess its safety.Methods: This study evaluated the safety of L. nuda mycelium by using genotoxicity assays (reverse mutation, chromosomal aberration, and micronuclei tests) and a short-term toxicity test.Results: Our results have indicated that L. nuda mycelium did not significantly increase the number of revertant colonies and chromosomal aberration in both in vitro assays. Furthermore, it did not induce any increase in micronuclei formation in mouse bone marrow.Conclusion: In summary, no mutagenic effects and no evidence of systemic toxicity were found in this safety assessment, and the use of L. nuda mycelia is safe at a dose of 3 g/kg body weight in S-D rats. Using a safety factor of 100, the calculated acceptable daily intake in humans is 30 mg/kg body weight/d

SOC Design for Speech-to-Speech Translation

Non

Estimating systemic fibrosis by combining galectin-3 and ST2 provides powerful risk stratification value for patients after acute decompensated heart failure

Background: Two fibrosis biomarkers, galectin-3 (Gal-3) and suppression of tumorigenicity 2 (ST2), provide prognostic value additive to natriuretic peptides and traditional risk factors in patients with heart failure (HF). However, it is to be investigated whether their combined measurement before discharge provides incremental risk stratification for patients after acute HF. Methods: A total of 344 patients with acute HF were analyzed with Gal-3, and ST2 measured. Patients were prospectively followed for 3.7 ± 1.3 years for deaths, and composite events (death/HF-related re-hospitalizations). Results: The levels of Gal-3 and ST2 were only slightly related (r = 0.20, p < 0.001). The medians of Gal-3 and ST2 were 18 ng/mL and 32.4 ng/mL, respectively. These biomarkers compensated each other and characterized patients with different risk factors. According to the cutoff at median values, patients were separated into four subgroups based on high and low Gal-3 (HG and LG, respectively) and ST2 levels (HS and LS, respectively). Kaplan-Meier survival curves showed that HGHS powerfully identified patients at risk of mortality (Log rank = 21.27, p < 0.001). In multivariable analysis, combined log(Gal-3) and log(ST2) was an in­dependent predictor. For composite events, Kaplan-Meier survival curves showed a lower event- -free survival rate in the HGHS subgroup compared to others (Log rank = 34.62, p < 0.001; HGHS vs. HGLS, Log rank = 4.00, p = 0.045). In multivariable analysis, combined log(Gal-3) and log(ST2) was also an independent predictor. Conclusions: Combination of biomarkers involving heterogeneous fibrosis pathways may identify patients with high systemic fibrosis, providing powerful risk stratification value

A Gell-Mann & Low Theorem Perspective on Quantum Computing: New Paradigm for Designing Quantum Algorithm

The Gell-Mann & Low theorem is a cornerstone of Quantum Field Theory (QFT) and condensed matter physics, and many-body perturbation theory is a foundational tool for treating interactions. However, their integration into quantum algorithms remains a largely unexplored area of research, with current quantum simulation algorithms predominantly operating in the Schr\"odinger picture, leaving the potential of the interaction picture largely untapped. Our Variational Interaction-Picture S-matrix Ansatz (VIPSA) now fills this gap, specifically in the context of the Fermi-Hubbard model -- a canonical paradigm in condensed matter physics which is intricately connected to phenomena such as high-temperature superconductivity and Mott insulator transitions. This work offers a new conceptual perspective for variational quantum computing based upon the Gell-Mann & Low theorem. We achieve this by employing an innovative mathematical technique to explicitly unfold the normalized S-matrix, thereby enabling the systematic reconstruction of the Dyson series on a quantum computer, order by order. This method stands in contrast to the conventional reliance on Trotter expansion for adiabatic time evolution, marking a conceptual shift towards more sophisticated quantum algorithmic design. We leverage the strengths of the recently developed ADAPT-VQE algorithm, tailoring it to reconstruct perturbative terms effectively. Our simulations indicate that this method not only successfully recovers the Dyson series but also exhibits robust and stable convergence. We believe that our approach shows great promise in generalizing to more complex scenarios without increasing algorithmic complexity.Comment: 12 pages, 10 figure

Site-directed in vitro immunization leads to a complete human monoclonal IgG4λ that binds specifically to the CDR2 region of CTLA-4 (CD152) without interfering the engagement of natural ligands

<p>Abstract</p> <p>Background</p> <p>The ability to acquire fully human monoclonal antibodies (mAbs) with pre-defined specificities is critical to the development of molecular tags for the analysis of receptor function in addition to promising immunotherapeutics. Yet most of the arriving affinity maturated and complete human immunoglobulin G (IgG) molecules, which are actually derived from single human B cells, have not widely been used to study the conserved self antigens (Ags) such as CD152 (cytotoxic T lymphocyte antigen-4, CTLA-4) because proper hosts are lacking.</p> <p>Results</p> <p>Here we developed an optimized protocol for site-directed <it>in vitro </it>immunizing peripheral blood mononuclear cells (PBMC) by using a selected epitope of human CD152, an essential receptor involved in down-regulation of T cell activation. The resultant stable trioma cell lines constantly produce anti-CD152 mAb (γ4λhuCD152), which contains variable (V) regions of the heavy chain and the light chain derived from the VH3 and Vλ human germline genes, respectively, and yet displays an unusual IgG4 isotype. Interestingly, γ4λhuCD152 has a basic pI not commonly found in myeloid monoclonal IgG4λs as revealed by the isoelectric focusing (IEF) analysis. Furthermore, γ4λhuCD152 binds specifically, with nanomolar affinity, to an extracellular constituency encompassing the putative second complementarity determining region (CDR2) of CD152, whereby it can react to activated CD3⁺cells.</p> <p>Conclusion</p> <p>In a context of specific cell depletion and conditioned medium,<it>in vitro </it>induction of human Abs against a conserved self Ag was successfully acquired and a relatively basic mAb, γ4λhuCD152, with high affinity to CDR2 of CD152 was thus obtained. Application of such a human IgG4λ mAb with designated CDR2 specificity may impact upon and prefer for CD152 labeling both <it>in situ </it>and <it>ex situ</it>, as it does not affect the binding of endogenous B7 ligands and can localize into the confined immunological synapse which may otherwise prevent the access of whole IgG1 molecules.</p

A protein interaction based model for schizophrenia study

<p>Abstract</p> <p>Background</p> <p>Schizophrenia is a complex disease with multiple factors contributing to its pathogenesis. In addition to environmental factors, genetic factors may also increase susceptibility. In other words, schizophrenia is a highly heritable disease. Some candidate genes have been deduced on the basis of their known function with others found on the basis of chromosomal location. Individuals with multiple candidate genes may have increased risk. However it is not clear what kind of gene combinations may produce the disease phenotype. Their collective effect remains to be studied.</p> <p>Results</p> <p>Most pathways except metabolic pathways are rich in protein-protein interactions (PPIs). Thus, the PPI network contains pathway information, even though the upstream-downstream relation of PPI is yet to be explored. Here we have constructed a PPI sub-network by extracting the nearest neighbour of the 36 reported candidate genes described in the literature. Although these candidate genes were discovered by different approaches, most of the proteins formed a cluster. Two major protein interaction modules were identified on the basis of the pairwise distance among the proteins in this sub-network. The large and small clusters might play roles in synaptic transmission and signal transduction, respectively, based on gene ontology annotation. The protein interactions in the synaptic transmission cluster were used to explain the interaction between the NRG1 and CACNG2 genes, which was found by both linkage and association studies. This working hypothesis is supported by the co-expression analysis based on public microarray gene expression.</p> <p>Conclusion</p> <p>On the basis of the protein interaction network, it appears that the NRG1-triggered NMDAR protein internalization and the CACNG2 mediated AMPA receptor recruiting may act together in the glutamatergic signalling process. Since both the NMDA and AMPA receptors are calcium channels, this process may regulate the influx of Ca²⁺. Reducing the cation influx might be one of the disease mechanisms for schizophrenia. This PPI network analysis approach combined with the support from co-expression analysis may provide an efficient way to propose pathogenetic mechanisms for various highly heritable diseases.</p

Degraded Impairment of Emotion Recognition in Parkinson&apos;s Disease Extends from Negative to Positive Emotions

Because of dopaminergic neurodegeneration, patients with Parkinson&apos;s disease (PD) show impairment in the recognition of negative facial expressions. In the present study, we aimed to determine whether PD patients with more advanced motor problems would show a much greater deficit in recognition of emotional facial expressions than a control group and whether impairment of emotion recognition would extend to positive emotions. Twenty-nine PD patients and 29 age-matched healthy controls were recruited. Participants were asked to discriminate emotions in Experiment 1 and identify gender in Experiment 2. In Experiment 1, PD patients demonstrated a recognition deficit for negative (sadness and anger) and positive faces. Further analysis showed that only PD patients with high motor dysfunction performed poorly in recognition of happy faces. In Experiment 2, PD patients showed an intact ability for gender identification, and the results eliminated possible abilities in the functions measured in Experiment 2 as alternative explanations for the results of Experiment 1. We concluded that patients&apos; ability to recognize emotions deteriorated as the disease progressed. Recognition of negative emotions was impaired first, and then the impairment extended to positive emotions

Puerarin inhibited oxidative stress and alleviated cerebral ischemia-reperfusion injury through PI3K/Akt/Nrf2 signaling pathway

Introduction: Puerarin (PUE) is a natural compound isolated from Puerariae Lobatae Radix, which has a neuroprotective effect on IS. We explored the therapeutic effect and underlying mechanism of PUE on cerebral I/R injury by inhibiting oxidative stress related to the PI3K/Akt/Nrf2 pathway in vitro and in vivo. Methods: The middle cerebral artery occlusion and reperfusion (MCAO/R) rats and oxygen-glucose deprivation and reperfusion (OGD/R) were selected as the models, respectively. The therapeutic effect of PUE was observed using triphenyl tetrazolium and hematoxylin-eosin staining. Tunel-NeuN staining and Nissl staining to quantify hippocampal apoptosis. The reactive oxygen species (ROS) level was detected by flow cytometry and immunofluorescence. Biochemical method to detect oxidative stress levels. The protein expression related to PI3K/ Akt/Nrf2 pathway was detected by using Western blotting. Finally, coimmunoprecipitation was used to study the molecular interaction between Keap1 and Nrf2. Results: In vivo and vitro studies showed that PUE improved neurological deficits in rats, as well as decreased oxidative stress. Immunofluorescence and flow cytometry indicated that the release of ROS can be inhibited by PUE. In addition, the Western blotting results showed that PUE promoted the phosphorylation of PI3K and Akt, and enabled Nrf2 to enter the nucleus, which further activated the expression of downstream antioxidant enzymes such as HO1. The combination of PUE with PI3K inhibitor LY294002 reversed these results. Finally, co-immunoprecipitation results showed that PUE promoted Nrf2-Keap1 complex dissociation. Discussion: Taken together, PUE can activate Nrf2 via PI3K/Akt and promote downstream antioxidant enzyme expression, which could further ameliorate oxidative stress, against I/R-induced Neuron injury