Effects of a novel recombinant somatostatin DNA vaccination on rat fertility and offspring growth

In this study, we investigated the immune effects of a novel somatostatin (SS) DNA vaccine—pVAX- asd-GS/2SS (pGS/2SS), administrated with intramuscular (IM) and subcutaneous (SC) two delivery routes on female rat fertility and offspring growth. Results show that this pGS/2SS DNA vaccine could induce effective  anti-SS immune response in rats (IM group and SC group). The antibody peak of female rats in IM group  occurred later than that in SC group (12th week vs. 10th week), but higher than that in SC group  (OD=1.122±0.273 vs. OD=0.614±0.183). Immunized groups had higher pregnancy rate, litter size, birth  weight of pup and weight gain of pup than the control group (P<0.05). Compared to SC immunization, IM  immunization had better improvement in the pregnancy rate of dam and the weight gain of pup (P<0.05).  However, in litter sizes and birth weight of pups, SC immunization was better than IM immunization. In  conclusion, pGS/2SS as a powerful DNA vaccine improves the fertility of female rats and the growth of pups.Key words: Somatostatin, DNA vaccine, rat, fertility, pup growth

Proteomic profiling and biomarker discovery for predicting the response to PD-1 inhibitor immunotherapy in gastric cancer patients

Background: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment; however, a significant proportion of gastric cancer (GC) patients do not respond to this therapy. Consequently, there is an urgent need to elucidate the mechanisms underlying resistance to ICIs and identify robust biomarkers capable of predicting the response to ICIs at treatment initiation.Methods: In this study, we collected GC tissues from 28 patients prior to the administration of anti-programmed death 1 (PD-1) immunotherapy and conducted protein quantification using high-resolution mass spectrometry (MS). Subsequently, we analyzed differences in protein expression, pathways, and the tumor microenvironment (TME) between responders and non-responders. Furthermore, we explored the potential of these differences as predictive indicators. Finally, using machine learning algorithms, we screened for biomarkers and constructed a predictive model.Results: Our proteomics-based analysis revealed that low activity in the complement and coagulation cascades pathway (CCCP) and a high abundance of activated CD8 T cells are positive signals corresponding to ICIs. By using machine learning, we successfully identified a set of 10 protein biomarkers, and the constructed model demonstrated excellent performance in predicting the response in an independent validation set (N = 14; area under the curve [AUC] = 0.959).Conclusion: In summary, our proteomic analyses unveiled unique potential biomarkers for predicting the response to PD-1 inhibitor immunotherapy in GC patients, which may provide the impetus for precision immunotherapy

Radix Rehmanniae Extract Ameliorates Experimental Autoimmune Encephalomyelitis by Suppressing Macrophage-Derived Nitrative Damage

Multiple sclerosis (MS) is a neuroinflammatory disease in central nervous system (CNS) without effective treatment or medication yet. With high prevalence of MS patients worldwide and poor therapeutic outcome, seeking novel therapeutic strategy for MS is timely important. Radix Rehmanniae (RR), a typical Chinese Medicinal herb, has been used for neuroinflammatory diseases in Traditional Chinese Medicine for centuries. However, scientific evidence and underlying mechanisms of RR for MS are unclear. In this study, we tested the hypothesis that RR could attenuate the progress and severity of MS via suppressing macrophage-derived nitrative damage and inflammation by using experimental autoimmune encephalomyelitis (EAE) model for mimicking MS pathology. The results showed the RR treatment effectively ameliorated clinical disease severity, inhibited inflammation/demyelination in spinal cord, and alleviated CNS infiltration of encephalitogenic T cells and activated macrophages. Meanwhile, RR possessed bioactivities of scavenging ONOO− and reducing the expression of iNOS and NADPH oxidases in the spinal cords of the EAE mice. Furthermore, RR treatment suppressed nuclear factor-κB (NF-κB) signaling pathway in the splenocytes of EAE mice. The in vitro experiments on macrophages and neuronal cells exerted consistent results with the in vivo animal experiments. Taken together, we conclude that Radix Rehmanniae extract has therapeutic values for ameliorating EAE/MS pathological process and disease severity and its underlying mechanisms are associated with anti-inflammation and inhibiting macrophage-derived nitrative damages. Further study could yield novel promising therapeutic agent for multiple sclerosis

Validating quantum-supremacy experiments with exact and fast tensor network contraction

The quantum circuits that declare quantum supremacy, such as Google Sycamore [Nature \textbf{574}, 505 (2019)], raises a paradox in building reliable result references. While simulation on traditional computers seems the sole way to provide reliable verification, the required run time is doomed with an exponentially-increasing compute complexity. To find a way to validate current ``quantum-supremacy" circuits with more than $50$ qubits, we propose a simulation method that exploits the ``classical advantage" (the inherent ``store-and-compute" operation mode of von Neumann machines) of current supercomputers, and computes uncorrelated amplitudes of a random quantum circuit with an optimal reuse of the intermediate results and a minimal memory overhead throughout the process. Such a reuse strategy reduces the original linear scaling of the total compute cost against the number of amplitudes to a sublinear pattern, with greater reduction for more amplitudes. Based on a well-optimized implementation of this method on a new-generation Sunway supercomputer, we directly verify Sycamore by computing three million exact amplitudes for the experimentally generated bitstrings, obtaining an XEB fidelity of $0.191\%$ which closely matches the estimated value of $0.224\%$. Our computation scales up to $41,932,800$ cores with a sustained single-precision performance of $84.8$ Pflops, which is accomplished within $8.5$ days. Our method has a far-reaching impact in solving quantum many-body problems, statistical problems as well as combinatorial optimization problems where one often needs to contract many tensor networks which share a significant portion of tensors in common.Comment: 7 pages, 4 figures, comments are welcome

The relationship between atrial fibrillation and NLRP3 inflammasome: a gut microbiota perspective

Atrial fibrillation (AF) is a common clinical arrhythmia whose pathogenesis has not been fully elucidated, and the inflammatory response plays an important role in the development of AF. The inflammasome is an important component of innate immunity and is involved in a variety of pathophysiologic processes. The NLRP3 inflammasome is by far the best studied and validated inflammasome that recognizes multiple pathogens through pattern recognition receptors of innate immunity and mediates inflammatory responses through activation of Caspase-1. Several studies have shown that NLRP3 inflammasome activation contributes to the onset and development of AF. Ecological dysregulation of the gut microbiota has been associated with the development of AF, and some evidence suggests that gut microbiota components, functional byproducts, or metabolites may induce or exacerbate the development of AF by directly or indirectly modulating the NLRP3 inflammasome. In this review, we report on the interconnection of NLRP3 inflammasomes and gut microbiota and whether this association is related to the onset and persistence of AF. We discuss the potential value of pharmacological and dietary induction in the management of AF in the context of the association between the NLRP3 inflammasome and gut microbiota. It is hoped that this review will lead to new therapeutic targets for the future management of AF

Validation of the plasma-wall self-organization model for density limit in ECRH-assisted start-up of Ohmic discharges on J-TEXT

A recently developed plasma-wall self-organization (PWSO) model predicts a significantly enhanced density limit, which may be attainable in tokamaks with ECRH-assisted ohmic startup and sufficiently high initial neutral density. Experiments have been conducted on J-TEXT to validate such a density limit scenario based on this model. Experimental results demonstrate that increasing the pre-filled gas pressure or ECRH power during the startup phase can effectively enhance plasma purity and raise the density limit at the flat-top. Despite the dominant carbon fraction in the wall material, some discharges approach the edge of the density-free regime of the 1D model of PWSO.Comment: 17 pages, 8 figure

Orientation bias of optically selected galaxy clusters and its impact on stacked weak-lensing analyses

Weak-lensing measurements of the averaged shear profiles of galaxy clusters binned by some proxy for cluster mass are commonly converted to cluster mass estimates under the assumption that these cluster stacks have spherical symmetry. In this paper, we test whether this assumption holds for optically selected clusters binned by estimated optical richness. Using mock catalogues created from N-body simulations populated realistically with galaxies, we ran a suite of optical cluster finders and estimated their optical richness. We binned galaxy clusters by true cluster mass and estimated optical richness and measure the ellipticity of these stacks. We find that the processes of optical cluster selection and richness estimation are biased, leading to stacked structures that are elongated along the line of sight. We show that weak-lensing alone cannot measure the size of this orientation bias. Weak-lensing masses of stacked optically selected clusters are overestimated by up to 3–6 per cent when clusters can be uniquely associated with haloes. This effect is large enough to lead to significant biases in the cosmological parameters derived from large surveys like the Dark Energy Survey, if not calibrated via simulations or fitted simultaneously. This bias probably also contributes to the observed discrepancy between the observed and predicted Sunyaev–Zel’dovich signal of optically selected clusters

Editor\u27s Notes, Chiba Medical Journal 90-1

Multiple sequence alignment of deduced amino acid sequences of 25 wheat annexin genes with rice annexin OsAnn2 (Os05g31760) obtained by ClustalW. (PDF 212 kb

Efficient and tunable liquid crystal random laser based on plasmonic-enhanced FRET

Random lasers (RLs), which possess peculiar advantages (e.g., emission and coherence tunable) over traditional lasers with optical resonators, have witnessed rapid development in the past decades. However, it is still a challenge to tune the lasing peak of an RL over a wide range. Here, a temperature-dependent Förster resonance energy transfer (FRET) RL is demonstrated in pyrromethene 597 (PM597, “donor”) and Nile blue (NB, “acceptor”) doped chiral liquid crystals. By changing the temperature that drives the liquid crystal bandgap shift, our RL device exhibits a lasing output change from 560 nm (yellow) to 700 nm (red). While the intrinsic FRET efficiency between PM597 and NB is relatively low, the red lasing is weak. By introducing gold nanorods (GNRs) into these RL devices and utilizing GNRs’ localized surface plasmon resonance (LSPR) effect, the efficiency of FRET transfer is increased by 68.9%, thereby reducing the threshold of the RL devices. By tuning the longitudinal LSPR to match the emission wavelength of NB, the best 200-fold lasing intensity enhancement is recorded. Our findings open a pathway toward realizing LSPR-enhanced FRET tunable RLs and broaden the range of their possible exploration in photonics research and technologies

Research progress and applications of epigenetic biomarkers in cancer

Epigenetic changes are heritable changes in gene expression without changes in the nucleotide sequence of genes. Epigenetic changes play an important role in the development of cancer and in the process of malignancy metastasis. Previous studies have shown that abnormal epigenetic changes can be used as biomarkers for disease status and disease prediction. The reversibility and controllability of epigenetic modification changes also provide new strategies for early disease prevention and treatment. In addition, corresponding drug development has also reached the clinical stage. In this paper, we will discuss the recent progress and application status of tumor epigenetic biomarkers from three perspectives: DNA methylation, non-coding RNA, and histone modification, in order to provide new opportunities for additional tumor research and applications