Gaussian variational method to Fermi Hubbard model in one and two dimensions

The study of ground-state properties of the Fermi-Hubbard model is a long-lasting task in the research of strongly correlated systems. Owing to the exponentially growing complexity of the system, a quantitative analysis usually demands high computational cost and is restricted to small samples, especially in two or higher dimensions. Here, we introduce a variational method in the frame of fermionic Gaussian states, and obtain the ground states of one- and two-dimensional attractive Hubbard models via imaginary-time evolution. We calculate the total energy and benchmark the results in a wide range of interaction strength and filling factor with those obtained via exact two-body results, the density matrix renormalization group based on matrix product states (MPS), and projector Quantum Monte Carlo (QMC) method. For both 1D and 2D cases, the Gaussian variational method presents accurate results for total energy with a maximum systematic error ~4% in the intermediate interaction region. The accuracy of these results has negligible dependence on the system size. We further calculate the double occupancy and find excellent agreement with MPS and QMC, as well as the experimental results of cold quantum gases in optical lattices. The results suggest that the Gaussian pairing state is a good approximation to the ground states of attractive Hubbard model, in particular in the strong and weak coupling limits. Moreover, we generalize the method to the attractive Hubbard model with a finite spin-polarization, which can be mapped to the repulsive interaction case via particle-hole transformation, and obtain accurate results of ground state energy and double occupancy. Our work demonstrates the ability of the Gaussian variational method to extract ground state properties of strongly correlated many-body systems with negligible computational cost, especially of large size and in higher dimensions.Comment: 9 pages, 6 figure

Characteristics of Pollen from Transgenic Lines of Apple Carrying the Exogenous CpTI Gene

AbstractIt is fundamental for gene transformation and ecosystem hazard evaluation to study the pollen characteristics of transgenic plants. In this research, the characteristics of pollen from 7- or 8-year-old transgenic apple plants carrying an exogenous CpTI gene were analyzed. The results showed that there was no significant difference in terms of size, morphology, or exine ornamentation between the pollen of the transgenic plants and the non-transgenic control. However, the transgenic plants had more abnormal pollen grains. Of the 13 transgenic lines tested, 12 had a significantly lower amount of pollen and six exhibited a significantly lower germination rate when cultured in vitro. The pollen viability of three transgenic lines was determined, with two showing significantly lower viability than the control. The transgenic Gala apple pollen grains germinated normally via controlled pollination on Fuji apple stigmas. However, the pollen tubes extended relatively slowly during the middle and late development stages, and another 8h were needed to reach the ovules compared with the control. The gibberellic acid concentration in transgenic Gala apple flowers was lower than in the non-transgenic control during all development stages tested. The abscisic acid concentration in the transgenic flowers was lower during the pink stage, and higher during the ball and fully open stages. Microscopic observation of the anther structure showed no difference. The tapetum of the pollen sac wall in transgenic plants decomposed late and affected pollen grain development, which could be one of the reasons for the lower number of pollen grains and poor viability in the transgenic plants

Mutations in TUBB8 and Human Oocyte Meiotic Arrest

BACKGROUND Human reproduction depends on the fusion of a mature oocyte with a sperm cell to form a fertilized egg. The genetic events that lead to the arrest of human oocyte maturation are unknown. METHODS We sequenced the exomes of five members of a four-generation family, three of whom had infertility due to oocyte meiosis I arrest. We performed Sanger sequencing of a candidate gene, TUBB8, in DNA samples from these members, additional family members, and members of 23 other affected families. The expression of TUBB8 and all other β-tubulin isotypes was assessed in human oocytes, early embryos, sperm cells, and several somatic tissues by means of a quantitative reverse- transcriptase–polymerase-chain-reaction assay. We evaluated the effect of the TUBB8 mutations on the assembly of the heterodimer consisting of one α-tubulin polypeptide and one β-tubulin polypeptide (α/β-tubulin heterodimer) in vitro, on microtubule architecture in HeLa cells, on microtubule dynamics in yeast cells, and on spindle assembly in mouse and human oocytes. RESULTS We identified seven mutations in the primate-specific gene TUBB8 that were responsible for oocyte meiosis I arrest in 7 of the 24 families. TUBB8 expression is unique to oocytes and the early embryo, in which this gene accounts for almost all the expressed β-tubulin. The mutations affect chaperone-dependent folding and assembly of the α/β-tubulin heterodimer, disrupt microtubule behavior on expression in cultured cells, alter microtubule dynamics in vivo, and cause catastrophic spindle-assembly defects and maturation arrest on expression in mouse and human oocytes. CONCLUSIONS TUBB8 mutations have dominant-negative effects that disrupt microtubule behavior and oocyte meiotic spindle assembly and maturation, causing female infertility. (Funded by the National Basic Research Program of China and others.

Management of neuropsychiatric adverse events in a prostate cancer patient undergoing chimeric antigen receptor T-cell immunotherapy (a phase I clinical trial): A case report

In previous clinical trials, chimeric antigen receptor T-cell immunotherapy has shown preliminary efficacy in patients with malignant solid tumors. However, the occurrence of adverse events, particularly neuropsychiatric adverse events (eg, anxiety) and cognitive dysfunction, during the course of treatment may reduce patient compliance and pose a threat to their safety. Nurses are in a unique position to promptly identify and manage such complications, thereby facilitating early diagnosis and treatment, as well as improving clinical and patient outcomes. Moreover, nurses can promote compliance through the provision of psychological support to patients

Gaussian variational method to Fermi-Hubbard model in one and two dimensions

The study of ground-state properties of the Fermi-Hubbard model is a long-lasting task in the research of strongly correlated systems, and is crucial for the understanding of notable quantum phenomena including superconductivity and magnetism. Owing to the exponentially growing complexity of the system, a quantitative analysis usually demands high computational cost and is restricted to small samples, especially in two or higher dimensions. Here, we introduce a variational method in the frame of fermionic Gaussian states, and obtain the ground states of one- and two-dimensional attractive Hubbard models via imaginary-time evolution. We calculate the total energy and benchmark the results in a wide range of interaction strength and filling factor with those obtained via exact two-body results, the density matrix renormalization group based on matrix product states (MPS), and projector Quantum Monte Carlo (QMC) method. For both 1D and 2D cases, the Gaussian variational method presents accurate results for total energy with a maximum systematic error ${\sim}4\%$ in the intermediate interaction region. The accuracy of these results has negligible dependence on the system size. We further calculate the double occupancy and find excellent agreement with MPS and QMC, as well as the experimental results of cold quantum gases in optical lattices. The results suggest that the Gaussian pairing state is a good approximation to the ground states of attractive Hubbard model, in particular in the strong and weak coupling limits. Moreover, we generalize the method to the attractive Hubbard model with a finite spin-polarization, which can be mapped to the repulsive interaction case via particle-hole transformation, and obtain accurate results of ground state energy and double occupancy. Our work demonstrates the ability of the Gaussian variational method to extract ground state properties of strongly correlated many-body systems with negligible computational cost, especially of large size and in higher dimensions

Exploration of the common pathogenic link between COVID‐19 and diabetic foot ulcers: An in silico approach

Abstract Background and Aims The Coronavirus Disease‐19 (COVID‐19) is posing an ongoing threat to human health. Patients of diabetic foot ulcer (DFU) are susceptible to COVID‐19‐induced adverse outcomes. Nevertheless, investigations into their mutual molecular mechanisms have been limited to date. In the present work, we tried to uncover the shared pathogenesis and regulatory gene targets of COVID‐19 and DFU. Methods In this study, we chose GSE161281 as the COVID‐19 data set, which contained severe acute respiratory syndrome coronavirus 2 infected human induced embryonic stem cell‐derived peripheral neurons (n = 2) with uninfected controls (n = 2). The GSE134431 designated as the DFU data set, comprising full‐thickness DFU (n = 13) and diabetic foot skin (n = 8) samples from diabetic patients. The differential expressed genes (DEGs) were identified from GSE161281 and GSE134431, and the common DEGs between COVID‐19 and DFU were extracted. Multifactor regulatory network and co‐expression network of the common DEGs were analyzed, along with candidate drug prediction. Results Altogether, six common DEGs (dickkopf‐related protein 1 [DKK1], serine proteinase inhibitor A3 [SERPINA3], ras homolog family member D [RHOD], myelin protein zero like 3 [MPZL3], Claudin‐11 [CLDN11], and epidermal growth factor receptor pathway substrate 8‐like 1 [EPS8L1]) were found between COVID‐19 and DFU. Functional analyses indicated that pathways of apoptotic and Wnt signaling may contribute to progression of COVID‐19. Gene co‐expression network implied the shared pathways of immune regulation and cytokine response participated collectively in the development of DFU and COVID‐19. A multifactor regulatory network was constructed integrating the corresponding microRNAs (miRNAs) and transcription factors. Additionally, we proposed potential drug objects for the combined therapy. Conclusion Our study revealed the shared molecular mechanisms underlying COVID‐19 and DFU. The identified pivotal targets and common pathways can provide new perspectives for further research and assist the development of management strategies in patients of DFU complicated with COVID‐19

Clonal expansion analysis of transposon insertions by high-throughput sequencing identifies candidate cancer genes in a PiggyBac mutagenesis screen.

Somatic transposon mutagenesis in mice is an efficient strategy to investigate the genetic mechanisms of tumorigenesis. The identification of tumor driving transposon insertions traditionally requires the generation of large tumor cohorts to obtain information about common insertion sites. Tumor driving insertions are also characterized by their clonal expansion in tumor tissue, a phenomenon that is facilitated by the slow and evolving transformation process of transposon mutagenesis. We describe here an improved approach for the detection of tumor driving insertions that assesses the clonal expansion of insertions by quantifying the relative proportion of sequence reads obtained in individual tumors. To this end, we have developed a protocol for insertion site sequencing that utilizes acoustic shearing of tumor DNA and Illumina sequencing. We analyzed various solid tumors generated by PiggyBac mutagenesis and for each tumor >10⁶ reads corresponding to >10⁴ insertion sites were obtained. In each tumor, 9 to 25 insertions stood out by their enriched sequence read frequencies when compared to frequencies obtained from tail DNA controls. These enriched insertions are potential clonally expanded tumor driving insertions, and thus identify candidate cancer genes. The candidate cancer genes of our study comprised many established cancer genes, but also novel candidate genes such as Mastermind-like1 (Mamld1) and Diacylglycerolkinase delta (Dgkd). We show that clonal expansion analysis by high-throughput sequencing is a robust approach for the identification of candidate cancer genes in insertional mutagenesis screens on the level of individual tumors

Genomic features of PiggyBac insertions in tumors and tail controls.

<div><p>A) Relative distribution of PiggyBac insertion sites over chromosomes, compared to proportion of TTAA sites on chromosomes. Note the overrepresentation of chromosome 10, which carries the transposon donor array. Chromosome Y, which consists mainly of highly repetitive elements, showed a slight preference for PiggyBac insertions.</p> <p>B) Local hopping effect on Chromosome 10. Histogram of insertion density on chromosome 10 reveals a positive bias for insertions at proximal end (arrows), where the ATP1-S2 donor array is located.</p> <p>C) Distribution of PiggyBac insertions in genomic regions: Promoter (10 kb upstream of TSS), exons, introns, and intergenic regions.</p></div

Genes associated with clonally expanded transposon insertions.

<div><p>A) Clonally expanded gene insertions in tumor samples, sorted by their average read frequencies (<i>f</i>). Three mice harbored two tumors each (tumor 01 and 08, tumor 05 and 09, and tumor 04 and 10, respectively). A blue asterisk denotes genes present in the Cancer Gene Census list, a list of 487 genes causally implicated in cancer. <i>Mamdl1</i> and <i>Dgkd</i> were hit in independent tumor samples and are highlighted in red and pink, respectively.</p> <p>B) Cellular processes affected by clonally expanded gene insertions. Process categories were compiled from functional gene information at <a href="http://www.omim.org" target="_blank">www.omim.org</a> and <a href="http://www.informatics.jax.org" target="_blank"><u>www.informatics.jax.org</u></a>.</p></div