DNMT3a in the hippocampal CA1 is crucial in the acquisition of morphine self‐administration in rats

Drug‐reinforced excessive operant responding is one fundamental feature of long-lasting addiction‐like behaviors and relapse in animals. However, the transcriptional regulatory mechanisms responsible for the persistent drug‐specific (not natural rewards) operant behavior are not entirely clear. In this study, we demonstrate a key role for one of the de novo DNA methyltransferase, DNMT3a, in the acquisition of morphine self‐administration (SA) in rats. The expression of DNMT3a in the hippocampal CA1 region but not in the nucleus accumbens shell was significantly up‐regulated after 1‐ and 7‐day morphine SA (0.3 mg/kg/infusion) but not after the yoked morphine injection. On the other hand, saccharin SA did not affect the expression of DNMT3a or DNMT3b. DNMT inhibitor 5‐aza‐2‐deoxycytidine (5‐aza) microinjected into the hippocampal CA1 significantly attenuated the acquisition of morphine SA. Knockdown of DNMT3a also impaired the ability to acquire the morphine SA. Overall, these findings suggest that DNMT3a in the hippocampus plays an important role in the acquisition of morphine SA and may be a valid target to prevent the development of morphine addiction. Includes Supplemental informatio

Looking Through the Glass: Neural Surface Reconstruction Against High Specular Reflections

Neural implicit methods have achieved high-quality 3D object surfaces under slight specular highlights. However, high specular reflections (HSR) often appear in front of target objects when we capture them through glasses. The complex ambiguity in these scenes violates the multi-view consistency, then makes it challenging for recent methods to reconstruct target objects correctly. To remedy this issue, we present a novel surface reconstruction framework, NeuS-HSR, based on implicit neural rendering. In NeuS-HSR, the object surface is parameterized as an implicit signed distance function (SDF). To reduce the interference of HSR, we propose decomposing the rendered image into two appearances: the target object and the auxiliary plane. We design a novel auxiliary plane module by combining physical assumptions and neural networks to generate the auxiliary plane appearance. Extensive experiments on synthetic and real-world datasets demonstrate that NeuS-HSR outperforms state-of-the-art approaches for accurate and robust target surface reconstruction against HSR. Code is available at https://github.com/JiaxiongQ/NeuS-HSR.Comment: 17 pages, 20 figure

Relationship between low-density lipoprotein levels on admission and 1-year outcome in patients with acute ST-segment-elevation myocardial infarction

AbstractThis study assessed the relationship between low-density lipoprotein cholesterol (LDL-C) levels on admission and the incidence of major adverse cardiovascular events (MACE) in patients with acute ST-segment-elevation myocardial infarction (ASTEMI). Patients with ASTEMI who had a lipid profile tested within 24 hours of symptom onset were enrolled. They were stratified into high and low LDL-C groups according to whether their LDL-C was above (n = 501) or below (n = 575) the median level, respectively. The incidence of MACE, cardiovascular death, non-fatal MI, revascularization, and stroke was compared between the groups at 1 month, 6 months, and 1 year. Survival analysis and Cox proportional hazard analysis were performed. In-hospital use of beta blockers was better in the high than in the low LDL-C group (76.6% vs. 69.7%, p = 0.01). Statin use was significantly higher in the high than in the low LDL-C group during follow-up (86.8% vs. 80.0%, p = 0.003 at1 month; 71.6% vs. 62.4%, p = 0.002 at 6 months; 67.8% vs. 61.2%, p = 0.03 at 1 year). The incidence of MACE on follow-up at 1 month was higher in the low than in the high LDL-C group (12.0% vs. 8.1%, p = 0.04). At 1 year, survival was not significantly different between the groups. Cox proportional hazards analysis indicated that the incidence of MACE was significantly associated with hypertension, current smoking, high-density lipoprotein cholesterol (HDL-C), in-hospital use of beta blockers, and statin use on follow-up (p < 0.01). LDL-C levels on admission in patients with ASTEMI had no significant effect on the 6-month and 1-year incidence of MACE, but the incidence of MACE was significantly higher in the low LDL-C group at 1 month. It would be relevant to further investigate the HDL-C level on admission, in-hospital use of beta blockers, and statin use during follow-up in relation to MACE

A case-control study on risk factors of breast cancer in China

Introduction: To screen the risk factors associated with breast cancer among Chinese women in order to evaluate the individual risk of developing breast cancer among women in China. Material and methods: A case-control study on 416 breast cancer patients and 1156 matched controls was conducted in 14 hospitals in 8 provinces of China in 2008. Controls were age- and region-matched to the cases. Clinicians conducted in-person interviews with the subjects to collect information on demographics and suspected risk factors for breast cancer that are known worldwide. Conditional logistic regression was used to derive odds ratios (OR) and 95% confidence intervals (CI) for the associations between risk factors and breast cancer. Results: Compared with matched controls, women with breast cancer were significantly more likely to have higher body mass index (BMI, OR = 4.07, 95% CI; 2.98-5.55), history of benign breast disease (BBD) biopsy (OR = 1.68, 95% CI; 1.19-2.38), older age of menarche (AOM) (OR = 1.41, 95% CI: 107-187), stress anticipation (SA), for grade 1-4, OR = 2.15, 95% CI; 1.26-3.66; for grade 5-9, OR = 3.48, 95% CI; 2.03-5.95) and menopause (OR = 2.22, 95% CI: 1.50-3.282) at the level of p &lt; 0.05. Family history of breast cancer (FHBC) in first-degree relatives (OR = 1.66, 95% CI; 0.77-3.59) and use of oral contraceptives (OC) (OR = 1.59, 95% CI; 0.83-3.05) were associated with an increased risk of breast cancer at the level of p &lt; 0.20. Conclusions: Our results showed that BMI, history of BBD biopsy, older AOM, SA and menopause were associated with increased risk of breast cancer among Chinese women. The findings derived from the study provided some suggestions for population-based prevention and control of breast cancer in China.Medicine, General &amp; InternalSCI(E)15ARTICLE2303-309

Genetic map of Triticum turgidum based on a hexaploid wheat population without genetic recombination for D genome

BACKGROUND: A synthetic doubled-haploid hexaploid wheat population, SynDH1, derived from the spontaneous chromosome doubling of triploid F(1) hybrid plants obtained from the cross of hybrids Triticum turgidum ssp. durum line Langdon (LDN) and ssp. turgidum line AS313, with Aegilops tauschii ssp. tauschii accession AS60, was previously constructed. SynDH1 is a tetraploidization-hexaploid doubled haploid (DH) population because it contains recombinant A and B chromosomes from two different T. turgidum genotypes, while all the D chromosomes from Ae. tauschii are homogenous across the whole population. This paper reports the construction of a genetic map using this population. RESULTS: Of the 606 markers used to assemble the genetic map, 588 (97%) were assigned to linkage groups. These included 513 Diversity Arrays Technology (DArT) markers, 72 simple sequence repeat (SSR), one insertion site-based polymorphism (ISBP), and two high-molecular-weight glutenin subunit (HMW-GS) markers. These markers were assigned to the 14 chromosomes, covering 2048.79 cM, with a mean distance of 3.48 cM between adjacent markers. This map showed good coverage of the A and B genome chromosomes, apart from 3A, 5A, 6A, and 4B. Compared with previously reported maps, most shared markers showed highly consistent orders. This map was successfully used to identify five quantitative trait loci (QTL), including two for spikelet number on chromosomes 7A and 5B, two for spike length on 7A and 3B, and one for 1000-grain weight on 4B. However, differences in crossability QTL between the two T. turgidum parents may explain the segregation distortion regions on chromosomes 1A, 3B, and 6B. CONCLUSIONS: A genetic map of T. turgidum including 588 markers was constructed using a synthetic doubled haploid (SynDH) hexaploid wheat population. Five QTLs for three agronomic traits were identified from this population. However, more markers are needed to increase the density and resolution of this map in the future study

CpG-binding protein CFP1 promotes ovarian cancer cell proliferation by regulating BST2 transcription

Epigenetic alterations have been functionally linked to ovarian cancer development and occurrence. The CXXC zinc finger protein 1 (CFP1) is an epigenetic regulator involved in DNA methylation and histone modification in mammalian cells. However, its role in ovarian cancer cells is unknown. Here, we show that CFP1 protein is highly expressed in human ovarian cancer tissues. Loss of CFP1 inhibited the growth of human ovarian cancer cells, promoted apoptosis, and increased senescence. CFP1 knockdown resulted in reduced levels of SETD1 (a CFP1 partner) and histone H3 trimethylation at the fourth lysine residue (H3K4me3). RNA-sequencing revealed that deletion of CFP1 resulted in mRNA reduction of bone marrow stromal cell antigen 2 (BST2). Bioinformatics analysis and chromatin immunoprecipitation showed that CFP1 binds to the promoter of BST2 and regulates its transcription directly. Overexpression of BST2 rescued the growth inhibitory effect of CFP1 loss. Furthermore, depletion of cullin-RING ubiquitin ligases 4 (CRL4) components ROC1 or CUL4A had significantly inhibited the expression of CFP1 and BST2 similar to MLN4924 treatment that blocked cullin neddylation and inactivated CRL4s. In conclusion, CFP1 promotes ovarian cancer cell proliferation and apoptosis by regulating the transcription of BST2, and the expression of CFP1 was affected by CRL4 ubiquitin ligase complex

(Z)3,4,5,4'-trans-tetramethoxystilbene, a new analogue of resveratrol, inhibits gefitinb-resistant non-small cell lung cancer via selectively elevating intracellular calcium level.

Calcium is a second messenger which is required for regulation of many cellular processes. However, excessive elevation or prolonged activation of calcium signaling would lead to cell death. As such, selectively regulating calcium signaling could be an alternative approach for anti-cancer therapy. Recently, we have identified an effective analogue of resveratrol, (Z)3,4,5,4′-trans-tetramethoxystilbene (TMS) which selectively elevated the intracellular calcium level in gefitinib-resistant (G-R) non-small-cell lung cancer (NSCLC) cells. TMS exhibited significant inhibitory effect on G-R NSCLC cells, but not other NSCLC cells and normal lung epithelial cells. The phosphorylation and activation of EGFR were inhibited by TMS in G-R cells. TMS induced caspase-independent apoptosis and autophagy by directly binding to SERCA and causing endoplasmic reticulum (ER) stress and AMPK activation. Proteomics analysis also further confirmed that mTOR pathway, which is the downstream of AMPK, was significantly suppressed by TMS. JNK, the cross-linker of ER stress and mTOR pathway was significantly activated by TMS. In addition, the inhibition of JNK activation can partially block the effect of TMS. Taken together, TMS showed promising anti-cancer activity by mediating calcium signaling pathway and inducing apoptosis as well as autophagy in G-R NSCLC cells, providing strategy in designing multi-targeting drug for treating G-R patients

Systems Chemical Genetics-Based Drug Discovery: Prioritizing Agents Targeting Multiple/Reliable Disease-Associated Genes as Drug Candidates

Genetic disease genes are considered a promising source of drug targets. Most diseases are caused by more than one pathogenic factor; thus, it is reasonable to consider that chemical agents targeting multiple disease genes are more likely to have desired activities. This is supported by a comprehensive analysis on the relationships between agent activity/druggability and target genetic characteristics. The therapeutic potential of agents increases steadily with increasing number of targeted disease genes, and can be further enhanced by strengthened genetic links between targets and diseases. By using the multi-label classification models for genetics-based drug activity prediction, we provide universal tools for prioritizing drug candidates. All of the documented data and the machine-learning prediction service are available at SCG-Drug (http://zhanglab.hzau.edu.cn/scgdrug)