The DDX6/KIFC1 signaling axis, as regulated by YY1, contributes to the malignant behavior of pancreatic cancer.

Human DEAD/H box RNA helicase DDX6 acts as an oncogene in several different types of cancer, where it participates in RNA processing. Nevertheless, the role of DDX6 in pancreatic cancer (PC), together with the underlying mechanism, has yet to be fully elucidated. In the present study, compared with adjacent tissues, the level of DDX6 was abnormally increased in human PC tissues, and this increased level of expression was associated with poor prognosis. Furthermore, the role of DDX6 in PC was investigated by overexpressing or silencing the DDX6 in the PC cell lines, SW1990 and PaTu-8988t. A xenograft model was established by injecting nude mice with either DDX6-overexpressing or DDX6-silenced SW1990 cells. DDX6 overexpression promoted the proliferation and cell cycle transition, inhibited the cell apoptosis of PC cells, and accelerated tumor formation, whereas DDX6 knockdown elicited the opposite effects. DDX6 exerted positive effects on PC. RNA immunoprecipitation assay showed that DDX6 bound to kinesin family member C1 (KIFC1) mRNA, which was further confirmed by RNA pull-down assay. These results suggested that DDX6 positively regulated the expression of KIFC1. KIFC1 overexpression enhanced the proliferative capability of PC cells with DDX6 knockdown and inhibited their apoptosis. By contrast, DDX6 overexpression reversed the inhibitory effect of KIFC1 silencing on tumor proliferation. Subsequently, the transcription factor Yin Yang 1 (YY1) was shown to negatively regulate DDX6 at both the mRNA and protein levels. Dual-luciferase reporter assay verified that YY1 targeted the promoter of DDX6 and inhibited its transcription. High expression levels of YY1 decreased the proliferation of PC cells and promoted cell apoptosis, although these effects were reversed by DDX6 overexpression. Taken together, YY1 may target the DDX6/KIFC1 axis, thereby negatively regulating its expression, leading to an inhibitory effect on pancreatic tumor.

GID2 Interacts With CDKN3 and Regulates Pancreatic Cancer Growth and Apoptosis.

Dysregulation of deubiquitinase or ubiquitinase-mediated protein expression contributes to various diseases, including cancer. In the present study, we identified GID2, a subunit of the glucose-induced degradation-deficient (GID) complex that functions as an E3 ubiquitin ligase, as a potential key candidate gene in pancreatic cancer (PC) progression. The functional role and potential mechanism of GID2 in PC progression were investigated. Integrated bioinformatics analysis was performed to identify differentially expressed genes in PC based on the Gene Expression Profiling Interactive Analysis data sets. We found that GID2 was upregulated in PC tissues and that a high level of GID2 expression in clinical PC samples was positively associated with tumor stage and poor survival. Functional assays elucidated that GID2 expression promoted cell growth in vitro and accelerated tumor growth in vivo. GID2 knockdown effectively attenuated the malignant behaviors of PC cells and tumor formation. Furthermore, the protein network that interacted with the GID2 protein was constructed based on the GeneMANIA website. Cyclin-dependent kinase inhibitor 3 (CDKN3), a cell cycle regulator, was identified as a potential target of the GID2 protein. We revealed that GID2 positively regulated CDKN3 expression and inhibited CDKN3 ubiquitination. Furthermore, CDKN3 downregulation reversed the promoting effects of GID2 on PC progression. Therefore, the present study demonstrated that GID2 might regulate PC progression by maintaining the stability of the CDKN3 protein. These findings highlight the potential roles of the GID2/CDKN3 axis as a potential therapeutic target in PC.

Genomic vulnerability to climate change in Quercus acutissima, a dominant tree species in East Asian deciduous forests.

Understanding the evolutionary processes that shape the landscape of genetic variation and influence the response of species to future climate change is critical for biodiversity conservation. Here, we sampled 27 populations across the distribution range of a dominant forest tree, Quercus acutissima, in East Asia, and applied genome-wide analyses to track the evolutionary history and predict the fate of populations under future climate. We found two genetic groups (East and West) in Q. acutissima that diverged during Pliocene. We also found a heterogeneous landscape of genomic variation in this species, which may have been shaped by population demography and linked selections. Using genotype-environment association analyses, we identified climate-associated SNPs in a diverse set of genes and functional categories, indicating a model of polygenic adaptation in Q. acutissima. We further estimated three genetic offset metrics to quantify genomic vulnerability of this species to climate change due to the complex interplay between local adaptation and migration. We found that marginal populations are under higher risk of local extinction because of future climate change, and may not be able to track suitable habitats to maintain the gene-environment relationships observed under the current climate. We also detected higher reverse genetic offsets in northern China, indicating that genetic variation currently present in the whole range of Q. acutissima may not adapt to future climate conditions in this area. Overall, this study illustrates how evolutionary processes have shaped the landscape of genomic variation, and provides a comprehensive genome-wide view of climate maladaptation in Q. acutissima.

IoTSim: Internet of Things-Oriented Binary Code Similarity Detection with Multiple Block Relations.

Binary code similarity detection (BCSD) plays a crucial role in various computer security applications, including vulnerability detection, malware detection, and software component analysis. With the development of the Internet of Things (IoT), there are many binaries from different instruction architecture sets, which require BCSD approaches robust against different architectures. In this study, we propose a novel IoT-oriented binary code similarity detection approach. Our approach leverages a customized transformer-based language model with disentangled attention to capture relative position information. To mitigate out-of-vocabulary (OOV) challenges in the language model, we introduce a base-token prediction pre-training task aimed at capturing basic semantics for unseen tokens. During function embedding generation, we integrate directed jumps, data dependency, and address adjacency to capture multiple block relations. We then assign different weights to different relations and use multi-layer Graph Convolutional Networks (GCN) to generate function embeddings. We implemented the prototype of IoTSim. Our experimental results show that our proposed block relation matrix improves IoTSim with large margins. With a pool size of 103, IoTSim achieves a recall@1 of 0.903 across architectures, outperforming the state-of-the-art approaches Trex, SAFE, and PalmTree.

BRT: An Efficient and Scalable Blockchain-Based Revocation Transparency System for TLS Connections.

Log-based public key infrastructure(PKI) refers to a robust class of CA-attack-resilient PKI that enhance transparency and accountability in the certificate revocation and issuance process by compelling certificate authorities (CAs) to submit revocations to publicly and verifiably accessible logs. However, log-based PKIs suffer from a reliance on centralized and consistent sources of information, rendering them susceptible to split-world attacks, and they regrettably fail to provide adequate incentives for recording or monitoring CA behavior. Blockchain-based PKIs address these limitations by enabling decentralized log audits through automated financial incentives. However, they continue to face challenges in developing a scalable revocation mechanism suited for lightweight clients. In this paper, we introduce BRT, a scalable blockchain-based system for certificate and revocation transparency. It serves to log, audit, and validate the status of certificates within the transport layer security (TLS)/secure sockets layer(SSL) PKI domain. We designed an audit-on-chain framework, coupled with an off-chain storage/computation system, to enhance the efficiency of BRT when operating in a blockchain environment. By implementing a blockchain-based prototype, we demonstrate that BRT achieves storage-efficient log recording with a peak compression rate reaching 8%, cost-effective log updates for large-scale certificates, and near-instantaneous revocation checks for users.

Linked selection shapes the landscape of genomic variation in three oak species.

Natural selection shapes genome-wide patterns of diversity within species and divergence between species. However, quantifying the efficacy of selection and elucidating the relative importance of different types of selection in shaping genomic variation remain challenging. We sequenced whole genomes of 101 individuals of three closely related oak species to track the divergence history, and to dissect the impacts of selective sweeps and background selection on patterns of genomic variation. We estimated that the three species diverged around the late Neogene and experienced a bottleneck during the Pleistocene. We detected genomic regions with elevated relative differentiation ('FST -islands'). Population genetic inferences from the site frequency spectrum and ancestral recombination graph indicated that FST -islands were formed by selective sweeps. We also found extensive positive selection; the fixation of adaptive mutations and reduction neutral diversity around substitutions generated a signature of selective sweeps. Prevalent negative selection and background selection have reduced genetic diversity in both genic and intergenic regions, and contributed substantially to the baseline variation in genetic diversity. Our results demonstrate the importance of linked selection in shaping genomic variation, and illustrate how the extent and strength of different selection models vary across the genome.

Gene flow, linked selection, and divergent sorting of ancient polymorphism shape genomic divergence landscape in a group of edaphic specialists.

Interpreting the formation of genomic variation landscape, especially genomic regions with elevated differentiation (i.e. islands), is fundamental to a better understanding of the genomic consequences of adaptation and speciation. Edaphic islands provide excellent systems for understanding the interplay of gene flow and selection in driving population divergence and speciation. However, discerning the relative contribution of these factors that modify patterns of genomic variation remains difficult. We analysed 132 genomes from five recently divergent species in Primulina genus, with four species distributed in Karst limestone habitats and the fifth one growing in Danxia habitats. We demonstrated that both gene flow and linked selection have contributed to genome-wide variation landscape, where genomic regions with elevated differentiation (i.e., islands) were largely derived by divergent sorting of ancient polymorphism. Specifically, we identified several lineage-specific genomic islands that might have facilitated adaptation of P. suichuanensis to Danxia habitats. Our study is amongst the first cases disentangling evolutionary processes that shape genomic variation of plant specialists, and demonstrates the important role of ancient polymorphism in the formation of genomic islands that potentially mediate adaptation and speciation of endemic plants in special soil habitats.

Genetic architecture and adaptation of flowering time among environments.

The genetic basis of flowering time changes across environments, and pleiotropy may limit adaptive evolution of populations in response to local conditions. However, little information is known about how genetic architecture changes among environments. We used genome-wide association studies (GWAS) in Boechera stricta (Graham) Al-Shehbaz, a relative of Arabidopsis, to examine flowering variation among environments and associations with climate conditions in home environments. Also, we used molecular population genetics to search for evidence of historical natural selection. GWAS found 47 significant quantitative trait loci (QTLs) that influence flowering time in one or more environments, control plastic changes in phenology between experiments, or show associations with climate in sites of origin. Genetic architecture of flowering varied substantially among environments. We found that some pairs of QTLs showed similar patterns of pleiotropy across environments. A large-effect QTL showed molecular signatures of adaptive evolution and is associated with climate in home environments. The derived allele at this locus causes later flowering and predominates in sites with greater water availability. This work shows that GWAS of climate associations and ecologically important traits across diverse environments can be combined with molecular signatures of natural selection to elucidate ecological genetics of adaptive evolution.

Laminin-dependent integrin ß1 signaling regulates milk protein synthesis via prolactin/STAT5 pathway in bovine mammary epithelial cells.

Successful induction of milk protein synthesis relies on prolactin/STAT5. In mice, both laminin and ß1 integrin were necessary for STAT5 activity induced by prolactin treatment, resulting in transcriptional activation of ß-casein. However, the mechanism by which ß1 integrin increases the bovine milk protein synthesis is not well known. In order to display the crosstalk between integrin signaling and lactogenic signaling, we investigated the mechanism by which laminin mediated lactogenic effects via interaction with ß1 integrin on bovine mammary epithelial cells (BMECs). Therefore, localization of ß1 integrin was examined by immunofluorescence. The mRNA and protein expression levels were determined by quantitative real-time PCR and western blotting. The results showed that ß1 integrin were detected in basal mammary cells and basal membrane surface of adherent BMECs. However, basal distribution of ß1 integrin was not sufficient to increase ß-casein synthesis in the absence of integrin activation by laminin. A lactogenic hormone cocktail of insulin, hydrocortisone, and prolactin stimulated overall lactogenic effects, including upregulated expression of ß1 integrin, activation of prolactin/STAT5 signaling, and consequent increase of ß-casein synthesis. In response to a 24 h prolactin treatment, the abundance of STAT5, ß1 integrin, and ß-casein in BMECs with laminin was higher compared to that with a control substratum. Meanwhile, laminin-dependent lactogenic effects were inhibited by blocking ß1 integrin function, resulting in attenuated STAT5 activity and decreased ß-casein synthesis. These results indicated that ß1 integrin was a key mediator of the laminin-dependent prolactin/STAT5 signaling, which regulated the sustained STAT5 activity necessary for ß-casein expression in BMECs.

Metabolic engineering of Escherichia coli for polyamides monomer δ-valerolactam production from feedstock lysine.

Nylon 5 and nylon 6,5 are recently explored as new commercial polyamides, of which the monomer includes δ-valerolactam. In this study, a novel catalytic activity of lysine 2-monooxygenase (DavB) was explored to produce δ-valerolactam from L-pipecolic acid (L-PA), functioning as oxidative decarboxylase on a cyclic compound. Recombinant Escherichia coli BS01 strain expressing DavB from Pseudomonas putida could synthesize δ-valerolactam from L-pipecolic acid with a concentration of 90.3 mg/L. Through the co-expression of recombinant apoptosis-inducing protein (rAIP) from Scomber japonicus, glucose dehydrogenase (GDH) from Bacillus subtilis, Δ1-piperideine-2-carboxylae reductase (DpkA) from P. putida and lysine permease (LysP) from E. coli with DavB, δ-valerolactam was produced with the highest concentration of 242 mg/L. α-Dioxygenases (αDox) from Oryza sativa could act as a similar catalyst on L-pipecolic acid. A novel δ-valerolactam synthesis pathway was constructed entirely via microbial conversion from feedstock lysine in this study. Our system has great potential in the development of a bio-nylon production process. KEY POINTS: • DavB performs as an oxidative decarboxylase on L-PA with substrate promiscuity. • Strain with rAIP, GDH, DpkA, LysP, and DavB coexpression could produce δ-valerolactam. • This is the first time to obtain valerolactam entirely via biosynthesis from lysine.

LoRa-Based Physical Layer Key Generation for Secure V2V/V2I Communications.

In recent years, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication brings more and more attention from industry (e.g., Google and Uber) and government (e.g., United States Department of Transportation). These Vehicle-to-Everything (V2X) technologies are widely adopted in future autonomous vehicles. However, security issues have not been fully addressed in V2V and V2I systems, especially in key distribution and key management. The physical layer key generation, which exploits wireless channel reciprocity and randomness to generate secure keys, provides a feasible solution for secure V2V/V2I communication. It is lightweight, flexible, and dynamic. In this paper, the physical layer key generation is brought to the V2I and V2V scenarios. A LoRa-based physical key generation scheme is designed for securing V2V/V2I communications. The communication is based on Long Range (LoRa) protocol, which is able to measure Received Signal Strength Indicator (RSSI) in long-distance as consensus information to generate secure keys. The multi-bit quantization algorithm, with an improved Cascade key agreement protocol, generates secure binary bit keys. The proposed schemes improved the key generation rate, as well as to avoid information leakage during transmission. The proposed physical layer key generation scheme was implemented in a V2V/V2I network system prototype. The extensive experiments in V2I and V2V environments evaluate the efficiency of the proposed key generation scheme. The experiments in real outdoor environments have been conducted. Its key generation rate could exceed 10 bit/s on our V2V/V2I network system prototype and achieve 20 bit/s in some of our experiments. For binary key sequences, all of them pass the suite of statistical tests from National Institute of Standards and Technology (NIST).

DIACYLGLYCEROL ACYLTRANSFERASE1 Contributes to Freezing Tolerance.

Freezing limits plant growth and crop productivity, and plant species in temperate zones have the capacity to develop freezing tolerance through complex modulation of gene expression affecting various aspects of metabolism and physiology. While many components of freezing tolerance have been identified in model species under controlled laboratory conditions, little is known about the mechanisms that impart freezing tolerance in natural populations of wild species. Here, we performed a quantitative trait locus (QTL) study of acclimated freezing tolerance in seedlings of Boechera stricta, a highly adapted relative of Arabidopsis (Arabidopsis thaliana) native to the Rocky Mountains. A single QTL was identified that contained the gene encoding ACYL-COENZYME A:DIACYLGLYCEROL ACYLTRANSFERASE1 (BstDGAT1), whose expression is highly cold responsive. The primary metabolic enzyme DGAT1 catalyzes the final step in assembly of triacylglycerol (TAG) by acyl transfer from acyl-CoA to diacylglycerol. Freezing tolerant plants showed higher DGAT1 expression during cold acclimation than more sensitive plants, and this resulted in increased accumulation of TAG in response to subsequent freezing. Levels of oligogalactolipids that are produced by SFR2 (SENSITIVE TO FREEZING2), an indispensable element of freezing tolerance in Arabidopsis, were also higher in freezing-tolerant plants. Furthermore, overexpression of AtDGAT1 led to increased freezing tolerance. We propose that DGAT1 confers freezing tolerance in plants by supporting SFR2-mediated remodeling of chloroplast membranes.

Sevoflurane inhibits the progression of ovarian cancer through down-regulating stanniocalcin 1 (STC1).

BACKGROUND: Ovarian cancer is one of the leading causes of female death worldwide, with a poor prognosis of advanced patients. Sevoflurane, a volatile anesthetic commonly used in clinical operations, has been reported to have anti-cancer activity against some tumors. In the present study, we aimed to investigate the effects of sevoflurane on the progression of ovarian cancer and its potential mechanism. METHODS: The effects of sevoflurane on ovarian cancer cell viability, proliferation, migration, invasion, cell cycle, and apoptosis were determined by functional experiments in vitro. Gelatin zymography assay was performed to examine MMP9 activity. In vivo, sevoflurane was injected into mice of transplantation tumor with SKOV3 cells or with pcDNA-STC1 treated SKOV3 cells. RESULTS: We found that sevoflurane inhibited the viability of SKOV3 and OVCAR3 cells in a dose-dependent manner, and colony formation assay revealed that sevoflurane inhibited ovarian cancer cell colony-formation abilities. Additionally, sevoflurane could induce cell cycle arrest and promote cell apoptosis in SKOV3 and OVCAR3 cells. Moreover, sevoflurane reduced the migration and invasion abilities of SKOV3 and OVCAR3 cells, as well as the MMP-9 activity. Furthermore, sevoflurane down-regulated the expression of stanniocalcin 1 (STC1), and up-regulation of STC1 could reverse the inhibitory effects of sevoflurane on cell proliferation and invasion. In vivo, sevoflurane significantly inhibited the tumor growth, which was be reversed by STC1 overexpression. CONCLUSION: These data reveal an anti-cancer activity of sevoflurane on the growth and invasion of ovarian cancer, which may be through down-regulating STC1. Sevoflurane may serve as a potential anti-cancer agent in ovarian cancer therapy.

Morphine and ketamine inhibit immune function of gastric cancer patients by increasing percentage of CD4(+)CD25(+)Foxp3(+) regulatory T cells in vitro.

BACKGROUND: There is conflicting evidence regarding effects of anesthetic and analgesic drugs on immune function of cancer patients. This study was designed to observe changes of T cell subpopulations in the gastric cancer (GC) patients and to assess effects of morphine and ketamine on the CD4(+) T cells, CD8(+) T cells, and regulatory T cells (Tregs) populations obtained from the GC patients in vitro. METHODS: The peripheral blood samples from 20 GC patients and 20 healthy volunteers were obtained. The peripheral blood mononuclear cells were isolated and incubated in a solution containing phorbol-myristate-acetate and ionomycin (2 µL/mL) in the presence or absence of morphine (50 ng/mL) or different-concentration ketamine (25, 50, and 100 µM). The CD4(+) T cells, CD8(+) T cells, and Tregs were determined using the flow cytometric assay. RESULTS: The percentages of CD8(+) T cells were significantly decreased, but the ratio of CD4(+)/CD8(+) T cells and Tregs populations was significantly increased in the GC control group compared with the normal control group (P < 0.05). The ratio of CD4(+)/CD8(+) T cells was significantly increased in the groups M and K3 compared with the control group (P < 0.05) but was significantly decreased in the group K1 compared with the group K3. The percentage of Tregs was significantly increased in the groups M, K1, K2, and K3 compared with the control group. With the increased concentrations, ketamine increased the number of Tregs. CONCLUSIONS: GC shifts the balance of CD4(+)/CD8(+) T cells toward CD4(+) T cells and increases the Tregs populations by inducing immune responses. Morphine increases the ratio of CD4(+)/CD8(+) T cells and Tregs populations. Ketamine affects the ratio of CD4(+)/CD8(+) T cells and Tregs populations in a dose-dependent model.

Effect of Oxycodone Combined With Dexmedetomidine for Intravenous Patient-Controlled Analgesia After Video-Assisted Thoracoscopic Lobectomy.

OBJECTIVE: To investigate the effect of the combination of oxycodone and dexmedetomidine for patient-controlled analgesia (PCA) after video-assisted thoracoscopic (VATS) lobectomy. DESIGN: A prospective, randomized, double-blind, controlled trial. SETTING: Shandong Cancer Hospital and Institute in Jinan, China. PARTICIPANTS: Eighty-four patients with lung cancer undergoing VATS lobectomies were recruited. INTERVENTIONS: Patients were randomly assigned to one of the following two groups: oxycodone and dexmedetomidine (group OD) or oxycodone alone (group O). Before induction of anesthesia, patients in group OD received 0.5 µg/kg, dexmedetomidine diluted to 20 mL with physiologic saline and infused for 10 minutes intravenously. The PCA protocol was 50 mg of oxycodone and 0.05 µg/kg/h dexmedetomidine diluted to 100 mL. Patients in group O received 20 mL of physiologic saline infused for 10 minutes. Their PCA protocol consisted of 50 mg of oxycodone diluted to 100 mL. Intravenous PCA was used for postoperative analgesia (lasting for 48 h). MEASUREMENTS AND MAIN RESULTS: Pain at rest and during movement was assessed by a blinded observer using the Visual Analog Scale pain score (VAS) at 4, 6, 24, and 48 hours after surgery, and the level of sedation simultaneously was assessed using the Ramsay Sedation Scale. Total oxycodone consumption, requirements for rescue analgesia, side effects, and satisfaction with pain management were recorded within 48 hours after surgery. Eighty patients' data were analyzed at the end of the study (40 in each group). Visual Analog Scale scores decreased at 4, 6, and 24 hours at rest and during movement in group OD compared with group O (p<0.05). The level of patient satisfaction in group OD was significantly higher than that in group O (p<0.05). Oxycodone consumption in group OD was significantly lower than that in group O (p<0.001). Group O experienced more nausea and vomiting 6 hours after surgery than did group OD (p< 0.05). CONCLUSION: The combination of oxycodone and dexmedetomidine for PCA after VATS lobectomy can reduce oxycodone consumption, improve patient satisfaction, and provide better analgesia with fewer side effects (nausea and vomiting) compared with PCA with oxycodone alone.

[Influence of artificial insemination with donor sperm on the pregnancy outcomes and safety of the offspring].

OBJECTIVE: To investigate the factors influencing the pregnancy outcomes of artificial insemination with donor sperm (AID), improve the pregnancy rate, and evaluate the safety of the offspring. METHODS: We retrospectively analyzed 7,761 cycles of AID for 5,109 infertile couples performed between July 1, 2005 and June 30, 2013 in the Center of Reproductive Medicine of Shenyang No 204 Hospital, the outcomes of pregnancy, and the incidence of birth defects. RESULTS: Totally, 2 252 clinical pregnancies were achieved by AID, in which the pregnancy rate per cycle was 29. 02% and the cumulative pregnancy rate was 44. 08%. The clinical pregnancy rate was remarkably higher in the females of ≤ 35 years than in those of > 35 years old (30.31% vs 20.18%, P < 0.01), in the women with < 5-year infertility than in those with > 5-year infertility (30.83% vs 28.16%, P < 0.01), and in the patients of the ovarian stimulation group than in those of the natural cycle group (33.22% vs 28.68%, P < 0.01) The clinical pregnancy rate was the highest in the first treatment cycle (29.87%), with statistically significant difference from the fourth cycle (23.61%) (P < 0.05), but not between the other cycles (P > 0.05). There were 28 cases of birth defects in the offspring (1.40%), including 6 cases (21.43%) involving the cardiovascular system, 4 (14.29%) involving the musculoskeletal system, 3 (10.71%) involving the urogenital system, 3 (10.71%) involving the central nervous system, 2 cases (7.14%) of cleft lip and palate, 2 (7.14%) involving the respiratory system, 2 (7.14%) involving the gastrointestinal digestive system, and other anomalies. CONCLUSION: Female age, infertility duration, and ovarian stimulation treatment are important factors influencing the clinical pregnancy rate of AID. Artificial insemination with cryopreserved donor sperm does not increase the incidence of birth defects, which is considered as a relatively safe technique of assisted reproduction.

Mitochondrial DNA capture and divergence in Pinus provide new insights into the evolution of the genus.

The evolution of the mitochondrial (mt) genome is far from being fully understood. Systematic investigations into the modes of inheritance, rates and patterns of recombination, nucleotide substitution, and structural changes in the mt genome are still lacking in many groups of plants. In this study, we sequenced >11kbp mtDNA segments from multiple accessions of 36 pine species to characterize the evolutionary patterns of mtDNA in the genus Pinus. We found extremely low substitution rates and complex repetitive sequences scattered across different genome regions, as well as chimeric structures that were probably generated by multiple intergenomic recombinations. The mtDNA-based phylogeny of the genus differed from that based on chloroplast and nuclear DNA in the placement of several groups of species. Such discordances suggest a series of mtDNA capture events during past range shifts of the pine species and that both vertical and horizontal inheritance are implicated in the evolution of mtDNA in Pinus. MtDNA dating revealed that most extant lineages of the genus originated during Oligocene-Miocene radiation and subgenus Strobus diversified earlier than subgenus Pinus. Our findings illustrate a reticular evolutionary pathway for the mt genome through capture and recombination in the genus Pinus, and provide new insights into the evolution of the genus.

Identification of genes and candidate agents associated with pancreatic cancer.

Pancreatic cancer is a malignant neoplasm originating from transformed cells arising in tissues forming the pancreas. A major challenge in current cancer research is biological interpretation of complexity of cancer somatic mutation profiles. It has been suggested that several molecular alterations may play important roles in pancreatic carcinogenesis. In this study, by using the GSE28735 affymetrix microarray data accessible from Gene Expression Omnibus (GEO) database, we identified differentially expressed genes (DEGs) between paired pancreatic cancer tissues and adjacent nontumor tissues, followed the protein-protein interaction of the DEGs. Our study identified thousands of DEGs involved in regulation of cell cycle and apoptosis in progression of pancreatic cancer. Sp1 was predicted to be the major regulator by transcription factors analysis. From the protein-protein interaction networks, we found that Tk1 might play an important role in the progression of pancreatic cancer. Finally, we predicted candidate agents, including tomatidine and nialamide, which may be used as drugs to treat pancreatic cancer. In conclusion, our data provide a comprehensive bioinformatics analysis of genes and pathways which may be involved in the progression of pancreatic cancer.

Analysis of dysregulation of immune system in pancreatic cancer based on gene expression profile.

The aim of this study was to explore the dysregulated expression of the immune system in pancreatic cancer and clarify the pathogenesis of pancreatic cancer. The Dataset GSE15471 was downloaded from GEO database, Student's t test was used to screen differentially expressed genes (DEGs) between the pancreatic cancer group and the normal control group. Kyoto Encyclopedia of Genes and Genomes (KEGG) provides functional annotation was employed to explore the significant DEGs involved in biological functions. We got 988 significantly DEGs, including 832 up-regulated genes and 156 down-regulated genes. The ratio of up-regulated genes and down-regulated genes was 5.3. Total 13 biological pathways which were significant enriched with DEGs by KEGG pathway enrichment analysis. Finally, we constructed a overall network of the immune system in pancreatic cancer with these biological pathways information. Our study reveals that dysregulated pathways in pancreatic cancer associated with the immune system. Besides, we also identify some important molecular biomarkers of the pancreatic cancer, including CXCR4 and CD4. Dysfunctional pathways and important molecular biomarkers of pancreatic cancer will provide useful information for potential treatment of pancreatic cancer.

Expression of stromal cell-derived factor 1 and CXCR7 ligand receptor system in pancreatic adenocarcinoma.

BACKGROUND: Stromal cell-derived factor 1 (SDF-1) is a chemokine that is expressed in some cancer cells and is involved in tumor cell migration and metastasis. CXCR7, a novel receptor for SDF-1, has been identified recently. Research has demonstrated that SDF-1/CXCR7 interaction could play an important role in cancer progression. In this study, we aimed to investigate the expression of the SDF-1/CXCR7 ligand receptor system and the relationship between this expressions and clinicopathological characteristics in pancreatic adenocarcinoma. METHODS: Expressions of SDF-1 and CXCR7 in 64 cases of pancreatic adenocarcinoma tissue and 24 cases of normal pancreatic tissue were detected immunohistochemically. RESULTS: Expressions of SDF-1 and CXCR7 were negative in normal pancreatic tissues. Respectively, positive expression rates of SDF-1 and CXCR7 in pancreatic adenocarcinoma were 45.3% and 51.6%. The expression of SDF-1 correlated with histological grades; the expression rate in moderate to low differentiation was higher than in high differentiation (P<0.05). The expression of CXCR7 positively correlated with lymph node metastasis (P<0.05). A log-rank test showed that the expression of SDF-1+/CXCR7+ correlated with poor prognosis (P<0.05). CONCLUSIONS: The SDF-1/CXCR7 receptor ligand system may take part in invasive progression and metastasis of pancreatic adenocarcinoma, and might be useful as an index for evaluating invasiveness and prognosis.