Cathelicidin suppresses lipid accumulation and hepatic steatosis by inhibition of the CD36 receptor.

Background and objectivesObesity is a global epidemic which increases the risk of the metabolic syndrome. Cathelicidin (LL-37 and mCRAMP) is an antimicrobial peptide with an unknown role in obesity. We hypothesize that cathelicidin expression correlates with obesity and modulates fat mass and hepatic steatosis.Materials and methodsMale C57BL/6 J mice were fed a high-fat diet. Streptozotocin was injected into mice to induce diabetes. Experimental groups were injected with cathelicidin and CD36 overexpressing lentiviruses. Human mesenteric fat adipocytes, mouse 3T3-L1 differentiated adipocytes and human HepG2 hepatocytes were used in the in vitro experiments. Cathelicidin levels in non-diabetic, prediabetic and type II diabetic patients were measured by enzyme-linked immunosorbent assay.ResultsLentiviral cathelicidin overexpression reduced hepatic steatosis and decreased the fat mass of high-fat diet-treated diabetic mice. Cathelicidin overexpression reduced mesenteric fat and hepatic fatty acid translocase (CD36) expression that was reversed by lentiviral CD36 overexpression. Exposure of adipocytes and hepatocytes to cathelicidin significantly inhibited CD36 expression and reduced lipid accumulation. Serum cathelicidin protein levels were significantly increased in non-diabetic and prediabetic patients with obesity, compared with non-diabetic patients with normal body mass index (BMI) values. Prediabetic patients had lower serum cathelicidin protein levels than non-diabetic subjects.ConclusionsCathelicidin inhibits the CD36 fat receptor and lipid accumulation in adipocytes and hepatocytes, leading to a reduction of fat mass and hepatic steatosis in vivo. Circulating cathelicidin levels are associated with increased BMI. Our results demonstrate that cathelicidin modulates the development of obesity

The antiangiogenic agent ZD4190 prevents tumour outgrowth in a model of minimal residual carcinoma in deep tissues

BACKGROUND: Tumour cells may persist at the operative site after seemingly adequate surgery. Radiotherapy is often given in an attempt to prevent repopulation, but this modality cannot be relied upon to prevent locoregional recurrence. An alternative strategy is to take advantage of the requirement of tumour cells to develop an independent blood supply and block this process to prevent recurrence. METHODS: In this study, we evaluate the effect of the angiogenesis inhibitor, ZD4190, using a rodent model of residual carcinoma in deep tissues, mimicking the clinical scenario where low numbers of malignant cells persist at the operative site. RESULTS: The tumour burden that could be eliminated was dependent on the site where the cells were implanted. Immediate treatment with ZD4190 prevented outgrowth of up to 2.5 x 10(5) cells in the rectus muscle and 1 x 10(5) in the gastrocnemius, whereas control animals developed large tumours. When more than 2.5 x 10(6) cells were implanted into the rectus or 1 x 10(6) into the gastrocnemius and treatment was maintained for 3 weeks, the carcinomas that developed in ZD4190-treated animals showed a reduced microvessel density and increased necrosis when compared with the vehicle-treated controls, but an infiltrative growth pattern was common. CONCLUSION: These findings suggest that antiangiogenic agents have a role to play in preventing outgrowth of residual carcinoma and are likely to be most effective when the tumour burden is minimal

Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016.

OBJECTIVE: To provide an update to "Surviving Sepsis Campaign Guidelines for Management of Sepsis and Septic Shock: 2012." DESIGN: A consensus committee of 55 international experts representing 25 international organizations was convened. Nominal groups were assembled at key international meetings (for those committee members attending the conference). A formal conflict-of-interest (COI) policy was developed at the onset of the process and enforced throughout. A stand-alone meeting was held for all panel members in December 2015. Teleconferences and electronic-based discussion among subgroups and among the entire committee served as an integral part of the development. METHODS: The panel consisted of five sections: hemodynamics, infection, adjunctive therapies, metabolic, and ventilation. Population, intervention, comparison, and outcomes (PICO) questions were reviewed and updated as needed, and evidence profiles were generated. Each subgroup generated a list of questions, searched for best available evidence, and then followed the principles of the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system to assess the quality of evidence from high to very low, and to formulate recommendations as strong or weak, or best practice statement when applicable. RESULTS: The Surviving Sepsis Guideline panel provided 93 statements on early management and resuscitation of patients with sepsis or septic shock. Overall, 32 were strong recommendations, 39 were weak recommendations, and 18 were best-practice statements. No recommendation was provided for four questions. CONCLUSIONS: Substantial agreement exists among a large cohort of international experts regarding many strong recommendations for the best care of patients with sepsis. Although a significant number of aspects of care have relatively weak support, evidence-based recommendations regarding the acute management of sepsis and septic shock are the foundation of improved outcomes for these critically ill patients with high mortality

Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

<p>Abstract</p> <p>Background</p> <p>With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality.</p> <p>Results</p> <p>Motivated by inferring transcriptional compensation (TC) interactions in yeast, a stepwise structural equation modeling algorithm (SSEM) is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations) from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC) SSEM works best. SSEM with Bayesian information criterion (BIC) results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions) rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1) small groups of genes that are synthetic sick or lethal (SSL) to SGS1, and (2) a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1), SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2) are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted.</p> <p>Conclusion</p> <p>SSEM is a useful tool for inferring genetic networks, and the results reinforce the possibility of predicting pathways of protein complexes via genetic interactions.</p

p53 Activation following Rift Valley Fever Virus Infection Contributes to Cell Death and Viral Production

Rift Valley fever virus (RVFV) is an emerging viral zoonosis that is responsible for devastating outbreaks among livestock and is capable of causing potentially fatal disease in humans. Studies have shown that upon infection, certain viruses have the capability of utilizing particular cellular signaling pathways to propagate viral infection. Activation of p53 is important for the DNA damage signaling cascade, initiation of apoptosis, cell cycle arrest and transcriptional regulation of multiple genes. The current study focuses on the role of p53 signaling in RVFV infection and viral replication. These results show an up-regulation of p53 phosphorylation at several serine sites after RVFV MP-12 infection that is highly dependent on the viral protein NSs. qRT-PCR data showed a transcriptional up-regulation of several p53 targeted genes involved in cell cycle and apoptosis regulation following RVFV infection. Cell viability assays demonstrate that loss of p53 results in less RVFV induced cell death. Furthermore, decreased viral titers in p53 null cells indicate that RVFV utilizes p53 to enhance viral production. Collectively, these experiments indicate that the p53 signaling pathway is utilized during RVFV infection to induce cell death and increase viral production

Growth arrest-specific gene 6 expression in human breast cancer

Growth arrest-specific gene 6 (Gas6), identified in 1995, acts as the ligand to the Axl/Tyro3 family of tyrosine kinase receptors and exerts mitogenic activity when bound to these receptors. Overexpression of the Axl/Tyro3 receptor family has been found in breast, ovarian and lung tumours. Gas6 is upregulated 23-fold by progesterone acting through the progesterone receptor B (PRB). Recently, Gas6 has been shown to be a target for overexpression and amplification in breast cancer. Quantitative real-time PCR analysis was used to determine the levels of Gas6 mRNA expression in 49 primary breast carcinomas. Expression of PRB protein was evaluated immunohistochemically with a commercially available PRB antibody. The results showed a positive association between PRB protein and Gas6 mRNA levels (P=0.04). Gas6 correlated positively with a number of favourable prognostic variables including lymph node negativity (P=0.0002), younger age at diagnosis (P=0.04), smaller size of tumours (P=0.02), low Nottingham prognostic index scores (P=0.03) and low nuclear morphology (P=0.03). This study verifies for the first time the association between PRB and Gas6 in breast cancer tissue

Angiotensin-converting enzyme gene insertion/deletion polymorphism is associated with risk of oral precancerous lesion in betel quid chewers

To investigate whether angiotensin-converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism is related to the risk of oral precancerous lesions (OPL) in Taiwanese subjects who chew betel quid, a total of 61 betel quid chewers having OPL were compared with 61 asymptomatic betel quid chewers matched for betel quid chewing duration and dosage. The frequency of homozygote for ACE D variant is significantly higher in the case subjects than that of the controls (44.3 vs 24.6%; P=0.0108). The adjusted odds ratio of the D homozygous for the risk of OPL is 8.10 (95% confidence interval (CI)=2.04–32.19, P=0.003). In the allelic base analysis, the D allele is also significantly associated with higher risk of OPL. When grouping the study subjects by smoking status, the association between ACE I/D polymorphism and risk of OPL was only observed in nonsmokers. Our results support the theory that genetic factors may contribute to the susceptibility of OPL and suggest that smoking and genetic factors may be differently involved in the development of OPL

Three non-autonomous signals collaborate for nuclear targeting of CrMYC2, a Catharanthus roseus bHLH transcription factor

<p>Abstract</p> <p>Background</p> <p>CrMYC2 is an early jasmonate-responsive bHLH transcription factor involved in the regulation of the expression of the genes of the terpenic indole alkaloid biosynthesis pathway in <it>Catharanthus roseus</it>. In this paper, we identified the amino acid domains necessary for the nuclear targeting of CrMYC2.</p> <p>Findings</p> <p>We examined the intracellular localization of whole CrMYC2 and of various deletion mutants, all fused with GFP, using a transient expression assay in onion epidermal cells. Sequence analysis of this protein revealed the presence of four putative basic nuclear localization signals (NLS). Assays showed that none of the predicted NLS is active alone. Further functional dissection of CrMYC2 showed that the nuclear targeting of this transcription factor involves the cooperation of three domains located in the C-terminal region of the protein. The first two domains are located at amino acid residues 454-510 and 510-562 and contain basic classical monopartite NLSs; these regions are referred to as NLS3 (KRPRKR) and NLS4 (EAERQRREK), respectively. The third domain, between residues 617 and 652, is rich in basic amino acids that are well conserved in other phylogenetically related bHLH transcription factors. Our data revealed that these three domains are inactive when isolated but act cooperatively to target CrMYC2 to the nucleus.</p> <p>Conclusions</p> <p>This study identified three amino acid domains that act in cooperation to target the CrMYC2 transcription factor to the nucleus. Further fine structure/function analysis of these amino acid domains will allow the identification of new NLS domains and will allow the investigation of the related molecular mechanisms involved in the nuclear targeting of the CrMYC2 bHLH transcription factor.</p

Systematic quantification of gene interactions by phenotypic array analysis

A phenotypic array method, developed for quantifying cell growth, was applied to the haploid and homozygous diploid yeast deletion strain sets. A growth index was developed to screen for non-additive interacting effects between gene deletion and induced perturbations. From a genome screen for hydroxyurea (HU) chemical-genetic interactions, 298 haploid deletion strains were selected for further analysis. The strength of interactions was quantified using a wide range of HU concentrations affecting reference strain growth. The selectivity of interaction was determined by comparison with drugs targeting other cellular processes. Bio-modules were defined as gene clusters with shared strength and selectivity of interaction profiles. The functions and connectivity of modules involved in processes such as DNA repair, protein secretion and metabolic control were inferred from their respective gene composition. The work provides an example of, and a general experimental framework for, quantitative analysis of gene interaction networks that buffer cell growth