Quinic acid derivatives from Pimpinella brachycarpa exert anti-neuroinflammatory activity in lipopolysaccharide-induced microglia

Five new quinic acid derivatives (1–5), together with 10 known quinic acid derivatives (6–15), were isolated from the MeOH extract of Pimpinella brachycarpa (Umbelliferae). Their structures were established on the basis of spectroscopic analyses including extensive 2D NMR studies (COSY, HMQC and HMBC). Isolated compounds 1–15 were evaluated for their inhibitory activities on nitric oxide (NO) production in an activated murine microglial cell line. Compounds 2, 3, 8 and 11 significantly inhibited NO production without high cell toxicity in lipopolysaccharide (LPS)-activated BV-2 cells, a microglia cell line (IC₅₀ = 4.66, 12.52, 9.04 and 12.11 μM, respectively).     

Immunogenicity of a Trivalent Human Papillomavirus L1 DNA-Encapsidated,Non-Replicable Baculovirus Nanovaccine

Previously, we developed a non-replicating recombinant baculovirus coated with human endogenous retrovirus envelope protein (AcHERV) for enhanced cellular delivery of human papillomavirus (HPV) 16L1 DNA. Here, we report the immunogenicity of an AcHERV-based multivalent HPV nanovaccine in which the L1 segments of HPV 16, 18, and 58 genes were inserted into a single baculovirus genome of AcHERV. To test whether gene expression levels were affected by the order of HPV L1 gene insertion, we compared the efficacy of bivalent AcHERV vaccines with the HPV 16L1 gene inserted ahead of the 18L1 gene (AcHERV-HP16/18L1) with that of AcHERV with the HPV 18L1 gene inserted ahead of the 16L1 gene (AcHERV-HP18/16L1). Regardless of the order, the bivalent AcHERV DNA vaccines retained the immunogenicity of monovalent AcHERV-HP16L1 and AcHERV-HP18L1 DNA vaccines. Moreover, the immunogenicity of bivalent AcHERV-HP16/18L1 was not significantly different from that of AcHERV-HP18/16L1. In challenge tests, both bivalent vaccines provided complete protection against HPV 16 and 18 pseudotype viruses. Extending these results, we found that a trivalent AcHERV nanovaccine encoding HPV 16L1, 18L1, and 58L1 genes (AcHERV-HP16/18/58L1) provided high levels of humoral and cellular immunogenicity against all three subtypes. Moreover, mice immunized with the trivalent AcHERV-based nanovaccine were protected from challenge with HPV 16, 18, and 58 pseudotype viruses. These results suggest that trivalent AcHERV-HPV16/18/58L1 could serve as a potential prophylactic baculoviral nanovaccine against concurrent infection with HPV 16, 18, and 58.     

Resolving the micro-heterogeneity and structural integrity of monoclonal antibodies by hybrid mass spectrometric approaches

For therapeutic monoclonal antibodies (mAbs), detailed analysis of the structural integrity and heterogeneity, which results from multiple types of post-translational modifications (PTMs), is relevant to various processes, including product characterization, storage stability and quality control. Despite the recent rapid development of new bioanalytical techniques, it is still challenging to completely characterize the proteoform profile of a mAb. As a nearly indispensable tool in mAb analysis, mass spectrometry (MS) provides unique structural information at multiple levels. Here, we tested a hybrid strategy for the comprehensive characterization of micro-heterogeneity by integrating 2 state-of-the-art MS-based approaches, high-resolution native MS and targeted glycan profiling, to perform complementary analysis at the intact protein level and released glycan level, respectively. We compared the performance of these methods using samples of engineered half-body IgG4s and a panel of mAbs approved for human use. The glycosylation characterization data derived from these approaches were found to be mutually consistent in composition profiling, and complementary in identification and relative-quantitation of low-abundant uncommon glycoforms. In addition, multiple other sources of micro-heterogeneity, such as glycation, lack of glycosylation, and loss of light chains, could be detected by this approach, and the contribution of multiple types of modifications to the overall micro-heterogeneity could be assessed using our superposition algorithm. Our data demonstrate that the hybrid strategy allows reliable and thorough characterization of mAbs, revealing product characteristics that would easily be missed if only a single approach were used.     

Human rhinovirus C infection is associated with asthma in children determined by xTAG respiratory viral panel FAST

<正>Dear Editor,Cumulative evidence supports the role of early-life viral infections,especially respiratory syncytial virus(RSV)and human rhinovirus(HRV),as major antecedents of childhood asthma(Lemanske,2002;Jackson et al.,2008).In this study,the x TAG respiratory viral panel FAST(RVP FAST)assay,a multiplex polymerase chain reaction(PCR)-based method(Arens et al.,2010;BaladaLlasat et al.,2011;Gharabaghi et al.,2011;Selvaraju,2012),was used to investigate the association of infec-     

A Modified Valley Restrained Monte Carlo Method to Efficiently Search the Low Energy Structures of Peptides

Abstract

A new Monte Carlo sampling scheme, namely the Modified Valley Restrained Monte Carlo procedure, is used to obtain the global energy minimum conformations for polypeptides, such as Met-enkephalin and Melittin. For each peptide, we found close agreement with previous results from both theoretical and experimental studies. The simple idea for controlling the step size according to the Valley Function, provides useful suggestions in searching the global energy minimum structures, and furthermore helps solve the multiple minima problem.     

Intermittent Hypoxia Can Aggravate Motor Neuronal Loss and Cognitive Dysfunction in ALS Mice

Background

Patients with ALS may be exposed to variable degrees of chronic intermittent hypoxia. However, all previous experimental studies on the effects of hypoxia in ALS have only used a sustained hypoxia model and it is possible that chronic intermittent hypoxia exerts effects via a different molecular mechanism from that of sustained hypoxia. No study has yet shown that hypoxia (either chronic intermittent or sustained) can affect the loss of motor neurons or cognitive function in an in vivo model of ALS.

Objective

To evaluate the effects of chronic intermittent hypoxia on motor and cognitive function in ALS mice.

Methods

Sixteen ALS mice and 16 wild-type mice were divided into 2 groups and subjected to either chronic intermittent hypoxia or normoxia for 2 weeks. The effects of chronic intermittent hypoxia on ALS mice were evaluated using the rotarod, Y-maze, and wire-hanging tests. In addition, numbers of motor neurons in the ventral horn of the spinal cord were counted and western blot analyses were performed for markers of oxidative stress and inflammatory pathway activation.

Results

Compared to ALS mice kept in normoxic conditions, ALS mice that experienced chronic intermittent hypoxia had poorer motor learning on the rotarod test, poorer spatial memory on the Y-maze test, shorter wire hanging time, and fewer motor neurons in the ventral spinal cord. Compared to ALS-normoxic and wild-type mice, ALS mice that experienced chronic intermittent hypoxia had higher levels of oxidative stress and inflammation.

Conclusions

Chronic intermittent hypoxia can aggravate motor neuronal death, neuromuscular weakness, and probably cognitive dysfunction in ALS mice. The generation of oxidative stress with activation of inflammatory pathways may be associated with this mechanism. Our study will provide insight into the association of hypoxia with disease progression, and in turn, the rationale for an early non-invasive ventilation treatment in patients with ALS.     

Indigo production in hairy root cultures of Polygonum tinctorium Lour.

The transformed root culture of Polygonum tinctorium Lour. was established by infecting leaf explants with Agrobacterium rhizogenes A4. These cultures were examined for their growth and indigo content under various culture conditions. Among the four different culture media tested, SH medium showed the highest yield for root growth (28 mg dry wt/30 ml) and indigo production (152 g/dry wt). In SH medium, 30 g sucrose l^–1, 2500 mg KNO₃ l^–1, 300 mg NH₄H₂PO₄ l^–1 were the best conditions for indigo production at pH 5.7. The production of indigo in hairy roots slightly increased with the addition of 200 mg chitosan l^–1 (186 g/dry wt) and 20 U pectinase l^–1 (181 g/dry wt).     

MicroRNA-206 has a bright application prospect in the diagnosis of cases with oral cancer

Previous studies have shown that microRNA-206 (miR-206) exhibits anti-tumour properties in various tumours. Nevertheless, diagnostic significance of miR-206 in oral cancer is still poorly known. Our research was carried out to explore the performance of miR-206 in the diagnosis of oral cancer. Quantitative real-time polymerase chain reaction (qRT-PCR) method was adopted to measure the level of miR-206 in serum specimens from oral cancer cases and control individuals. Chi-square test was performed to analyse the correlation between miR-206 level and clinicopathological parameters of the cases. Receiver operating characteristic (ROC) curve was constituted to assess diagnostic accuracy of miR-206 in oral cancer. Serum miR-206 level in oral cancer patients was significantly lower than that in control individuals (P < .001). miR-206 expression was obviously related to T classification (P = .033), TNM stage (P = .008) and lymph node metastasis (P = .028). The area under the curve (AUC) of the ROC curve was 0.846 (95% CI = 0.797-0.896, P < .001) with a specificity of 72.7% and a sensitivity of 81.2%. It revealed that miR-206 might be a non-invasive indicator in differentiating oral cancer cases from control individuals. Down-regulation of miR-206 is related to the development of oral cancer. Serum miR-206 might be an effective indicator for early detection of oral cancer.     

High concentration of sodium chloride could induce the viable and culturable states of Escherichia coli O157:H7 and Salmonella enterica serovar Enteritidis

In the present study, Escherichia coli O157:H7 and Salmonella enterica serovar Enteritidis were transferred into Luria–Bertani medium without NaCl (LBWS) and adjusted to various pHs (4, 5, 6 and 7) with lactic acid containing 0·75, 5, 10 and 30% NaCl, and stored at 25°C until the bacterial populations reached below detectable levels on tryptic soy agar (TSA). Although E. coli O157:H7 and S. Enteritidis did not grow on TSA when incubated in LBWS with 30% NaCl for 35 and 7 days, more than 60 and 70% of the bacterial cells were shown to be viable via fluorescent staining with SYTO9 and propidium iodide (PI), respectively, suggesting that a number of cells could be induced into the viable but nonculturable (VBNC) state. These bacteria that were induced into a VBNC state were transferred to a newly prepared tryptic soy broth (TSB) and then incubated at 37°C for several days. After more than 7 days, E. coli O157:H7 and S. Enteritidis regained their culturability. We, therefore, suggest that E. coli O157:H7 and S. Enteritidis entered the VBNC state under the adverse condition of higher salt concentrations and were revived when these conditions were reversed.     

A field guide to cultivating computational biology

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.

Do you want to attract computational biologists to your project or to your department? Despite the major contributions of computational biology, those attempting to bridge the interdisciplinary gap often languish in career advancement, publication, and grant review. Here, sixteen computational biologists around the globe present "A field guide to cultivating computational biology," focusing on solutions.

Biology in the digital era requires computation and collaboration. A modern research project may include multiple model systems, use multiple assay technologies, collect varying data types, and require complex computational strategies, which together make effective design and execution difficult or impossible for any individual scientist. While some labs, institutions, funding bodies, publishers, and other educators have already embraced a team science model in computational biology and thrived [1–7], others who have not yet fully adopted it risk severely lagging behind the cutting edge. We propose a general solution: “deep integration” between biology and the computational sciences. Many different collaborative models can yield deep integration, and different problems require different approaches (Fig 1).Open in a separate windowFig 1Supporting interdisciplinary team science will accelerate biological discoveries.Scientists who have little exposure to different fields build silos, in which they perform science without external input. To solve hard problems and to extend your impact, collaborate with diverse scientists, communicate effectively, recognize the importance of core facilities, and embrace research parasitism. In biologically focused parasitism, wet lab biologists use existing computational tools to solve problems; in computationally focused parasitism, primarily dry lab biologists analyze publicly available data. Both strategies maximize the use and societal benefit of scientific data.In this article, we define computational science extremely broadly to include all quantitative approaches such as computer science, statistics, machine learning, and mathematics. We also define biology broadly, including any scientific inquiry pertaining to life and its many complications. A harmonious deep integration between biology and computer science requires action—we outline 10 immediate calls to action in this article and aim our speech directly at individual scientists, institutions, funding agencies, and publishers in an attempt to shift perspectives and enable action toward accepting and embracing computational biology as a mature, necessary, and inevitable discipline (Box 1).Box 1. Ten calls to action for individual scientists, funding bodies, publishers, and institutions to cultivate computational biology. Many actions require increased funding support, while others require a perspective shift. For those actions that require funding, we believe convincing the community of need is the first step toward agencies and systems allocating sufficient support

1. Respect collaborators’ specific research interests and motivationsProblem: Researchers face conflicts when their goals do not align with collaborators. For example, projects with routine analyses provide little benefit for computational biologists.Solution: Explicit discussion about interests/expertise/goals at project onset.Opportunity: Clearly defined expectations identify gaps, provide commitment to mutual benefit.
2. Seek necessary input during project design and throughout the project life cycleProblem: Modern research projects require multiple experts spanning the project’s complexity.Solution: Engage complementary scientists with necessary expertise throughout the entire project life cycle.Opportunity: Better designed and controlled studies with higher likelihood for success.
3. Provide and preserve budgets for computational biologists’ workProblem: The perception that analysis is “free” leads to collaborator budget cuts.Solution: When budget cuts are necessary, ensure that they are spread evenly.Opportunity: More accurate, reproducible, and trustworthy computational analyses.
4. Downplay publication author order as an evaluation metric for computational biologistsProblem: Computational biologist roles on publications are poorly understood and undervalued.Solution: Journals provide more equitable opportunities, funding bodies and institutions improve understanding of the importance of team science, scientists educate each other.Opportunity: Engage more computational biologist collaborators, provide opportunities for more high-impact work.
5. Value software as an academic productProblem: Software is relatively undervalued and can end up poorly maintained and supported, wasting the time put into its creation.Solution: Scientists cite software, and funding bodies provide more software funding opportunities.Opportunity: More high-quality maintainable biology software will save time, reduce reimplementation, and increase analysis reproducibility.
6. Establish academic structures and review panels that specifically reward team scienceProblem: Current mechanisms do not consistently reward multidisciplinary work.Solution: Separate evaluation structures to better align peer review to reward indicators of team science.Opportunity: More collaboration to attack complex multidisciplinary problems.
7. Develop and reward cross-disciplinary training and mentoringProblem: Academic labs and institutions are often insufficiently equipped to provide training to tackle the next generation of biological problems, which require computational skills.Solution: Create better training programs aligned to necessary on-the-job skills with an emphasis on communication, encourage wet/dry co-mentorship, and engage younger students to pursue computational biology.Opportunity: Interdisciplinary students uncover important insights in their own data.
8. Support computing and experimental infrastructure to empower computational biologistsProblem: Individual computational labs often fund suboptimal cluster computing systems and lack access to data generation facilities.Solution: Institutions can support centralized compute and engage core facilities to provide data services.Opportunity: Time and cost savings for often overlooked administrative tasks.
9. Provide incentives and mechanisms to share open data to empower discovery through reanalysisProblem: Data are often siloed and have untapped potential.Solution: Provide institutional data storage with standardized identifiers and provide separate funding mechanisms and publishing venues for data reuse.Opportunity: Foster new breed of researchers, “research parasites,” who will integrate multimodal data and enhance mechanistic insights.
10. Consider infrastructural, ethical, and cultural barriers to clinical data accessProblem: Identifiable health data, which include sensitive information that must be kept hidden, are distributed and disorganized, and thus underutilized.Solution: Leadership must enforce policies to share deidentifiable data with interoperable metadata identifiers.Opportunity: Derive new insights from multimodal data integration and build datasets with increased power to make biological discoveries.