“Unblocking” Serum Activity <Emphasis Type="Italic">in vitro</Emphasis> in the Polyoma System may Correlate with Antitumour Effects of Antiserum <Emphasis Type="Italic">in vivo</Emphasis>

In a variety of tumour systems, individuals carrying progressively growing neoplasms have lymphoid cells with a specific cytotoxic effect on cultured tumour cells from the same individual^1–4. Since the sera of tumour-bearing individuals have been shown to prevent tumour cell destruction by immune lymphocytes in vitro^2,5–8 and since this serum blocking activity appears early in primary and transplant tumour development^5,7, it has been suggested that the appearance of this serum blocking activity might be responsible for the progressive growth of tumours in individuals having cytotoxic lymphocytes. Counteraction of this blocking activity would thus be of primary importance in facilitating the function of an already existing or bolstered cell-mediated immunity. The serum blocking activity might be inhibited in various ways, by preventing the formation of blocking antibody or by interfering with its action (“unblocking”), as demonstrated in Moloney sarcoma regressor sera⁹. This type of serum also has a therapeutic effect on Moloney sarcomas in vivo^10,11, which has been tentatively attributed to its unblocking activity^8,9 or, possibly, to a complement-dependent cytotoxicity¹⁰. Tumour growth in the Moloney sarcoma system, however, might be due in part to continuous recruitment of neoplastic cells by virus-induced transformation and so the therapeutic effect could be due to a virus-neutralizing serum activity^9,10.     

On the mechanism of ATP-induced shape changes in the human erythrocyte membranes: the role of ATP

In the preceding paper (Sheetz, M. and S.J. Singer. 1977. J Cell Biol. 73:638-646) it was shown that erythrocyte ghosts undergo pronounced shape changes in the presence of mg-ATP. The biochemical effects of the action of ATP are herein examined. The biochemical effects of the action of ATP are herein examined. Phosphorylation by ATP of spectrin component 2 of the erythrocyte membrane is known to occur. We have shown that it is only membrane protein that is significantly phosphorylated under the conditions where the shape changes are produced. The extent of this phosphorylation rises with increasing ATP concentration, reaching nearly 1 mol phosphoryle group per mole of component 2 at 8mM ATP. Most of this phosphorylation appears to occur at a single site on the protein molecule, according to cyanogen bromide peptide cleavage experiments. The degree of phosphorylation of component 2 is apparently also regulated by a membrane-bound protein phosphatase. This activity can be demonstrated in erythrocyte ghosts prepared from intact cells prelabeled with [(32)P]phosphate. In addition to the phosphorylation of component 2, some phosphorylation of lipids, mainly of phosphatidylinositol, is also known to occur. The ghost shape changes are, however, shown to be correlated with the degree of phosphorylation of component 2. In such experiment, the incorporation of exogenous phosphatases into ghosts reversed the shape changes produced by ATP, or by the membrane-intercalating drug chlorpromazine. The results obtained in this and the preceding paper are consistent with the proposal that the erythrocyte membrane possesses kinase and phosphates activities which produce phosphorylation and dephosphorylation of a specific site on spectrin component 2 molecules; the steady-state level of this phosphorylation regulates the structural state of the spectrin complex on the cytoplasmic surface of the membrane, which in turn exerts an important control on the shape of the cell.     

Selective inhibition of prostaglandin biosynthesis by gold salts and phenylbutazone

Gold salts and phenylbutazone selectively inhibit the synthesis of PGF_2α and PGE₂ respectively. Lowered production of one prostaglandin species is accompanied by an increased production of the other. Selective inhibition by these drugs was observed in the presence of adrenaline, reduced glutathione and copper sulphate under conditions when most anti-inflammatory compounds inhibited PGE₂ and PGF_2α syntheses equally. It is postulated that selective inhibitors may have a different mode of action and beneficial effects may be related to the endogenous ratio of PGE to PGF required for normal function.     

Age‐related ultrastructural changes of the basement membrane in the mouse blood‐brain barrier

The blood‐brain barrier (BBB) is essential for a functional neurovascular unit. Most studies focused on the cells forming the BBB, but very few studied the basement membrane (BM) of brain capillaries in ageing. We used transmission electron microscopy and electron tomography to investigate the BM of the BBB in ageing C57BL/6J mice. The thickness of the BM of the BBB from 24‐month‐old mice was double as compared with that of 6‐month‐old mice (107 nm vs 56 nm). The aged BBB showed lipid droplets gathering within the BM which further increased its thickness (up to 572 nm) and altered its structure. The lipids appeared to accumulate toward the glial side of the BM. Electron tomography showed that the lipid‐rich BM regions are located in small pockets formed by the end‐feet of astrocytes. These findings suggest an imbalance of the lipid metabolism and that may precede the structural alteration of the BM. These alterations may favour the accretion of abnormal proteins that lead to neurodegeneration in ageing. These findings warrant further investigation of the BM of brain capillaries and of adjoining cells as potential targets for future therapies.     

A web server to locate periodicities in a sequence

Summary : FT is a tool written in C++, which implements the Fourier analysis method to locate periodicities in aminoacid or DNA sequences. It is provided for free public use on a WWW server with a Java interface. Availability : The server address is http://o2.db. uoa.gr/FT Contact : shamodr@atlas.uoa.gr      

Heterocellular molecular contacts in the mammalian stem cell niche

Adult tissue homeostasis and repair relies on prompt and appropriate intervention by tissue-specific adult stem cells (SCs). SCs have the ability to self-renew; upon appropriate stimulation, they proliferate and give rise to specialized cells. An array of environmental signals is important for maintenance of the SC pool and SC survival, behavior, and fate. Within this special microenvironment, commonly known as the stem cell niche (SCN), SC behavior and fate are regulated by soluble molecules and direct molecular contacts via adhesion molecules providing connections to local supporting cells and the extracellular matrix. Besides the extensively discussed array of soluble molecules, the expression of adhesion molecules and molecular contacts is another fundamental mechanism regulating niche occupancy and SC mobilization upon activation. Some adhesion molecules are differentially expressed and have tissue-specific consequences, likely reflecting the structural differences in niche composition and design, especially the presence or absence of a stromal counterpart. However, the distribution and identity of intercellular molecular contacts for adhesion and adhesion-mediated signaling within stromal and non-stromal SCN have not been thoroughly studied. This review highlights common details or significant differences in cell-to-cell contacts within representative stromal and non-stromal niches that could unveil new standpoints for stem cell biology and therapy.     

Amiloride does not alter NaCl avoidance in Fischer-344 rats

Fischer-344 (F-344) rats differ from other common rat strains in that they fail to show any preference for NaCl at any concentration in two- bottle preference tests. Because 100 microM amiloride partially blocks the NaCl-evoked chorda tympani (CT) response in electrophysiological studies, we tested NaCl preference (0.068-0.273 M) in F-344 rats with and without 100 microM amiloride solution as the solvent. A third group was tested with unadulterated NaCl solutions following CT transection. Amiloride had no significant effect on the NaCl preference-aversion function, whereas CT transection significantly reduced NaCl avoidance. These results suggest that the amiloride-sensitive component of the NaCl response is not necessary for F-344 rats to display avoidance of NaCl, but the entire CT input is.      

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.