Dendritic cell biology: Current state of the art

The current state of the art in morphometric cell biology is reviewed by looking at the developmental state of stereological methods, and at the approaches used to arrive at quantitative structure-function correlation. Stereological methods have reached a fairly advanced level of sophistication since mathematical stereology has been developed as a branch of geometric probability theory. The application of these methods in cell biology lags behind, both quantitatively and qualitatively. Among the strategies used in exploiting stereological methods in cell biology the physiological approach (where a change is induced experimentally and its effect on the cells is followed by biochemical and morphometric methods) ranks highest and is still valid. More analytical approaches, such as combining stereology and biochemistry in cell fraction studies, are fraught with difficulties. In considering future developments of stereological methods, the emphasis will have to be 1) on developing procedures for eliminating biases such as section thickness or resolution effects, and 2) on increasing the efficiency of the methods by better sampling rules and improved instrumentation. The future trends in morphometric cell biology might best be served by exploiting the potentials of histochemistry and stereology by combining them with a view to 1) establishing procedures for cell-specific sampling and 2) developing methods towards "molecular morphometry" on the basis of immunocytochemical labeling.

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Hypertension: Blood pressure regulating systems: cellular, integrative, and therapeutic aspects

Canadian Journal of Physiology and Pharmacology ◽

10.1139/y87-238 ◽

1987 ◽

Vol 65 (8) ◽

pp. 1515-1515

Author(s):

Paul I. Korner ◽

Frans H. H. Leenen

Keyword(s):

Blood Pressure ◽

Information Exchange ◽

Cell Biology ◽

Large Range ◽

State Of The Art ◽

South Australia ◽

Current State ◽

History Of ◽

Generous Financial Support ◽

Formed Part

This is only the second time in the long history of the International Physiological Congresses that a symposium on hypertension has formed part of the official satellite programme. After the 1983 IUPS Congress in Sydney, John Chalmers organized a magnificent satellite meeting at the Flinders Medical Centre in South Australia and we felt that we wished to continue the "tradition." Hypertension research has provided a wonderful example in recent years of how exciting it can be to apply very basic discoveries to the solution of practical problems. This meeting breaks new ground in being the first scientific event sponsored jointly by the Canadian Hypertension Society and the Australian High Blood Pressure Council. The meeting was made possible by generous financial support from Pfizer Canada and Pfizer Australia with, as co-contributors, Bayer Germany and Sandoz Australia. We would also like to acknowledge the help of Mrs. A. Garat of Pfizer Canada Medical Services in the organization of the meeting and Dr. Andrew Rankin who was responsible for all local arrangements.The Hypertension Satellite was held at Whistler, B.C., July 19–21, 1986, following the 30th International Congress of the International Union of Physiological Sciences in Vancouver. It provided a good forum for interdisciplinary information exchange. It also proved to be a pleasant social occasion in the beautiful setting of the coastal range of the Canadian Rockies. There were 48 invited speakers from Canada, Australia, Europe, the U.S.A., Japan, and New Zealand. We were fortunate in having as our patrons two great names in hypertension research, Dr. Arthur Guyton and Dr. Sydney Friedman.Emphasis was on a large range of mechanisms that regulate blood pressure. There were sessions on cell biology, the kidney, autonomic nervous regulation, peptides (including, of course, atrial natriuretic peptide and arginine vasopressin), and pathogenesis. The proceedings provide an up-to-date account of the position of the current "state of the art" in a number of important areas.

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New Frontiers in Stem Cell Research and Translational Approaches

Biology ◽

10.3390/biology9010011 ◽

2020 ◽

Vol 9 (1) ◽

pp. 11

Author(s):

Nicola Alessio ◽

Dario Siniscalco ◽

Gianfranco Peluso ◽

Umberto Galderisi

Keyword(s):

Stem Cell ◽

Stem Cell Research ◽

Cell Biology ◽

Applied Research ◽

State Of The Art ◽

Research Area ◽

Current State ◽

Challenging Research ◽

Translational Approach ◽

Basic And Applied Research

Stem cell biology represents a challenging research area with a huge potential translational approach. This review focuses on the most recent findings on stem cell basics and clinics in several fields of research, as final outcome of the 10th conference held by Stem Cell Research Italy (SCR Italy) in Naples, Italy in June 2019. Current state-of-the-art and novel findings on stem cell research are discussed, bringing together basic and applied research with the newest insights in stem cell therapy.

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12 Grand Challenges in Single-Cell Data Science

10.7287/peerj.preprints.27885 ◽

2019 ◽

Author(s):

David Laehnemann ◽

Johannes Köster ◽

Ewa Szczurek ◽

Davis J McCarthy ◽

Stephanie C Hicks ◽

...

Keyword(s):

Single Cell ◽

Cell Biology ◽

Data Science ◽

Single Cell Analysis ◽

State Of The Art ◽

Cell Analysis ◽

Open Problems ◽

Single Cell Sequencing ◽

Current State ◽

Cell Data

The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single-Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single-Cell Data Science' for the coming years.

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12 Grand challenges in single-cell data science

10.7287/peerj.preprints.27885v1 ◽

2019 ◽

Cited By ~ 1

Author(s):

David Laehnemann ◽

Johannes Köster ◽

Ewa Szcureck ◽

Davis McCarthy ◽

Stephanie C Hicks ◽

...

Keyword(s):

Single Cell ◽

Cell Biology ◽

Data Science ◽

Single Cell Analysis ◽

State Of The Art ◽

Cell Analysis ◽

Open Problems ◽

Single Cell Sequencing ◽

Current State ◽

Cell Data

The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single Cell Data Science' for the coming years.

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12 Grand Challenges in Single-Cell Data Science

10.7287/peerj.preprints.27885v3 ◽

2019 ◽

Cited By ~ 1

Author(s):

David Laehnemann ◽

Johannes Köster ◽

Ewa Szczurek ◽

Davis J McCarthy ◽

Stephanie C Hicks ◽

...

Keyword(s):

Single Cell ◽

Cell Biology ◽

Data Science ◽

Single Cell Analysis ◽

State Of The Art ◽

Cell Analysis ◽

Open Problems ◽

Single Cell Sequencing ◽

Current State ◽

Cell Data

The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single-Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single-Cell Data Science' for the coming years.

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12 Grand challenges in single-cell data science

10.7287/peerj.preprints.27885v2 ◽

2019 ◽

Author(s):

David Laehnemann ◽

Johannes Köster ◽

Ewa Szczurek ◽

Davis J McCarthy ◽

Stephanie C Hicks ◽

...

Keyword(s):

Single Cell ◽

Cell Biology ◽

Data Science ◽

Single Cell Analysis ◽

State Of The Art ◽

Cell Analysis ◽

Open Problems ◽

Single Cell Sequencing ◽

Current State ◽

Cell Data

The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single Cell Data Science' for the coming years.

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Behavioral Genetics: Concepts for Research and Practice in Language Development and Disorders

Journal of Speech Language and Hearing Research ◽

10.1044/jshr.3805.1126 ◽

1995 ◽

Vol 38 (5) ◽

pp. 1126-1142 ◽

Cited By ~ 14

Author(s):

Jeffrey W. Gilger

Keyword(s):

Language Development ◽

Behavioral Genetics ◽

State Of The Art ◽

Genetic Research ◽

Great Promise ◽

Behavioral Genetic ◽

Fine Grained ◽

Future Goals ◽

Current State ◽

Research Designs

This paper is an introduction to behavioral genetics for researchers and practioners in language development and disorders. The specific aims are to illustrate some essential concepts and to show how behavioral genetic research can be applied to the language sciences. Past genetic research on language-related traits has tended to focus on simple etiology (i.e., the heritability or familiality of language skills). The current state of the art, however, suggests that great promise lies in addressing more complex questions through behavioral genetic paradigms. In terms of future goals it is suggested that: (a) more behavioral genetic work of all types should be done—including replications and expansions of preliminary studies already in print; (b) work should focus on fine-grained, theory-based phenotypes with research designs that can address complex questions in language development; and (c) work in this area should utilize a variety of samples and methods (e.g., twin and family samples, heritability and segregation analyses, linkage and association tests, etc.).

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Schizophrenia Research: Current State of the Art

Contemporary Psychology ◽

10.1037/015267 ◽

1976 ◽

Vol 21 (7) ◽

pp. 497-498

Author(s):

STANLEY GRAND

Keyword(s):

State Of The Art ◽

Current State

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Umbral Calculus

The Electronic Journal of Combinatorics ◽

10.37236/24 ◽

2002 ◽

Vol 1000 ◽

Author(s):

A. Di Bucchianico ◽

D. Loeb

Keyword(s):

19Th Century ◽

Finite Differences ◽

State Of The Art ◽

Umbral Calculus ◽

Current State ◽

Logical Foundation ◽

Complete Bibliography ◽

The 19Th Century ◽

Mathematical Literature

We survey the mathematical literature on umbral calculus (otherwise known as the calculus of finite differences) from its roots in the 19th century (and earlier) as a set of “magic rules” for lowering and raising indices, through its rebirth in the 1970’s as Rota’s school set it on a firm logical foundation using operator methods, to the current state of the art with numerous generalizations and applications. The survey itself is complemented by a fairly complete bibliography (over 500 references) which we expect to update regularly.

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