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Research Objectives – Types, Examples and Writing Guide

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Research Objectives

Research Objectives

Research objectives refer to the specific goals or aims of a research study. They provide a clear and concise description of what the researcher hopes to achieve by conducting the research . The objectives are typically based on the research questions and hypotheses formulated at the beginning of the study and are used to guide the research process.

Types of Research Objectives

Here are the different types of research objectives in research:

  • Exploratory Objectives: These objectives are used to explore a topic, issue, or phenomenon that has not been studied in-depth before. The aim of exploratory research is to gain a better understanding of the subject matter and generate new ideas and hypotheses .
  • Descriptive Objectives: These objectives aim to describe the characteristics, features, or attributes of a particular population, group, or phenomenon. Descriptive research answers the “what” questions and provides a snapshot of the subject matter.
  • Explanatory Objectives : These objectives aim to explain the relationships between variables or factors. Explanatory research seeks to identify the cause-and-effect relationships between different phenomena.
  • Predictive Objectives: These objectives aim to predict future events or outcomes based on existing data or trends. Predictive research uses statistical models to forecast future trends or outcomes.
  • Evaluative Objectives : These objectives aim to evaluate the effectiveness or impact of a program, intervention, or policy. Evaluative research seeks to assess the outcomes or results of a particular intervention or program.
  • Prescriptive Objectives: These objectives aim to provide recommendations or solutions to a particular problem or issue. Prescriptive research identifies the best course of action based on the results of the study.
  • Diagnostic Objectives : These objectives aim to identify the causes or factors contributing to a particular problem or issue. Diagnostic research seeks to uncover the underlying reasons for a particular phenomenon.
  • Comparative Objectives: These objectives aim to compare two or more groups, populations, or phenomena to identify similarities and differences. Comparative research is used to determine which group or approach is more effective or has better outcomes.
  • Historical Objectives: These objectives aim to examine past events, trends, or phenomena to gain a better understanding of their significance and impact. Historical research uses archival data, documents, and records to study past events.
  • Ethnographic Objectives : These objectives aim to understand the culture, beliefs, and practices of a particular group or community. Ethnographic research involves immersive fieldwork and observation to gain an insider’s perspective of the group being studied.
  • Action-oriented Objectives: These objectives aim to bring about social or organizational change. Action-oriented research seeks to identify practical solutions to social problems and to promote positive change in society.
  • Conceptual Objectives: These objectives aim to develop new theories, models, or frameworks to explain a particular phenomenon or set of phenomena. Conceptual research seeks to provide a deeper understanding of the subject matter by developing new theoretical perspectives.
  • Methodological Objectives: These objectives aim to develop and improve research methods and techniques. Methodological research seeks to advance the field of research by improving the validity, reliability, and accuracy of research methods and tools.
  • Theoretical Objectives : These objectives aim to test and refine existing theories or to develop new theoretical perspectives. Theoretical research seeks to advance the field of knowledge by testing and refining existing theories or by developing new theoretical frameworks.
  • Measurement Objectives : These objectives aim to develop and validate measurement instruments, such as surveys, questionnaires, and tests. Measurement research seeks to improve the quality and reliability of data collection and analysis by developing and testing new measurement tools.
  • Design Objectives : These objectives aim to develop and refine research designs, such as experimental, quasi-experimental, and observational designs. Design research seeks to improve the quality and validity of research by developing and testing new research designs.
  • Sampling Objectives: These objectives aim to develop and refine sampling techniques, such as probability and non-probability sampling methods. Sampling research seeks to improve the representativeness and generalizability of research findings by developing and testing new sampling techniques.

How to Write Research Objectives

Writing clear and concise research objectives is an important part of any research project, as it helps to guide the study and ensure that it is focused and relevant. Here are some steps to follow when writing research objectives:

  • Identify the research problem : Before you can write research objectives, you need to identify the research problem you are trying to address. This should be a clear and specific problem that can be addressed through research.
  • Define the research questions : Based on the research problem, define the research questions you want to answer. These questions should be specific and should guide the research process.
  • Identify the variables : Identify the key variables that you will be studying in your research. These are the factors that you will be measuring, manipulating, or analyzing to answer your research questions.
  • Write specific objectives: Write specific, measurable objectives that will help you answer your research questions. These objectives should be clear and concise and should indicate what you hope to achieve through your research.
  • Use the SMART criteria: To ensure that your research objectives are well-defined and achievable, use the SMART criteria. This means that your objectives should be Specific, Measurable, Achievable, Relevant, and Time-bound.
  • Revise and refine: Once you have written your research objectives, revise and refine them to ensure that they are clear, concise, and achievable. Make sure that they align with your research questions and variables, and that they will help you answer your research problem.

Example of Research Objectives

Examples of research objectives Could be:

Research Objectives for the topic of “The Impact of Artificial Intelligence on Employment”:

  • To investigate the effects of the adoption of AI on employment trends across various industries and occupations.
  • To explore the potential for AI to create new job opportunities and transform existing roles in the workforce.
  • To examine the social and economic implications of the widespread use of AI for employment, including issues such as income inequality and access to education and training.
  • To identify the skills and competencies that will be required for individuals to thrive in an AI-driven workplace, and to explore the role of education and training in developing these skills.
  • To evaluate the ethical and legal considerations surrounding the use of AI for employment, including issues such as bias, privacy, and the responsibility of employers and policymakers to protect workers’ rights.

When to Write Research Objectives

  • At the beginning of a research project : Research objectives should be identified and written down before starting a research project. This helps to ensure that the project is focused and that data collection and analysis efforts are aligned with the intended purpose of the research.
  • When refining research questions: Writing research objectives can help to clarify and refine research questions. Objectives provide a more concrete and specific framework for addressing research questions, which can improve the overall quality and direction of a research project.
  • After conducting a literature review : Conducting a literature review can help to identify gaps in knowledge and areas that require further research. Writing research objectives can help to define and focus the research effort in these areas.
  • When developing a research proposal: Research objectives are an important component of a research proposal. They help to articulate the purpose and scope of the research, and provide a clear and concise summary of the expected outcomes and contributions of the research.
  • When seeking funding for research: Funding agencies often require a detailed description of research objectives as part of a funding proposal. Writing clear and specific research objectives can help to demonstrate the significance and potential impact of a research project, and increase the chances of securing funding.
  • When designing a research study : Research objectives guide the design and implementation of a research study. They help to identify the appropriate research methods, sampling strategies, data collection and analysis techniques, and other relevant aspects of the study design.
  • When communicating research findings: Research objectives provide a clear and concise summary of the main research questions and outcomes. They are often included in research reports and publications, and can help to ensure that the research findings are communicated effectively and accurately to a wide range of audiences.
  • When evaluating research outcomes : Research objectives provide a basis for evaluating the success of a research project. They help to measure the degree to which research questions have been answered and the extent to which research outcomes have been achieved.
  • When conducting research in a team : Writing research objectives can facilitate communication and collaboration within a research team. Objectives provide a shared understanding of the research purpose and goals, and can help to ensure that team members are working towards a common objective.

Purpose of Research Objectives

Some of the main purposes of research objectives include:

  • To clarify the research question or problem : Research objectives help to define the specific aspects of the research question or problem that the study aims to address. This makes it easier to design a study that is focused and relevant.
  • To guide the research design: Research objectives help to determine the research design, including the research methods, data collection techniques, and sampling strategy. This ensures that the study is structured and efficient.
  • To measure progress : Research objectives provide a way to measure progress throughout the research process. They help the researcher to evaluate whether they are on track and meeting their goals.
  • To communicate the research goals : Research objectives provide a clear and concise description of the research goals. This helps to communicate the purpose of the study to other researchers, stakeholders, and the general public.

Advantages of Research Objectives

Here are some advantages of having well-defined research objectives:

  • Focus : Research objectives help to focus the research effort on specific areas of inquiry. By identifying clear research questions, the researcher can narrow down the scope of the study and avoid getting sidetracked by irrelevant information.
  • Clarity : Clearly stated research objectives provide a roadmap for the research study. They provide a clear direction for the research, making it easier for the researcher to stay on track and achieve their goals.
  • Measurability : Well-defined research objectives provide measurable outcomes that can be used to evaluate the success of the research project. This helps to ensure that the research is effective and that the research goals are achieved.
  • Feasibility : Research objectives help to ensure that the research project is feasible. By clearly defining the research goals, the researcher can identify the resources required to achieve those goals and determine whether those resources are available.
  • Relevance : Research objectives help to ensure that the research study is relevant and meaningful. By identifying specific research questions, the researcher can ensure that the study addresses important issues and contributes to the existing body of knowledge.

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How to Develop a Good Research Question? — Types & Examples

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Cecilia is living through a tough situation in her research life. Figuring out where to begin, how to start her research study, and how to pose the right question for her research quest, is driving her insane. Well, questions, if not asked correctly, have a tendency to spiral us!

Image Source: https://phdcomics.com/

Questions lead everyone to answers. Research is a quest to find answers. Not the vague questions that Cecilia means to answer, but definitely more focused questions that define your research. Therefore, asking appropriate question becomes an important matter of discussion.

A well begun research process requires a strong research question. It directs the research investigation and provides a clear goal to focus on. Understanding the characteristics of comprising a good research question will generate new ideas and help you discover new methods in research.

In this article, we are aiming to help researchers understand what is a research question and how to write one with examples.

Table of Contents

What Is a Research Question?

A good research question defines your study and helps you seek an answer to your research. Moreover, a clear research question guides the research paper or thesis to define exactly what you want to find out, giving your work its objective. Learning to write a research question is the beginning to any thesis, dissertation , or research paper. Furthermore, the question addresses issues or problems which is answered through analysis and interpretation of data.

Why Is a Research Question Important?

A strong research question guides the design of a study. Moreover, it helps determine the type of research and identify specific objectives. Research questions state the specific issue you are addressing and focus on outcomes of the research for individuals to learn. Therefore, it helps break up the study into easy steps to complete the objectives and answer the initial question.

Types of Research Questions

Research questions can be categorized into different types, depending on the type of research you want to undergo. Furthermore, knowing the type of research will help a researcher determine the best type of research question to use.

1. Qualitative Research Question

Qualitative questions concern broad areas or more specific areas of research. However, unlike quantitative questions, qualitative research questions are adaptable, non-directional and more flexible. Qualitative research question focus on discovering, explaining, elucidating, and exploring.

i. Exploratory Questions

This form of question looks to understand something without influencing the results. The objective of exploratory questions is to learn more about a topic without attributing bias or preconceived notions to it.

Research Question Example: Asking how a chemical is used or perceptions around a certain topic.

ii. Predictive Questions

Predictive research questions are defined as survey questions that automatically predict the best possible response options based on text of the question. Moreover, these questions seek to understand the intent or future outcome surrounding a topic.

Research Question Example: Asking why a consumer behaves in a certain way or chooses a certain option over other.

iii. Interpretive Questions

This type of research question allows the study of people in the natural setting. The questions help understand how a group makes sense of shared experiences with regards to various phenomena. These studies gather feedback on a group’s behavior without affecting the outcome.

Research Question Example: How do you feel about AI assisting publishing process in your research?

2. Quantitative Research Question

Quantitative questions prove or disprove a researcher’s hypothesis through descriptions, comparisons, and relationships. These questions are beneficial when choosing a research topic or when posing follow-up questions that garner more information.

i. Descriptive Questions

It is the most basic type of quantitative research question and it seeks to explain when, where, why, or how something occurred. Moreover, they use data and statistics to describe an event or phenomenon.

Research Question Example: How many generations of genes influence a future generation?

ii. Comparative Questions

Sometimes it’s beneficial to compare one occurrence with another. Therefore, comparative questions are helpful when studying groups with dependent variables.

Example: Do men and women have comparable metabolisms?

iii. Relationship-Based Questions

This type of research question answers influence of one variable on another. Therefore, experimental studies use this type of research questions are majorly.

Example: How is drought condition affect a region’s probability for wildfires.  

How to Write a Good Research Question?

good research question

1. Select a Topic

The first step towards writing a good research question is to choose a broad topic of research. You could choose a research topic that interests you, because the complete research will progress further from the research question. Therefore, make sure to choose a topic that you are passionate about, to make your research study more enjoyable.

2. Conduct Preliminary Research

After finalizing the topic, read and know about what research studies are conducted in the field so far. Furthermore, this will help you find articles that talk about the topics that are yet to be explored. You could explore the topics that the earlier research has not studied.

3. Consider Your Audience

The most important aspect of writing a good research question is to find out if there is audience interested to know the answer to the question you are proposing. Moreover, determining your audience will assist you in refining your research question, and focus on aspects that relate to defined groups.

4. Generate Potential Questions

The best way to generate potential questions is to ask open ended questions. Questioning broader topics will allow you to narrow down to specific questions. Identifying the gaps in literature could also give you topics to write the research question. Moreover, you could also challenge the existing assumptions or use personal experiences to redefine issues in research.

5. Review Your Questions

Once you have listed few of your questions, evaluate them to find out if they are effective research questions. Moreover while reviewing, go through the finer details of the question and its probable outcome, and find out if the question meets the research question criteria.

6. Construct Your Research Question

There are two frameworks to construct your research question. The first one being PICOT framework , which stands for:

  • Population or problem
  • Intervention or indicator being studied
  • Comparison group
  • Outcome of interest
  • Time frame of the study.

The second framework is PEO , which stands for:

  • Population being studied
  • Exposure to preexisting conditions
  • Outcome of interest.

Research Question Examples

  • How might the discovery of a genetic basis for alcoholism impact triage processes in medical facilities?
  • How do ecological systems respond to chronic anthropological disturbance?
  • What are demographic consequences of ecological interactions?
  • What roles do fungi play in wildfire recovery?
  • How do feedbacks reinforce patterns of genetic divergence on the landscape?
  • What educational strategies help encourage safe driving in young adults?
  • What makes a grocery store easy for shoppers to navigate?
  • What genetic factors predict if someone will develop hypothyroidism?
  • Does contemporary evolution along the gradients of global change alter ecosystems function?

How did you write your first research question ? What were the steps you followed to create a strong research question? Do write to us or comment below.

Frequently Asked Questions

Research questions guide the focus and direction of a research study. Here are common types of research questions: 1. Qualitative research question: Qualitative questions concern broad areas or more specific areas of research. However, unlike quantitative questions, qualitative research questions are adaptable, non-directional and more flexible. Different types of qualitative research questions are: i. Exploratory questions ii. Predictive questions iii. Interpretive questions 2. Quantitative Research Question: Quantitative questions prove or disprove a researcher’s hypothesis through descriptions, comparisons, and relationships. These questions are beneficial when choosing a research topic or when posing follow-up questions that garner more information. Different types of quantitative research questions are: i. Descriptive questions ii. Comparative questions iii. Relationship-based questions

Qualitative research questions aim to explore the richness and depth of participants' experiences and perspectives. They should guide your research and allow for in-depth exploration of the phenomenon under investigation. After identifying the research topic and the purpose of your research: • Begin with Broad Inquiry: Start with a general research question that captures the main focus of your study. This question should be open-ended and allow for exploration. • Break Down the Main Question: Identify specific aspects or dimensions related to the main research question that you want to investigate. • Formulate Sub-questions: Create sub-questions that delve deeper into each specific aspect or dimension identified in the previous step. • Ensure Open-endedness: Make sure your research questions are open-ended and allow for varied responses and perspectives. Avoid questions that can be answered with a simple "yes" or "no." Encourage participants to share their experiences, opinions, and perceptions in their own words. • Refine and Review: Review your research questions to ensure they align with your research purpose, topic, and objectives. Seek feedback from your research advisor or peers to refine and improve your research questions.

Developing research questions requires careful consideration of the research topic, objectives, and the type of study you intend to conduct. Here are the steps to help you develop effective research questions: 1. Select a Topic 2. Conduct Preliminary Research 3. Consider Your Audience 4. Generate Potential Questions 5. Review Your Questions 6. Construct Your Research Question Based on PICOT or PEO Framework

There are two frameworks to construct your research question. The first one being PICOT framework, which stands for: • Population or problem • Intervention or indicator being studied • Comparison group • Outcome of interest • Time frame of the study The second framework is PEO, which stands for: • Population being studied • Exposure to preexisting conditions • Outcome of interest

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research topic objectives and questions

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Research Questions & Hypotheses

Generally, in quantitative studies, reviewers expect hypotheses rather than research questions. However, both research questions and hypotheses serve different purposes and can be beneficial when used together.

Research Questions

Clarify the research’s aim (farrugia et al., 2010).

  • Research often begins with an interest in a topic, but a deep understanding of the subject is crucial to formulate an appropriate research question.
  • Descriptive: “What factors most influence the academic achievement of senior high school students?”
  • Comparative: “What is the performance difference between teaching methods A and B?”
  • Relationship-based: “What is the relationship between self-efficacy and academic achievement?”
  • Increasing knowledge about a subject can be achieved through systematic literature reviews, in-depth interviews with patients (and proxies), focus groups, and consultations with field experts.
  • Some funding bodies, like the Canadian Institute for Health Research, recommend conducting a systematic review or a pilot study before seeking grants for full trials.
  • The presence of multiple research questions in a study can complicate the design, statistical analysis, and feasibility.
  • It’s advisable to focus on a single primary research question for the study.
  • The primary question, clearly stated at the end of a grant proposal’s introduction, usually specifies the study population, intervention, and other relevant factors.
  • The FINER criteria underscore aspects that can enhance the chances of a successful research project, including specifying the population of interest, aligning with scientific and public interest, clinical relevance, and contribution to the field, while complying with ethical and national research standards.
  • The P ICOT approach is crucial in developing the study’s framework and protocol, influencing inclusion and exclusion criteria and identifying patient groups for inclusion.
  • Defining the specific population, intervention, comparator, and outcome helps in selecting the right outcome measurement tool.
  • The more precise the population definition and stricter the inclusion and exclusion criteria, the more significant the impact on the interpretation, applicability, and generalizability of the research findings.
  • A restricted study population enhances internal validity but may limit the study’s external validity and generalizability to clinical practice.
  • A broadly defined study population may better reflect clinical practice but could increase bias and reduce internal validity.
  • An inadequately formulated research question can negatively impact study design, potentially leading to ineffective outcomes and affecting publication prospects.

Checklist: Good research questions for social science projects (Panke, 2018)

research topic objectives and questions

Research Hypotheses

Present the researcher’s predictions based on specific statements.

  • These statements define the research problem or issue and indicate the direction of the researcher’s predictions.
  • Formulating the research question and hypothesis from existing data (e.g., a database) can lead to multiple statistical comparisons and potentially spurious findings due to chance.
  • The research or clinical hypothesis, derived from the research question, shapes the study’s key elements: sampling strategy, intervention, comparison, and outcome variables.
  • Hypotheses can express a single outcome or multiple outcomes.
  • After statistical testing, the null hypothesis is either rejected or not rejected based on whether the study’s findings are statistically significant.
  • Hypothesis testing helps determine if observed findings are due to true differences and not chance.
  • Hypotheses can be 1-sided (specific direction of difference) or 2-sided (presence of a difference without specifying direction).
  • 2-sided hypotheses are generally preferred unless there’s a strong justification for a 1-sided hypothesis.
  • A solid research hypothesis, informed by a good research question, influences the research design and paves the way for defining clear research objectives.

Types of Research Hypothesis

  • In a Y-centered research design, the focus is on the dependent variable (DV) which is specified in the research question. Theories are then used to identify independent variables (IV) and explain their causal relationship with the DV.
  • Example: “An increase in teacher-led instructional time (IV) is likely to improve student reading comprehension scores (DV), because extensive guided practice under expert supervision enhances learning retention and skill mastery.”
  • Hypothesis Explanation: The dependent variable (student reading comprehension scores) is the focus, and the hypothesis explores how changes in the independent variable (teacher-led instructional time) affect it.
  • In X-centered research designs, the independent variable is specified in the research question. Theories are used to determine potential dependent variables and the causal mechanisms at play.
  • Example: “Implementing technology-based learning tools (IV) is likely to enhance student engagement in the classroom (DV), because interactive and multimedia content increases student interest and participation.”
  • Hypothesis Explanation: The independent variable (technology-based learning tools) is the focus, with the hypothesis exploring its impact on a potential dependent variable (student engagement).
  • Probabilistic hypotheses suggest that changes in the independent variable are likely to lead to changes in the dependent variable in a predictable manner, but not with absolute certainty.
  • Example: “The more teachers engage in professional development programs (IV), the more their teaching effectiveness (DV) is likely to improve, because continuous training updates pedagogical skills and knowledge.”
  • Hypothesis Explanation: This hypothesis implies a probable relationship between the extent of professional development (IV) and teaching effectiveness (DV).
  • Deterministic hypotheses state that a specific change in the independent variable will lead to a specific change in the dependent variable, implying a more direct and certain relationship.
  • Example: “If the school curriculum changes from traditional lecture-based methods to project-based learning (IV), then student collaboration skills (DV) are expected to improve because project-based learning inherently requires teamwork and peer interaction.”
  • Hypothesis Explanation: This hypothesis presumes a direct and definite outcome (improvement in collaboration skills) resulting from a specific change in the teaching method.
  • Example : “Students who identify as visual learners will score higher on tests that are presented in a visually rich format compared to tests presented in a text-only format.”
  • Explanation : This hypothesis aims to describe the potential difference in test scores between visual learners taking visually rich tests and text-only tests, without implying a direct cause-and-effect relationship.
  • Example : “Teaching method A will improve student performance more than method B.”
  • Explanation : This hypothesis compares the effectiveness of two different teaching methods, suggesting that one will lead to better student performance than the other. It implies a direct comparison but does not necessarily establish a causal mechanism.
  • Example : “Students with higher self-efficacy will show higher levels of academic achievement.”
  • Explanation : This hypothesis predicts a relationship between the variable of self-efficacy and academic achievement. Unlike a causal hypothesis, it does not necessarily suggest that one variable causes changes in the other, but rather that they are related in some way.

Tips for developing research questions and hypotheses for research studies

  • Perform a systematic literature review (if one has not been done) to increase knowledge and familiarity with the topic and to assist with research development.
  • Learn about current trends and technological advances on the topic.
  • Seek careful input from experts, mentors, colleagues, and collaborators to refine your research question as this will aid in developing the research question and guide the research study.
  • Use the FINER criteria in the development of the research question.
  • Ensure that the research question follows PICOT format.
  • Develop a research hypothesis from the research question.
  • Ensure that the research question and objectives are answerable, feasible, and clinically relevant.

If your research hypotheses are derived from your research questions, particularly when multiple hypotheses address a single question, it’s recommended to use both research questions and hypotheses. However, if this isn’t the case, using hypotheses over research questions is advised. It’s important to note these are general guidelines, not strict rules. If you opt not to use hypotheses, consult with your supervisor for the best approach.

Farrugia, P., Petrisor, B. A., Farrokhyar, F., & Bhandari, M. (2010). Practical tips for surgical research: Research questions, hypotheses and objectives.  Canadian journal of surgery. Journal canadien de chirurgie ,  53 (4), 278–281.

Hulley, S. B., Cummings, S. R., Browner, W. S., Grady, D., & Newman, T. B. (2007). Designing clinical research. Philadelphia.

Panke, D. (2018). Research design & method selection: Making good choices in the social sciences.  Research Design & Method Selection , 1-368.

  • Frontiers in Cell and Developmental Biology
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Cytoskeletal Networks in the Spatiotemporal Regulation of Metabolism and Disease

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About this Research Topic

The cytoskeleton, particularly the actomyosin network, plays a fundamental role in the spatial and temporal regulation of cellular processes, including metabolism and disease progression. This intricate system of fibers not only provides structural support but also coordinates signaling networks that influence membrane dynamics, thereby affecting the entire cell's behavior. The actomyosin cytoskeleton, through its dynamic interactions with various cellular components, is pivotal in the spatiotemporal regulation of metabolic pathways, directly impacting energy production and bioenergetics. These regulatory mechanisms are essential for maintaining cellular homeostasis and responding to environmental changes. Dysfunctions in these processes can lead to altered metabolic states and contribute to the onset and progression of diseases. Understanding how the cytoskeletal networks modulate metabolism in a spatial and temporal manner offers valuable insights into the complex interplay between cellular structure, function, and disease, opening new avenues for targeted therapeutic strategies. The primary goal of this research topic is to elucidate the complex mechanisms by which cytoskeletal networks, particularly the actomyosin cytoskeleton, regulate metabolism and influence disease progression through spatiotemporal dynamics. This objective addresses the critical gap in understanding the bidirectional interactions between cytoskeletal architecture and metabolic signaling pathways. Achieving this goal involves integrating recent advances in imaging techniques, molecular biology, and bioinformatics to dissect the intricate relationships between cytoskeletal organization, signaling networks, and membrane dynamics. By focusing on the actomyosin cytoskeleton's role in mediating metabolic responses and energy production, this research aims to uncover novel regulatory mechanisms that could inform the development of therapeutic strategies for metabolic disorders and diseases characterized by cytoskeletal dysfunctions. Furthermore, it seeks to advance our understanding of bioenergetics by exploring how changes in the cytoskeletal network affect cellular metabolism and contribute to disease pathology. Collaborative efforts across disciplines will be pivotal in achieving a comprehensive understanding of these complex systems, ultimately leading to innovative approaches to modulate cytoskeletal and metabolic functions for disease intervention. This Research Topic aims to explore the multifaceted roles of cytoskeletal networks in the spatiotemporal regulation of metabolism and disease progression. We welcome contributions that delve into the interactions between the actomyosin cytoskeleton, signaling networks, membrane dynamics, and their collective impact on metabolic processes, bioenergetics, and disease progression. Specific themes of interest include but are not limited to the molecular mechanisms underlying cytoskeletal regulation of metabolism, the influence of cytoskeletal dynamics on cellular energy production, and the contribution of cytoskeletal alterations to disease pathology. We encourage the submission of both original research articles that present new experimental data and theoretical models, as well as comprehensive review articles that summarize recent advances and outline future directions in the field. By bringing together insights from across these themes, this Research Topic aims to shed light on novel regulatory pathways and offer potential targets for therapeutic intervention in metabolic and cytoskeletal-related diseases.

Keywords : Actomyosin Cytoskeleton, Signaling Networks, Membrane Dynamics, Spatiotemporal Regulation, Metabolism, Energy Production, Bioenergetics, Disease Progression

Important Note : All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Manuscripts can be submitted to this Research Topic via the following journals:

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Harvard Staff Writer

Researchers publish largest-ever dataset of neural connections

A cubic millimeter of brain tissue may not sound like much. But considering that that tiny square contains 57,000 cells, 230 millimeters of blood vessels, and 150 million synapses, all amounting to 1,400 terabytes of data, Harvard and Google researchers have just accomplished something stupendous.   

Led by Jeff Lichtman, the Jeremy R. Knowles Professor of Molecular and Cellular Biology and newly appointed dean of science , the Harvard team helped create the largest 3D brain reconstruction to date, showing in vivid detail each cell and its web of connections in a piece of temporal cortex about half the size of a rice grain.

Published in Science, the study is the latest development in a nearly 10-year collaboration with scientists at Google Research, combining Lichtman’s electron microscopy imaging with AI algorithms to color-code and reconstruct the extremely complex wiring of mammal brains. The paper’s three first co-authors are former Harvard postdoc Alexander Shapson-Coe, Michał Januszewski of Google Research, and Harvard postdoc Daniel Berger.

The ultimate goal, supported by the National Institutes of Health BRAIN Initiative , is to create a comprehensive, high-resolution map of a mouse’s neural wiring, which would entail about 1,000 times the amount of data the group just produced from the 1-cubic-millimeter fragment of human cortex.  

“The word ‘fragment’ is ironic,” Lichtman said. “A terabyte is, for most people, gigantic, yet a fragment of a human brain — just a minuscule, teeny-weeny little bit of human brain — is still thousands of terabytes.”  

Headshot of Jeff Lichtman.

Jeff Lichtman.

Kris Snibbe/Harvard Staff Photographer

The latest map contains never-before-seen details of brain structure, including a rare but powerful set of axons connected by up to 50 synapses. The team also noted oddities in the tissue, such as a small number of axons that formed extensive whorls. Because the sample was taken from a patient with epilepsy, the researchers don’t know whether such formations are pathological or simply rare.

Lichtman’s field is connectomics, which seeks to create comprehensive catalogs of brain structure, down to individual cells. Such completed maps would unlock insights into brain function and disease, about which scientists still know very little.

Google’s state-of-the-art AI algorithms allow for reconstruction and mapping of brain tissue in three dimensions. The team has also developed a suite of publicly available tools researchers can use to examine and annotate the connectome.

“Given the enormous investment put into this project, it was important to present the results in a way that anybody else can now go and benefit from them,” said Google collaborator Viren Jain.

Next the team will tackle the mouse hippocampal formation, which is important to neuroscience for its role in memory and neurological disease.

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Taking RNAi from interesting science to impactful new treatments

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There are many hurdles to clear before a research discovery becomes a life-changing treatment for patients. That’s especially true when the treatments being developed represent an entirely new class of medicines. But overcoming those obstacles can revolutionize our ability to treat diseases.

Few companies exemplify that process better than Alnylam Pharmaceuticals. Alnylam was founded by a group of MIT-affiliated researchers who believed in the promise of a technology — RNA interference, or RNAi.

The researchers had done foundational work to understand how RNAi, which is a naturally occurring process, works to silence genes through the degradation of messenger RNA. But it was their decision to found Alnylam in 2002 that attracted the funding and expertise necessary to turn their discoveries into a new class of medicines. Since that decision, Alnylam has made remarkable progress taking RNAi from an interesting scientific discovery to an impactful new treatment pathway.

Today Alnylam has five medicines approved by the U.S. Food and Drug Administration (one Alnylam-discovered RNAi therapeutic is licensed to Novartis) and a rapidly expanding clinical pipeline. The company’s approved medicines are for debilitating, sometimes fatal conditions that many patients have grappled with for decades with few other options.

The company estimates its treatments helped more than 5,000 patients in 2023 alone. Behind that number are patient stories that illustrate how Alnylam has changed lives. A mother of three says Alnylam’s treatments helped her take back control of her life after being bed-ridden with attacks associated with the rare genetic disease acute intermittent porphyria (AIP). Another patient reported that one of the company’s treatments helped her attend her daughter’s wedding. A third patient, who had left college due to frequent AIP attacks, was able to return to school.

These days Alnylam is not the only company developing RNAi-based medicines. But it is still a pioneer in the field, and the company’s founders — MIT Institute Professor Phil Sharp, Professor David Bartel, Professor Emeritus Paul Schimmel, and former MIT postdocs Thomas Tuschl and Phillip Zamore — see Alnylam as a champion for the field more broadly.

“Alnylam has published more than 250 scientific papers over 20 years,” says Sharp, who currently serves as chair of Alnylam’s scientific advisory board. “Not only did we do the science, not only did we translate it to benefit patients, but we also described every step. We established this as a modality to treat patients, and I’m very proud of that record.”

Pioneering RNAi development

MIT’s involvement in RNAi dates back to its discovery. Before Andrew Fire PhD ’83 shared a Nobel Prize for the discovery of RNAi in 1998, he worked on understanding how DNA was transcribed into RNA, as a graduate student in Sharp’s lab.

After leaving MIT, Fire and collaborators showed that double-stranded RNA could be used to silence specific genes in worms. But the biochemical mechanisms that allowed double-stranded RNA to work were unknown until MIT professors Sharp, Bartel, and Ruth Lehmann, along with Zamore and Tuschl, published foundational papers explaining the process. The researchers developed a system for studying RNAi and showed how RNAi can be controlled using different genetic sequences. Soon after Tuschl left MIT, he showed that a similar process could also be used to silence specific genes in human cells, opening up a new frontier in studying genes and ultimately treating diseases.

“Tom showed you could synthesize these small RNAs, transfect them into cells, and get a very specific knockdown of the gene that corresponded to that the small RNAs,” Bartel explains. “That discovery transformed biological research. The ability to specifically knockdown a mammalian gene was huge. You could suddenly study the function of any gene you were interested in by knocking it down and seeing what happens. … The research community immediately started using that approach to study the function of their favorite genes in mammalian cells.”

Beyond illuminating gene function, another application came to mind.

“Because almost all diseases are related to genes, could we take these small RNAs and silence genes to treat patients?” Sharp remembers wondering.

To answer the question, the researchers founded Alnylam in 2002. (They recruited Schimmel, a biotech veteran, around the same time.) But there was a lot of work to be done before the technology could be tried in patients. The main challenge was getting RNAi into the cytoplasm of the patients’ cells.

“Through work in Dave Bartel and Phil Sharp's lab, among others, it became evident that to make RNAi into therapies, there were three problems to solve: delivery, delivery, and delivery,” says Alnylam Chief Scientific Officer Kevin Fitzgerald, who has been with the company since 2005.

Early on, Alnylam collaborated with MIT drug delivery expert and Institute Professor Bob Langer. Eventually, Alnylam developed the first lipid nanoparticles (LNPs) that could be used to encase RNA and deliver it into patient cells. LNPs were later used in the mRNA vaccines for Covid-19.

“Alnylam has invested over 20 years and more than $4 billion in RNAi to develop these new therapeutics,” Sharp says. “That is the means by which innovations can be translated to the benefit of society.”

From scientific breakthrough to patient bedside

Alnylam received its first FDA approval in 2018 for treatment of the polyneuropathy of hereditary transthyretin-mediated amyloidosis, a rare and fatal disease. It doubled as the first RNAi therapeutic to reach the market and the first drug approved to treat that condition in the United States.

“What I keep in mind is, at the end of the day for certain patients, two months is everything,” Fitzgerald says. “The diseases that we’re trying to treat progress month by month, day by day, and patients can get to a point where nothing is helping them. If you can move their disease by a stage, that’s huge.”

Since that first treatment, Alnylam has updated its RNAi delivery system — including by conjugating small interfering RNAs to molecules that help them gain entry to cells — and earned approvals to treat other rare genetic diseases along with high cholesterol (the treatment licensed to Novartis). All of those treatments primarily work by silencing genes that encode for the production of proteins in the liver, which has proven to be the easiest place to deliver RNAi molecules. But Alnylam’s team is confident they can deliver RNAi to other areas of the body, which would unlock a new world of treatment possibilities. The company has reported promising early results in the central nervous system and says a phase one study last year was the first RNAi therapeutic to demonstrate gene silencing in the human brain.

“There’s a lot of work being done at Alnylam and other companies to deliver these RNAis to other tissues: muscles, immune cells, lung cells, etc.,” Sharp says. “But to me the most interesting application is delivery to the brain. We think we have a therapeutic modality that can very specifically control the activity of certain genes in the nervous system. I think that’s extraordinarily important, for diseases from Alzheimer’s to schizophrenia and depression.”

The central nervous system work is particularly significant for Fitzgerald, who watched his father struggle with Parkinson’s.

“Our goal is to be in every organ in the human body, and then combinations of organs, and then combinations of targets within individual organs, and then combinations of targets within multi-organs,” Fitzgerald says. “We’re really at the very beginning of what this technology is going do for human health.”

It’s an exciting time for the RNAi scientific community, including many who continue to study it at MIT. Still, Alnylam will need to continue executing in its drug development efforts to deliver on that promise and help an expanding pool of patients.

“I think this is a real frontier,” Sharp says. “There’s major therapeutic need, and I think this technology could have a huge impact. But we have to prove it. That’s why Alnylam exists: to pursue new science that unlocks new possibilities and discover if they can be made to work. That, of course, also why MIT is here: to improve lives.”

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