THE SPEAKER

Sara De Biasi, PhD - Assistant Professor, University of Modena and Reggio Emilia

Sara De Biasi is an Italian immunologist and researcher affiliated with the University of Modena and Reggio Emilia, where she works within the Department of Medical and Surgical Sciences for Children and Adults. She obtained her PhD in Clinical and Experimental Medicine (Immunology) from the same institution and has continued her academic career there, progressing from postdoctoral research to a research and teaching role in general pathology and immunology. Her research focuses on the human immune system, particularly T cell biology and immune responses in conditions such as HIV infection, autoimmune diseases, cancer, and multiple sclerosis. In recent years, De Biasi has been actively involved in investigations related to COVID-19, examining immune markers and vaccine responses, as well as broader immunological mechanisms underlying severe infections and neurological disorders. With over a decade of scientific activity and numerous peer-reviewed publications, she is recognized for her contributions to translational immunology and her role in advancing understanding of immune dysfunction in complex diseases.

WEBINAR SUMMARY

This webinar will present recent advances in translational immunology through the lens of single-cell metabolic profiling, with a particular focus on the scMEP (single-cell Metabolic Profiling) approach. Over the past two years, this framework has enabled the dissection of immune cell heterogeneity by integrating functional and metabolic features at single-cell resolution. The session will explore how immunometabolism shapes immune responses across different contexts, including cancer and autoimmune diseases, highlighting the relationship between metabolic programs, immune cell activation, and disease progression. In addition, emerging insights into vaccine responses will be discussed, with emphasis on the identification of metabolic signatures associated with effective and durable immunity.
 
The webinar will also address the impact of aging on the immune system, examining how metabolic rewiring contributes to immunosenescence and altered immune competence in older individuals. Overall, this talk will provide an overview of how scMEP and multi-omics approaches can advance our understanding of immune regulation and support the development of more precise and personalized strategies in oncology, autoimmunity, and vaccinology.

Learning Objectives:
Participants will learn:
- how to measure metabolic alterations in immune cells by mass cytometry
- why metabolism is important for cell function
- how to predict vaccine response on the basis of metabolic function of immune cells

Who Should Attend:
Computational Biologists/Bioinformaticians, Research Scientists, Trainees (graduate students, postdocs, early-career researchers), Translational Immunologists

Keywords: metabolism, aging, cancer, multiple sclerosis 

CMLE Credit: 1.0

THE SPEAKER

Smita Krishnaswamy, PhD - Professor, Yale University

Smita Krishnaswamy is a Professor of Computer Science and Genetics at Yale University. She is also affiliated with the Program for Applied Mathematics and WTI Institute for NeuroComputation and Machine Intelligence at Yale and an affiliate member of the MILA Quebec AI Institute. Smita's lab works on fundamental deep learning and mathematical machine learning methods for accelerating discovery from biomedical and neuroscientific data. Her work features many methods for generative modeling, graph-based learning, visualization, dynamics modeling and optimal transport as well as multimodal integration of high dimensional data. She has applied her techniques to discovery from cellular, molecular, and imaging data from neuroscience, psychology, stem cell biology, cancer, and immunology. Smita obtained her Ph.D. from the University of Michigan in Computer Science. Smita's work has won several awards including the NSF CAREER Award, Sloan Faculty Fellowship, and Blavatnik Fund for Innovation. Smita teaches deep learning, unsupervised learning, geometry topology in ML and other courses at the intersection of CS and applied math. She also teaches special courses in computational genomics at CGSI (UCLA), CSHL, as well as being a mentor for the Yale SUMRY math REU program.

WEBINAR SUMMARY

In this talk, Dr. Krishnaswamy will cover progress towards building a fundamentally new type of AI scientist that goes beyond orchestrating existing analysis pipelines or selecting among pre-defined tools. Instead, this scientist infers mechanistically plausible generative models of complex, systems-level data by unifying mathematical modeling with deep learning. Unlike current AI scientists, which primarily automate experimental design, literature synthesis, or statistical analysis, our approach seeks to learn an explicit, interpretable model of the underlying system itself. For example, in cellular data, the system infers an abstract but mechanistically grounded model of a cell that could generate the observed molecular measurements. Towards this end I will cover "ingredients" of this that we have been developing including geometric data representations, data shape detection, flow-based models for trajectory inference, and graph and sheaf ODE models for dynamics and perturbation modeling. These tools can then be orchestrated by an LLM agent.

 
Learning Objectives:

Participants will develop an understanding of:
- Representation Learning, Trajectory Inference, Dynamics modeling, AI Scientists, Lab-in-the-loop AI

Who Should Attend:
Computational Biologists/Bioinformaticians, Data Analysts, Educators/Trainers, Industry Scientists (vendor-agnostic, tool developers, method innovators) Research Scientists, Share Resource Laboratory (SRL) Staff,  Trainees (graduate students, postdocs, early-career researchers), Translational Immunologists

Keywords: Representation Learning, Trajectory Inference, Dynamics modeling, AI Scientists, Lab-in-the-loop AI

CMLE Credit: 1.0

Includes recordings of select Scientific Tutorials complimentary for ISAC members and discounted package rate for visitors/non-members. 

Click on the Content tab to see an overview of the sessions included. Earn 2.0 CMLE credits for each session.

Minimum standards and best practices to ensure reproducibility in longitudinal flow cytometry studies
Approaches to Spectral Unmixing Challenges, journey of a detective
Decoding CAR T Dynamics: Flow Cytometry–Driven Insights from Autologous and Allogeneic Trials
How to develop and implement a biosafety plan for a cytometry lab
Key Steps for Assay Standardization across Cytometer Platforms
Meta Logical: Structuring Your Cytometry Data for Cleaner Models and Clearer Insights
Challenging Sample Types in SRL Cores: From Biomedical to Environmental Cytometry
Crimes Against Data Analysis
Panel Gains Without the Pains: Smarter Re-Optimization for High-Parameter Flow
Solutions to SICS --Techniques and Technologies to mitigate Sorter Induced Cellular Stress
Excellence and Integrity in Cytometry Publishing: A Guide for Authors, Reviewers, and Associate Editors
Standardization for Precision: Building Best Practices for Automated Cell Sample Preparation Across Multi-Site Flow Cytometry Labs
Business Intelligence for Flow Cytometry
Navigating SRL Recognition: How to Prepare Your Application
Fundamental Considerations for Quantitative Fluorescence Standardization
CYTO Women: Career Pathways Panel Discussion

Standardization for Precision: Building Best Practices for Automated Cell Sample Preparation Across Multi-Site Flow Cytometry Labs

Presenters:
Lili Wang, PhD, Senior Scientist, National Institute of Standards and Technology
Tom Hayday, PhD, Co-founder and Chief Research Officer, IMU Biosciences
John Ferbas, PhD, Senior Director, Cytometry & Imaging Sciences, Amgen
Raffaello Cimbro, PhD, Director of Flow Cytometry, AstraZeneca

Problem Focus/Summary:

Standardization and reproducibility remain the cornerstone challenges in translating high-dimensional flow cytometry data into clinically meaningful outcomes. Recent multi-institutional efforts led by the NIST Flow Cytometry Consortium have accelerated consensus-building on pre-analytical variables, assay standardization and validation frameworks, and data quality benchmarks.

This tutorial will explore how automation and standards are converging to address these challenges—from sample handling to antibody cocktailing and washing—by minimizing operator-driven variability and enabling traceable, reproducible workflows.

This tutorial will explore:

Define and Apply Reference Process Standards
Integrate Automation into Standardized Workflows
Evaluate Cross-Site Validation Strategies

Keywords: Sample Prep, Protocol standardization, Cytometry Hardware, Experimental Design & controls

CMLE Credit: 1.5

CYTO Women: Career Pathways Panel Discussion

Panelists: 
Arielle Ginsberg, MSc, SCYM, CEO, terraFlow
Kathy Muirhead, PhD COO, SciGro, Inc.
Laura Ferrer-Font, PhD, Scientific Solutions Manager -Scientific Affairs, R&D, Waters Biosciences
Pratip Chattopadhyay, PhD, Founder and CEO, Talon Biomarkers

Unlock the secrets to a fulfilling career in cytometry! Whether you are a student, a postdoc, or a seasoned professional, this essential mentoring session is designed to help you navigate your next chapter within the flow cytometry field. Join distinguished leaders Arielle Ginsberg, Kathy Muirhead, Peter Mage, and Pratip Chattopadhyay as they share firsthand accounts of the career paths, pivots, and breakthroughs that shaped their journeys. Gain actionable strategies for long-term planning and participate in an open Q&A to get personalized advice on your professional development.

Don’t leave your future to chance—come learn how to turn your passion for cytometry into a strategic career roadmap!

Keywords: CYTO, CYTO Women, Career Development

CMLE Credit: 1.5

Fundamental Considerations for Quantitative Fluorescence Standardization

Presenters:
Vera Tang, PhD, Facility Manager & Adjunct Professor, University of Ottawa
Joshua Welsh, PhD, Staff Scientist, BD Biosciences

Problem Focus/Summary:
Standardization of flow cytometry data reporting is necessary for reproducibility irrespective of the sample type across flow cytometry platforms. Cross-platform standardization as a topic is becoming increasingly important in both clinical and academic research settings. Fluorescence quantification is a method used to standardize reporting of flow cytometry data, making intra- and inter-platform comparisons possible. These are published methods, but there are currently a multitude of tools available for fluorescence standardization. In this tutorial we will identify the different tiers of standardization and then provide practical guidance on the tools necessary to achieve these different levels of standardization.

Goals: The purpose of this tutorial is to provide insight and guidance towards selecting methods and materials for fluorescence quantification, aiming to address specific standardization goals, and provide options to achieve concordance in standardized data reporting.

What this Tutorial will not do: Cover pre-acquisition variables – sample isolation/processing, staining optimization, panel design.

Learning Objectives:
To understand the different tiers of flow cytometer assay standardization from longitudinal single instrument studies to cross-platform comparison studies.
To understand the nuance in definitions for fluorescence quantification, calibration, normalization, and standardization.
To understand the practical differences between each of the fluorescence calibration units available, including cost, consistency, and ergonomics.
To demonstrate the impact of different fluorescence units on concordance in comparing cross-platform data, i.e. ERF, MESF, and ABC.

Keywords: Calibration, Quantitative, Fundamental Concepts, Hardware, Standardization, Experimental Design

CMLE Credit: 1.5

Navigating SRL Recognition: How to Prepare Your Application

Presenters:
Jessica Prieto-Chavez, MSc, Co-Coordinator of the Cytometry Network of the Health Research Coordination, Mexican Social Security Institute (IMSS)

Abstract:
The ISAC SRL Recognition Program is a cornerstone initiative to promote quality, reproducibility, and sustainability in shared resource laboratories (SRLs). As participation grows worldwide, many applicants seek clearer guidance on how to prepare strong, well-documented submissions.

This tutorial provides practical, evidence-based insights drawn from real applicant experiences and reviewer feedback. Presenters will highlight common challenges encountered during the Recognition process, typical strengths and weaknesses observed in evaluation reports, and concrete strategies that have helped SRLs achieve success.

Through presentations and an interactive discussion, participants will learn how to:
- Interpret ISAC’s expectations at each application stage.
- Identify internal documentation and quality practices most valued by reviewers.
- Avoid frequent pitfalls that delay or weaken submissions.
- Apply lessons learned from recognized SRLs of different sizes and organizational structures.
- Recognize the tangible and long-term benefits of applying for SRL Recognition — including improved documentation, standardized procedures, and enhanced visibility within the community.

Ultimately, attendees will leave with a clearer understanding of how to plan, structure, and execute their SRL Recognition applications—while also strengthening their lab’s internal processes and culture of continuous improvement.

Learning Objectives:
Describe the structure and evaluation criteria of the ISAC SRL Recognition process.
Recognize common challenges and recurring feedback themes from reviewer reports.
Apply proven strategies and documentation practices that strengthen an SRL Recognition application.
Evaluate their own lab’s readiness and identify steps for sustained quality development beyond application submission.

Keywords: Management, Training and Education, SRL Recognition Program

CMLE Credit: 1.5

Business Intelligence for Flow Cytometry

Presenters:
Antonio Cosma, PhD, Head of the National Cytometry Platform, Luxembourg Institute of Health

Abstract:
The vast amount of data produced by cytometry, along with its accompanying metadata, necessitates the deployment of advanced and innovative tools. These tools must be adapted to manage data sourced from a multitude of origins. They must also be capable of generating visualizations that are specifically tailored for effective data analysis and sharing.  Business Intelligence (BI) addresses all these needs, but it is usually used in the business sector and not in a scientific environment. A critical, not fully recognized aspect of BI is the capability to transfer analytical capabilities to domain experts (i.e., cytometrists) rather than relying on generalized analysts who lack specialized knowledge of the data and the scientific context.

In this tutorial, I will initially lay the basis of data management with a special focus on cytometry. I will show how to organize files for instrument acquisition and introduce the concept of enriched FCS. I will then introduce the concepts of aggregation, joining, filtering, and levels of detail. Once the basis is established, I will proceed to the data preparation and visualization steps. At the end of the tutorial, I will showcase some well-known examples of data sharing already widely used by the cytometry community: (1) the OMIP Cytometry A database, (2) CPHEN Comprehensive Phenotypic Reports, and (3) HCDM CDmap database.

Attendees will learn the principles of BI applied to flow cytometry, enabling them to prepare data and create simple visualizations. The learning curve for BI software is relatively flat, and this introduction will allow participants to get started quickly with their own data.

Keywords: Instrument Monitoring, Bioinformatics, SRL, Shared Resource Laboratories, Operations and Finance, Management

CMLE Credit: 1.5

Excellence and Integrity in Cytometry Publishing: A Guide for Authors, Reviewers, and Associate Editors

Presenters:
Bartek Rajwa, PhD, Editor-in-Chief, Cytometry Part A

Introduction:
For over 40 years, Cytometry Part A – The Journal of Quantitative Cell Science has been the home for innovative research in single-cell analysis, publishing peer-reviewed studies on measurement, separation, manipulation, engineering, and modeling of cells. The journal also covers high-content screening and the molecular mechanisms underlying cellular function. As the field continues to evolve, Cytometry A remains committed to advancing quantitative cell biology and supporting the development of cutting-edge methods for cellular systems analysis.

At the same time, scientific publishing is undergoing rapid changes. The rise of open access, the growth of semi-predatory publishers, the demand for faster review cycles, and the popularity of preprints are reshaping how we share scientific knowledge. These shifts present both challenges and opportunities for Cytometry A. In response, we are expanding our editorial board, strengthening peer review, and broadening our scope to encompass emerging areas such as high-content screening and single-cell omics.

Learning objectives:
By participating in this tutorial, attendees will be able to:

1) Understand and navigate the peer review process for Cytometry Part A, including the workflow from submission to decision, time expectations for reviewers and Associate Editors, and how to craft constructive reviews that strengthen manuscripts.
2) Apply statistical rigor and data quality standards expected for publication, including proper analysis of cytometry data, avoiding common statistical pitfalls, and implementing FAIR data principles with appropriate use of RRIDs and data sharing practices.
3) Evaluate manuscript quality and publication readiness, understanding what distinguishes strong submissions from those likely to be rejected, technical requirements for figures and supplementary data, and how to assess scientific impact, novelty, and significance.
4) Recognize the role and value of OMIP (Optimized Multicolor Immunofluorescence Panel) publications, understanding how these standardized, validated panel descriptions advance reproducibility and serve as community resources for researchers designing multi-parameter cytometry experiments.

Content: 
This tutorial will reintroduce Cytometry A to the ISAC community and explain how members can contribute as reviewers and Associate Editors. We'll examine the practical mechanics of peer review: manuscript evaluation workflow, timelines, time commitments, and how to write constructive, actionable reviews. We'll provide guidance on what distinguishes strong submissions from desk rejections, technical requirements for figures and data files, and when manuscripts are appropriate for Cytometry Part Aversus Part B.

A special focus will be placed on OMIP papers, which document fully validated, ready-to-use multi-parameter panels complete with reagent details, compensation strategies, and gating schemes. OMIPs serve as essential community resources that promote standardization, reproducibility, and facilitate the adoption of complex cytometry approaches. We'll discuss the criteria for OMIP submissions and how these papers differ from standard research articles.

We'll address critical research ethics issues: identifying and managing conflicts of interest, authorship disputes, image manipulation policies, and recognizing red flags for paper mills and data fraud that threaten the peer review system.

We'll also discuss the professional development benefits of serving as a reviewer or Associate Editor: career enhancement, networking opportunities, staying current with emerging methods, and contributing to the scientific community.

Statistical analysis and data representation remain critical areas where submissions often fall short. We'll review common statistical mistakes in cytometry data, including understanding of spectral unmixing, compositional data analysis issues, multiple testing corrections, and appropriate controls. We'll cover standards for reporting statistical methods, data visualization best practices, high-dimensional data representation, validation approaches for computational analyses, and transparency in parameter selection.

Finally, we'll explain how the journal supports FAIR data principles through policies on Research Resource Identifiers (RRIDs), code availability, and data deposition. Throughout the tutorial, we'll emphasize the journal's commitment to scientific impact, novelty, and significance, and welcome questions about any aspect of the submission, review, or editorial process."

Keywords: Publication, Peer Review, Cytometry Part A, Journal, OMIPs

CMLE Credit: 1.5

Solutions to SICS --Techniques and Technologies to mitigate Sorter Induced Cellular Stress

Presenters:
Peter Lopez, BS, Research Associate Professor, NYU Grossman School of Medicine

Abstract:
Purification of cell populations has been an important technique used in biological research since the early 1900's. Various purification techniques provide different levels of specificity and purification, ranging from filtration to purify cells based on size, to flow cytometric techniques delivering high purity of populations differentiated using dozens of phenotypic

markers. The advent of FACS , a flow cytometric purification technique, provided a mainstay purification technique which arguably changed the playing field for cellular purification and facilitated many critical discoveries in biological research. FACS, based on electrostatic droplet deflection, provides highly purified cell populations,. In some cases cells purified by FACS have downstream functional deficits, and depending on cell type may have issues with viability or proliferative capacity. The perturbed performance of purified cells has been described as SICS. This tutorial will review the various forms of SICS, and will then present methods and
technologies including optimization of traditional FACS as well as alternative flow cytometric approaches that can help mitigate SICS.

Learning Objectives:
1-- Learn the history of cell purification technologies, their strengths and weaknesses.
2-- Understand the definition of SICS-- metrics and manifestations.
3– Understand the specific SICS outcomes observed using FACS.
4-- Learn the latest techniques and new purification technologies that help mitigate SICS.

Keywords: Metabolomics, Cell Proliferation and Death, Cell Sorting, Sorting, Sorter, Cell Separation

CMLE Credit: 1.5