COVID | data analysis (new CAAT 4.3 release)

WARNING. I am not a medical doctor nor an epidemiologist. The analysis I am sharing here is only for the data geeks around that are curious. Please follow the advice of your national authorities and health system.


I have just published a new release of CAAT, Matlab code to analyse Johns Hopkins dataset on the SARS-CoV-2 pandemics. The usual caveat is that data is likely to be underestimates. Underestimation does not occur only because of lack of transparency but most of the times because of differences in definitions of COVID-related fatalities and efficiency of reporting systems across countries. For example, using the excess mortality statistics we know that about 30-50% under reporting is rather physiological because of deaths occurring outside the hospital settings or because people might die positive to COVID but not for COVID. This also accounted to a significant adjustment of statistics we have noticed in the past in Hubei. However, changes over time within a country might be more reliable and, therefore, there is still something to learn from this data.

I started analyzing data when the UK government decided to drop the policies set up for containment of SARS-CoV-2. Now that data has been extensively discussed in the UK, I curate CAAT only for others that would like to explore the data. However, at this release it is worth mentioning just the main observation. While the first acute phase of the pandemics is subsiding in Europe and Northern America, it is now flaring in South America at worrying pace.

Relative fatalities in the population at risk for each country. This is a new visualization I provide. Both bar graphs are ordered according to the values shown to the right, i.e. the fraction of the population at risk who has already died. At the right, the weekly rate of fatalities during the current week and the preceding two weeks. Those countries that, so far, has experienced high casualties are showing a significant reduction of weekly fatalities showing the positive effects of policies aimed to contain the virus.

Commenting out line 362 ‘d_ord = p_ord;’, you can order the weekly rate of fatalities according to the last week. This might reveal which are the countries at most risk now. Several South American countries are topping this list. In Brazil, Ecuador and Peru, about 0.5% of the population at risk died during the last week and, sadly is several countries this rate is accelerating.
Let’s also focus on some good news. This is one of the several plots hard coded in CAAT, comparing Italy, UK, Germany, Denmark and Sweden. As it is well established by now, new fatalities are dropping significantly and lock-down measures are gradually abandoned in favor of social distancing measures. The individual outbreaks started at different times and at different rates. Comparisons between countries are therefore difficult but the effectiveness of policies within countries can be evaluated. If you were interested in different graphs or comments, let me know but I will not elaborate more on this at this stage.
This graph is a bit of a mess but I present it for completeness. In North America lock-down measures are having a clear effect. In South America we see alarming increases. As I do not follow South American politics and specific news, I can’t draw conclusions, but it is evident that – assuming no change in reporting occurred, Argentina has slowed down the outbreak but not yet put it under control.

Although I have explained this before, I should probably clarify how I evaluate the population at risk. To estimate how many people might die in each country in the (unrealistic) scenario where everyone would get ill, I used the age-dependent fatality rates published in The Lancet by Ferguson’s group and multiplied these values with the demographics of each country as reported by the UN.

Tackling cancer heterogeneity by live single-cell ‘systems biology’.

NOTE: This assay is the introduction to my research vision I wrote five years ago but that did not make into the programme grant we wrote. I think this is still current and, as it is unlikely I will publish this text, I am releasing it in the public domain with very little editing. I should note, particularly, that some paragraph remains unreferenced.

The genome, biochemical networks and phenotypes | Somatic mutations and gene copy number variations (CNVs) accumulate over time, stochastically altering the abundance and the functions of gene products. At first glance, efforts to identify and characterize somatic mutations provided a comparatively simple model: a few hundreds genes (proto-oncogenes and tumour suppressor genes) are often mutated contributing mechanistically to tumourigenesis (driver mutations). Some driver mutations are very frequent, but driver mutations that are less frequent in a cancer type overall dominate in number within an individual tumour, presumably conferring a more subtle growth advantage than others taken individually [1,2]. Also CNVs are very common in cancer. Sometimes, a clear role of CNVs in tumourigenesis can be established; most of the times, however, the effects of CNVs are difficult to predict or characterize because of the very different possible dependencies between phenotype and concentration of a gene products (e.g., haplo-insufficiency, quasi-sufficiency, triplo-sufficiency, etc.) [3,4]. Concentration effects and “subtle driver mutations” complicate the interpretation of genomic studies and may be best described by a continuum model for tumorogenesis where the all-or-none effects of individual genomic alterations are the frequent exception rather than the rule [4,5]. Notwithstanding the invaluable insights that genomics studies have provided and will continue to provide in our understanding of cancer, diagnostics and therapy, the role of these genomic alterations in tumorogenesis will be better understood in the context of the alteration of molecular networks underlying the respective cancer-associated phenotypes [1,6].

Few phenotypes are selected by mutation, those that enable cancer evolution [7] by increasing clonal heterogeneity (by genetic mutation, aneuploidy or epigenetic instability) and that permit growing in a hostile environment (avoidance of immunosurvaillance, metabolic deregulation and stromal hijacking). Moreover, cell survival, cell fate determination and, later in cancer evolution, cell migration are the key phenotypes that make of cancer the devastating diseases it is. Genomic alterations select for these phenotypes by influencing a comparatively small number of biochemical networks. Indeed, cancer-associated somatic mutations cluster in pathways controlling cell-cycle or cell-death, RAS/PI3K/MAPK, TGFβ, APC, STAT, NOTCH, WNT, HH and mTor [1,4,7]. Unsurprisingly, somatic evolution of cancer reshapes a comparatively small number of biochemical pathways that control cellular and tissue homeostasis to offset, often in a subtle manner, the net proliferative rate of cells. The study of these pathways is no less daunting than the understanding of complex genomic alterations. However, biochemical networks have evolved to exhibit robustness in the presence of intrinsic noise present in biological systems (e.g. stochastic variations in transcription or cytokines concentrations). Robustness of biochemical pathways permit to stably encode for cellular functions and cellular states. It is therefore conceivable that the myriads of possible genomic alterations and individual gene-products simply concur to generate a discrete set of biochemical states corresponding to cancer-associated phenotypes.

Other “big data disciplines” (e.g., transcriptomics, proteomics and metabolomics) have provided the opportunity to study the working mechanisms of biological systems alongside genomics. Some groups have suggested that integrative biology [8,9], the effort to integrate data from these various disciplines, may permit avoiding the biases and inherent flows of individual –omics techniques and, at the same time, may deliver a new approach to the study of human disease. This approach is summarized by the term “network medicine” highlighting that molecular networks altered in disease can be both the target for future therapeutic strategies and the possible source of novel biomarkers. A biochemical network, common to many different cell types or even species, exhibit a different “network utilization” in different physiological and pathological contexts. Mutations can therefore offset the utilization of molecular networks and their dynamics. On the one hand, better understanding of how networks encode functional states and cellular decisions under physiological conditions and how these are altered in disease will offer more and better targeted therapeutic opportunities. On the other hand, defining cancer-associated network utilizations and engineering tools (probes and instrumentation) to reveal them will provide fundamental insights to optimize patient stratification for improved theranostics and prognostics.

Heterogeneity, causality and phenotypes | Phenotypic heterogeneity, including genetic and epigenetic polymorphism, and polyphenism, is at the basis of both unicellular and complex lifeforms. These three levels of phenotypic heterogeneity are recapitulated in cancer and constitute often insurmountable obstacles to effective therapeutic intervention. Intra-tumour heterogeneity, either within the primary tumour, within a metastasis or between different metastatic foci is indeed the primary cause for the emergence of drug resistance and tumour relapse. The genetic basis for phenotypic heterogeneity within a tumour is rather established. However, other non-genetic factors can be regarded as equally important.

For instance, upon treatment, a fraction of tumour often exhibit drug resistance. In part, this can be caused by pre-existing tumour cell clones carrying mutations that, by chance, will confer resistance to any given drug. Alternatively, this may be caused by tumour initiating cancer cells, stem-like cells that are usually quiescent, less vulnerable to treatment and that can regenerate the tumour upon termination of the therapy. Moreover, non-Darwinian mechanisms for the emergence of drug resistance have been proposed as well, whereby cells trigger a transient drug-resistant phenotype that, in time, can be then converted to a stable inheritable state by subsequent somatic evolution.  Fractional killing may also be explained by non-genetic heterogeneity. For instance, Spencer et al. have shown that in a clonal population of cells, TRAIL elicits a heterogeneous phenotypic response with cells undergoing apoptosis at different times or surviving indefinitely. The authors elegantly demonstrate that this phenomenon is caused by stochastic variations in the abundances of the many proteins involved in the apoptotic molecular network.

Genomics, transcriptomics, proteomics and metabolomics allow the characterization of tens of thousands of biomolecules at the same time. Furthermore, the increasing sensitivity of these techniques provides – or may provide in the future –  single cell “–omics” characterization. However, the invasiveness of these techniques will limit their applications to the study of individual time points. Thus, causality can be established only by inference. Techniques capable to provide low invasiveness and biochemical information on living cells are thus extremely useful to complement models derived by ‑omics techniques and to provide a tool for testing hypothesis derived from analysis of big data.

It is thus evident that time-lapse imaging of individual living cells with biochemical information is strategic for the understanding of the heterogeneous response of biological systems and to establish causality between biochemical events and cellular decisions. At the same time, genetic heterogeneity within a tumour and between tumours induces differences in network utilizations with significant consequences for prognosis and treatment. Also in this context, biochemical imaging techniques are necessary to understand the phenotypic heterogeneity of a tumour and, at the same time, may be useful to define network-based biomarkers.

The next generation of Systems Biology | Several groups have identified the need to integrate fluorescence microscopy in the systems level study of the cell and organisms [10-15]. The term “Systems Microscopy” has been suggested for the description of microscopy tools applied to this field [14]. In order to strategically complement other approaches, Systems Microscopy has to deliver single cell resolution, temporal characterization of living cells and high quality quantitative data and has to be applied to the most appropriate biological context (e.g., for epithelial cancers, adherent 2D, 3D, organotypic cultures or in vivo rather than in suspension or cellular homogenates) [10]. Whereas –omic techniques can sample the biological space over the fullness of biochemical moieties (genes, RNAs, proteins, metabolites) albeit with poor sampling of individual cellular behaviours and spatio-temporal organization, Systems Microscopy samples the fullness of the spatio-temporal organization of molecular networks but reports about a limited number of gene products or biochemical events [10]. Therefore, Systems Microscopy elegantly complements big data studies.   

We envisage two (not mutually exclusive) approaches to Systems Microscopy: high throughput screening platforms and single cell biochemical multiplexing. High Content Screening (HCS, also known as imaging cytometry or high throughput imaging) is the current tool of choice for Systems Microscopy. Relying on robotics, automation and unsupervised or semi-supervised data analysis, HCS enables the screening of large numbers of cellular perturbations (e.g., siRNA or compound libraries) with commercial instrumentation making the correlation of these perturbations with morphological estimators and fluorescent markers possible. Several groups have also highlighted the importance of integrating quantitative biophysical imaging techniques such as Fluorescence Correlation Spectroscopy (FCS) and Foerster Resonance Energy Transfer (FRET) in Systems Microscopy in order to deliver data of high quality. Despite this, HCS has been integrated with these techniques only in a few academic-based efforts [16-19]. HCS expands the sampling of biological space of imaging technologies to deliver another set of “big data” but with single cell resolution.

We are pursuing a different approach to Systems Microscopy that maps in space and time an increasing number of fluorescent markers within the living cell. Fluorescence is not amenable to the simultaneous detection of many fluorescent molecules because of the broad excitation and emission spectra of common fluorophores. Therefore, we are determined to develop new techniques (bioprobes and instruments) that exploit all properties of light (photon arrival times, colour and polarization) efficiently to maximize the biochemical resolving power of microscopy. We aim to monitor nodes of molecular networks (e.g., quantifying the dynamic phosphorylation of several substrates) in living cells in response to stimuli, discerning between physiological and pathological (oncogene-driven) network behaviour (topology). The integration of Optogenetics tools (e.g., light-inducible oncogenic signalling) enables perturbational analysis of biochemical networks and facilitates the execution of complex biochemical imaging assays fully automated with no requirement for sample manipulation other than by light. Therefore, these techniques will be strategic for the study of biological networks at low throughput with high quality data; thanks to this all-optical approach, they may also be integrated with HCS increasing the quality and quantity of information and decreasing steps in chemical manipulations of the samples (e.g., addition of doxycycline to stimulate the expression of a gene)

[1] Vogelstein et al. (2013) “Cancer Genome Landscapes” Science
[2] Wood et al. (2007) “The genomic landscapes of human breast and colorectal cancers” Science
[3] Solimini et al. (2012) “Recurrent hemizygous deletions in cancers may optimize proliferative potential.” Science
[4] Davoli et al. (2013) “Cumulative Haploinsufficiency and Triplosensitivity Drive Aneuploidy Patterns to Shape the Cancer Genome” Cell
[5] Berger et al. (2011) “A continuum model for tumour suppression.” Nature
[6] Jorgensen&Linding (2010) “Simplistic pathways or complex networks?” Current Opinions in Genetics and Development
[7] Hanahan&Weinberg (2010) “Hallmarks of Cancer: The Next Generation” Cell
[8] Erler&Linding (2010) “Network-based drug and biomarkers” J Pathology
[9] Barbasi et al (2011) “Network Medicine: A Network-based Approach to Human Disease” Nat Rev Genet
[10] Megason et al. (2007) “Imaging in Systems Biology” Cell
[11] Verveer&Bastiaens (2008) “Quantitative microscopy and systems biology” Histochem Cell Biol
[12] Ankers et al. (2008) “Spatio-temporal protein dynamics in single living cells” Current Opinion in Biotechnology
[13] Pepperkok&Ellenberg (2006) “High-throughput fluorescence microscopy for systems biology” NAt Rev Mol Cell Biol
[14] Lock&Stromblad (2010) “Systems microscopy: An emerging strategy for the life sciences” Exp Cell Res
[15] Conrad&Gerlich (2009) “Automated microscopy for high-content
RNAi screening” J Cell Biol
[16] Esposito et al. (2007) “Unsupervised fluorescence lifetime imaging microscopy for high content and high throughput screening” Mol Cell Proteomics
[17] Mathews et al. (2008) “A high-content screening platform utilizing polarization anisotropy and FLIM microscopy” SPIE BIOS
[18] Talbot et al. (2008) “High speed unsupervised fluorescence lifetime imaging confocal multiwell plate reader for high content analysis” J Biophotonics
[19] Barber et al. (2013) “The Gray Institute ‘open’ high‐content, fluorescence lifetime microscopes” J Microsc

Our superpower is you (first draft)

This is a preliminary draft for a leaflet aimed at outreach events. Following the work we have done on Women in STEM at the last year Cambridge Science Festival, this year we’ll add a second leaflet to be more inclusive. This will be a word search puzzle that we will release into the public domain for your peruse. The idea is to have a list of people to include different genders, ethnicities, sexual orientations and disabilities. While my team is working on the graphics and the production of the leaflet, I prepared the first draft of the name list. As I believe it can be certainly improved  I wished to ask for suggestions and criticism.  

The message: “There is not much in common among these inspirational people, no colour, no gender, no physical ability. Hard working and smart, nothing else defines a scientist. A scientist is someone like you.”

Alan Turing (1912-1954),  Mathematician, a founder of Theory of Computation

Florence Nightingale (1820-1910), Social reformer and statistician, the founder of modern nursing. nurse

Neil Divine (1939-1994), Astrophysicist, a major contributor to the modern theory of
star formation.

Lynn Ann Conway (1938), Computer scientist and electrical engineer. Pioneer in electronics and computing.

George Washington Carver (1860-1943), Agricultural scientist and inventor. Promoted alternative crops to cotton and methods to prevent soil depletion.

Ernest Everett Just (1883–1941), Biologist, a pioneer in the studies of fertilization and early development,

Stephen Hawking (1942-2018), Theoretical physicist and cosmologist, a pioneer in the modern theory of cosmology and black holes.

Edwin Krebs (1918-2009), Biochemist. Pioneering work on post-translational modification of proteins and cell regulation.

Albert Einstein (1879-1955),  Theoretical physicist, founder of the theory of relativity, one of the two pillars of modern physics.

Charles Darwin (1809-1882), Naturalist, geologist and biologist, a pioneer in the science of evolution.

Rita Levi-Montalcini (1909-2012), Neurobiologist, pioneering discoveries in neurophysiology.

Chien-Shiung Wu (1912-1997), Experimental physicist who made significant contributions in the field of nuclear physics.

The design of the leaflet will be based on a diverse group of superheroes, with the message “Our superpower is you” meaning that science main resource is one: people.



This is ATLAS.ONE (a high speed high resolution biochemical imaging platform)

Project ATLAS

In 2018, we decided to invest capital funds provided by the MRC and the MRC-DBT with the aim to make our technologies more accessible to the biomedical researcher laying down also the possibility to deliver advanced biophysical assays at high throughput [REF1] with a focus on 3D cultures. Why ATLAS? I often code-name internal projects, possibly with evocative names that might capture the pathos of the project. As these are capital investments to strengthen specific areas that will be essential for our long-term applications, I named this investment ATLAS, as the Titan that was condemned to hold up the heavens on its shoulders. In our case, I am building the base for two microscopes that will support my research projects, and support those of the others working at the MRC CU, in the longer period.


Here, I will briefly introduce ATLAS.ONE, the first of the two microscopes we have started to develop. The aim is to develop high spatiotemporal and biochemical resolution with a imaging platform that could be readily accessible by a non-expert user. We are testing the solid-state FLIM (Fluorescence Lifetime Imaging Microscopy) camera PCO.FLIM by PCO for video-rate biochemical read-out of genetically encoded probes or protein-protein interactions.  This is the commercial incarnation of part of my PhD work [REF2REF3] so brilliantly developed and delivered by PCO (no commercial conflict). After considering different possibilities to gain some resolution to better discriminate cellular compartments, we decided to integrate this platform with a simple SIM (structured illumination microscopy) setup based on LCoS spatial light modulators. Biochemical perturbations will be implemented with a CellASICS microfluidic platform. This is a capital investment and we will first focus on methodological advancements, however, we will deploy this platform to characterize genetic and non-genetic heterogeneity in cancer cell lines. While we will look for external funding, we’ll start working on KRAS-dependent signalling pathways and metabolic pathways.


Who is involved?

You are welcome to get in touch if you wished to coordinate developments or to use this platform – once established – either with own resources or common grant applications. Currently, ATLAS.ONE is supported by the MRC and the MRC-DBT for capital funds and the following people for development and applications.

Andrew Trinh and Alessandro Esposito (MRC Cancer Unit), developing the system and applications together with Christian Frezza and Annie Howitt (MRC Cancer Unit), developing single-cell metabolic assays.

Guy Hagen, University of Colorado, to collaboratively develop SIM

Gerhard Holst, PCO to advise on camera integration.


SOP – Ti:Sapphire / Leica SP5 alignment

This SOP is published only for a social media discussion. The author does not take any responsibility for the utilization of this procedure. The system discussed here is a customized two-photon microscope, based on a Coherent Chameleon Vision 2 and Leica SP5. The optical path is fully enclosed and the SOP is written for maintenance. 

Basic rules

1.       Align laser with a lid room (smaller iris, smaller damage to the eye)

2.       Never align eyes with the height/direction of the laser beam

3.       Use the most appropriate personal protective equipment such as goggles and a white lab coat

4.       Perform laser alignments with the least number of people present in the room. Ideally, alignment is a 1 person job and a colleague is aware you are performing this task, within core hours

5.       Use devices such cards, cameras and viewers to visualize the laser beam

6.       Take short breaks every ~45 minutes of work. Do not continue alignment if too tired. Alignment of optics can be a stressful and lengthy procedure; try to identify the right moment to take a long break to relax

7.       Alignment is carried out only by authorized users

PPE for Ti:Sapphire laser

          VC5 IR card viewer from Thorlabs. WARNING: card viewers reflect part of the laser beam. Therefore, they must be used with caution, strictly using protective goggles, directing reflection away from the eyes

          Hand-held IR viewer from Newport. WARNING: hand-held IR viewers limit dexterity and must be used always with protective goggles.

          LG9 Amber lenses from Thorlabs. OD5+ on the 720-1090nm range; OD7+ on the 750-1064nm range. WARNING: goggles never fully protect from direct high power laser beam.

List of authorized users

Alessandro Esposito (MRC Cancer Cell Unit)

Coherent’s field engineer can align the laser under their own responsibility. Coherent’s field engineer can align the beam path until after the Pulse-Picker. The rest of the optical path must enclosed at any time or isolated with a beam stop.

Leica’s field engineer can align the complete beam path under their own responsibility with the exception of the Pulse-Picker. Alterations of the beam path have been discussed with Leica representatives.

Standard Operating Procedure

Room preparation

1.       Show warning at the door

2.       Lock the door

3.       Switch on the system as needed (shutters ON)

4.       Wear PPE as appropriate

5.       Open the beam path as needed (keep lens tube arriving to the scan-head until the last moment)

6.       If a large section of the beam path is opened, always block the laser beam with the beam stop after the optical element that is aligned in order to avoid the laser beam being reflected in dangerous directions (eye, skin, fire hazard) when misaligned

Beam alignment

7.       Always activate laser shutter when the beam is not undergoing alignment

8.       Apply #6 every time a section of the laser beam is aligned

9.       Start laser alignment, proceed with pairs of mirrors from the position closer to the laser up to the scan-head, trying to operate the laser beam within a central part of the mirrors

10.   Always ascertain that all optomechanics is stably connected to the optical table and that no optical device can fall, tilt, flip…

11.   Re-aligned section should be covered (at least temporarily) while progressing towards the scan-head

12.   When arrived at the EOM, remove the device (Leica’s shutter and half-plate may be removed as well). WARNING: the entrance window of the EOM is located within a brass cavity. Upwards reflections of the laser are possible.

13.   Using irises, make sure the laser beam is parallel to the table

14.   Reposition the EOM, coarsely aligned to the laser beam. WARNING: after the EOM there is a periscope. Use a beam-stop before the periscope, beam reflection towards undesired direction is otherwise possible.

15.   With a power meter, measure power of the laser before the EOM. Relocate the power meter after the EOM and iteratively maximize power through the power meter with the EOM in “high” state.

16.   Coarsely align the periscope if necessary, then reintroduce Leica’s shutter and half-plate if previously removed. BE SURE the periscope is locked to the optical table in a stable manner.

17.   Remove lens tube and MFP cover.

18.   Install Leica’s alignment tool on the scan-head

19.   Iteratively align the front iris of the alignment tool and the back aperture of the alignment tool.

20.   WARNING. During the iterative alignment of scan-head, PPE is usually hindering an already lengthy procedure. Avoid removing PPE. Check actions to be taken.

21.   When the two apertures are aligned, start scanning trying to see fluorescence from a bright sample on the screen. Keep adjusting alignment and MFP screws until alignment is completed.

Preparing the room to normal operation

22.   Close the optical path. Before securing all covers and panels, check that the alignment is still ok.

23.   Secure all safety panels

24.   With the laser ON, shutter OFF and during scanning, verify with the IR viewer that no beam is exciting the enclosed laser path.

25.   Remove safety warning on the door and operate equipment as normal.

Embrace your public speaking anxiety

About a decade ago, I went to a PI during a retreat to ask a question. Nervously, but politely, he asked me to be left alone as he was rather anxious for a talk he was about to deliver.  A few hours later, a PhD student at the time, I was freaking out for my own talk, but it was comforting, in a way, to see that an established scientist I highly regarded and I had considered rather self-confident was in a similar state-of-mind.

Comforting? Why not scary? Would you never get rid of public speaking anxiety? I am no anxiety coach and, for that, browse around. However, I wished to share my own experience as it might be useful for students. I now noticed I am that ‘senior’ scientist at that retreat (or something similar) and that junior colleagues might misunderstand my confident speaking in public as evidence of no-stress, no-shyness, a gift from birth. So, even though your solution might be a different one, here I tell you which was mine.

Be prepared! Be prepared? (take 1)

Trivial, isn’t it? I am not going to give practical suggestions here, except set yourself comfortable deadlines. With experience, you will be able to work on a talk until a few minutes before delivery, but earlier in carrier, you have to prepare all your material far in advance. However, even very experienced academics and businessmen when facing more unique scenarios work hard to prep a meeting and give this enough time and resources.

Be prepared! Be prepared? (take 2)

Perhaps, the most difficult thing you might find, it is to commit to a deadline, after which you have to be ready. But, here the challenging bit, even if you feel still unprepared (and some people may never be able to shred off that feeling) or if you are actually unprepared because you miscalculated something, you have anyway to commit to the next difficult bit, be mentally and physically prepared, something you might be completing neglecting. Deadlines are deadlines and the starting time of your talk is unmovable. Therefore, start to mature a process and to understand how long you need to be ready before a talk. Some people is a natural and need no or little preparation. Other people need time: never underestimate how long time you need. Most of my following comments are about this stage of preparation. The bottom line, when the deadline strikes, be sure you are ready and if you are not, do not allow doubts to undermine the next phase of preparation.

Commit physically: water and energy

During a stressful moment, your physiology will be heavily altered and you might lose control. So, think how not to. Personally, before a talk I try to drink lots of water to ensure I will be properly hydrated, and I also make sure I have water available during the talk. Once I didn’t, and I was not well. I coughed though all my talk and it was not a very ideal situation. Also, be sure you have energy, so a bar of chocolate or a juice, can help. Ah… ok, is this obvious?… pay attention – water in > water out. As basic as it seems, be sure you went to the toilet at the latest opportunity before the event. You do not want to be dehydrated, but even not to be distracted by your bladder while on stage.

Mind you that this is even more true when you have very long days, such as more articulated interviews or conference commitments.

Commit physically: oxygen

Breathing, for me, is the next most important issue. You might find yourself in need of oxygen after a few slides and attempting to do the world record in apnoea while speaking in public. You could pass through an entire 20 minutes presentation incapable to breath properly, increasing your level of anxiety at each slide. You are in front of an audience, it could be two people at an interview, or a thousand people in a theatre, if not a million in TV. However, giving a good breath permitting your lungs to be completely emptied and filled with fresh air takes a few seconds. This can be easily concealed in a transition between two slides, or during a question. And… if you cannot conceal it… do it anyway, 5 seconds spent silently breathing properly will be immediately forgotten by your audience, but a poorly delivered 20 minutes talk will be remembered.

Once again, get ready for it. First of all reflect on your breathing habits, far away from a talk. If you give enough thoughts about the issue, whenever you will struggle, a mental trigger will snap and make you aware of the occurring issue for you to take action. More importantly, if issues in breathing are recurrent for you, just do exercises in the 5 minutes preceding your talk. Breath in deeply and breath out slowly. This will decrease your anxiety and will prepare your breathing for the talk. You can do it while seating in the audience or even while speaking with others.

Commit physically: avoid distractions

Personally, I have a routine. Before a talk, I remove everything from my pockets, or even the badge, anything superfluous. After a few talks delivered with my pockets inside-out dangling from my trousers, I also double-check that I am generally presentable! So, on stage or seating in front of a panel, I have no distractions from the badge hitting the microphone, the phone vibrating, the keys stuck in my thigh. Well, the phone: switch it off well in advance of your talk and dump everything in you bag.

Commit mentally: have fun

Those were a few suggestions, and more or different tricks will work for you, to ensure your physical state will be ready to support the potential stress you might experience while speaking in public. Of course, your state of mind will play an equally important role. Perhaps, I should advise to not care, to convince yourself that the event you are preparing does not matter. This is probably key, more in general, to achieve the resilience necessary in the academic world. For me that does not work very well, as I tend to be heavily invested in everything I do. So, what it works for me is to repeat myself I need to have fun speaking about science, my work, or the work of others – otherwise is really not worth. A bit of self-couching targeted to focus your mood towards excitement, how great can be to speak or debate science.

I did receive my dose of criticisms in my career, but let me tell you which is one of the best compliment I ever got. Do you remember the talk I was freaking out during my PhD? Well, after my talk, which might not have been even an excellent one, I overheard the head of a department advising two junior PIs to speak with the energy and enthusiasm I was speaking with. I guess you should remind yourself of how exciting the work you do is and if you disagree with this, change job or lie to yourself for a couple of hours.

Commit mentally: focus

You would not run the athletics world final 100m, physically unprepared and with no excitement. You would also not run it thinking about random stuff or worrying not to win it. Watch athletes on their blocks, the intensity of their eyes, the deep focus they concentrate on the start gun and those few seconds after. Focusing might take a fraction of a second if you were a natural or simply experienced. Also, keep your focus during the talk, try to nurture that unconscious little voice that can warn you everytime you are going off-track.

The top right-hand corner syndrome (TRiHCS) is a risky issue in our business. TRiHCS happen when your mind wonders off, but you keep speaking. TRiHCS happen when you zone out and speak for 2 minutes about an irrelevant detail being fixated on a corner of a room, while you are not engaging with the audience and perhaps even with the main topic of the talk. If you get TRiHCSed, your timing and narrative will derail. But, do not worry, if you notice it in time, you can easily recover.

OK, ok… TRiHCS? I just made this up, but I promise you, it is something that does happen!

Look after yourself…

Pay attention to yourself. It is easy to get anxiety compromise your health in the long term, or your performance in the short term. In an ideal world, you can sleep, eat, drink, meditate as a Yogi. In the real world, assaulted by too many things to do, it is likely you will experience periods of stress and long hours. However, you will have to know your limits and try to stay far from the edge and arrive to an event in good physical and mental conditions. Your institution and funders will offer you a provision of well-being courses, advice and activities. However, your institution and funders will implicitly ask you to neglect completely their own advice and deliver huge returns for them at any cost (for you). Like for any job, the day will come that you cannot run any longer over the edge. Then, manage anxiety, either it is just for public speaking, or for anything else… embrace it, as in ‘do not ignore it’, ‘do not fight it’ as it fights back, but manage it and if you can’t, ask for help.

Look after yourself… plan your cool-off stage

I did some crazy things aiming to present data still warm from the microscope (yes, it is a thing if you use high power lasers), consciously cutting sleeping times down (within reason) and working over the edge. Even if you do not, but public speaking really takes a toll on you, look after yourself after the main event. You need to consider two phases. One, which might be short or very long, depending on the event, is the immediate aftermath. I used to be a runner, and I used to give everything until the end of the race, which made it very likely for me to fall on the ground exhausted after the line… but you learn to immediately stand-up, walk, then do a run at slow space and hydrate.

Somehow, after a peak of stress you need to do something similar, often quietly and in public. This may have to happen in a few seconds before taking further questions. So, regain mental and physical composure, re-gather your focus and energy, again consider drinking water or a juice.  You will need this, particularly, in a day-long event full of meetings. It can really take just one minute, but if you do not do it, you might crash and underperform in the aftermath of a public speaking event. Do not underestimate the task you will have to follow after the main event and the energy you will need for them.

Then, at last, all is over. Really look after yourself because if the event you prepared took really a lot of energy from you, there might be consequences. You will discover what is best for you, if to completely relax and instruct yourself, or to simply take it easy for a few hours or a few days.


Keep in mind that what I have written here it is not an expert-opinion, but a personal experience. My suggestion to embrace your public speaking anxiety comes from trying to advise junior colleagues and realizing I did not wish to give the same suggestion a GP once gave to me: ‘you should avoid stress’. This is the wrong suggestion, in my opinion, as most of us, certainly in the ultra-competitive academic world, will have to manage plenty of stressful situation. Thus, the keyword is ‘manage’ not ‘avoid’, be the master or mistress of your stress-responses and, yes, avoid only those things that might push you too far beyond what you can manage. So, embrace your public anxiety speaking, mould your response to it in time and you will eventually grow out of it, or if not, at least you will manage.

Of course, whatever I described here is not something I usually think about, even during big talks. I made an effort to catalogue the various ‘tricks’ I – sometimes unconsciously -matured in 15 years of presenting scientific work in public. But recently, I had noticed that – either as a natural predisposition or by training – delivering a talk is more than just speaking in public. It is a process that requires physical and psychological strengths, like an actor preparing for a play or an athlete for a race. Scientists, noticing it or not, need to nurture these strengths, even not for their audience, but at least for looking after their health.

[TALK] Goldilocks and the two ERKs; signalling in the ‘sweet spot’ underpins resistance to ERK pathway inhibitors

Friday 14/09 at 14.30 | Dr. Simon Cook (Signalling Laboratory, The Babraham Institute) will present the following talk, at the Clifford Allbutt Lecture Theatre, Clifford Allbutt Building (former LMB building). All welcome to attend.

 Goldilocks and the two ERKs; signalling in the ‘sweet spot’ underpins resistance to ERK pathway inhibitors

Simon Cook, Signalling Laboratory, The Babraham Institute

Tumour cells with BRAF or RAS mutations are ‘addicted’ to ERK1/2 signalling for proliferation and RAFi and/or MEKi are now approved for use in the clinic.  However, despite some striking clinical responses, resistance emerges within 9-12 months resulting in disease progression. Acquired resistance to MEKi often occurs through amplification of BRAFV600E or KRASG13D which act to reinstate ERK1/2 signalling.

Here we show that BRAFV600E amplification and MEKi resistance are fully reversible following drug withdrawal.  Resistant cells with BRAFV600E amplification become addicted to MEKi to clamp ERK1/2 signalling at a level optimal for cell survival and proliferation (2-3% of total ERK1/2 active, quantified by mass spectrometry).  This is seen in cell culture and in vivo where growth of resistant cells with BRAFV600E amplification as tumour xenografts is inhibited in mice that do not receive MEKi.  ERK1/2 hyperactivation (~20% active) following MEKi withdrawal drives expression of the cyclin-dependent kinase inhibitor (CDKI) p57KIP2, which promotes G1 cell cycle arrest and senescence, or expression of NOXA and cell death; these ‘terminal’ responses select against those cells with amplified BRAFV600E.  ERK1/2-dependent p57KIP2 expression is required for loss of BRAFV600E amplification and determines the rate of reversal of MEKi resistance.  Thus, BRAFV600E amplification confers a fitness deficit during drug withdrawal, providing a rationale for intermittent dosing (‘drug holidays’) to forestall resistance.

Remarkably, MEKi resistance driven by KRASG13D amplification is not reversible. ERK1/2 reactivation in the context of amplified KRASG13D does not inhibit proliferation but drives a ZEB1-dependent epithelial-to-mesenchymal transition that increases cell motility and promotes resistance to chemotherapy agents, arguing strongly against the use of ‘drug holidays’ in cases of resistance to MEKi driven by KRASG13D amplification.