Reviewer #3 (Public review):

In this study, O'Brien et al. address the need for scalable and cost-effective approaches to finding lead compounds for the treatment of the growing number of Mendelian diseases. They used state-of-the-art phenotypic screening based on an established high-dimensional phenotypic analysis pipeline in the nematode C. elegans.

First, a panel of 25 C. elegans models was created by generating CRISPR/Cas9 knock-out lines for conserved human disease genes. These mutant strains underwent behavioral analysis using the group's published methodology. Clustering analysis revealed common features for genes likely operating in similar genetic pathways or biological functions. The study also presents results from a more focused examination of ciliopathy disease models.

Subsequently, the study focuses on the NALCN channel gene family, comparing the phenotypes of mutants of nca-1, unc-77, and unc-80. This initial characterization identifies three behavioral parameters that exhibit significant differences from the wild type and could serve as indicators for pharmacological modulation.

As a proof-of-concept, O'Brien et al. present a drug repurposing screen using an FDA-approved compound library, identifying two compounds capable of rescuing the behavioral phenotype in a model with UNC80 deficiency. The relatively short time and low cost associated with creating and phenotyping these strains suggest that high-throughput worm tracking could serve as a scalable approach for drug repurposing, addressing the multitude of Mendelian diseases. Interestingly, by measuring a wide range of behavioural parameters, this strategy also simultaneously reveals deleterious side effects of tested drugs that may confound the analysis.

Considering the wealth of data generated in this study regarding important human disease genes, it is regrettable that the data is not made accessible to researchers less versed in data analysis methods. This diminishes the study's utility. It would have a far greater impact if an accessible and user-friendly online interface were established to facilitate data querying and feature extraction for specific mutants. This would empower researchers to compare their findings with the extensive dataset created here.

Another technical limitation of the study is the use of single alleles. Large deletion alleles were generated by CRISPR/Cas9 gene editing. At first glance, this seems like a good idea because it limits the risk that background mutations, present in chemically-generated alleles, will affect behavioral parameters. However, these large deletions can also remove non-coding RNAs or other regulatory genetic elements, as found, for example, in introns. Therefore, it would be prudent to validate the behavioral effects by testing additional loss-of-function alleles produced through early stop codons or targeted deletion of key functional domains.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review): 

Summary: 

As the scientific community identifies increasing numbers of genetic variants that cause rare human diseases, a challenge is how the field can most quickly identify pharmacological interventions to address known deficits. The authors point out that defining phenotypic outcomes required for drug screen assays is often challenging, and emphasize how invertebrate models can be used for quick ID of compounds that may address genetic deficits. A major contribution of this work is to establish a framework for potential intervention drug screening based on quantitative imaging of morphology and mobility behavior, using methods that the authors show can define subtle phenotypes in a high proportion of disease gene knockout mutants. 

Overall, the work constitutes an elegant combination of previously developed high-volume imaging with highly detailed quantitative phenotyping (and some paring down to specific phenotypes) to establish proof of principle on how the combined applications can contribute to screens for compounds that may address specific genetic deficits, which can suggest both mechanism and therapy. 

In brief, the authors selected 25 genes for which loss of function is implicated in human neuro-muscular disease and engineered deletions in the corresponding C. elegans homologs. The authors then imaged morphological features and behaviors prior to, during, and after blue light stimuli, quantitating features, and clustering outcomes as they elegantly developed previously (PMID 35322206; 30171234; 30201839). In doing so, phenotypes in 23/25 tested mutants could be separated enough to distinguish WT from mutant and half of those with adequate robustness to permit high-throughput screens, an outcome that supports the utility of general efforts to ID phenotypes in C. elegans disease orthologs using this approach. A detailed discussion of 4 ciliopathy gene defects, and NACLN-related channelopathy mutants reveals both expected and novel phenotypes, validating the basic approach to modeling vetted targets and underscoring that quantitative imaging approaches reiterate known biology. The authors then screened a library of nearly 750 FDA-approved drugs for the capacity to shift the unc-80 NACLN channel-disrupted phenotype closer to the wild type. Top "mover" compound move outcome in the experimental outcome space; and also reveal how "side effects" can be evaluated to prioritize compounds that confer the fewest changes of other parameters away from the center. 

Strengths: 

Although the imaging and data analysis approaches have been reported and the screen is limited in scope and intervention exposure, it is important that the authors strongly combine individual approach elements to demonstrate how quantitative imaging phenotypes can be integrated with C. elegans genetics to accelerate the identification of potential modulators of disease (easily extendable to other goals). Generation of deletion alleles and documentation of their associated phenotypes (available in supplemental data) provide potentially useful reagents/data to the field. The capacity to identify "over-shooting" of compound applications with suggestions for scale back and to sort efficacious interventions to minimize other changes to behavioral and physical profiles is a strong contribution. 

Weaknesses: 

The work does not have major weaknesses, although it may be possible to expand the discussion to increase utility in the field: 

(1) Increased discussion of the challenges and limitations of the approach may enhance successful adaptation application in the field. 

It is quite possible that morphological and behavioral phenotypes have nothing to do with disease mechanisms and rather reflect secondary outcomes, such that positive hits will address "off-target" consequences. 

This is possible and can only be determined with human data. We now discuss the possibility in the discussion.

The deletion approach is adequately justified in the text, but the authors may make the point somewhere that screening target outcomes might be enhanced by the inclusion of engineered alleles that match the human disease condition. Their work on sod-1 alleles (PMID 35322206) might be noted in this discussion. 

We agree and now mention this work in the discussion. We are currently working on a collection of strains with patient-specific mutations.

Drug testing here involved a strikingly brief exposure to a compound, which holds implications for how a given drug might engage in adult animals. The authors might comment more extensively on extended treatments that include earlier life or more extended targeting. The assumption is that administering different exposure periods and durations, but if the authors are aware as to whether there are challenges associated with more prolonged applications, larger scale etc. it would be useful to note them. 

More prolonged applications are definitely possible. We chose short treatments for this screen to model the potential for changing neural phenotypes once developmental effects of the mutation have already occurred. We now briefly discuss this choice and the potential of longer treatments in the discussion.

(2) More justification of the shift to only a few target parameters for judging compound effectiveness. 

- In the screen in Figure 4D and text around 313, 3 selected core features of the unc-80 mutant (fraction that blue-light pause, speed, and curvature) were used to avoid the high replicate requirements to identify subtle phenotypes. Although this strategy was successful as reported in Figure 5, the pared-down approach seems a bit at odds with the emphasis on the range of features that can be compared mutant/wt with the author's powerful image analysis. Adding details about the reduced statistical power upon multiple comparisons, with a concrete example calculated, might help interested scientists better assess how to apply this tool in experimental design. 

To empirically test the effect of including more features on the subsequent screen, we have repeated the analysis using increasing numbers of features. In a new supplementary figure we find increasing the number of features reduces our power to detect rescue. At 256 features, we would not be able to detect any compounds that rescued the disease model phenotype.

(3) More development of the side-effect concept. The side effects analysis is interesting and potentially powerful. Prioritization of an intervention because of minimal perturbation of other phenotypes might be better documented and discussed a bit further; how reliably does the metric of low side effects correlate with drug effectiveness? 

Ultimately this can only be determined with clinical trial data on multiple drugs, but there are currently no therapeutic options for UNC80 deficiency in humans. We have included some extra discussion of the side effect concept.

Reviewer #2 (Public Review): 

Summary and strengths: 

O'Brien et al. present a compelling strategy to both understand rare disease that could have a neuronal focus and discover drugs for repurposing that can affect rare disease phenotypes. Using C. elegans, they optimize the Brown lab worm tracker and Tierpsy analysis platform to look at the movement behaviors of 25 knockout strains. These gene knockouts were chosen based on a process to identify human orthologs that could underlie rare diseases. I found the manuscript interesting and a powerful approach to making genotype-phenotype connections using C. elegans. Given the rate at which rare Mendelian diseases are found and candidate genes suggested, human geneticists need to consider orthologous approaches to understand the disease and seek treatments on a rapid time scale. This approach is one such way. Overall, I have a few minor suggestions and some specific edits. 

Weaknesses: 

(1) Throughout the text on figures, labels are nearly impossible to read. I had to zoom into the PDF to determine what the figure was showing. Please make text in all figures a minimum of 10-point font. Similarly, the Figure 2D point type is impossible to read. Points should be larger in all figures. Gene names should be in italics in all figures, following C. elegans convention. 

We have updated all figures with larger labels and, where necessary, split figures to allow for better readability. We’ve also corrected italicisation.

(2) I have a strong bias against the second point in Figure 1A. Sequencing of trios, cohorts, or individuals NEVER identifies causal genes in the disease. This technique proposes a candidate gene. Future experiments (oftentimes in model organisms) are required to make those connections to causality. Please edit this figure and parts of the text. 

We have removed references to causation. We were thinking of cases where a known variant is found in a patient where causality has already been established rather than cases of new variant discovery.

(3) How were the high-confidence orthologs filtered from 767 to 543 (lines 128-131)? Also, the choice of the final list of 25 genes is not well justified. Please expand more about how these choices were made. 

We now explain the extra keyword filtering step. For the final filtering step, we simply examined the list and chose 25. There is therefore little justification to provide and we acknowledge these cannot be seen as representative of the larger set according to well-defined rules. The choice was based on which genes we thought would be interesting using their descriptions or our prior knowledge (“subjective interestingness” in the main text).

(4) Figures 3 and 4, why show all 8289 features? It might be easier to understand and read if only the 256 Tierpsy features were plotted in the heat maps. 

In this case, we included all features because they were all tested for differences between mutants and controls. By consistently using all features for each fingerprint we can be sure that the features that are different that we want to highlight in box plots can be referred to in the fingerprint.

(5) The unc-80 mutant screen is clever. In the feature space, it is likely better to focus on the 256 less-redundant Tierpsy features instead of just a number of features. It is unclear to me how many of these features are correlated and not providing more information. In other words, the "worsening" of less-redundant features is far more of a concern than the "worsening" of 1000 correlated features. 

This is a good point. We’ve redone the analysis using the Tierpsy 256 feature set and included this as a supplementary figure. We find that the same trend exists when looking at this reduced feature set.

Reviewer #3 (Public Review): 

In this study, O'Brien et al. address the need for scalable and cost-effective approaches to finding lead compounds for the treatment of the growing number of Mendelian diseases. They used state-of-the-art phenotypic screening based on an established high-dimensional phenotypic analysis pipeline in the nematode C. elegans. 

First, a panel of 25 C. elegans models was created by generating CRISPR/Cas9 knock-out lines for conserved human disease genes. These mutant strains underwent behavioral analysis using the group's published methodology. Clustering analysis revealed common features for genes likely operating in similar genetic pathways or biological functions. The study also presents results from a more focused examination of ciliopathy disease models. 

Subsequently, the study focuses on the NALCN channel gene family, comparing the phenotypes of mutants of nca-1, unc-77, and unc-80. This initial characterization identifies three behavioral parameters that exhibit significant differences from the wild type and could serve as indicators for pharmacological modulation. 

As a proof-of-concept, O'Brien et al. present a drug repurposing screen using an FDA-approved compound library, identifying two compounds capable of rescuing the behavioral phenotype in a model with UNC80 deficiency. The relatively short time and low cost associated with creating and phenotyping these strains suggest that high-throughput worm tracking could serve as a scalable approach for drug repurposing, addressing the multitude of Mendelian diseases. Interestingly, by measuring a wide range of behavioural parameters, this strategy also simultaneously reveals deleterious side effects of tested drugs that may confound the analysis. 

Considering the wealth of data generated in this study regarding important human disease genes, it is regrettable that the data is not actually made accessible. This diminishes the study's utility. It would have a far greater impact if an accessible and user-friendly online interface were established to facilitate data querying and feature extraction for specific mutants. This would empower researchers to compare their findings with the extensive dataset created here. Otherwise, one is left with a very limited set of exploitable data. 

We have now made the feature data available on Zenodo (https://doi.org/10.5281/zenodo.12684118) as a matrix of feature summaries and individual skeleton timeseries data (the feature matrix makes it more straightforward to extract the data from particular mutants for reanalysis). We have also created a static html version of the heatmap in Figure 2 containing the entire behavioural feature set extracted by Tierpsy. This can be opened in a browser and zoomed for detailed inspection. Mousing over the heatmap shows the names of features at each position making it easier to arrive at intuitive conclusions like ‘strain A is slow’ or ‘strain B is more curved’.

Another technical limitation of the study is the use of single alleles. Large deletion alleles were generated by CRISPR/Cas9 gene editing. At first glance, this seems like a good idea because it limits the risk that background mutations, present in chemically-generated alleles, will affect behavioral parameters. However, these large deletions can also remove non-coding RNAs or other regulatory genetic elements, as found, for example, in introns. Therefore, it would be prudent to validate the behavioral effects by testing additional loss-of-function alleles produced through early stop codons or targeted deletion of key functional domains. 

We have added a note in the main text on limitations of deletion alleles. We like the idea of making multiple alleles in future studies, especially in cases where a project is focussed on just one or a few genes.

Recommendations for the authors

Reviewer #1 (Recommendations For The Authors): 

Note that none of the above suggestions or the one immediately below are considered mandatory. 

One additional minor point: The dual implication of mevalonate perturbations for NACLM deficiencies is striking. At the same time, the mevalonate pathway is critical for embryo viability among other things, which prompts questions about how reproductive physiology is integrated in this screen approach. It appears that sterilization protocols are not used to prepare screen target animals, but it would be useful to know if there were a signature associated with drug-induced sterility that might help identify one potential common non-interesting outcome of compound treatments in general. In this work, the screen treatment is only 4 hours, which is probably too short to compromise reproduction, but as noted above, it is likely users would intend to expose test subjects for much longer than 4-hour periods. 

This is an interesting point. In its current form our screen doesn’t assess reproductive physiology. This is something that we will consider in ongoing projects.

Figures 

Figure 1D might be omitted or moved to supplement. 

We have removed 1D and moved figure 1E as a standalone table (Table 1) to improve readability.

Figure 2D "key" is hard to make out size differences for prestim, bluelight, and poststim -more distinctive symbols should be used. 

We have increased the size of the symbols so that the key is easier to read.

Line 412 unc-25 should be in italics 

Corrected

Reviewer #2 (Recommendations For The Authors): 

Specific edits: 

All of the errors below have been corrected.

Line 47, "loss of function" should be hyphenated because it is a compound adjective that modifies mutations. 

Line 50, "genetically-tractable" should not be hyphenated because it is not a compound adjective. It is an adverb-adjective pair. Line 102 has the same grammatical issue. 

Line 85, "rare genetic diseases" do not "affect nervous system function". The disease might have deficits in this function, but the disease does not do anything to function. 

Line 86, it should be mutations not mutants. Mutations are changes to DNA. Mutants are individuals with mutations. 

Throughout, wild-type should be hyphenated when it is used as a compound adjective. 

Figure 4, asterisks is spelled incorrectly. 

Reviewer #3 (Recommendations For The Authors): 

- As stated in the public review, the utility of the study is limited by the lack of access to the complete dataset. The wealth of data produced by the study is one of its major outputs. 

We have made the data publicly available on Zenodo. We appreciate the request.

- Describe the exact break-points of the different alleles, because it was not readily feasible to derive them from the gene fact sheets provided in the supplementary materials. 

We have now provided the start position and total length of deletion for each gene in the gene fact sheets.

- Figure 1C: what does "Genetic homology"/"sequence identity" refer to? How were these values calculated? 

UNC-49 is clearly not 95% identical to vertebrate GABAR subunits at the protein level. 

We have changed the axis label to “BLAST % Sequence Identity” to clarify that these values are calculated from BLAST sequence alignments on WormBase and the Alliance Genom Resources webpages.

- Figure 1E : The data presented in Figure 1E appears somewhat unreliable. For example, a cursory check showed: 

(1) Wrong human ortholog: unc-49 is a Gaba receptor, not a Glycine receptor as indicated in the second column. 

(2) Wrong disease association: dys-1 is not associated with Bardet-Biedl syndrome; overall the data indicated in the table does not seem to fully match the HPO database. 

(3) Inconsistent disease association: why don't the avr-14 and glc-2 (and even unc-49) profiles overlap/coincide given that they present overlapping sets of human orthologs. 

Thank you for catching this! We have corrected gene names which were mistakenly pasted. We have also made this a standalone table (Table 1) for improved readability.

- Error in legend to figure 4I : "with ciliopathies and N2" > ciliopathies should be "NALCN disease". 

- Error at line 301: "Figures 2E-H" should be "Figures 4E-H". 

Corrected.

RESTATEMENT ANNOTAIONS

1. (0:37) Though at times AI can be extremely helpful, as we often hear in the media, there is also a dark side to these functions. For instance, one chatbot suggested that the solution to one man's problems was to file for divorce. Another suggested a sure-to-please recipe for a large gathering, that contained chlorine gas among its list of ingredients.

2. (1:19) AI does not exist in solitude. Its affects have left the digital world and have begun to affect our physical world. AI models have been noted to contribute to climate change, use artist and authors work without their consent, and discriminate against entire groups of people.

3. (1:56) In regard to sustainability, the figurative cloud we imagine AI resides upon is not something only contained within the digital world. We often fail to acknowledge the large quantity of materials needed to build these models as well as the sizeable amount of energy required to sustain them.

departure from tuck and yang

Important to realize that if referring to a model with auxiliary view, focus on the top and front views to get accurate dimensions. Auxiliary is not true to its sizing

Cela n'est pas inhérent à l'automatisation numérique en elle-même, il s'agit là d'un souci plus systémique -> l'IA et les Nouvelles Technologies ne font que refléter en prolongeant les problèmes qui existent déjà, ce ne sont que des outils

Même risque exposé que celui de l'article précédent.

"Empty" land becomes a place to extract resources for profit.

Welcome back and in this video I want to cover the differences between stateful and stateless firewalls.

And to do that I need to refresh your knowledge of how TCP and IP function.

So let's just jump in and get started.

In the networking fundamentals videos I talk about how TCP and IP worked together.

You might already know this if you have networking experience in the real world, but when you make a connection using TCP, what's actually happening is that each side is sending IP packets to each other.

These IP packets have a source and destination IP and are carried across local networks and the public internet.

Now TCP is a layer 4 protocol which runs on top of IP.

It adds error correction together with the idea of ports, so HTTP runs on TCP port 80 and HTTPS runs on TCP port 443 and so on.

So keep that in mind as we continue talking about the state of connections.

So let's say that we have a user here on the left Bob and he's connecting to the Categoram application running on a server on the right.

What most people imagine in this scenario is a single connection between Bob's laptop and the server.

So Bob's connecting to TCP port 443 on the server and in doing so he gets information back, in this case many different categories.

Now you know that below the surface at layer 3 this single connection is handled by exchanging packets between the source and the destination.

Conceptually though you can imagine that each connection, in this case it's an outgoing connection from Bob's laptop to the server.

Each one of these is actually made up of two different parts.

First we've got the request part where the client requests some information from a server, in this case from Categors, and then we have the response part where that data is returned to the client.

Now these are both parts of the same interaction between the client and server, but strictly speaking you can think of these as two different components.

What actually happens as part of this connection setup is this.

First the client picks a temporary port and this is known as an ephemeral port.

Now typically this port has a value between 1024 and 65535, but this range is dependent on the operating system which Bob's laptop is using.

Then once this ephemeral port is chosen the client initiates a connection to the server using a well-known port number.

Now a well-known port number is a port number which is typically associated with one specific popular application or protocol.

In this case TCP port 443 is HTTPS.

So this is the request part of the connection, it's a stream of data to the server.

You're asking for something, some cat pictures or a web page.

Next the server responds back with the actual data.

The server connects back to the source IP of the request part, in this case Bob's laptop, and it connects to the source port of the request part, which is the ephemeral port which Bob's laptop has chosen.

This part is known as the response.

So the request is from Bob's laptop using an ephemeral port to a server using a well-known port.

The response is from the server on that well-known port to Bob's laptop on the ephemeral port.

Now it's these values which uniquely identify a single connection.

So that's a source port and source IP.

And a destination IP and a destination port.

Now hope that this makes sense so far, if not then you need to repeat this first part of the video again because this is really important to understand.

If it does make sense then let's carry on.

Now let's look at this example in a little bit more detail.

This is the same connection that we looked at on the previous screen.

We have Bob's laptop on the left and the Catering Server on the right.

Obviously the left is the client and the right is the server.

I also introduced the correct terms on the previous screen so request and response.

So the first part is the client talking to the server asking for something and that's the request.

And the second part is the server responding and that's the response.

But what I want to get you used to is that the directionality depends on your perspective and let me explain what I mean.

So in this case the client initiates the request and I've added the IP addresses on here for both the client and the server.

So what this means is the packets will be sent from the client to the server and these will be flowing from left to right.

These packets are going to have a source IP address of 119.18.36.73, which is the IP address of the client.

So Bob's laptop and they will have a destination IP of 1.3.3.7, which is the IP address of the server.

Now the source port will be a temporary or ephemeral port chosen by the client and the destination port will be a well-known port.

In this case we're using HTTPS so TCP port 443.

Now if I challenge you to take a quick guess, would you say that this request is outbound or inbound?

If you had to pick, if you had to define a firewall rule right now, would you pick inbound or outbound?

Well this is actually a trick question because it's both.

From the client perspective this request is an outbound connection.

So if you're adding a firewall rule on the client you would be looking to allow or deny an outbound connection.

From the server perspective though it's an inbound connection so you have to think about perspective when you're working with firewalls.

But then we have the response part from the server through to the client.

This will also be a collection of packets moving from right to left.

This time the source IP on those packets will be 1.3.3.7, which is the IP address of the server.

The destination IP will be 119.18.36.73, which is the IP address of the client.

So Bob's laptop.

The source port will be TCP port 443, which is the well-known port of HTTPS and the destination port will be the ephemeral port chosen originally by the client.

Now again I want you to think about the directionality of this component of the communication.

Is it outbound or inbound?

Well again it depends on perspective.

The server sees it as an outbound connection from the server to the client and the client sees it as an inbound connection from the server to itself.

Now this is really important because there are two things to think about when dealing with firewall rules.

The first is that each connection between a client and a server has two components, the request and the response.

So the request is from a client to a server and the response is from a server to a client.

The response is always the inverse direction to the request.

But the direction of the request isn't always outbound and isn't always inbound.

It depends on what that data is together with your perspective.

And that's what I want to talk about a bit more on the next screen.

Let's look at this more complex example.

We still have Bob and his laptop on the CaterGram server, but now we have a software update server on the bottom left.

Now the CaterGram server is inside a subnet which is protected by a firewall.

And specifically this is a stateless firewall.

A stateless firewall means that it doesn't understand the state of connections.

What this means is that it sees the request connection from Bob's laptop to CaterGram and the response of from CaterGram to Bob's laptop as two individual parts.

You need to think about allowing or denying them as two parts.

You need two rules.

In this case one inbound rule which is the request and one outbound rule for the response.

This is obviously more management overhead.

Two rules needed for each thing.

Each thing which you as a human see as one connection.

But it gets slightly more confusing than that.

For connections to the CaterGram server, so for example when Bob's laptop is making a request, then that request is inbound to the CaterGram server.

The response logically enough is outbound, sending data back to Bob's laptop, which is possible to have the inverse.

Consider the situation where the CaterGram server is performing software updates.

Well in this situation the request will be from the CaterGram server to the software update server, so outbound, and the response will be from the software update server to the CaterGram server, so this is inbound.

So when you're thinking about this, start with the request.

Is the request coming to you or going to somewhere else?

The response will always be in the reverse direction.

So this situation also requires two firewall rules.

One outbound for the request and one inbound for the response.

Now there are two really important points I want to make about stateless firewalls.

First, for any servers where they accept connections and where they initiate connections, and this is common with web servers which need to accept connections from clients, but where they also need to do software updates.

In this situation you'll have to deal with two rules for each of these, and they will need to be the inverse of each other.

So get used to thinking that outbound rules can be both the request and the response, and inbound rules can also be the request and the response.

It's initially confusing, but just remember, start by determining the direction of the request, and then always keep in mind that with stateless firewalls you're going to need an inverse rule for the response.

Now the second important thing is that the request component is always going to be to a well-known port.

If you're managing the firewall for the category application, you'll need to allow connections to TCP port 443.

The response though is always from the server to a client, but this always uses a random ephemeral port, because the firewall is stateless, it has no way of knowing which specific port is used for the response, so you'll often have to allow the full range of ephemeral ports to any destination.

This makes security engineers uneasy, which is why stateless firewalls which I'll be talking about next are much better.

Just focus on these two key elements, that every connection has a request and a response, and together with those keep in mind the fact that they can both be in either direction, so a request can be inbound or outbound, and a response will always be the inverse to the directionality of the request.

Also you'll keep in mind that any rules that you create for the response will need to often allow the full range of ephemeral ports.

That's not a problem with stateless firewalls which I want to cover next.

So we're going to use the same architecture, we've got Bob's laptop on the top left, the category server on the middle right, and the software update server on the bottom left.

A stateless firewall is intelligent enough to identify the response for a given request, since the ports and IPs are the same, it can link one to the other, and this means that for a specific request to category from Bob's laptop to the server, the firewall automatically knows which data is the response, and the same is true for software updates, for a given connection to a software update server, the request, the firewall is smart enough to be able to see the response or the return data from the software update server back to the category server, and this means that with a stateful firewall, you'll generally only have to allow the request or not, and the response will be allowed or not automatically.

This significantly reduces the admin overhead and the chance for mistakes, because you just have to think in terms of the directionality and the IPs and ports of the request, and it handles everything else.

In addition, you don't need to allow the full ephemeral port range, because the firewall can identify which port is being used, and implicitly allow it based on it being the response to a request that you allow.

Okay, so that's how stateless and stateful firewalls work, and now it's been a little bit abstract, but this has been intentional, because I want you to understand how they work, and sexually, before I go into more detail with regards to how AWS implements both of these different security firewall standards.

Now at this point, I've finished with the abstract description, so go ahead and finish this video, and when you're ready, I'll look forward to you joining me in the next.

contradicts the message of keep to your self, do what you want, don't care about what others think

Getting a strong individualism vibe.

unpopular opinions cause estrangement.

I thought this was interesting because in Octavia Butler's Parable of the Sower there was this sense of "denial and desiring." I interpreted this in a way that Lauren desired to fit in with the world around her but also despised that she had to change herself to fit in. This was very distinct to me in Lauren's world because when she had to leave her homeland, one of the first things she did was cut her hair to make herself resemble a man. The reason for this is that she knows in society she will be more feared if she presents herself as a man. We see throughout the novel how she suffers with her own femininity because of it. Where she finds being a woman sad a disadvantage. It's interesting to me how Frazier was able to point out this complex idea that both Butler and Mutu portray in their works.

Did the actions of Protestants via 17th-England correlate with the ideal type of Protestant?

ideal type- the social construction of what something should be??

believes in necessity of generalizations and concepts but wary of over encompassing categories that try to explain literally everything. Additionally, wary of too narrow a focus of a case or a situation.

science is an occupation or method, cannot interpret meaning of the universe

Would you be willing to provide the code you used for this project as a GitHub repo or a gist?

It would be interesting to see a side-by-side comparison to PDB and ViralZone. Where does BFDV have more coverage? Where does ViralZone or PDB have more depth (more sequences per represented sequence in BFDV)

As commented above, it would be interesting to know more details on how you did this splitting

Would you consider expanding it to all viral proteins in UniProt, or to a higher clustering resolution than UniRef30 (such as UniRef50 or UniRef90)?

In general, it would be interesting to know more about this trade off. Some questions I would love to know the answers to:

1. How much computational cost and database size did you save by using UniRef30 over all UniProt viral proteins? It looks like you did 351K that represent 3M sequences. Is 3M too many to do?
2. How taxonomically mixed are the UniRef30 clusters? For example, I looked at the representative sequence for a protein PB1 in influenza A and it's sequence PB1 in influenza B, so they're very closely related. Is this usually the case because viruses are so diverse?
3. Do PDB and ViralZone provide more resolution for the virsues they do cover? For example, if I'm more interested in Eukaryotic viruses, will I get more exact results using one of those databases because they don't reduce down so much (e.g. UniRef30)?

I think it could be interesting to repeat this experiment but with a metagenome where the viruses of interest are not bacteriophages. As written, this doesn't really highlight the benefit of BFVD.

It may also be interesting to report the additional metadata you receive from annotating with BFVD instead of AFDB. If the phage structures come from hits to prophages, AFDB would presumably provide "host" information while BFVD would provide viral taxonomy (or at least taxonomy of sequences in the cluster that have a hit).

Maybe I'm misunderstanding, but I thought in the previous paragraph you stated that most of these sequences had high pLDDT, so were high confidence? That makes this sentence confusing, as well as the following one.

not sure what to make of this statement...

*

hmmm

marketization is subsumed into a creative solution (another aspect of problem-solving!)

for creative entrepreneurs, the creative tends to come first!

yep

very interesting How do you relate to this?

huh

ok - this statement is, on the other hand, exactly like Peter's. creativity = problem solving. A curious definition. But it also opens the door to allow everybody in ... (independent of entrepreneurial labels...)

!

we all exist as (relative) experts within some domain/field or other, acting creatively within it (with others) -- not just folk in the creative industry!

(it's just that they have this specific focus...)

quite a distinct outlook from Peter's point of view! Which do you find more persuasive?

the arbitrariness of it all! Purposeful entrepreneurial identity nowhere near as significant as the serendipity of retroactively putting the pieces together...

interesting

getting into the different case studies

...

So, can we speak of all entrepreneurs as creative entrepreneurs, not just those employed in creative fields (much like the debate about "cultural" entrepreneurs)?

this is fascinating to me.

surprise and randomness are not factors to be expunged but in fact are integral to the discovery process

what about the "creative" entrepreneur -- who might use knowledge, but even moreso, perhaps intuition... and inspiration. Perhaps knowledge is not so much in the head but in the gut, a feeling, an emotional need that must be met, a chord that must be struck...

I'm digging this too...

it reminds me of the statement that genius is nothing more nor less than doing well what anyone can do badly.

an interesting concept...

but it makes me wonder if this somehow constrains the potential of individuals to CREATIVELY seek and create opportunities where others couldn't see them... hmmm

*

a different factor for creative entrepreneurs!

the conundrum...

interesting

nice overview

!

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creativity has to come from somewhere (people interact with and are influenced by their environment!)

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it's a broad field! -- note the use of the term "autotelic" -- see my "journal prompts" for further explanation of this!

Yep!

all of this seems self-evident...

the only constant is change...

yep - this is basically how the other article concluded. This one provides actual narratives...

ok - that seems to fit with the overall arc of this course material for sure!

ok...

Just like (traditional) discourses surrounding entrepreneurship!

focusing specifically upon the 2nd type of cultural entrepreneur (as identified by the other article, which was really just trying to outline the importance of the concept and understanding the implications of how we use the terms...)

justifying the narrative-based approach

interesting - kind of the antithesis of the opening argument of this course...

I use the term "connective tissue" all the time!

ooh! -- on the road to turning creativity into a commodity...

what's your opinion of this? Does the existence of a tribe change this?

hah - relates to one of my seminar prompts... Funny enough, though, there's the contrary perspective that some world famous artists (like Damien Hirst in the world of contemporary art or Drake (!) a musical artist - pictured below, together for an article titled "Damien Hirst Simply Cannot Stop Painting Things for Drake") are commercially successful AND artistic innovators...

...

View 2: people engaged in the "arts" do it ... providing cultural good and services

ok - so not anyone can change people's beliefs ... but the best examples of cultural entrepreneurs are those who change society's belief structures...

View 1: everyone engages in culture!

I like this lingo. T'is true - the artistic innovation sphere might hardly ever be highlighted in "conventional" entrepreneurship...

I like this!

culture (and business) being revolutionized alongside each other. But seriously, Henry Ford changed culture even if that's not what we predominantly associate with him

the expertise of the cultural entrepreneur goes beyond possessing cultural capital - but affecting how we perceive cultural capital, how we negotiate its contours ... interesting...

I like this distinction, though, as it clarifies that everyone can be a cultural entrepreneur, as long as you're working "creatively"

interesting - cultural entrepreneurs as those who can change the beliefs of others...

the commercial aspect is never (entirely) absent...

this is an interesting definition (also circular in nature) -- the cultural entrepreneur will exhibit all the best qualities of someone undertaking a career in cultural sectors...

so we've come full circle - a cultural entrepreneur CAN be someone working in "industry" who has a profound impact on the wider culture (not just someone working in the "cultural industry/ies")

much more basic... a cultural entrepreneur produces a cultural good...

hah

not a circular argument at all!

interesting - a values (morality) based argument for entrepreneurship!

interesting - this might also serve as an inclusive definition of entrepreneur (without the "cultural" modifier). But people in the arts definitely highlight the cultural (and maybe the social) value of their creations, while also recognizing the economic nature of their practices...

yep!

seems like something of a theme in a lot of the weeks we've looked at so far!

interesting ... what makes us "cultured" or "cultivated"?

creativity --> creation --> culture --> cultivation --> GROWTH

ok ... an industrious person doesn't necessarily work in an industry, but labours to create ... and cultural industries create all manner of material (that may "elevate" their citizens...)

ok - so let's explore these different directions in greater depth...

classic Frankfurt School thinking...

art and culture can create social change, yes?

so, just as culture is always in flux, so too are the cultural industries. As capitalism develops, so too does the innovation sectors...

ouch!

interesting - "regular" folk typically are passive, but the artist, the true original, they CREATE!

yep - so let's look a little closer at culture then...

Before the course started, some of you expressed a desire to learn about the history of entrepreneurship (who the first one was, etc). This is about as close as we can get (describing how the term came to be...)

a wider scope than traditional commercial entrepreneurship...

so, cultural entrepreneurship tends to be specific to entrepreneurship concerning cultural fields/industries ... NOT the cultural impact of entrepreneurship efforts...

aha! Now we're getting somewhere!

What do you think of this analogy? Artists don't typically think of themselves as entrepreneurs (too much ideological baggage), but successful artists have to be entrepreneurial!

ah, neoliberalism (and liquid times) strike again...

good ole Schumpeter...

love it! Let's all be "undertakers"

they found dead birds that fell down the chimney. It is also sad and painful.

powerful implications

wanting to tell a different story, with different characters that weave a different plot

a grand narrative minimizes or marginalizes alternative stories

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its a variegated reality...

also not the point...

not the point...

!!

curiously, my kids were involved in a "venture" at their school where they collected old milk bags and "knit" them into sleeping mats. Not barefoot, but social entrepreneurship that was inherently viatorized (?!)

!

turning the disposable into something valuable. Upcycling...

the barefoot entrepreneur doesn't exist in a vacuum but in a community instead!

yep

! collective rather than individual effort

learning stories allows us to finesse a definition of barefoot entrepreneuring that is distinct from "necessity" entrepreneurship (understood as the shadowy side of conventional opportunity-seeking entrepreneurship)

interesting

!!

...

!!

aha! Clear link to the other reading (and hence, the title of the week as an all-inclusive "unconventional" umbrella -- broader in scope than intended by the other reading...)

good approach... inductive vs. deductive research

connecting the mainstream and marginal contexts...

field-research -- opportunistic, and "real" -- these stories aren't processed like the published accounts of successful (commercial) entrepreneurs...

privileging the "nobodies" (rather than ignoring them).

ethnographic connection with the research subject (empathy)

politics clarified

there is a definite link to communities and "tribes" here (though not consumer based!), networks of support...

Privilege!

The same thing is true when we speak of "capital" (economic, human, social, cultural...)

the languages and experiences of those living "barefoot" require different ways of thinking ...

a political and social agenda, not just economic!

just another reminder...

the (conventional) enterprising individual...

link to indigenous entrepreneurship...

!!

mainstream context, again

**

there's that term again!

a narrative based approach - people's stories about their lives and their struggles (either marginal or mainstream) tell you who they are, their values, etc...

also interesting ! The tribe, but more nomadic than monadic!

!! barefoot entrepreneurs are obviously unconventional...

poorer populations aren't concerned with efficiency or maximizing growth...

context

their mission statement - to re-frame "marginal" actors and actions as entrepreneurial ... so "unconventional" can become the norm?

refuting the great-man or hero-centric entrepreneurial ideology

those who live on the "margins of the neoliberal economic world" are still part of it!

mundane acts of living (often necessary for survival...)

reminder of the mythic and discursive function of the entrepreneur ...

AI has an equal potential to displace people in the workplace or flatten the wealth gap.

bad stuff

good stuff

a fancy way of saying that the constant need to update and maintain an attractive self-image in order to cultivate followers is damaging to one's mental health.

Are autopreneurs "unconventional entrepreneurs"? Are they part of a tribe?

more... the constant emphasis on performance, leading to an illogical and unhealthy end...

curious! I missed this reference to Ashman's piece in my first read...

Are autopreneurs "unconventional entrepreneurs"? Are they part of a tribe?

!!

yowza

ok

can't get my highlighter to cover the text that I want! Liquid times call out for anchors - for we need stability. Passions can become that anchor (for the self, and a sense of community).

social media = social networking = networked entrepreneurship, promoting our selves (via our interests & passions).

cool -- so the unconventional figure has now become the archetype of current (liquid) times.

Do you buy what they're selling?

reinforcing Szeman...

kind of a cool statement with big time implications...

tribes brief definition -- if you really want to get into it, consult Maffesoli, Michel (1996). The Time of the Tribes: The Decline of Individualism in Mass Society.-- in this book Maffesoli claims that neotribalism will replace individualism in a postmodern society that follows modernity (Zygmunt Bauman's notion of liquid society charts some of the same ground ... since modern times are solid times). Neo-tribes are typically consumer tribes (groupings), but also ephemeral and lacking stability (i.e. liquid...)

ripe for tribal entrepreneurship ...

unconventional entrepreneurs likely face a trickier balancing act than conventional entrepreneurs.

the role, further explained...

clear link to emotional intelligence (3 weeks hence) (but also really useful for the concept of emotional labour -- often the most difficult to monetize!)

sketching the contours of liquid times...

so, transcendence, but connection at the same time... bit of a paradox (but that resonates with material from Richard Branson's narrative...)

see fig.1 again!

yep

the role of unconventional entrepreneurs -- a kind of cultural translator...

interesting!

according to this definition, unconventional entrepreneurship is tribal in nature.

the unconventional entrepreneur, fuelled by passion, connects with a tribe of like-minded others, and is able to monetize that passion by selling it to others in the tribe...

a vacation spurred a vocation, fuelled by avocation (passion)

entrepreneurial passion is central to all entrepreneurial activities -- without it one wouldn't carry on in the face of adversity, one wouldn't have the strength to "swim against the current" etc. BUT, domain passion is different...

I found the term "need" to be potentially interesting here. How does this read differently if the word "desire" replaced "need"?

Do you have any experience with this? It doesn't have to be an "extreme sport" like bodybuilding or surfing...

passions related to the personal!

and as a rejoinder, the (also familiar) Szeman-esque response that uncertainty is everywhere, and we all have to be entrepreneurs to cope with the rampant riskiness of everything.

laying out the structure of the subsequent analysis - part 1

Ouch - the authors are talking about you (in a couple of months)!

love it - the things you care most about are what you spend most of your time developing, in turn cultivating (shared) interests, creating new innovation, new products, new opportunities for developing that passion...

more background

does this make inherent sense to you? Because it kind-of flies in the face of neoliberal instrumentalism...

more (familiar) background

cool phrasing

crucial point...

unconventional entrepreneurs try to stay afloat in unconventional (liquid) times.

Note the link to an earlier article!

interesting... link to next highlight...

What's your take on this?

entrepreneurship fills a void that's especially felt at certain times in life...

!!

yep...