I got all sorts of work units that need to be uploaded. 
Mebbe I’ll try to do so later this weekend.
03/31 update:
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So, hurry up and wait, amirite?
Naw, you don’t have to hurry up.
Good. I’m oooooooooooooold. 
Mebbe I’ll pour myself a little more 
.
Here’s the monthly update on World Community Grid points:
Statistics last updated: 4/1/23 23:59:59 (UTC) [18 hour(s) ago]
Member Name Points Monthly
Generated Change
mbplatt 196,258,288 643
KlaymenAO 166,537,077 645
1695814 80,831,847
Wannabe Actuary 63,409,705
Macroman 59,218,021
Actuarialsuck 34,160,646 674
yoyo_58 31,629,551 670
Breadmaker 10,537,605
meepbobeep 10,014,585
SpaceLobster 6,691,350
GoA_Kenny 366,069
:qunq:Available:qunq: WCG Projects
OpenPandemics - COVID-19
Africa Rainfall Project
Help Stop TB
Mapping Cancer Markers
Smash Childhood Cancer
WCG discussion forums can be found here .
An update on what the raisin is going on with WCG can be found here.
Here’s the monthly update on Folding@Home points:
Monthly
Name Credit Change
1695814 28,894,289 1,736,239
Celalta 12,739,827 101,874
Breadmaker 4,356,785 117,599
Three’s Company, amirite?
Typical Folding@Home Projects
COVID-19
Alzheimer’s
Cancer
Huntington’s
Parkinson’s
For a comprehensive list see https://apps.foldingathome.org/psummary
If you’d like to join us in finding a cure for COVID-19, Cancer, Ebola, AIDS, and other stuff, see the OP ( <-- clicky clicky! ) for links to get the downloads
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The storage failure recovery process has been completed and we have resumed computation on the new storage system.
Read more here: BOINC System Restart
I’ll see if my home computers have received the memo when I get home.
in the best case scenario we will be able to solve all of these issues and prepare for the complete WCG restart.
Oh, maybe not. I have no idea what’s going on anymore.
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My completed work units uploaded!!! 
No new work units available tho. Terry Bradshaw shouldn’t get too comfortable and complacent… I’m jus’ sayin’… 
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And on the big computers too!
Getting ready to cure some covid 19!!!
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Daddy got hizzelf some work units toooooooo!!! 
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α 
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Just got a 1 year badge for OpenPandemics - COVID 19!!! COVID-19 can go fluff itself!!!
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More newsletters!
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RIP Dylan Bucci.
FUCK CANCER!!!
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Smash it with your hulk hands!
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I just installed WCG on my cell phone!!! 
:terrybradshaw: 
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Fazebook update:
The MCM team’s research into lung cancer biomarkers has identified 26 genes that are present with top scores across all the signature sizes considered. This update focuses on a potential biomarker gene called FARP1, which is linked to metastatic development.
Read more here: Research update from the MCM team (April 2023)
read more, Seymour
Research update from the MCM team (April 2023)
The MCM team’s research into lung cancer biomarkers has identified 26 genes that are present with top scores across all the signature sizes considered. This update focuses on a potential biomarker gene called FARP1, which is linked to lung cancer metastasis.
Project: Mapping Cancer Markers
Published on: 28 Apr 2023
Background
The Mapping Cancer Markers project aims to identify the markers associated with various types of cancer with the goal to identify biomarkers to detect cancer earlier, identify high-risk patients and customize treatment for individual patients. To date, over 818,200 CPU years have been donated to the project by WCG volunteers across the world. Thank you all for your support.
In our previous MCM project update, we started to introduce putative lung cancer biomarkers that are present with top scores across all the signature sizes considered. The first update focused on VAMP1, a gene linked to patient survival and differentially expressed in normal lung compared to lung cancer. This update highlights a potential biomarker gene called FARP1, which is linked to metastatic development.
New developments
The protein FARP1 encodes is a guanine nucleotide exchange factor that plays a role in dendritic formation and growth. FARP1 can be found in cell membranes, cytoplasm, synapses and dendrites (Uniprot). Since both VAMP1 and FARP1 are involved with synapses, we investigated whether the two proteins interact together. While they do not interact directly (IID; Integrated Interaction Database) they share two interacting partners, RAB6A and APBA1. RAB6A plays a role in neuron projection development, while APBA1 regulates APP (Alzheimer’s disease amyloid precursor protein), and is thought to have a role in the secretion of synaptic vesicles.
Neither RAB6A nor APBA1 are present in the top 99th percentile, but they suggest that there is indeed a neuronal signal associated with our two proteins of interest – VAMP1 and FARP1. The importance of this finding is related to the difficult-to-study connection between lung cancer and one of its most frequent sites of metastasis: the brain[1]. Moreover, it has been shown that FARP1 is one of the key drivers of migration and invasion in lung cancer[2].
We thus decided to investigate further the importance of this gene using external datasets. FARP1 is a potential diagnostic biomarker, similar to VAMP1, as highlighted in Figure 1. Furthermore, FARP1 is differentially expressed in metastatic samples, strengthening the connection between the molecular function of this protein and the phenotype it can help develop.
Figure 1. Expression of FARP1 in normal samples, lung cancer and metastatic samples.
cBioPortal shows that FARP1 is significantly linked to the patients’ smoking status, and according to mirDIP, it is targeted by hsa-mir-105 (a microRNA specific to former smokers, similarly to VAMP1) and hsa-mir-150 (a microRNA specific to never smokers)[3]. The connection between smoking and lung cancer development is well established, but the molecular landscape behind such development is still not completely understood. Our signatures, derived from a dataset of patients with a history of smoking, can shed light on the molecular mechanisms and support researchers investigating the connection.
While we keep validating our results, we are excited about the impact our results can have on patient lives and research, computed by thousands of volunteers. Thank you for the contribution to this research.
If you have any comments or questions, please leave them in this thread for us to answer. Thank you for your support, patience and understanding.
References:
- Xie M, Su C. Microenvironment and the progress of immunotherapy in clinical practice of NSCLC brain metastasis. Front Oncol. 2023 Jan 24;12:1006284. doi: 10.3389/fonc.2022.1006284. PMID: 36761422; PMCID: PMC9902941.
- Cooke M, Kreider-Letterman G, Baker MJ, Zhang S, Sullivan NT, Eruslanov E, Abba MC, Goicoechea SM, García-Mata R, Kazanietz MG. FARP1, ARHGEF39, and TIAM2 are essential receptor tyrosine kinase effectors for Rac1-dependent cell motility in human lung adenocarcinoma. Cell Rep. 2021 Nov 2;37(5):109905. doi: 10.1016/j.celrep.2021.109905. PMID: 34731623; PMCID: PMC8627373.
- Vucic EA, Thu KL, Pikor LA, Enfield KS, Yee J, English JC, MacAulay CE, Lam S, Jurisica I, Lam WL. Smoking status impacts microRNA mediated prognosis and lung adenocarcinoma biology. BMC Cancer. 2014 Oct 24;14:778. doi: 10.1186/1471-2407-14-778. PMID: 25342220; PMCID: PMC4216369.
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Here’s the monthly update on World Community Grid points:
Member Name Points Monthly
Generated Change
mbplatt 197,784,653 1,526,365
KlaymenAO 169,165,810 2,628,733
1695814 83,110,799 2,278,952
Wannabe Actuary 64,457,144 1,047,439
Macroman 59,284,944 66,923
Actuarialsuck 36,027,722 1,867,076
yoyo_58 32,567,368 937,817
Breadmaker 10,756,882 219,277
meepbobeep 10,145,198 130,613
SpaceLobster 7,342,329 650,979
GoA_Kenny 366,069
Statistics last updated: 4/30/23 23:59:59 (UTC) [3 hour(s) ago]
Available WCG Projects:
OpenPandemics - COVID-19
Africa Rainfall Project
Help Stop TB
Mapping Cancer Markers
Smash Childhood Cancer
WCG discussion forums can be found here .
Here’s the monthly update on Folding@Home points:
Monthly
Name Credit Change
1695814 29,546,356 652,067
Breadmaker 4,505,277 148,492
And then there were two.
Typical Folding@Home Projects
COVID-19
Alzheimer’s
Cancer
Huntington’s
Parkinson’s
For a comprehensive list see https://apps.foldingathome.org/psummary
If you’d like to join us in finding a cure for COVID-19, Cancer, Ebola, AIDS, and other stuff, see the OP ( <-- clicky clicky! ) for links to get the downloads
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From the face off…
The Microbiome Immunity Project team has published a new article about the structure and function of human microbiome proteins.
Read more here: Research update from the Microbiome Immunity Project team (May 2023)
…or here:
readme.txt.jpg
Research update from the Microbiome Immunity Project team (May 2023)
The Microbiome Immunity Project team has published a new article about the structure and function of human microbiome proteins.
Project: Microbiome Immunity Project
Published on: 5 May 2023
Background
While bacteria in general can be harmful to humans, as it can cause diseases such as pneumonia, meningitis, strep throat, food poisoning (Escherichia coli and Salmonella), bacteria in the human gut also have protective functions. For many years scientists have studied the various types of bacteria in the human body and characterized those that could be harmful or useful, but the vast majority remain poorly characterized. With an estimated 3 million unique bacterial genes known to exist, studying all of the resulting proteins and determining their function is a complex task.
The Microbiome Immunity Project started in August 2017 with the goal to speedup protein molecule research thanks to the power of grid computing. By the time the computation finished in December 2021, World Community Grid volunteers donated nearly 146,000 CPU years to the MIP. This effort enabled the team to predict the structure of almost 200,000 proteins, discover over 150 new protein shapes (folds), describe several previously unknown functions of protein structures, and nearly double the number of annotated proteins in the human gut microbiome.
Protein Universe Paper
The MIP team has recently published their paper in Nature Communications titled Sequence-structure-function relationships in the microbial protein universe [1]. This article explores the notion that proteins with similar sequences will not necessarily create similar structures that perform the same functions, contrary to a long-held belief among scientists. Using the MIP database that WCG volunteers helped create, the paper explores examples where proteins similar in sequence perform different functions.
The MIP team analyzed 2 million protein sequences that had no known structure in any other database. They then used Rosetta and DMPFold methods to predict the protein structures in a three-step process. To filter out low quality predictions, they first determined a threshold amount of coil residues (that form helices) above which the structures were not reliable. Second, they used confidence and quality assessment scores to determine the predicted quality[2]. Third, priority was given to models in agreement between the 2 methods. In the end, about 200,000 models were identified and characterized.
Figure 1. Flowchart of the process to arrive at ~200,000 de novo protein models covering a diverse sequence space[1]. Reused from Koehler et al., Nature Communications, 2023 paper with permission, under the Creative Common license CCBY3.0.
This new database provides a unique view into gut microbiome, as it is different in coverage and scope from previous efforts. The researchers compared the set of 200,000 models to the PDB90 database from the Protein Data Bank and other protein structure databases to determine that the predicted structures were novel. A factor affecting the difference of the two databases is the presence of proteins from Archaea and Bacteria in the MIP database, a species poorly represented in other databases. Moreover, the sequence size analyzed is smaller than in other databases (protein structures predicted were ranging from 40-200 residues in size), and less biased towards proteins of interest, as is the case for PDB90 (that contains proteins more prone to structure determination and possible pharmaceutical targets, leading to multiple close variants of the same structures). This makes MIP complementary to other databases.
To test if this had any effect on the sequence-structure-function relationship, they analyzed the structural and functional similarities of 5,000 structures from the MIP and 1,000 baseline structures from the PDB databases. When correlating structural and functional similarity, the majority of pairs showed the expected behavior (i.e., different structure, different function or same structure, same function), but a notable number of pairs behaved contrary to their expectations. Analyzing the discordant pairs, the authors found that more generic functions can be performed by multiple types of structures, while very specific mechanisms are carried out only by unique structures.
Figure 2. Heatmaps that show the functional similarity between pairs of protein clusters. Clusters 158 and 153 (top left and right) cover proteins with similar structures (bottom left and right) and diverging functions[1]. Reused from Koehler et al., Nature Communications, 2023 paper with permission, under the Creative Common license CCBY3.0.
This study paves the road to the development of tools to explore and predict site-specific protein functions for other organisms as well, in order to better understand the role of specific structures and functions related to biological functions.
“Until now, we have been talking about the microbiome in the same language one would use to describe the biodiversity of a rainforest,” Dr. Tomasz Kosciolek, a member of the MIP research team says. “We hope to start talking about it in more mechanistic terms, like what molecules might amplify, inhibit or change certain biological processes.”
Thank you to the Microbiome Immunity Project team for providing this update. If you have any comments or questions, please leave them in this thread for us to answer. Thank you for your continued support that accelerates large-scale scientific research for the betterment of humanity.
References:
- Koehler Leman, J., Szczerbiak, P., Renfrew, P.D. et al. Sequence-structure-function relationships in the microbial protein universe. Nature Communications 14, 2351 (2023). Sequence-structure-function relationships in the microbial protein universe | Nature Communications.
- Zhang Y, Skolnick J. Scoring function for automated assessment of protein structure template quality. Proteins. 2004 Dec 1;57(4):702-10. doi: 10.1002/prot.20264. Erratum in: Proteins. 2007 Sep 1;68(4):1020. PMID: 15476259
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