Learn FGF23 in 3 minutes | Fibroblast growth factor 23

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Does your next experiment involve Fibroblast growth factor 23 (FGF23)? This is a presentation about FGF23 intended for scientists who are designing controls and performing immunoassays detecting FGF23. It contains useful info such as Western blot band size, protein expression, and interesting facts. Anti-FGF23 Antibody Picoband™ (PB9868): https://www.bosterbio.com/anti-fgf23-picoband-trade-antibody-pb9868-boster.html References: Uniprot.org, ProteinAtlas.org, PMC5595838, PMC7010663, PMC7880350, PMC4121311 Learn more about FGF23 (infographic and discussion): https://www.bosterbio.com/bosterbio-gene-info-cards/FGF23 Boster Biological Technology Website: www.bosterbio.com Email: support@bosterbio.com

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FGF23 IN 3 MINUTES
Quick facts, control designs, Western Blot MW.
Info you can use to find the best FGF23 antibody.

FACTS
01.
Function, structure, etc.
TISSUES
02.
Expressing tissues/cells
WESTERN BLOT
03.
Expected band sizes
HISTORY
04.
…and medical significance
TABLE OF CONTENTS

● Fibroblast Growth Factor 23
(FGF23)
● Phosphotropic hormone secreted
from osteoblasts and osteocytes
● Important for phosphate recycling
● Involved in Vitamin D metabolism
and regulation
● FGF23 is 251 amino acids long
● Protein size: ~32 kDa
01. FACTS
AlphaFold predicted structure
Image source: https://alphafold.ebi.ac.uk/entry/Q9GZV9

02. TISSUES
Image source: https://www.proteinatlas.org/ENSG00000118972-FGF23/tissue

03. FGF23 WESTERN BLOT
123 images available on PMC:
https://www.ncbi.nlm.nih.gov/pmc?term=FGF23+western+blot&report=imagesdocsum
After reviewing several WB images, we observe FGF23 at ~32 kDa.
PMC5595838 Figure 3
PMC7880350 Figure 2
Boster Bio FGF23
Antibody (PB9868,
Rabbit Polyclonal)
PMC7010663 Figure 12
PMC4121311 Figure 2

FGF23 was discovered in 2000 in
mouse brain samples.
04. HISTORY
FGF23 mutations that lead to loss-
of-function of the protein result in
autosomal dominant hereditary
rickets (ADHR) and tumor-induced
osteomalacia (TIO).
2000 CLINICAL POTENTIAL

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EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...

Sérgio Sacani

Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions among stars. Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars. The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun. Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically, the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec. Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation were carried out using the ACIS-Extract software. Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a photon flux threshold of approximately 2 × 10−8 photons cm−2 s −1 . The X-ray sources exhibit a highly concentrated spatial distribution, with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.

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Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...

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The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.

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The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions. Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability. Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields. I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating). I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems. Exposé invité Journées Nationales du GDR GPL 2024

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Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024). Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).

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Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.

Immersive Learning That Works: Research Grounding and Paths Forward

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We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.

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Learn FGF23 in 3 minutes | Fibroblast growth factor 23

1. www.bosterbio.com FGF23 IN 3 MINUTES Quick facts, control designs, Western Blot MW. Info you can use to find the best FGF23 antibody.

2. FACTS 01. Function, structure, etc. TISSUES 02. Expressing tissues/cells WESTERN BLOT 03. Expected band sizes HISTORY 04. …and medical significance TABLE OF CONTENTS

3. ● Fibroblast Growth Factor 23 (FGF23) ● Phosphotropic hormone secreted from osteoblasts and osteocytes ● Important for phosphate recycling ● Involved in Vitamin D metabolism and regulation ● FGF23 is 251 amino acids long ● Protein size: ~32 kDa 01. FACTS AlphaFold predicted structure Image source: https://alphafold.ebi.ac.uk/entry/Q9GZV9

4. 02. TISSUES Image source: https://www.proteinatlas.org/ENSG00000118972-FGF23/tissue

5. 03. FGF23 WESTERN BLOT 123 images available on PMC: https://www.ncbi.nlm.nih.gov/pmc?term=FGF23+western+blot&report=imagesdocsum After reviewing several WB images, we observe FGF23 at ~32 kDa. PMC5595838 Figure 3 PMC7880350 Figure 2 Boster Bio FGF23 Antibody (PB9868, Rabbit Polyclonal) PMC7010663 Figure 12 PMC4121311 Figure 2

6. FGF23 was discovered in 2000 in mouse brain samples. 04. HISTORY FGF23 mutations that lead to loss- of-function of the protein result in autosomal dominant hereditary rickets (ADHR) and tumor-induced osteomalacia (TIO). 2000 CLINICAL POTENTIAL

7. 3942 B Valley Ave Pleasanton, CA 94566 Tel: (888) 466-3604 Email: support@bosterbio.com www.bosterbio.com

Editor's Notes

Does your next experiment involve FGF23? This video is for scientists who want to run Western blot, IHC, flow or other immunoassays against FGF23.
We will cover some basic facts, protein expression, and FGF23’s expected behavior in Western blot. All information in this video is based on public information and no proprietary experimental evidence was used.
Topic 1: Quick facts about FGF23. Fibroblast endothelial growth factor 23, or FGF23, is a phosphotropic hormone that is secreted from specific cells. It is highly involved in the recycling of phosphate as well as regulating and metabolizing Vitamin D. FGF23 is 251 amino acids long and runs about 32 kilodaltons on a western blot.
Topic 2: Where is FGF23 expressed? FGF23 is expressed in osteoblasts and osteoclasts, then secreted to circulate the body. FGF23 RNA is also expressed in the brain. You can find more information on protein atlas dot org to check out which cell lines express FGF23 and which ones don’t. This information will come in handy when designing positive and negative controls for western blot and immunohistochemistry.
Topic 3: FGF23 in Western blotting. Antibody specificity can make or break an experiment. After looking through Western blot images from publications and antibody companies, we can see that typically one band can be expected in an FGF23 western blot at about 32 kilodaltons. Check out the PMC link for more images, which is also provided in the description box.
Topic 4: Some interesting facts about FGF23. FGF23 was originally discovered in 2000 in mouse brain samples. Certain mutations on FGF23 that cause loss of function of the protein can lead to autosomal dominant hereditary rickets and tumor-induced osteomalacia.

Learn FGF23 in 3 minutes | Fibroblast growth factor 23

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