And what they don’t tell you is Agflow boost is around 85% MAP blended with Agras. Agras, Macropro Extra & K-Till extra plus are the only true 100% compounded products. The rest are “Compound Blends”

CSBP drop us from AgNP to Agflow Boost xtra. Fair enough Price calculator shows they have kept their compounded product margin. Ie they charge 20-30% more for same nutrition for fully compounded I feel like they should have taken the hit on that. What’s everyone else think?

1. Faire - lnkd.in/gYRNr9VM 2. Renaissance Learning - lnkd.in/gesiM_Dw 3. Rec Room - lnkd.in/gErDuTNa 4 AgFlow : agflow.com 5. Quest Software - lnkd.in/gqaB5RTN (2/n) #remotejobs #remotework #remotecareer #remoteopportunities #WorkFromHome

Learning Human T Cell Behaviors through Generative AI Embeddings of T Cell Receptors １．This paper introduces Tarpon, a generative AI model trained on over one million human TCR sequences, that creates interpretable embeddings capturing T cell behaviors across development and disease. ２．Tarpon embeddings can stratify CD4 and CD8 T cell fates across fetal and adult stages using only CDR3 sequences, independent of V/J gene identity, revealing physicochemical signatures that track developmental trajectories. ３．Using Tarpon, the authors developed AgFlow, a flow-based generative model that learns antigen-specific TCR distributions and can generate de novo, physiochemically realistic TCRs specific to antigens like SARS-CoV-2 YLQPRTFLL. ４．AgFlow generated YLQ-specific TCRs that matched experimentally validated activation profiles and even reproduced dominant public TCRs absent from training data, demonstrating potential for in silico TCR discovery. ５．Tarpon’s embeddings correlate with physicochemical properties, enabling interpretable latent dimensions; TCRs cluster by hydrophobicity, aromaticity, and charge, supporting downstream biological insights and mining efforts. ６．Embeddings also reflect antigen specificity: different viral antigens (e.g., CMV, IAV) occupy distinct, learnable regions in latent space, with shared features across immunogenic TCRs suggesting a conserved “immunogenicity signature.” ７．Cross-dataset mapping revealed that CD4/CD8 TCR distinctions learned in fetal thymus generalized to adult cancer and COVID-19 cohorts; fetal-trained models even outperformed adult-trained ones on fetal data. ８．Atypical adult CD8 T cells with “CD4-like” TCRs were associated with severe COVID-19 and higher inflammation markers, suggesting that deviations from fetal-like TCR rules may relate to disease susceptibility. ９．Tarpon uncovered hidden heterogeneity within fetal type I innate T cells, mapping them to adult MAIT and KIR T cell subsets. Transcriptomic analyses confirmed this dual identity, highlighting new developmental links. １０．The model outperforms traditional CDR3-based distance metrics like TCRdist in identifying biologically meaningful distinctions and is computationally efficient (100M embeddings in under 20 minutes on a single GPU). １１．By generating de novo, antigen-specific TCRs and offering interpretable latent features, Tarpon provides a scalable, open framework for TCR repertoire analysis, synthetic TCR design, and cross-cohort immune profiling. 💻Code: github.com/danielgchen/Tarpo… 📜Paper: biorxiv.org/content/10.1101/… #Immunology #TCR #GenAI #DeepLearning #SingleCell #SyntheticBiology #CD4 #CD8 #COVID19 #CancerImmunology

Learning Human T Cell Behaviors through Generative AI Embeddings of T Cell Receptors １．This paper introduces Tarpon, a generative AI model trained on over one million human TCR sequences, that creates interpretable embeddings capturing T cell behaviors across development and disease. ２．Tarpon embeddings can stratify CD4 and CD8 T cell fates across fetal and adult stages using only CDR3 sequences, independent of V/J gene identity, revealing physicochemical signatures that track developmental trajectories. ３．Using Tarpon, the authors developed AgFlow, a flow-based generative model that learns antigen-specific TCR distributions and can generate de novo, physiochemically realistic TCRs specific to antigens like SARS-CoV-2 YLQPRTFLL. ４．AgFlow generated YLQ-specific TCRs that matched experimentally validated activation profiles and even reproduced dominant public TCRs absent from training data, demonstrating potential for in silico TCR discovery. ５．Tarpon’s embeddings correlate with physicochemical properties, enabling interpretable latent dimensions; TCRs cluster by hydrophobicity, aromaticity, and charge, supporting downstream biological insights and mining efforts. ６．Embeddings also reflect antigen specificity: different viral antigens (e.g., CMV, IAV) occupy distinct, learnable regions in latent space, with shared features across immunogenic TCRs suggesting a conserved “immunogenicity signature.” ７．Cross-dataset mapping revealed that CD4/CD8 TCR distinctions learned in fetal thymus generalized to adult cancer and COVID-19 cohorts; fetal-trained models even outperformed adult-trained ones on fetal data. ８．Atypical adult CD8 T cells with “CD4-like” TCRs were associated with severe COVID-19 and higher inflammation markers, suggesting that deviations from fetal-like TCR rules may relate to disease susceptibility. ９．Tarpon uncovered hidden heterogeneity within fetal type I innate T cells, mapping them to adult MAIT and KIR T cell subsets. Transcriptomic analyses confirmed this dual identity, highlighting new developmental links. １０．The model outperforms traditional CDR3-based distance metrics like TCRdist in identifying biologically meaningful distinctions and is computationally efficient (100M embeddings in under 20 minutes on a single GPU). １１．By generating de novo, antigen-specific TCRs and offering interpretable latent features, Tarpon provides a scalable, open framework for TCR repertoire analysis, synthetic TCR design, and cross-cohort immune profiling. 💻Code: github.com/danielgchen/Tarpo… 📜Paper: biorxiv.org/content/10.1101/… #Immunology　#TCR　#GenAI　#DeepLearning　#SingleCell　#SyntheticBiology　#CD4　#CD8　#COVID19　#CancerImmunology

We love seeing our fertilisers in action! Theo and his team are north of Cranbrook, powering through the final 1,400 hectares of wheat seeding with Agflow Mn and banded Flexi-N. 🌾 Their early-sown canola is coming through nicely. 💪🌱

1000 Remote Companies List currently Hiring🚨 Completely Free !! - 10up - 15Five - 17hats - 1Password - abiturma GmbH - Ably - ActiveCampaign - Ad Hoc LLC - Adaface - AddStructure Sweden - Adzuna - AE Studio - Aerolab - AgFlow - Airbank - AIVITEX - ...... - ....... - ...... - ...... - 984 more.. 𝑻𝒐 𝑮𝒆𝒕 𝒕𝒉𝒆 𝒇𝒖𝒍𝒍 𝒍𝒊𝒔𝒕 , 1. Like & Reply “ 𝑹𝒆𝒎𝒐𝒕𝒆 ” 2. Repost (much appreciated☺) 3. Follow me, Harsa Dash (so that I can DM) #Hiring #Job #Placement #RemoteCompanies #RtemoteJobs

Our new @voxeu analysis with @TDeryugina and Wiktor Rajca, using detailed agricultural shipment data from @AgFlow.

1. Faire - lnkd.in/gYRNr9VM 2. Renaissance Learning - lnkd.in/gesiM_Dw 3. Rec Room - lnkd.in/gErDuTNa 4 AgFlow : agflow.com 5. Quest Software- lnkd.in/gqaB5RTN (2/n) #remotejobs #remotework #remotecareer #remoteopportunities #WorkFromHome

1. Faire - lnkd.in/gYRNr9VM 2. Renaissance Learning - lnkd.in/gesiM_Dw 3. Rec Room - lnkd.in/gErDuTNa 4 AgFlow : agflow.com 5. Quest Software - lnkd.in/gqaB5RTN (2/n) #remotejobs #remotework #remotecareer #remoteopportunities

1. Faire - lnkd.in/gYRNr9VM 2. Renaissance Learning - lnkd.in/gesiM_Dw 3. Rec Room - lnkd.in/gErDuTNa 4 AgFlow : agflow.com 5. Quest Software - lnkd.in/gqaB5RTN (2/n) #remotejobs #remotework #remotecareer #remoteopportunities #WorkFromHome

Explore trends and seize opportunities on African agricultural markets! 🚀 Our latest data expansion offers unparalleled insights into #Rice & #Sugar commodities. Grow with AgFlow: hubs.ly/Q02cPwRQ0 #Agribusiness #MarketIntelligence

US soybean prices have shown an interesting trajectory over the last six months. Initial rise, mid-year dip, stabilization, and autumn decline. 📉🌱 Find out more on AgFlow: hubs.ly/Q0280S-M0 #SoybeanMarket #TradeTrends #AgriculturalEconomics

👉 Aerolab : aerolab.co 👉 Aerostrat : aerostratsoftware.com 👉 AgFlow : agflow.com 👉 Aha! : aha.io 👉 Algorithmia : algorithmia.com 👉 ALICE : aliceplatform.com 👉 Alight Solutions : alight.com

It's peak export season for US #soybeans, but look where the ships are. 41 at the PNW for taking soybeans to China, but a plethora of ships destined for China at Brazil, or on their way to China from Brazil. Just one at the Gulf. Map compliments of @agflow #oatt

تقارب #العصابة_الأنجلوسلطانية مع #روسيا 🇷🇺 مؤخراً وزيارة قائد الجيش السلطاني لمعرض آرميا العسكري قبل أيام، ومنح الأوسمة وغيرها من المظاهر،ليست سياسة نأي عن #بريطانيا 🇬🇧حاشا لله فالعصابة يستحيل أن تفعل ذلك. لكن السبب هو الخبز 👇🏻 #عُمان #الامارات_تدنس_جزيره_سقطرى [@agflow 📊]

▶️#AgriDZ [MAÏS] Pour @agflow,l'#Algérie a importé du #maïs: Bresil 0,41 million de tonnes en juillet 2023, Argentine 0,39 million de tonnes. Les importations ont atteint 2,1 millions de tonnes entre janvier et juillet 2023. Les fournisseurs: Brésil,Argentine et la Roumanie,

👉 Aerolab : aerolab.co 👉 Aerostrat : aerostratsoftware.com 👉 AgFlow : agflow.com 👉 Aha! : aha.io 👉 Algorithmia : algorithmia.com 👉 ALICE : aliceplatform.com 👉 Alight Solutions : alight.com

👉 Aerolab : aerolab.co 👉 Aerostrat : aerostratsoftware.com 👉 AgFlow : agflow.com 👉 Aha! : aha.io 👉 Algorithmia : algorithmia.com 👉 ALICE : aliceplatform.com 👉 Alight Solutions : alight.com

👉 Aerolab : aerolab.co 👉 Aerostrat : aerostratsoftware.com 👉 AgFlow : agflow.com 👉 Aha! : aha.io 👉 Algorithmia : algorithmia.com 👉 ALICE : aliceplatform.com 👉 Alight Solutions : alight.com