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Merck & Co high throughput screening
High Throughput Screening, supplied by Merck & Co, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/throughput+screening/electrochemistry+for+high+throughput/pmc13019620-27-7-11
Average 86 stars, based on 1 article reviews
high throughput screening - by Bioz Stars, 2026-11
86/100 stars

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Related Articles

Labeling:

Article Title: Lipid Droplet-Driven Ribosome Collisions Trigger ZAKα-p38 Signaling to Accelerate Testicular Aging.
Article Snippet: The permeability assay of Sertoli cells was performed using a 24- well Transwell chamber with a pore size of 0.4 μm (Corning). .. Fluorescein isothiocyanate (FITC)- labeled dextran (0.5 mg/mL) (Merck) was introduced into the upper chamber and incubated at 37°C for 2 h. The fluorescence intensity of the lower chamber solution (Ex/Em: 492/530 nm) was assessed using a highthroughput multimode detection system. .. Quantifications of fluorescence images and immunoblotting were performed using ImageJ (version 1.8.0).

Incubation:

Article Title: Lipid Droplet-Driven Ribosome Collisions Trigger ZAKα-p38 Signaling to Accelerate Testicular Aging.
Article Snippet: The permeability assay of Sertoli cells was performed using a 24- well Transwell chamber with a pore size of 0.4 μm (Corning). .. Fluorescein isothiocyanate (FITC)- labeled dextran (0.5 mg/mL) (Merck) was introduced into the upper chamber and incubated at 37°C for 2 h. The fluorescence intensity of the lower chamber solution (Ex/Em: 492/530 nm) was assessed using a highthroughput multimode detection system. .. Quantifications of fluorescence images and immunoblotting were performed using ImageJ (version 1.8.0).

Fluorescence:

Article Title: Lipid Droplet-Driven Ribosome Collisions Trigger ZAKα-p38 Signaling to Accelerate Testicular Aging.
Article Snippet: The permeability assay of Sertoli cells was performed using a 24- well Transwell chamber with a pore size of 0.4 μm (Corning). .. Fluorescein isothiocyanate (FITC)- labeled dextran (0.5 mg/mL) (Merck) was introduced into the upper chamber and incubated at 37°C for 2 h. The fluorescence intensity of the lower chamber solution (Ex/Em: 492/530 nm) was assessed using a highthroughput multimode detection system. .. Quantifications of fluorescence images and immunoblotting were performed using ImageJ (version 1.8.0).

High Throughput Screening Assay:

Article Title: Lipid Droplet-Driven Ribosome Collisions Trigger ZAKα-p38 Signaling to Accelerate Testicular Aging.
Article Snippet: The permeability assay of Sertoli cells was performed using a 24- well Transwell chamber with a pore size of 0.4 μm (Corning). .. Fluorescein isothiocyanate (FITC)- labeled dextran (0.5 mg/mL) (Merck) was introduced into the upper chamber and incubated at 37°C for 2 h. The fluorescence intensity of the lower chamber solution (Ex/Em: 492/530 nm) was assessed using a highthroughput multimode detection system. .. Quantifications of fluorescence images and immunoblotting were performed using ImageJ (version 1.8.0).

Article Title: Artificial Intelligence in HPLC Method Development: A Critical Review of Technological Integration, Limitations, and Future Directions.
Article Snippet: The integration of Artificial Intelligence (AI) into High-Performance Liquid Chromatography (HPLC) method development marks a paradigm shift from empirical and interpretive frameworks toward adaptive, data-driven optimization.. This critical review dissects the technological evolution from traditional Design of Experiments (DoE) and retention modeling to AI-powered platforms employing machine learning (ML), deep learning (DL), and reinforcement learning (RL).. While AI offers unmatched capabilities in predicting retention times, optimizing gradient conditions, and enabling real-time control, its adoption remains fragmented due to critical challenges in model interpretability, regulatory validation, and data standardization.

High Performance Liquid Chromatography:

Article Title: Artificial Intelligence in HPLC Method Development: A Critical Review of Technological Integration, Limitations, and Future Directions.
Article Snippet: The integration of Artificial Intelligence (AI) into High-Performance Liquid Chromatography (HPLC) method development marks a paradigm shift from empirical and interpretive frameworks toward adaptive, data-driven optimization.. This critical review dissects the technological evolution from traditional Design of Experiments (DoE) and retention modeling to AI-powered platforms employing machine learning (ML), deep learning (DL), and reinforcement learning (RL).. While AI offers unmatched capabilities in predicting retention times, optimizing gradient conditions, and enabling real-time control, its adoption remains fragmented due to critical challenges in model interpretability, regulatory validation, and data standardization.

Biomarker Discovery:

Article Title: Artificial Intelligence in HPLC Method Development: A Critical Review of Technological Integration, Limitations, and Future Directions.
Article Snippet: The integration of Artificial Intelligence (AI) into High-Performance Liquid Chromatography (HPLC) method development marks a paradigm shift from empirical and interpretive frameworks toward adaptive, data-driven optimization.. This critical review dissects the technological evolution from traditional Design of Experiments (DoE) and retention modeling to AI-powered platforms employing machine learning (ML), deep learning (DL), and reinforcement learning (RL).. While AI offers unmatched capabilities in predicting retention times, optimizing gradient conditions, and enabling real-time control, its adoption remains fragmented due to critical challenges in model interpretability, regulatory validation, and data standardization.

Control:

Article Title: Artificial Intelligence in HPLC Method Development: A Critical Review of Technological Integration, Limitations, and Future Directions.
Article Snippet: The integration of Artificial Intelligence (AI) into High-Performance Liquid Chromatography (HPLC) method development marks a paradigm shift from empirical and interpretive frameworks toward adaptive, data-driven optimization.. This critical review dissects the technological evolution from traditional Design of Experiments (DoE) and retention modeling to AI-powered platforms employing machine learning (ML), deep learning (DL), and reinforcement learning (RL).. While AI offers unmatched capabilities in predicting retention times, optimizing gradient conditions, and enabling real-time control, its adoption remains fragmented due to critical challenges in model interpretability, regulatory validation, and data standardization.

Food & Beverages:

Article Title: Artificial Intelligence in HPLC Method Development: A Critical Review of Technological Integration, Limitations, and Future Directions.
Article Snippet: The integration of Artificial Intelligence (AI) into High-Performance Liquid Chromatography (HPLC) method development marks a paradigm shift from empirical and interpretive frameworks toward adaptive, data-driven optimization.. This critical review dissects the technological evolution from traditional Design of Experiments (DoE) and retention modeling to AI-powered platforms employing machine learning (ML), deep learning (DL), and reinforcement learning (RL).. While AI offers unmatched capabilities in predicting retention times, optimizing gradient conditions, and enabling real-time control, its adoption remains fragmented due to critical challenges in model interpretability, regulatory validation, and data standardization.

other:

Article Title:
Article Snippet: In 2001 and 2002, we entered into collaboration agreements with each of Elan Pharmaceuticals,Inc., SciosInc., Cytokinetics,Inc., Schering-Plough Research Institute,Inc. and Merck& Co.,Inc. to jointly design custom high-throughput screening compound libraries that we will synthesize and qualify.

Article Title: SLFN11-mediated ribosome biogenesis impairment induces TP53-independent apoptosis.
Article Snippet: Protein signals were visualized with Clarity Max Western ECL Substrate (Bio-Rad Laboratories) and an ImageQuant LAS 4000 mini (Cytiva) imager.

shRNA:

Article Title: CD97 maintains tumorigenicity of glioblastoma stem cells via mTORC2 signaling and is targeted by CAR Th9 cells
Article Snippet: Fluorescence images were obtained and analyzed using an Operetta CLS microscope (PerkinElmer Inc.) and Harmony software (PerkinElmer Inc.). .. All shRNA vectors to deplete endogenous human CD97 were purchased from Merck. ..



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