Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literature
Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
8 authors at 3 institutions in 1 country.
Arafat MeahMultiplex Biotechnology Laboratory, Department of Biomedical Engineering, State University of New York at Stony Brook, Stony Brook, NY 11794, USA.ORCID 0009-0009-4908-6523
Vadanasundari VedarethinamMultiplex Biotechnology Laboratory, Department of Biomedical Engineering, State University of New York at Stony Brook, Stony Brook, NY 11794, USA.
Robert BronsteinDivision of Nephrology and Hypertension, Department of Medicine, Stony Brook School of Medicine, Stony Brook, NY 11794, USA.
Nehaben GujaratiDivision of Nephrology and Hypertension, Department of Medicine, Stony Brook School of Medicine, Stony Brook, NY 11794, USA.
Tanya JainChemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Sandeep K MallipattuDivision of Nephrology and Hypertension, Department of Medicine, Stony Brook School of Medicine, Stony Brook, NY 11794, USA.
Yueming LiChemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Jun WangMultiplex Biotechnology Laboratory, Department of Biomedical Engineering, State University of New York at Stony Brook, Stony Brook, NY 11794, USA.
State University of New York · USStony Brook School · USMemorial Sloan Kettering Cancer Center · US
Funding
X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Regulation of y-secretase activity by modulatory proteinsR01AG061350 · NIA · SLOAN-KETTERING INST CAN RESEARCH · PI LI, YUEMING · 2019 to 2023
$4.3M
Transcriptional control of mitochondrial function by KLF6 in diabetic kidney diseaseR01DK112984 · NIDDK · STATE UNIVERSITY NEW YORK STONY BROOK · PI Sandeep K Mallipattu · 2017 to 2026
$3.5M
Molecular mechanisms of gamma-secretase modulation central to Alzheimer’s diseaseR01AG080684 · NIA · SLOAN-KETTERING INST CAN RESEARCH · PI Liang Feng, YUEMING LI · 2023 to 2026
$3.2M
Mechanisms mediating podocyte-parietal epithelial cell crosstalk in proliferative glomerulopathiesR01DK121846 · NIDDK · STATE UNIVERSITY NEW YORK STONY BROOK · PI HE, JOHN CIJIANG, MALLIPATTU, SANDEEP K · 2020 to 2024
$2.7M
Development of Single-Cell Multiplex in Situ Tagging Microtechnology for Comprehensive Profiling of Functionally Diverse Subpopulations and Their Signaling PathwaysR01GM128984 · NIGMS · STATE UNIVERSITY OF NEW YORK AT ALBANY · PI WANG, JUN · 2018 to 2021
$1.3M
High-Resolution Spatial MIST Technology for Functional Proteomic Study of Neuroinflammation in Alzheimer's DiseaseR21AG075087 · NIA · STATE UNIVERSITY NEW YORK STONY BROOK · PI WANG, JUN · 2022 to 2022
$463k
Single-Cell Functional Proteomics Study of Neurodegeneration in Alzheimer's DiseaseR21AG072076 · NIA · STATE UNIVERSITY NEW YORK STONY BROOK · PI WANG, JUN · 2021 to 2021
$439k
ShEEP Request for High-throughput Single Cell Genomics InstrumentationIS1BX004815 · VA · NORTHPORT VA MEDICAL CENTER · PI MALLIPATTU, SANDEEP K · 2019 to 2019
–
Role of KLF15 in proximal tubule metabolismI01BX003698 · VA · NORTHPORT VA MEDICAL CENTER · PI Sandeep K Mallipattu · 2018 to 2026
High-multiplex detection of protein biomarkers across tissue regions has been an attractive spatial biology approach due to significant advantages over traditional immunohistochemistry (IHC) methods. Different from most methods, spatial multiplex in situ tagging (MIST) transfers the spatial protein expression information to an ultrahigh-density, large-scale MIST array. This technique has been optimized to reach single-cell resolution by adoption of smaller array units and 30% 8-arm PEG polymer as transfer medium. Tissue cell nuclei stained with lamin B have been clearly visualized on the MIST arrays and are colocalized with detection of nine mouse brain markers. Pseudocells defined at 10 μm in size have been used to fully profile tissue regions including cells and the intercellular space. We showcased the versatility of our technology by successfully detecting 20 marker proteins in kidney samples with the addition of five minutes atop the duration of standard immunohistochemistry protocols. Spatial MIST is amenable to iterative staining and detection on the same tissue samples. When 25 proteins were co-detected on 1 mouse brain section for each round and 5 rounds were executed, an ultrahigh multiplexity of 125 proteins was obtained for each pseudocell. With its unique abilities, this single-cell spatial MIST technology has the potential to become an important method in advanced diagnosis of complex diseases.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Single-Cell Spatial MIST for Versatile, Scalable Detection of Protein Markers. · full record | OpenQuestion