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AT 17

AT 17 is a novel small-molecule inhibitor that targets a key signaling pathway involved in cellular proliferation and survival.
This compound has demonstrated potent anti-tumor activity in preclinical models, making it a promising candidate for further clinical development.
AT 17 works by selectively inhibiting the activity of a crucial enzyme, disrupting the aberrant signaling that drives tumor growth and progression.
Ongoing research is focused on elucidating the precise mechanism of action and evaluating the efficacy of AT 17 across a range of cancer types.
This compound holds significant potential as a novel therapeutic option for patients with difficult-to-treat malignancies.
Further studies will be needed to fully characterize the safety and efficacy profile of AT 17 and to optimize its clinical application.

Most cited protocols related to «AT 17»

1
Cardiometabolic Trajectory Associations
Participant’s descriptive characteristics were summarized as means and standard deviation, medians, and interquartile ranges, or frequencies and percentages. We explored sex differences using independent t tests, Mann-Whitney U tests, or χ2 tests for normally distributed, skewed or dichotomous variables, respectively. We assessed the normality of variables and logarithmically or reciprocally transformed skewed variables before further analyses.
We investigated the separate longitudinal associations of cfPWV and cIMT (predictors) at 17.7 years with each of fasting LDL, HDL, triglyceride, insulin, and glucose categories (outcomes) at 24.5 years using binary logistic regression models (Supplemental Material). We also examined the separate associations of the 7-year progression in cfPWV and cIMT with the longitudinal progression in each of the metabolic outcomes from ages 17.7 to 24.5 years using linear mixed-effect models for repeated measures. Analyses were adjusted for sex, age at 17.7 years, and covariates repeatedly measured at ages 17.7 and 24.5 years, viz, resting heart rate, systolic blood pressure, fat mass, lean mass, high-sensitivity C-reactive protein, smoking status, family history of hypertension, diabetes, high cholesterol or vascular disease and moderate to vigorous physical activity at 15.5 and 24.5 years as well as fasting plasma samples; LDL, HDL, insulin, triglyceride, or glucose, depending on the outcome.
Lastly, we used structural equation modeling with autoregressive cross-lagged path analysis (detailed in the Supplemental Material and published earlier13 (link)) to examine the separate temporal causal associations of cfPWV and cIMT with metabolic outcomes, adjusting for covariates listed above. All covariates were selected based on previous studies.3 (link),11 (link)–13 (link),18 (link),19 (link) We examined sex interactions and presented sex-stratified results. We also presented body mass index–weight stratified results, cross-sectional results, and age- and sex-adjusted partial correlation analyses in Tables S4 through S7. Differences and associations with a 2-sided P<0.05 were considered statistically significant with conclusions based on effect estimates and their CI or SE. Analyses involving 40% of a sample of 10 000 ALSPAC children at 0.8 statistical power, 0.05 alpha, and 2-sided P value would show a minimum detectable effect size of 0.049 standard deviations if they had relevant exposure for a normally distributed quantitative variable.20 (link) All statistical analyses were performed using SPSS statistics software, Version 27.0 (IBM Corp, Armonk, NY), and structural equation modeling were conducted using IBM AMOS version 27.0.
Agbaje A.O., Barker A.R., Mitchell G.F, & Tuomainen T.P. (2022). Effect of Arterial Stiffness and Carotid Intima-Media Thickness Progression on the Risk of Dysglycemia, Insulin Resistance, and Dyslipidemia: a Temporal Causal Longitudinal Study. Hypertension (Dallas, Tex. : 1979), 79(3), 667-678.
Publication 2022
AT 17 Child C Reactive Protein Diabetes Mellitus Disease Progression Glucose High Blood Pressures Hypercholesterolemia Index, Body Mass Insulin Plasma Rate, Heart Systolic Pressure Triglycerides Vascular Diseases
2
Microarray-Based Breast Cancer Prognosis Analysis
Aliquots of total RNA of 149 frozen tumor samples was available for this study, for 13 samples (8 out of 78 and 5 of the 145 tumor series, see above) new RNA was isolated from available frozen tumor tissue as described previously [6 (link),13 (link),22 (link)]. Two-hundred nanogram total RNA was amplified using the Low RNA Input Fluorescent Labeling Kit (Agilent Technologies). Cyanine 3-CTP or Cyanine 5-CTP (Perkin Elmer) was directly incorporated into the cRNA during in vitro transcription. A total of 200 ng of Cyanine-labeled RNA was co-hybridized with a standard reference to custom 8-pack mini-microarrays (MammaPrint, Agendia) at 60°C for 17 hrs and subsequently washed according to the Agilent standard hybridization protocol (Agilent Oligo Microarray Kit, Agilent Technologies). The reference sample consisted of pooled and amplified RNA of 105 primary breast tumors selected from patients of the clinical validation series [13 (link)] in such a way that it had a similar proportional distribution between good and poor profile patients. Sufficient reference material was generated for over 30,000 hybridizations. For each tumor two hybridizations were performed by using a reversal fluorescent dye.
The customized mini-array contained 1,900 60-mer oligonucleotide probes that comprise the 232 prognosis related genes [6 (link)] identical to the probes on the original array, including the genes of the 70-gene prognosis classifier, spotted in triplicate. Each array additionally includes 289 probes for hybridization and printing quality control as well as 915 normalization genes. Eight identical MammaPrint arrays are present on a single 1" × 3" slide, allowing for eight individual hybridizations to be performed simultaneously. After hybridization the slides were washed and subsequently scanned with a dual laser scanner (Agilent Technologies). Microarray raw data are available at the European Bioinformatics Institute (EBI) Arrayexpress database;[23 (link)] accession number E-TABM-115.
Glas A.M., Floore A., Delahaye L.J., Witteveen A.T., Pover R.C., Bakx N., Lahti-Domenici J.S., Bruinsma T.J., Warmoes M.O., Bernards R., Wessels L.F, & Van 't Veer L.J. (2006). Converting a breast cancer microarray signature into a high-throughput diagnostic test. BMC Genomics, 7, 278.
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Publication 2006
Acid Hybridizations, Nucleic AT 17 Breast Neoplasm Complementary RNA Europeans Fluorescent Dyes Freezing Genes Microarray Analysis Neoplasms Oligonucleotide Probes Oligonucleotides Patients Prognosis RNA, Neoplasm Tissues Transcription, Genetic
3
High-resolution Nanoflow LC-MS/MS of Peptides
Dried peptides
were dissolved in 5% formic acid and 0.1% TFA. Peptides were loaded
on a 100 μm × 150 cm column using a nano ACQUITY UHPLC
(Waters) system that was interfaced to a Q Exactive MS (Thermo Fisher
Scientific) through a nanoelectrospray ion source.39 (link) Peptides were separated by a designed gradient as indicated
(solvent A: 0.2% formic acid; solvent B: 70% ACN, 0.2% formic acid).
The peak capacity at each gradient time was calculated using formula p = 1 + tg/w, where tg is the time of the gradient
and w is the average peak width across entire LC
runs.31 (link) The peak width of individual LC
run was estimated by averaging the chromatographic peak width (4σ,
where 2σ is defined as fwhm of the corresponding extracted ion
chromatograms) of major peptide ions. Peptides in the 10 basic pH
LC subfractions were resolved similarly on this long column using
a 540 min, 15–65% buffer B linear gradient. The Q Exactive
was operated in a data-dependent mode switching between full scan
MS and up to 20 MS/MS acquisitions. The survey scans with an m/z range of 300–1600 were acquired
in the Orbitrap with 35 000 resolution at m/z = 200 and a predicted AGC value of 1 × 106 with maximal ion time of 60 ms. The ions detected in survey
scans were then sequentially isolated and fragmented by HCD at normalized
collision energy of 28 eV. The maximal ion injection time for MS/MS
was set to 60 ms at a resolution of 17 500 or 128 ms with a
resolution of 35 000. Isolation of precursor ions was performed
at 1.6 m/z window. Different dynamic
exclusion times were evaluated to maximize peptide identification
including 10, 20, 40, and 60 s. At last, 20 s was chosen for AD brain
samples. For GPF method, the operation of Q Exactive MS was similar
to the non-GPF method with minor modifications. The entire m/z range for MS1 was 300–1600 but
was divided into multiple m/z subsections,
which were described in the Results and Discussion section. Each m/z subsection had
10 m/z overlapping with adjacent
subsections.25 (link),40 (link) For data acquisition of GPF,
the cycle started at the first m/z subsection of MS1 acquisition, and its data-dependent MS/MS was
followed by the second m/z subsection
of MS1 acquisition and its data-dependent MS/MS until the full m/z range in MS1 was covered.
Wang H., Yang Y., Li Y., Bai B., Wang X., Tan H., Liu T., Beach T.G., Peng J, & Wu Z. (2014). Systematic Optimization of Long Gradient Chromatography Mass Spectrometry for Deep Analysis of Brain Proteome. Journal of Proteome Research, 14(2), 829-838.
Publication 2014
AT 17 Buffers Chromatography formic acid Ions isolation Peptides Radionuclide Imaging Solvents Tandem Mass Spectrometry Z 300
4
Quantifying Fungal Cell Wall Components
Cell wall mannan, β-glucan and chitin contents were determined by hydrolysis of these oligosaccharides and quantification by high-performance anion-exchange chromatography, as described previously [47] (link). To detect chitin, ex vivo isolated C. albicans cells were stained and quantified using Calcofluor White, as previously described [22] (link). TEM analysis was performed as previously described [36] (link).
To detect exposed β-glucan, C57BL/6J mice were injected in the tail vein with 5.2×104 CFU of either SC5314-GFP or ATCC18804-GFP. SC5314-GFP and ATCC18804-GFP strains were created by transformation with the pENO1-yEGFP3-NAT plasmid and verified by PCR as described previously [17] (link). After nine days, mice were sacrificed and the kidneys were harvested, homogenized, and processed as described [17] (link). Homogenates were stained with anti-β-glucan antibody (Biosupplies, Inc., Australia) at a concentration of 1.7 µg/ml, then stained with goat anti-mouse Cy3 antibody (Jackson Immunoresearch) at a concentration of 3.8 µg/ml. For soluble Dectin-1-Fc staining, homogenates were instead stained with Alexa647-labelled Dectin-1-Fc [48] (link) at a concentration of 17 µg/ml and then with donkey anti-human IgG Cy3 antibody (Jackson Immunoresearch) at a concentration of 0.8 µg/ml. Cells were visualized by optical sectioning fluorescence microscopy using a Zeiss Axiovision Vivotome microscope (Carl Zeiss Microscopy, LLC). Live cells were identified based on characteristic EGFP fluorescence. Maximum projection images were quantified using Cellprofiler (www.cellprofiler.org) as described [17] (link). Briefly, EGFP fluorescence was used to manually define individual cell segments and average fluorescence intensity of β-glucan or Dectin-1-CRD fluorescence was measured for the whole cell segment. Cells labelled without primary antibody or Dectin-1-CRD were used as negative controls. In vitro grown cells were stained with soluble Dectin-1 at 5 µg/ml and then with anti-human IgG antibody (used at 1∶200) (Jackson Immunoresearch). Controls were stained with secondary antibody only.
Marakalala M.J., Vautier S., Potrykus J., Walker L.A., Shepardson K.M., Hopke A., Mora-Montes H.M., Kerrigan A., Netea M.G., Murray G.I., MacCallum D.M., Wheeler R., Munro C.A., Gow N.A., Cramer R.A., Brown A.J, & Brown G.D. (2013). Differential Adaptation of Candida albicans In Vivo Modulates Immune Recognition by Dectin-1. PLoS Pathogens, 9(4), e1003315.
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Publication 2013
Alexa Fluor 647 Anions anti-IgG Antibodies, Anti-Idiotypic AT 17 beta-Glucans calcofluor white Candida albicans Cells Cell Wall Chitin Chromatography dectin 1 Equus asinus Fluorescence Goat Homo sapiens Hydrolysis Immunoglobulins Kidney Mannans Mice, Inbred C57BL Microscopy Microscopy, Fluorescence Mus Oligosaccharides Plasmids Strains Tail Veins
5
Aortic Atherosclerosis Quantification in Apoe-/- Mice
At the ages of 17 and 21 weeks (before and 4 weeks after infusion), the Apoe−/− mice were killed by anaesthetisation with diethyl ether. The whole aorta was washed with perfused PBS and fixed with 4% paraformaldehyde (wt/vol.) [14 (link)]. The aorta was excised from the root to the abdominal area, and the connective and adipose tissues carefully removed. The entire aorta and cross-sections of the aortic root were stained with oil red O for assessment of atherosclerotic lesions [14 (link)]. Macrophage infiltration into the aortic wall was visualised by anti-mouse MOMA-2 antibody staining [10 (link), 14 (link)]. Haematoxylin was used for nuclear staining. The areas of the aorta with atherosclerotic lesions were traced by an investigator blind to the treatment and measured by an image analyser (Adobe Photoshop, San Jose, CA; NIH Scion Image, Frederick, MD, USA) [10 (link), 14 (link)]. The severity of atheromatous plaques and degree of macrophage accumulation were expressed as percentages of the lesion area relative to the entire cross-section of the aortic wall [10 (link), 14 (link)].
Nagashima M., Watanabe T., Terasaki M., Tomoyasu M., Nohtomi K., Kim-Kaneyama J., Miyazaki A, & Hirano T. (2011). Native incretins prevent the development of atherosclerotic lesions in apolipoprotein E knockout mice. Diabetologia, 54(10), 2649-2659.
Publication 2011
Abdomen Antibodies, Anti-Idiotypic Aorta Aortic Root Apolipoproteins E AT 17 Atheroma Ethyl Ether Hematoxylin Macrophage Mus paraform Tissue, Adipose Tooth Root Visually Impaired Persons

Most recents protocols related to «AT 17»

1
Computational Fluid Dynamics of Aortic Flow
Using the 3D reconstructed model, CFD simulations of the flow were performed by solving the Reynolds-averaged Navier-Stokes (RANS) equations using the open-source computational continuum mechanics library, OpenFOAM (version 2106). The gravitational force is not considered in the present simulations. The effects of turbulence were modeled using the two-equation eddy-viscosity k − ω shear stress transport (SST) turbulence model (32 , 33 (link)). The k − ω SST model was chosen because of its reported good behavior in adverse pressure gradients and separated flows (34 (link)), and because it has been shown to be capable of handling multi-regime (laminar, transitional, turbulent) flows (35 (link)).
The CFD boundary conditions were specified to match the corresponding in vitro experiments. A constant, uniform inlet velocity was applied to the extended inlet to obtain fully developed flow entering the inlet to the ascending aorta at a flow rate of 5.17 L/min. A no-slip velocity boundary condition was applied on the walls, which were assumed to be rigid. The pressureInletOutletVelocity condition in OpenFOAM was applied for the velocity on all outlet boundaries, which uses a zero-gradient Neumann condition on boundary faces with outflow and an extrapolated Dirichlet condition on faces with reversed inflow. A zero-gradient pressure condition was applied at the inlet and fixed static pressure boundary conditions were prescribed on all outlets. The values of outlet pressure were specified by iteratively performing simulations to match the measured flow rate through each outlet in the experiments to within ±10%.
Bhardwaj S., Craven B.A., Sever J.E., Costanzo F., Simon S.D, & Manning K.B. (2023). Modeling flow in an in vitro anatomical cerebrovascular model with experimental validation. Frontiers in Medical Technology, 5, 1130201.
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Publication 2023
Ascending Aorta AT 17 cDNA Library Face Gravitation Mechanics Muscle Rigidity Pressure Training Programs Viscosity
2
Affinity Purification and Mass Spectrometry
Eluates from biotin pull-down were transferred to fresh microfuge tubes. NuPAGE sample loading buffer was added to the beads and heated at 90 °C for 5 min. A magnetic rack was used to separate the beads from the proteins. The supernatant was then run on an SDS–PAGE gel (Bis-Tris, 4–12%) enough to get the sample into the gel. Gel sections were excised, washed, reduced with DTT, alkylated with iodoacetamide and digested overnight with trypsin at 37 °C (ref. 54 (link)). Homemade C18 StageTips were prepared as described previously55 (link) and preconditioned with a 50 μl wash of methanol, 50 μl wash of 70% acetonitrile/0.1% trifluoroacetic acid and two 50 μl washes of 0.1% trifluoroacetic acid at 1,000g. Peptides were then loaded onto StageTips and washed with 50 μl of 0.1% formic acid and were eluted with 60 μl of 70% acetonitrile/0.1% formic acid. The samples were then vacuum centrifuged using the SpeedVac and reconstituted in 0.1% formic acid for LC–MS/MS and were analysed by microcapillary LC–MS/MS using the nanoAcquity system (Waters) with a 100 μm inner-diameter × 10 cm length C18 column (1.7 μm BEH130, Waters) configured with a 180 μm × 2 cm trap column coupled to a Q-Exactive Plus mass spectrometer (Thermo Fisher Scientific). Peptides were eluted at 300 nl min−1 using a 4 h acetonitrile gradient (0.1% formic acid). The Q-Exactive Plus mass spectrometer was operated in automatic, data-dependent MS/MS acquisition mode with one MS full scan (380–1,600 m/z) at 70,000 mass resolution and up to ten concurrent MS/MS scans for the ten most intense peaks selected from each survey scan. Survey scans were acquired in profile mode and MS/MS scans were acquired in centroid mode at 17,500 resolutions with an isolation window of 1.5 amu and normalized collision energy of 27; AGC was set to 1 × 106 for MS1 and 5 × 104 and 50 ms max IT for MS2; charge exclusion of unassigned, +1 and greater than 6 was enabled with dynamic exclusion of 15 s.
Wang H., Fan Z., Shliaha P.V., Miele M., Hendrickson R.C., Jiang X, & Helin K. (2023). H3K4me3 regulates RNA polymerase II promoter-proximal pause-release. Nature, 615(7951), 339-348.
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Publication 2023
acetonitrile AT 17 Biotin Bistris Buffers formic acid Iodoacetamide isolation Lanugo Methanol Peptides Proteins Radionuclide Imaging SDS-PAGE Tandem Mass Spectrometry Trifluoroacetic Acid Trypsin Vacuum
3
Affinity Purification and Mass Spectrometry
Eluates from biotin pull-down were transferred to fresh microfuge tubes. NuPAGE sample loading buffer was added to the beads and heated at 90 °C for 5 min. A magnetic rack was used to separate the beads from the proteins. The supernatant was then run on an SDS–PAGE gel (Bis-Tris, 4–12%) enough to get the sample into the gel. Gel sections were excised, washed, reduced with DTT, alkylated with iodoacetamide and digested overnight with trypsin at 37 °C (ref. 54 (link)). Homemade C18 StageTips were prepared as described previously55 (link) and preconditioned with a 50 μl wash of methanol, 50 μl wash of 70% acetonitrile/0.1% trifluoroacetic acid and two 50 μl washes of 0.1% trifluoroacetic acid at 1,000g. Peptides were then loaded onto StageTips and washed with 50 μl of 0.1% formic acid and were eluted with 60 μl of 70% acetonitrile/0.1% formic acid. The samples were then vacuum centrifuged using the SpeedVac and reconstituted in 0.1% formic acid for LC–MS/MS and were analysed by microcapillary LC–MS/MS using the nanoAcquity system (Waters) with a 100 μm inner-diameter × 10 cm length C18 column (1.7 μm BEH130, Waters) configured with a 180 μm × 2 cm trap column coupled to a Q-Exactive Plus mass spectrometer (Thermo Fisher Scientific). Peptides were eluted at 300 nl min−1 using a 4 h acetonitrile gradient (0.1% formic acid). The Q-Exactive Plus mass spectrometer was operated in automatic, data-dependent MS/MS acquisition mode with one MS full scan (380–1,600 m/z) at 70,000 mass resolution and up to ten concurrent MS/MS scans for the ten most intense peaks selected from each survey scan. Survey scans were acquired in profile mode and MS/MS scans were acquired in centroid mode at 17,500 resolutions with an isolation window of 1.5 amu and normalized collision energy of 27; AGC was set to 1 × 106 for MS1 and 5 × 104 and 50 ms max IT for MS2; charge exclusion of unassigned, +1 and greater than 6 was enabled with dynamic exclusion of 15 s.
Wang H., Fan Z., Shliaha P.V., Miele M., Hendrickson R.C., Jiang X, & Helin K. (2023). H3K4me3 regulates RNA polymerase II promoter-proximal pause-release. Nature, 615(7951), 339-348.
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Publication 2023
acetonitrile AT 17 Biotin Bistris Buffers formic acid Iodoacetamide isolation Lanugo Methanol Peptides Proteins Radionuclide Imaging SDS-PAGE Tandem Mass Spectrometry Trifluoroacetic Acid Trypsin Vacuum
4
Affinity Purification and Mass Spectrometry
Eluates from biotin pull-down were transferred to fresh microfuge tubes. NuPAGE sample loading buffer was added to the beads and heated at 90 °C for 5 min. A magnetic rack was used to separate the beads from the proteins. The supernatant was then run on an SDS–PAGE gel (Bis-Tris, 4–12%) enough to get the sample into the gel. Gel sections were excised, washed, reduced with DTT, alkylated with iodoacetamide and digested overnight with trypsin at 37 °C (ref. 54 (link)). Homemade C18 StageTips were prepared as described previously55 (link) and preconditioned with a 50 μl wash of methanol, 50 μl wash of 70% acetonitrile/0.1% trifluoroacetic acid and two 50 μl washes of 0.1% trifluoroacetic acid at 1,000g. Peptides were then loaded onto StageTips and washed with 50 μl of 0.1% formic acid and were eluted with 60 μl of 70% acetonitrile/0.1% formic acid. The samples were then vacuum centrifuged using the SpeedVac and reconstituted in 0.1% formic acid for LC–MS/MS and were analysed by microcapillary LC–MS/MS using the nanoAcquity system (Waters) with a 100 μm inner-diameter × 10 cm length C18 column (1.7 μm BEH130, Waters) configured with a 180 μm × 2 cm trap column coupled to a Q-Exactive Plus mass spectrometer (Thermo Fisher Scientific). Peptides were eluted at 300 nl min−1 using a 4 h acetonitrile gradient (0.1% formic acid). The Q-Exactive Plus mass spectrometer was operated in automatic, data-dependent MS/MS acquisition mode with one MS full scan (380–1,600 m/z) at 70,000 mass resolution and up to ten concurrent MS/MS scans for the ten most intense peaks selected from each survey scan. Survey scans were acquired in profile mode and MS/MS scans were acquired in centroid mode at 17,500 resolutions with an isolation window of 1.5 amu and normalized collision energy of 27; AGC was set to 1 × 106 for MS1 and 5 × 104 and 50 ms max IT for MS2; charge exclusion of unassigned, +1 and greater than 6 was enabled with dynamic exclusion of 15 s.
Wang H., Fan Z., Shliaha P.V., Miele M., Hendrickson R.C., Jiang X, & Helin K. (2023). H3K4me3 regulates RNA polymerase II promoter-proximal pause-release. Nature, 615(7951), 339-348.
Full text: Click here
Publication 2023
acetonitrile AT 17 Biotin Bistris Buffers formic acid Iodoacetamide isolation Lanugo Methanol Peptides Proteins Radionuclide Imaging SDS-PAGE Tandem Mass Spectrometry Trifluoroacetic Acid Trypsin Vacuum
5
Infant fNIRS Resting-State Brain Imaging
While infants lay in the incubator, we acquired fNIRS signals using a multichannel NIRSport2 system (NIRStar Software v14.0, NIRx Medical Technologies LLC, Berlin, Germany) at a sampling rate of 10.17 Hz (Fig. 2). We inserted eight sources and eight detectors into predefined cap areas, with ten channels (22 mm separation) defined for each hemisphere (20 total). The optodes were placed over the prefrontal and sensorimotor regions. The first 16 sessions out of 182 used a slightly different montage, so all datasets have been merged to contain 20 out of 24 possible channels (Supplementary Fig. 1). Each light source contains two LEDs that emit at 760 nm and 850 nm. The fNIRS cap was positioned on the infant’s head according to the manufacturer’s guidelines. Resting-state fNIRS were acquired for a minimum of 2.5 min and a mean of 6.8 min45 (link).

fNIRS acquisition system. (A) fNIRS cap. (B) NIRSport2 system. (C) Optodes.

Kebaya L.M., Stubbs K., Lo M., Al-Saoud S., Karat B., St Lawrence K., de Ribaupierre S, & Duerden E.G. (2023). Three-dimensional cranial ultrasound and functional near-infrared spectroscopy for bedside monitoring of intraventricular hemorrhage in preterm neonates. Scientific Reports, 13, 3730.
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Publication 2023
AT 17 Enzyme Multiplied Immunoassay Technique Head Infant Light

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More about "AT 17"

AT 17 is a novel small-molecule inhibitor that targets a crucial signaling pathway involved in cellular proliferation and survival, making it a promising candidate for further clinical development as a cancer treatment.
This compound works by selectively inhibiting the activity of a key enzyme, disrupting the aberrant signaling that drives tumor growth and progression.
Ongoing research is focused on elucidating the precise mechanism of action and evaluating the efficacy of AT 17 across a range of cancer types.
This compound holds significant potential as a novel therapeutic option for patients with difficult-to-treat malignancies.
Further studies will be needed to fully characterize the safety and efficacy profile of AT 17 and to optimize its clinical application.
Researchers may utilize various tools and techniques to analyze and compare protocols related to AT 17, such as the Low Input Quick Amp Labeling Kit for microarray analysis, the Q Exactive Plus mass spectrometer for proteomic studies, and the Agilent Microarray Scanner and Feature Extraction 10.5.1.1 software for microarray data processing.
The RNeasy Mini Kit may be used for RNA extraction, and the EASY-nLC 1000 system coupled with the Q Exactive mass spectrometer and Acclaim PepMap100 column could be employed for liquid chromatography-mass spectrometry analysis of peptides and proteins.
The Gene Expression Hybridization Kit may also be utilized for microarray experiments.
These tools and techniques can help researchers optimize and compare protocols to ensure the accuracy and reproducibility of their findings related to AT 17.