「plasma」の検索結果

Turn a set of structures into absorption, distribution, metabolism, excretion, and toxicity estimates with ADMET-AI, and read them as a developability verdict rather than a table of numbers. Use this skill to run batch prediction over a library, interpret each endpoint against its DrugBank-approved percentile, and flag the liabilities that stop a series — hERG blockade, CYP inhibition, poor Caco-2 permeability, high clearance, and plasma protein binding. Also trigger on ADMET-AI, admet_ai, Chemprop-RDKit, hERG liability, CYP3A4 inhibition, Caco-2, bioavailability prediction, or developability triage.

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Extracts cfDNA fragmentomics features (DELFI genome-wide short/long ratios, WPS nucleosome positioning, Griffin GC-corrected accessibility profiles, end-motifs/MDS, OCF) for cancer detection and tissue-of-origin from plasma WGS. Centers on the nuclease-footprint reframe (every feature re-reads one nucleosome object), the mandatory GC correction, and the cross-protocol non-comparability that breaks naive classifiers. Runs FinaleToolkit (real CLI/Python, MIT) and the Griffin Snakemake pipeline; DELFI is a method, not a package. Use when deriving fragment-based signal from cfDNA, choosing a feature family for detection vs subtyping, or diagnosing why a fragmentomic model failed validation.

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Detects somatic mutations in circulating tumor DNA, treating low-VAF detection as a signal-versus-noise problem set by error suppression and molecules sampled, not by the choice of caller. Distinguishes de novo CALLING (scanning a panel for unknown variants, bounded by per-locus error and multiple testing) from tumor-informed DETECTION (tracking a pre-specified variant set, where panel integration reaches single-ppm). Covers VarDict and Mutect2 for de novo calling, UMI-aware callers, and a pysam-based known-variant VAF tracker, with matched-WBC subtraction as the mandatory defense against clonal hematopoiesis (the dominant false positive). Use when calling or tracking tumor mutations from plasma cfDNA, setting a VAF threshold, or deciding whether a low-VAF call is tumor versus CHIP.

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Runs cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes plus colocalization triangulation, phenome-wide on-target adverse-effect scans, cross-platform Olink/SomaScan replication, and PAV (protein-altering variant) sensitivity. Use when nominating or de-risking a drug target from plasma-proteome GWAS, mimicking pharmacological inhibition via cis-pQTL instruments, separating shared-causal from LD-confounded signal under the Schmidt 2020 cis-MR framework, screening on-target adverse phenotypes pheWAS-style, or producing publication-grade STROBE-MR plus PP.H4 evidence for a target gene.

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Identifies patients with a positive aldosterone-to-renin ratio screening who may proceed directly to subtype testing without confirmatory testing based on specific clinical criteria. Triggers include spontaneous hypokalemia, baseline plasma aldosterone concentration >100 pg/mL (CLEIA), renin suppression, or a clinician questioning the need for a confirmatory test after a positive screen.

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Identifies young patients with classic primary aldosteronism features who may proceed directly to unilateral adrenalectomy without adrenal venous sampling based on high probability of unilateral disease. Triggered when a clinician sees a patient <35 years with hypokalemia, unilateral adrenal tumor on CT, and high plasma aldosterone concentration and asks whether AVS can be bypassed.

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This skill determines whether confirmatory testing can be omitted after a positive aldosterone-to-renin ratio (ARR) in patients with suspected primary aldosteronism. It is applied when a patient exhibits spontaneous hypokalemia, undetectable renin, and a plasma aldosterone concentration ≥20 ng/dL (550 pmol/L).

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Interprets the saline infusion test (SIT) to assess the probability of primary aldosteronism when a patient has a positive aldosterone-to-renin ratio (ARR) and requires confirmatory testing. Triggers include evaluating post‑infusion plasma aldosterone concentration (PAC) after a positive ARR, hypertension work‑up, or when deciding whether to proceed to adrenal venous sampling (AVS).

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This skill recommends simultaneous measurement of plasma renin and aldosterone in patients with primary adrenal insufficiency (PAI) to determine the presence of mineralocorticoid deficiency. It is triggered when assessing for mineralocorticoid deficiency in PAI, such as in patients with unexplained hyponatremia, hyperkalemia, or salt craving despite glucocorticoid replacement.

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In patients with primary aldosteronism receiving mineralocorticoid receptor antagonist therapy, the guideline recommends titrating the MRA dose upward to raise renin when blood pressure remains uncontrolled and renin is suppressed. Consider this step when hypertension is not at goal despite MRA therapy and plasma renin activity (or direct renin concentration) is low.

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Calculates the lowest effective glucocorticoid dose (dexamethasone or prednisone) to normalize blood pressure and serum potassium in glucocorticoid-remediable aldosteronism (GRA/FH-I) by titrating to biochemical and clinical targets. Indicated when initiating medical treatment for confirmed GRA, triggered by findings such as early-onset hypertension, family history of stroke before age 40, spontaneous hypokalemia, or suppressed plasma renin activity with elevated aldosterone.

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Cell-free DNA analysis pipeline from plasma sequencing to tumor monitoring. Preprocesses cfDNA reads, analyzes fragment patterns, estimates tumor fraction from sWGS, and optionally detects mutations from targeted panels. Use when analyzing liquid biopsy samples for cancer detection or monitoring.

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Pharmacokinetic (PK) analysis of concentration-time data — non-compartmental analysis (NCA) for Cmax, Tmax, AUC (0-t and 0-∞), terminal half-life, clearance (CL), volume of distribution (Vd), MRT, and absolute bioavailability (F). Also one-compartment fitting. Use when you have plasma/serum drug concentrations over time after a dose and need PK parameters, or to compute bioavailability from IV + oral AUCs. NOT for ADMET property prediction from structure (use tooluniverse-admet-prediction).

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Runs cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes plus colocalization triangulation, phenome-wide on-target adverse-effect scans, cross-platform Olink/SomaScan replication, and PAV (protein-altering variant) sensitivity. Use when nominating or de-risking a drug target from plasma-proteome GWAS, mimicking pharmacological inhibition via cis-pQTL instruments, separating shared-causal from LD-confounded signal under the Schmidt 2020 cis-MR framework, screening on-target adverse phenotypes pheWAS-style, or producing publication-grade STROBE-MR plus PP.H4 evidence for a target gene.

日本語の概要は準備中です。原文の説明を表示しています。

Runs cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes plus colocalization triangulation, phenome-wide on-target adverse-effect scans, cross-platform Olink/SomaScan replication, and PAV (protein-altering variant) sensitivity. Use when nominating or de-risking a drug target from plasma-proteome GWAS, mimicking pharmacological inhibition via cis-pQTL instruments, separating shared-causal from LD-confounded signal under the Schmidt 2020 cis-MR framework, screening on-target adverse phenotypes pheWAS-style, or producing publication-grade STROBE-MR plus PP.H4 evidence for a target gene.

日本語の概要は準備中です。原文の説明を表示しています。