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- No figures saved for this notebookA 58-year-old AfricanAmerican woman presents to the ER with e...Updated Feb 22, 2026 · Created Feb 22, 2026Verification result: Decision_ Supported. ACADM encodes medium-chain acyl_CoA dehydrogenase, a mitochondrial enzyme that catalyzes the dehydrogenation (first step) of medium_chain (roughly C4_C12) acyl_CoA substrates duri... Verifying claim 3/71: ACADS catalyzes the dehydrogenation of short_chain acyl_CoAs in mitochondrial beta_oxidation.... Executing tool: clinical_trial_search Executing tool: clinical_trial_search Executing tool: clinical_trial_search Executing tool: clinical_trial_search Executing tool: clinical_trial_search Executing tool: clinical_trial_search Executing tool: clinical_trial_search Verification result: Decision_ Supported._Evidence_NCBI Gene summary for ACADS (Gene ID 35) states that ACADS encodes _a tetrameric mitochondrial flavoprotein, which is a member of the acyl-CoA dehydrogenase family_ and e... Verifying claim 4/71: ECHS1 functions as a mitochondrial enoyl_CoA hydratase catalyzing hydration of trans_2_enoyl_CoA int... Verification result: Supported._The NCBI Gene summary for human ECHS1 (Gene ID 1892) states that the protein _functions in the second step of the mitochondrial fatty acid beta-oxidation pathway. It catalyzes the hydration... Verifying claim 5/71: ECH1 encodes a peroxisomal_mitochondrial enoyl_CoA hydratase involved in fatty_acid chain shortening... Executing tool: get_trial_details Executing tool: evaluate_eligibility Executing tool: evaluate_eligibility Executing tool: evaluate_eligibility Executing tool: evaluate_eligibility Executing tool: evaluate_eligibility Verification result: Decision_ Partially true _ ECH1 encodes a peroxisomal enoyl-CoA hydratase involved in fatty-acid beta-oxidation, but mitochondrial localization is clearly documented for the rat ortholog (not definiti... Verifying claim 6/71: HADH encodes the mitochondrial 3_hydroxyacyl_CoA dehydrogenase that oxidizes 3_hydroxyacyl_CoAs in b... Executing tool: evaluate_eligibility Executing tool: evaluate_eligibility Executing tool: evaluate_eligibility Verification result: Decision_ Supported._Evidence 1_ NCBI Gene summary for HADH (RefSeq, May 2010) states that the encoded protein _functions in the mitochondrial matrix to catalyze the oxidation of straight-chain 3-hydr... Verifying claim 7/71: ACAA2 encodes mitochondrial thiolase (acetyl_CoA acyltransferase) that cleaves 3_ketoacyl_CoAs to re... Verification result: Decision_ Supported_Evidence 1 _ NCBI Gene summary (ACAA2, UID 10449)_The RefSeq summary for human ACAA2 describes the encoded protein as _acetyl-CoA acyltransferase 2_ and states_ _The encoded protei... Verifying claim 8/71: DECR1 encodes 2,4_dienoyl_CoA reductase, an auxiliary mitochondrial enzyme required for beta_oxidati... Below I evaluate the 10 trials for which detailed eligibility was retrieved and rank the most suitable options for this 58‑year‑old woman who presented to the ED with new episodic anterior pressing/burning chest pain (started 2 days ago). Because the clinical note is minimal, I flag required data that will determine final eligibility (ECG, troponin(s), vitals, HEART/TIMI score, prior CAD history, renal function/eGFR, allergies to contrast/gadolinium, whether she requires continuous monitoring, and ability to consent). I assume she is able to consent and is not pregnant. Ranked trials (each entry: Rank / NCT ID — title) 1) Rank 1 — NCT07027891 - Title: The Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram (ROMIAE) 2 Trial - Eligibility assessment: LIKELY_ELIGIBLE - Eligibility score (0–1): 0.80 - Key matching points: - Inclusion is broad: chest pain suspicious for AMI → patient presenting with new chest pain fits. - Exclusions are mostly clear, acute, or traumatic presentations (STEMI, trauma, cardiac arrest, obvious non-cardiac chest pain) — none are stated in the note. - Key concerns / information needed: - Need ECG to exclude STEMI (if STEMI → excluded). - Need confirmation she is not a revisit within 1 week, not transferred, not clearly non‑cardiac etiology. - Site locations are in South Korea (logistics/availability). - Brief rationale: - This is a low-burden, ED diagnostic study testing an AI-ECG triage tool for suspected AMI. If the patient’s ECG is non‑STEMI and clinician suspects ischemia, she likely qualifies and participation could support rapid triage without changing standard care. 2) Rank 2 — NCT05896826 - Title: Magnetocardiography in the Accurate Identification of Myocardial Infarction - Eligibility assessment: LIKELY_ELIGIBLE - Eligibility score: 0.70 - Key matching points: - Inclusion for chest pain patients aged 18–79 undergoing standard ACS workup (ECG, troponin, imaging) — patient fits age and presenting complaint. - Observational, noninvasive test adjunct to routine care. - Key concerns / information needed: - Exclusion criteria include significant preexisting structural heart disease, arrhythmias, severe systemic disease, obesity extremes, or inability to cooperate. - Need ECG and basic medical history to rule out exclusions (arrhythmia, prior cardiomyopathy, severe renal/liver disease, BMI). - Site is in China — logistics. - Brief rationale: - Noninvasive adjunct diagnostic study appropriate for ED chest pain patients; relatively broad inclusion meaning good chance of eligibility if routine vitals/ECG and history are acceptable. Useful if clinician wants additional diagnostic support. 3) Rank 3 — NCT06295978 - Title: Multimarker Approach in Acute Chest Pain - Eligibility assessment: LIKELY_ELIGIBLE / UNCERTAIN (depending on troponin/ECG) - Eligibility score: 0.60 - Key matching points: - Observational biomarker study recruiting ED patients with chest pain of presumable cardiac origin and ECG not diagnostic for ischemia; patient could fit. - Key concerns / information needed: - Requires ECG not diagnostic for ischemia and troponin within limits (cTnI ultra within limits) — need troponin and ECG results. - Excludes prior coronary events, known heart failure, known cardiovascular disease — need past medical history. - Site in Italy — logistics. - Brief rationale: - This observational study is low risk and likely open to patients with nondiagnostic ECG and normal troponin; if that applies, enrollment is straightforward and could provide useful diagnostic biomarker data. 4) Rank 4 — NCT05897632 - Title: CARE-CP (Cardiovascular Ambulatory Rapid Evaluation for Patients With Chest Pain) - Eligibility assessment: UNCERTAIN - Eligibility score: 0.60 - Key matching points: - Targets ED patients with chest pain at moderate risk (HEART score 4–6) and non‑ischemic ECG with low troponins → many ED chest‑pain patients fit this profile. - Compares outpatient rapid evaluation vs hospitalization — potentially relevant if clinician judges moderate risk. - Key concerns / information needed: - Must have HEART score 4–6, two troponins < sex‑specific URSL (women <15 pg/mL), non‑ischemic ECG, and no prior CAD — need history, ECG, and troponins. - Excludes unstable vitals and ESRD; need vitals and eGFR. - US sites (Detroit, Charlotte, Winston‑Salem) — availability possible. - Brief rationale: - If the patient is moderate risk with normal troponins and no prior CAD, this trial could offer outpatient evaluation (avoiding hospitalization). Determination depends on ECG/troponin/HEART score. 5) Rank 5 — NCT04748237 - Title: Coronary Computed Tomographic Angiography in Intermediate-risk Chest Pain Patients - Eligibility assessment: UNCERTAIN - Eligibility score: 0.50 - Key matching points: - Enrolls ED patients within 24 hours of presentation with HEART score >3 (so many intermediate‑risk patients). - If patient’s HEART score is >3, non‑ischemic ECG and no prior obstructive CAD, she could qualify. - Key concerns / information needed: - Need HEART score components (history, ECG, age, risk factors, troponin). - Excludes acute MI, known obstructive CAD (>50%), eGFR <30, iodinated contrast allergy — need troponin, renal function, prior cardiac history, allergy history. - Site is in Sweden — logistics. - Brief rationale: - If intermediate risk and no contraindications to CT, this trial offers early CTCA as the diagnostic strategy and may speed diagnosis; suitability depends on ECG/troponin/history/eGFR. 6) Rank 6 — NCT06860997 - Title: Clinical Echocardiography and S' Wave for Early Recognition of ACS in the ED - Eligibility assessment: UNCERTAIN - Eligibility score: 0.50 - Key matching points: - Recruits ED chest pain patients without STEMI who require continuous cardiac monitoring — patient could qualify if triage places her under monitoring. - Noninvasive echo test; excludes arrhythmias, known cardiomyopathy, severe valvular disease, LBBB/pacemaker. - Key concerns / information needed: - Need to know whether triage assigns continuous cardiac monitoring, ECG rhythm (arrhythmias), and prior heart disease. - Single‑center in Belgium — availability/logistics. - Brief rationale: - If the patient is being observed on the telemetry/monitoring unit and has no exclusionary cardiac history or arrhythmia, this is a reasonable, low‑risk diagnostic study. 7) Rank 7 — NCT05344612 - Title: Comparing Upfront CTCA With Standard of Care in Patients With Chest Pain and Suspected CAD - Eligibility assessment: LIKELY_INELIGIBLE - Eligibility score: 0.30 - Key matching points: - Large randomized trial of CTCA-first diagnostic strategy for suspected CAD. - Key concerns / information needed: - Excludes presentation with acute coronary syndrome and ACS within last 3 months. Our patient presents acutely to the ED with chest pain — if clinician suspects ACS, this trial excludes her. - Also excludes prior obstructive CAD or prior PCI/CABG. Need history. - Sites in the Netherlands — logistics. - Brief rationale: - This trial is aimed at outpatient/stable chest pain and explicitly excludes acute ACS presentations. If treating team judges her chest pain is non‑ACS (unlikely to be known at presentation), she might qualify, but generally this is not the best immediate fit. 8) Rank 8 — NCT06566625 - Title: Cardiac MRI Prior to Invasive Coronary Angiography in Patients With Suspected NSTEMI - Eligibility assessment: LIKELY_INELIGIBLE - Eligibility score: 0.25 - Key matching points: - Designed for patients with suspected NSTEMI who are planning invasive coronary angiography (ICA). - Key concerns / information needed: - Requires suspected NSTEMI and planned ICA; our patient currently only has chest pain and no documented troponin elevation or plan for ICA. - Excludes CMR contraindications (eGFR <30, implants, etc.) — need renal function and implants history. - Site in Sweden — logistics. - Brief rationale: - Not suitable unless the patient becomes a clear NSTEMI with planned ICA (i.e., troponin positive/clinical course) — not first‑line for an initial undifferentiated ED chest pain patient. 9) Rank 9 — NCT05322395 - Title: Pragmatic Trial of the ESC 0/1 Versus 0/3 Hour Troponin Pathway - Eligibility assessment: LIKELY_INELIGIBLE - Eligibility score: 0.10 - Key matching points: - Trial targets patients presenting within 12 hours of chest pain onset; clinician suspects myocardial ischemia. - Key concerns / information needed: - This patient’s chest pain began 2 days before arrival (48 hours), so she does not meet the <12 hours onset requirement. - If clinical judgement says “unknown duration” might apply, but note is explicit (2 days), so likely excluded. - Site in the UK — logistics. - Brief rationale: - Troponin pathway trials usually enroll early presenters; this patient is a late presenter so this trial is unlikely to be appropriate. 10) Rank 10 — NCT06861582 - Title: Effect of Point-of-care Analysis of Ultrasensitive Troponin I on Length of Stay (POC Troponina) - Eligibility assessment: LIKELY_INELIGIBLE - Eligibility score: 0.10 - Key matching points: - Trial requires symptom onset between 3 and 12 hours after arrival (serial troponin planned). - Key concerns / information needed: - Patient’s chest pain began 2 days earlier → does not meet the 3–12 hour onset window. - Excludes chronic renal failure, cancer, chronic lung disease; need PMH. - Site in São Paulo, Brazil — logistics. - Brief rationale: - The timing window makes enrollment unlikely. This is otherwise relevant for ED troponin workflows but not for this late‑presenter. Summary — top recommendations and important caveats Top trials to discuss with the treating clinician (top 3–5): 1. NCT07027891 (ROMIAE 2, AI‑ECG) — best immediate fit for an ED patient with new chest pain; low burden and broad inclusion. Verify ECG (exclude STEMI) and confirm clinician suspicion of ischemia. 2. NCT05896826 (Magnetocardiography) — observational diagnostic adjunct that accepts ED chest pain patients; check for arrhythmias, prior cardiomyopathy, major comorbidities, and site availability. 3. NCT06295978 (Multimarker in Acute Chest Pain) — observational biomarker study appropriate if ECG is nondiagnostic and troponin is within limits and no prior CAD/heart failure. 4. NCT05897632 (CARE‑CP ambulatory rapid evaluation) — consider if patient is moderate risk (HEART 4–6), troponins are normal, and no prior CAD; can provide outpatient vs inpatient pathway. Needs HEART score, troponins, eGFR, prior CAD history. 5. NCT04748237 (CTCA in intermediate-risk) — if HEART score and labs fit and no contraindication to iodinated contrast, early CTCA could be considered. Essential data needed to confirm eligibility for these recommendations: - 12‑lead ECG (to exclude STEMI, identify arrhythmias, new ischemic changes) - At least one high‑sensitivity troponin and planned serial troponins (to determine NSTEMI, troponin timing windows, or troponin‑normal status) - Vital signs (hemodynamic stability) - Past cardiac history (prior MI, PCI, CABG, known obstructive CAD, heart failure) - Renal function / eGFR (contraindication to CT iodinated contrast or gadolinium) - Medication list, allergy history (iodinated contrast, gadolinium) - Whether the patient requires continuous cardiac monitoring/telemetry (for echo trial) - BMI, presence of implants (for magnetocardiography/CMR considerations) - Local availability/logistics (trials are international; enrollment requires treatment center involvement) If you would like, I can: - Take the next step and produce a short checklist for the ED team to rapidly determine which of the top trials are feasible (including suggested wording for consent/approach). - Retrieve trial contact/site availability near your facility (if you tell me the patient’s hospital or geographic region). - Re-evaluate after you provide ECG, troponin, vitals, and past medical history — I will then give definitive eligibility for each trial and recommended enrollment steps. Which next step would you prefer?
3 figures+2 moreSummarize the file /app/custom_data/pone.world.happiness2.xls...Updated Feb 22, 2026 · Created Feb 20, 2026analysis: - Hypothesis restated (concise): The user asked for a concise summary of the Excel file /app/custom_data/pone.world.happiness2.xlsx and for suggested, testable hypotheses to pursue with the data. - Data provenance and loading: The file is local at /app/custom_data/pone.world.happiness2.xlsx and contains five sheets named 2020, 2021, 2022, 2023, 2024. I loaded all sheets and concatenated them into one table with a Year column. - Structure and variables (cleaned/coalesced): After coalescing equivalent columns, the cleaned dataframe (df_clean) has 771 rows and these key columns: - Year (2020–2024), Country (string), Region (sparse), Rank - Score (Happiness score) - GDP_per_capita (Economy) - Social_support (Family) - Healthy_life_expectancy (Health / Life expectancy) - Freedom (Freedom to make life choices) - Generosity - Perceptions_of_corruption (Trust) - Dystopia_residual (partial coverage) - Sample sizes & coverage: - Rows: 771 (sum of rows across all sheets) - Unique countries: 181 - Per-year row counts: 2020:156, 2021:157, 2022:155, 2023:156, 2024:147 - Many countries have data for all 5 years (e.g., Afghanistan, Albania, Argentina have 5 rows). Region column is present but sparse (157 non-null), so some regional analyses will need merging or use of alternative region mapping. - Missingness and data quality notes: - Most main predictor columns (Score, GDP_per_capita, Social_support, Healthy_life_expectancy, Freedom) are non-missing for all 771 rows in the coalesced table. - Generosity: 1 missing; Perceptions_of_corruption: 2 missing. - Dystopia_residual available only for a subset (~312 non-null) — treat carefully. - Duplicate country-year rows were not found beyond the concatenation of sheets (dataset structured as one row per country per year). - Exploratory statistics (computed): - Score overall: n=771, mean ≈ 5.45 (std ≈ 1.13), range ~1.36–7.77. Distribution is roughly unimodal, slightly left skew for low scores (histogram produced). - Yearly means (Score): 2020: 5.407, 2021: 5.382, 2022: 5.354, 2023: 5.376, 2024: 5.578 — small upward movement in 2024. - Top countries by mean Score (countries with ≥3 years): Finland (~7.60), Denmark (~7.54), Iceland (~7.50), Norway (~7.49), Netherlands (~7.39). - Pairwise associations (computed): I computed Pearson and Spearman correlations between Score and candidate predictors (n≈771 for most tests): - Healthy_life_expectancy: Pearson r = 0.572 (p ≈ 4.5e-68); Spearman rho = 0.648 (p ≈ 4.4e-93). - GDP_per_capita: Pearson r = 0.310 (p ≈ 1.1e-18); Spearman rho = 0.62 (p ≈ 1.3e-83). - Social_support: Pearson r = 0.286 (p ≈ 5.9e-16); Spearman rho = 0.51 (p ≈ 3.5e-52). - Freedom: Pearson r = 0.353 (p ≈ 4.8e-24); Spearman rho = 0.458 (p ≈ 2.9e-41). - Generosity: Pearson r = 0.264 (p ≈ 9.6e-14); Spearman rho = 0.212 (p ≈ 2.8e-09). - Perceptions_of_corruption: Pearson r = 0.262 (p ≈ 1.5e-13); Spearman rho = 0.273 (p ≈ 1.2e-14). - Interpretation: Healthy life expectancy shows the strongest positive association with happiness score (both Pearson and Spearman). GDP per capita and social support also show substantial positive associations. All listed associations are statistically significant at conventional levels given large n, but effect sizes differ. - Visual checks: histogram of Score (all years), scatter Score vs Healthy life expectancy with an OLS line, and a Spearman correlation heatmap (Score and predictors) were produced. These confirm monotonic positive relationships and do not show extreme multimodality or gross data errors. - Statistical approach and robustness: Given large per-test sample sizes (~771), parametric tests (Pearson, OLS) are reasonable; I also reported Spearman correlations which are robust to nonlinearity and outliers. For inferential models, I recommend multivariable regression controlling for Year and Region (or using country fixed effects / mixed-effects models for longitudinal analyses) and multiple-testing correction (e.g., Benjamini–Hochberg) if many hypotheses are tested. results (concrete numeric/statistical outcomes): - Dataset size: 771 rows × 12 coalesced columns; unique countries = 181; years 2020–2024. - Score: mean ≈ 5.45, sd ≈ 1.13, min ≈ 1.36, max ≈ 7.769. - Yearly mean Scores: 2020=5.407, 2021=5.382, 2022=5.354, 2023=5.376, 2024=5.578. - Correlations with Score (Spearman rho, n≈771): - Healthy_life_expectancy: rho ≈ 0.648, p ≈ 4.4e-93 - GDP_per_capita: rho ≈ 0.62, p ≈ 1.3e-83 - Social_support: rho ≈ 0.51, p ≈ 3.5e-52 - Freedom: rho ≈ 0.458, p ≈ 2.9e-41 - Generosity: rho ≈ 0.212, p ≈ 2.8e-09 - Perceptions_of_corruption: rho ≈ 0.273, p ≈ 1.2e-14 - Top-mean countries (mean Score across years, ≥3 years): Finland mean ≈ 7.6038, Denmark ≈ 7.5448, Iceland ≈ 7.5018. conclusion: direct answers and recommended testable hypotheses - Direct summary answer: The file contains World Happiness Report-style country-year records for 2020–2024 (771 rows, 181 countries) with standard happiness predictors (GDP per capita, social support/family, healthy life expectancy, freedom, generosity, perceptions of corruption). Data quality is generally good: core predictors are present for essentially all rows; a few columns (Dystopia residual, Region) are partially missing. - Suggested hypotheses to test (specific, testable, with recommended test and preprocessing): 1) Hypothesis A (Primary): Higher healthy life expectancy is associated with higher national happiness scores. - Test: Multivariable linear regression (Score ~ Healthy_life_expectancy + GDP_per_capita + Social_support + Freedom + Generosity + Perceptions_of_corruption + Year + Region). Report coefficient for Healthy_life_expectancy, 95% CI and p-value. - Rationale: Strongest bivariate association observed (Spearman rho ≈ 0.65). Controls needed to test partial association. - Preprocessing: Standardize predictors, check collinearity (VIF), handle missing Dystopia_residual by exclusion or imputation. 2) Hypothesis B: GDP per capita positively predicts happiness, but much of its effect is mediated by social support and health. - Test: Mediation analysis (e.g., causal steps or bootstrapped indirect effect) with GDP → (Social_support, Healthy_life_expectancy) → Score. Alternatively, structural equation model. - Rationale: GDP and social support / health are correlated (Spearman GDP–health ≈ 0.85, GDP–social_support ≈ 0.77), suggesting mediation is plausible. - Preprocessing: Center variables, run mediation with bootstrapped CIs; address multicollinearity. 3) Hypothesis C: Freedom to make life choices contributes independently to happiness after controlling for GDP and health. - Test: Multivariable regression as in (1); specifically test coefficient of Freedom. Consider hierarchical models adding blocks of predictors (economy → social → health → freedom). 4) Hypothesis D: Regional differences exist in mean happiness scores. - Test: ANOVA (or Kruskal–Wallis if non-normal) comparing Score across regions; follow with pairwise tests (Tukey or Dunn) and adjust for multiple testing. - Rationale: Regions may capture cultural, institutional differences. Note: Region field is partially missing; consider mapping countries to regions externally if needed. 5) Hypothesis E (longitudinal): National happiness scores changed over 2020–2024, with different trends by country. - Test: Linear mixed-effects model (Score ~ Year + (Year | Country)) to estimate average time trend and country-specific slopes. Alternatively, fixed-effects panel regression controlling for country fixed effects. - Rationale: Yearly means suggest a small bump in 2024; mixed models will quantify significant trends and heterogeneity. 6) Hypothesis F: Perceived corruption is negatively associated with happiness (or positively if variable coding is reversed — check sign) and moderates the effect of GDP. - Test: Include Perceptions_of_corruption and interaction GDP*Perceptions_of_corruption in regression. Check sign and significance; use robust SEs. - Preprocessing: Confirm coding (higher value = greater perception of corruption or less corruption); recode if necessary. - Practical notes for all tests: - Use Spearman for robust correlation summaries and Pearson/OLS for effect-size estimation with diagnostics (residuals, heteroscedasticity). - Apply multiple-testing correction when running many hypothesis tests (e.g., BH FDR). - For country/longitudinal analyses prefer mixed-effects or panel fixed-effects to account for within-country correlation. - If Region is required but missing, map countries to regions using an external reference and document the mapping. - Limitations: - Some variables (Region, Dystopia_residual) are partially missing and may limit specific analyses. - Observational dataset: causal claims require caution and appropriate causal inference design. - Potential multicollinearity among predictors (GDP, health, social support); check VIF and use mediation or dimension-reduction when needed. If you want, I can next: - Run the specific regression(s) above and report coefficients/CIs and diagnostics, or - Map countries to regions and run the region ANOVA, or - Fit a mixed-effects time-trend model (Score ~ Year + (Year|Country)). Which of these follow-up analyses would you like me to run now?
1 figureBar ChartUpdated Feb 1, 2026 · Created Feb 1, 2026# Analysis: The user requested a plot of the numeric values [1, 100]. Since the data was directly provided, no external data sources or preprocessing were required. A simple line plot with markers was generated using matplotlib to visualize the two points indexed by their position in the list. No statistical tests were applicable. The plot was visually inspected to confirm correct rendering. # Results: A line plot was created with two points: at index 0 with value 1, and at index 1 with value 100. The plot includes grid lines, axis labels, and a title for clarity. # Conclusion: The hypothesis to plot the values [1, 100] was successfully fulfilled with a clear and accurate chart.