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Christopher Carpenter

Publications and source records attributed to Christopher Carpenter.

10 recordsLinked to original sources
PubMed2026

scBaseCount: An AI agent-curated, standardized, auto-updated single-cell data repository.

Single-cell RNA sequencing has transformed cell biology by enabling precise transcriptomic measurements of individual cells. The Sequence Read Archive (SRA) is the largest public repository of sequencing reads, yet much of it remains underutilized due to unstandardized metadata. Here, we introduce scBaseCount, a database that leverages an AI agent to automate discovery and metadata extraction and standardize data processing. Built by mining all 10x Genomics datasets, scBaseCount is the largest public repository of single-cell gene expression data, comprising over 502 million cells across 27 organisms and 75 tissues. It offers an unbiased view of the data landscape within the SRA and enables the training of more performant computational models through access to broader phenotypic diversity. Uniform processing enables measurement of both intronic and exonic reads and non-coding gene expression and improves alignment across experiments. Moreover, scBaseCount provides a blueprint for how AI can be leveraged to autonomously curate biological data repositories.

Single-Cell Analysis↗
PubMed2026

Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution.

We present Tahoe-100M, a giga-scale single-cell perturbation atlas comprising 100 million transcriptomes from 50 diverse cancer cell lines treated with 1,100 drug-dose conditions. This parallel profiling of thousands of perturbations at single-cell resolution with minimal batch effects is enabled by the Mosaic platform, which multiplexes genetically distinct cell models into balanced "cell villages." Beyond cataloging transcriptomic shifts, Tahoe-100M systematically quantifies cellular phenotypes, including proliferation, cytotoxicity, lineage-specific vulnerabilities, and cell-cycle changes. It captures population-level transcriptomic heterogeneity, characterizing whether drug responses drive cells toward divergent fates or convergent states. Pathway-based signatures define drug-induced expression programs, classify mechanisms of action, reveal off-target activities, and expose adaptive stress responses associated with resistance. By unifying cellular and molecular readouts, this broadly applicable perturbation atlas advances our ability to model gene regulation, drug response, and network dynamics. Its public release enables the training of AI frameworks to advance predictive models of cell behavior.

Humans↗
PubMed2026

Predicting cellular responses to perturbation across diverse contexts with State.

While machine learning models offer potential for predicting transcriptomic effects of perturbation, they currently struggle to generalize across cellular contexts. Here, we introduce State, a machine learning model that predicts perturbation effects while accounting for cellular heterogeneity within and across experiments. State is trained using single-cell gene expression data to predict perturbation effects across sets of cells. State improved discrimination of effects on large datasets by more than 30% and identified differentially expressed genes across genetic, signaling, and chemical perturbations with significantly improved accuracy compared with baselines. Its cell embeddings trained on observational data from 167 million cells enable the identification of strong perturbations in cellular contexts where no perturbations were observed during training. We further introduce Cell-Eval, a comprehensive evaluation framework that can be used to evaluate future models. Overall, the performance and flexibility of State set the stage for scaling the development of AI models of cell state.

Machine Learning↗
PubMed2006

The effects of state parity laws on the use of mental health care.

OBJECTIVE: We used a quasiexperimental research design to measure the effect of state parity laws on the use of mental health care in the past year. METHODS: We pooled cross-sectional data from the 2001, 2002, and 2003 National Surveys on Drug Use and Health. Our sample included 83,531 adults 18 years of age or over with private health insurance stratified by the level of mental and emotional distress experienced in the worst month of the past year. We used a state and year-fixed effects approach to measure the effect of parity. Similar to a difference-in-difference analysis, the effect of parity was measured by comparing pre-/postchanges in mental health service use within states that switched active parity status to changes in service use within states that did not change parity status in the same calendar year. For each subgroup, we report predictions of the percentage point change in any mental health care use, prescription drug use, and outpatient care use resulting from parity laws. RESULTS: Depending on the time window used to define active parity status, we found that parity increased the probability of using any mental health care in the past year by as much as 1.2 percentage points (P<0.01) for the lower distress group and by as much as 1.8 percentage points (P<0.05) in the middle distress group. We found no statistically significant changes in service use for the upper distress group. Whether measured differences were attributable to changes in the use of prescription drug or outpatient care also depended on the definition of active parity status. CONCLUSIONS: Overall, the results of this study suggest that state parity laws succeeded in expanding access to mental health care for those with relatively mild mental health problems.

Adolescent↗
PubMed2005

Youth alcohol use and risky sexual behavior: evidence from underage drunk driving laws.

Recent research calls into question previous methods for estimating the relationship between alcohol use and risky sexual behavior among youths [Rashad, I., Kaestner, R., 2004. Teenage sex, drugs and alcohol use: problems identifying the cause of risky behaviors. Journal of Health Economics 23, 493-503]. This paper provides new evidence on this question by using reductions in heavy alcohol use among underage males induced by state adoption of very strict age-targeted "Zero Tolerance" drunk driving laws. I estimate reduced form models of the effects of Zero Tolerance laws on state gonorrhea rates by age group and race over the period 1981-2000, controlling for state and year fixed effects and state-specific time trends. I find that adoption of a Zero Tolerance law was associated with a significant reduction in gonorrhea rates among 15-19-year-old white males, with no effect for slightly older males age 20-24 whose drinking behavior was unaffected by the tougher policies. I find mixed effects for white females and no significant effects for blacks. While not conclusive, these results suggest an important role for alcohol use in risky sexual behavior among young men.

Adolescent↗
PubMed2004

How do Zero Tolerance Drunk Driving Laws work?

This paper provides the first comprehensive analysis of the effects of "Zero Tolerance" (ZT) Drunk Driving Laws--which set very low legal blood alcohol limits for individuals under age 21--on self-reported alcohol use and drunk driving using data from the 1984 to 2001 Behavioral Risk Factor Surveillance System (BRFSS). I estimate two-way fixed effects models of alcohol-related behaviors of 18-20-year-olds that can condition on unobserved differences across states that may be correlated with determinants of drinking and drunk driving, and I use 22-24-year-olds as a control group. Results indicate that the laws reduced heavy episodic drinking (five or more drinks at one sitting) among underage males by 13%. This result is supported by models that use variation in treatment intensity induced by differences in body weight. I find mixed evidence of ZT effects for females, and no robust effects on drinking participation or drunk driving for either sex.

Adolescent↗
PubMed2003

Systemic and primary cutaneous anaplastic large cell lymphomas.

Anaplastic large cell lymphoma (ALCL) is a neoplasm of activated lymphocytes, commonly expressing T-cell antigens and cytotoxic proteins. Histopathology reveals distinctive infiltration of sinuses and paracortical T-cell-rich regions of lymph nodes by tumor cells which have abundant cytoplasm and large irregular/convoluted nuclei, and which are frequently multinucleated with prominent nucleoli. ALCL often presents in advanced clinical stages with B symptoms; extranodal disease occurs in 40% of patients. The pathogenesis of systemic ALCL is linked to phosphorylation of a tyrosine kinase (ALK) resulting in unregulated growth of affected lymphoid cells. ALK is activated through chromosomal translocations/inversions with any of several partner genes, most commonly nucleophosmin (NPM). Downstream signal transduction pathway(s) are not fully defined but appear to involve phospholipase Cgamma, phosphatidylinositol (PI)3K/Akt, and STAT-3 and STAT-5 proteins. Primary cutaneous ALCL appears to have a different pathogenesis and better prognosis than does systemic ALCL, presenting as one or more skin tumors, usually localized. Excision or local irradiation is usually effective treatment. A clinically benign variant of primary cutaneous ALCL is lymphomatoid papulosis (LyP), characterized by recurrent crops of papules/nodules up to 2 cm in diameter which undergo spontaneous regression. LyP is managed by observation, ultraviolet light therapy, or low-dose methotrexate. LyP patients have a predisposition to develop malignant lymphomas, including Hodgkin's lymphoma, mycosis fungoides, and non-Hodgkin's lymphoma, by as yet unknown mechanisms. The prognosis for patients with LyP is otherwise excellent.

Anaplastic Lymphoma Kinase↗
PubMed2003

Seasonal variation in self-reports of recent alcohol consumption: racial and ethnic differences.

OBJECTIVE: This study considered whether monthly variation in self-reports of recent alcohol consumption differs systematically by race. METHOD: Telephone survey data collected by the Centers for Disease Control's Behavioral Risk Factor Surveillance System (BRFSS) were used to measure self-reports of drinking and heavy episodic drinking in the 30 days before the interview. The sample (N = 1,087,813) comprises adults over the years 1985-2000. Monthly variation in self-reports of any drinking and heavy episodic use were evaluatedusing logistic regression, controlling for demographic characteristics, year effects and state clustering. RESULTS: The previously documented "January effect" in past month alcohol consumption--that people interviewed in January are much more likely to report drinking behavior relative to the overall odds--is found to exist for every racial group. Seasonal variation in reports of heavy episodic use, however, differs substantially by race. Black and white respondents are more likely to report this behavior when interviewed in January, whereas the associated peak for Hispanic men is in June. Asians reveal no significantly different heavy episodic drinking behavior in any month relative to the overall odds. Cultural specific factors may contribute to this racial variation in heavy episodic drinking behavior. CONCLUSIONS: Demographic characteristics, such as race and ethnicity are important determinants of seasonal variation in self-reports of recent alcohol consumption and should be taken into account by researchers and policymakers.

Alcohol Drinking↗