Placenta accreta spectrum (PAS) is a leading cause of obstetric morbidity and peripartum hysterectomy. Rising cesarean delivery rates, advanced maternal age, and assisted reproductive technologies have increased its incidence. Early, standardized diagnosis is essential for multidisciplinary planning and improved outcomes, yet formal screening guidelines are lacking. To raise awareness of the importance of antenatal screening for PAS, summarize key clinical and imaging risk factors, and propose a standardized mid-trimester ultrasound protocol for high-risk patients. An expert panel convened under the Pan-American Society for the Placenta Accreta Spectrum (PAS2) reviewed available evidence, risk stratification models, and prior consensus statements to develop practical recommendations for PAS screening. PAS risk rises with the number of prior cesarean deliveries, especially in the setting of concurrent placenta previa or anterior low-lying placenta. Combined transabdominal and transvaginal ultrasound using grayscale and low-flow color Doppler (<10 cm/s) best identifies characteristic markers such as loss of the clear zone, myometrial thinning, bladder-wall interruption, placental bulge, uterovesical hypervascularity, lacunae, and bridging vessels. Standardized imaging protocols and structured reporting improve detection and facilitate referral to specialized centers. All patients with placenta previa or low-lying placenta and prior cesarean delivery should undergo targeted PAS screening at the time of anatomic survey. Early, systematic assessment and referral improve safety and outcomes.
Spinal infections are rare but serious conditions requiring timely diagnosis. Non-contrast computed tomography (CT) is widely used and may incidentally reveal spinal abnormalities; however, subtle infectious findings are often missed, especially on axial images without sagittal reconstruction. To investigate a deep learning approach for diagnosing primary spinal infections using non-contrast CT images. This retrospective dual-center study included 157 patients with primary spinal infection. A Swin Transformer model was developed using non-contrast CT slices. Patients from the primary center (n = 127) were randomly split 7:3 into training and internal validation sets. An independent external cohort (n = 30) from a second center was used for external validation. Per-slice diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and F1-score, with a probability threshold ≥0.5 determined by the Youden index. Model performance was compared with that of two radiologists. The Swin Transformer model demonstrated excellent per-slice diagnostic performance. In the internal validation set, the model achieved an AUC of 0.979, sensitivity of 96.2%, specificity of 90.5%, and accuracy of 89.4%. In the external cohort, similar results were obtained: AUC 0.989, sensitivity 98.2%, specificity 98.3%, and accuracy 98.3%. The deep learning model significantly outperformed both radiologists in AUC and sensitivity across cohorts (all P < 0.05). With artificial intelligence (AI) assistance, both radiologists showed substantial improvements in diagnostic performance and efficiency in both internal and external validation (all P < 0.05). The model's reading time was markedly shorter than that of unassisted radiologists, and AI assistance reduced radiologists' reading time (P < 0.001). Presence of spinal epidural abscess and pathogen type significantly influenced diagnostic outcomes (P < 0.001). This Swin Transformer-based deep learning model achieves high diagnostic accuracy for detecting spinal infections on axial non-contrast CT images, with performance comparable to or exceeding that of musculoskeletal radiologists. By enhancing radiologists' sensitivity and reducing reading time, the model shows promise as a clinical decision support tool to reduce missed diagnoses, particularly in emergency or resource-limited settings where magnetic resonance imaging (MRI) is unavailable. Its robust performance on external validation supports generalizability and lays the foundation for future multicenter prospective studies and extension to other spinal pathologies.
Combination immunotherapy is widely used as first-line treatment for metastatic renal cell carcinoma (mRCC), but pretreatment prognostic stratification remains insufficiently established. To evaluate the performance of various prognostic scores in the first-line treatment of metastatic renal cell carcinoma (mRCC) with combination immunotherapy. We retrospectively analyzed 145 patients who started first-line combination immunotherapy at six institutions from December 2015 to February 2025. We calculated IMDC, LIPI, RMH, PMHI, GRIm, C-PLAN, mGPS, and Meet-URO scores and performed survival (PFS, OS) and ROC analyses (PD, ORR). Survival analyses also evaluated the prognostic ability of each score by concordance index. At a median follow-up period of 28.8 months, the median progression-free survival (PFS) was 35.1 months and the median overall survival (OS) was not reached. Kaplan-Meier analysis showed significant differences for all scores except between IMDC and C-PLAN (PFS) and IMDC and mGPS (OS). Among these, PMHI and RMH demonstrated superior results in the C-index. ROC analysis showed no score had prognostic value for PD or ORR. PMHI and RMH may be useful prognostic scores for survival outcomes in mRCC patients treated with immunotherapy. However, their ability to predict treatment efficacy (ORR and PD) is limited and further research is needed.
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Computational protein design (CPD) is a central problem in biotechnology, with applications in enzyme engineering and therapeutic design, but its combinatorial complexity poses a significant challenge for classical optimization methods. In this work, we formulate fixed-backbone CPD as a quadratic Hamiltonian over rotamer variables, enabling solution using Quantum Computing Inc.'s photonic entropy computing platform, Dirac-3. We evaluate solution quality by benchmarking against an exact classical cost function network (CFN) solver, which provides provably optimal baselines. On a set of standard benchmark proteins ranging from 493 to 943 variables, Dirac-3 produces best-observed solutions (over 100 samples per instance) within 0.16-2.47% of the optimal energies. These results show that the proposed formulation can identify low-energy configurations on directly solvable CPD instances, while sample-level energy distributions vary by instance. Runtime behavior is reported over the tested regime, where CFN remains faster in absolute terms, while Dirac-3 exhibits moderate growth in runtime with problem size. This study focuses on optimization performance as measured by energy relative to exact baselines under a pairwise fixed-backbone energy model. Exploratory experiments on larger instances using decomposition-based approaches are provided in the Supplementary Material. Overall, the results establish a benchmark for entropy-based optimization on CPD formulations within the directly solvable regime.
Ethanol affects lipid metabolism through multiple pathways, leading to fatty liver development in most alcohol-related liver disease (ALD) patients. Recent studies have highlighted the role of calpain, a calcium-dependent protease, in liver inflammation and fibrosis. Calpain activity is regulated by its essential subunit, Capns1 (calpain-4), which stabilizes and modulates the activity of its catalytic isoforms, calpain-1 and calpain-2. This study investigated calpain's impact on lipid metabolism in ALD. Six-week-old C57Bl6/J mice were injected with rAAV8 vectors encoding Capns1 shRNA or control vectors. After 4 weeks, mice underwent a 10-day period of ad libitum ethanol consumption, followed by a single gavaged ethanol administration on day 11. Capns1 knockdown attenuated ethanol-induced microvesicular steatosis. Hepatic triglyceride and free fatty acid levels were not significantly altered, whereas cholesterol levels were significantly reduced in the ethanol group with Capns1 knockdown. Cpt1a expression increased significantly in the ethanol group with Capns1 knockdown. Western blot analysis revealed increased Cleaved-3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR) to Pro-HMGCR ratio in Capns1-knockdown mice, suggesting reduced HMGCR activity and suppressed cholesterol biosynthesis. LXRα expression was mainly increased in the cytoplasm in the ethanol group, and following Capns1 knockdown, it was relocalized to the nucleus via its activation. In addition, RNA sequencing analysis indicated that Capns1 knockdown contributes to the reprogramming of ethanol-induced disruptions in metabolic pathways, primarily those involving cholesterol metabolism. Further investigation into the relationship between Capns1 and cholesterol biosynthesis proteins may provide insights into using calpain inhibitors as a therapeutic approach for alcohol-related liver disease.
The claspers are the copulatory organs in male elasmobranchs, responsible for directing the semen into the female cloaca (C). However, the microscopic morphology of the claspers remains poorly understood. This study describes the morphology of the claspers and clasper glands (CGs) of cururu stingray (Potamotrygon wallacei) at different maturational stages, including neonates, juveniles, and adult active males. These secondary sexual organs were analyzed anatomically and processed using standard histological and histochemical staining techniques. The claspers of P. wallacei have a tubular shape and a brown coloration with light spots, intensified in juveniles and active males. Claspers are flexible in neonates, show an increased rigidity in juveniles, and are fully rigid in adults. Gradual rigidity of the claspers results from mesenchyme (ME) replacement by cartilage followed by mineralization. The claspers are lined by an epidermis (EP) with mucous cells (MC) secreting neutral and acid carboxylate mucosubstances; spermatic groove (SG) with cells exhibiting neutral mucosubstances; vascularized connective tissue and musculature associated with nerve bundles. Such tissue characteristics can assist in penetration, protection, rotational movements, and opening of the claspers during copulation. The CG is recognizable in neonates and becomes progressively more structured through ontogeny, reaching full differentiation in adults. The CG is delimited by two external muscular tunics, with secretory units (SU) formed by a simple columnar epithelium, demonstrating a holocrine secretion with neutral and acid carboxylate mucosubstances, more intense in adults. This secretion can assist in sperm capacitation, nutrition, and motility. These results confirm that secondary sexual organs undergo morphophysiological changes during sexual maturation in P. wallacei.
Systemic cervical cancer management continues to be challenging. Numerous chemotherapies have been approved, but predicting response is difficult due to the lack of biomarkers. Here, we analyze the genetic and protein profiles of 20 cervical cancer cell lines (CCCLs) and explore their correlation with drug response patterns to commonly used drugs, aiming to identify novel biomarkers of treatment response or resistance. Twenty cell lines (CLs) were characterized for HPV type, for genetic alterations, and protein expression profiles. Pharmacoprofiling in 10 selected CLs was carried out against 34 drugs used in the clinic, assessing drug concentrations needed to reach half maximal inhibitory concentration (IC50) in nanomolar and micromolar ranges. Subtractive bioinformatics analyses aimed to identify genetic alterations (609 genes of clinical interest), associated with CL drug resistance or on the contrary with synthetic lethality. Despite a small sample size, genetic alteration frequencies and types of CCCLs were in line with those in clinical samples, except for the detection of a higher frequencyin specific genetic alterations such as NBPF1 and STK11 in CLs. Pharmacological screening identified drugs exhibiting therapeutic activity in most CLs while others were highly selective. Bioinformatics analyses suggested, loss-of-function (LoF) alterations in PAPBC3 in CLs sensitive to microtubule interfering agentsin addition to 50 variably present alterations in the microtubule pathway. LoF alterations in CSMD3, OBSCN, ZNF 717, ALPK2, CLDND1, GTF3A, NLRP1, SI, and TRIM66 were associated with Epigenetic acting drug activity and LoF of OSBPL1A with Eprenetapopt (APR-246) activity. Drug synergistic effects were observed with certain drug combinations. This paper reports genetic variants in 20 CLs as well as the results of the assessment on whether those variants may help predict response or resistance to certain drug families. With a few exceptions, genetic alteration frequency in CCCLs, conducted in the same analytical batches, compares favorably with published patient data. Results need confirmation in independent larger studies both in CLs and in clinical settings.
Large Language Models (LLMs) have achieved high accuracy on medical question-answer (QA) benchmarks, yet their capacity for flexible clinical reasoning has been debated. Here, we asked whether advances in reasoning LLMs improve their cognitive flexibility in clinical reasoning. We assessed reasoning models from the OpenAI, Grok, Gemini, Claude, and DeepSeek families on the medicine abstraction and reasoning corpus (mARC), an adversarial medical QA benchmark which utilizes the Einstellung effect to induce inflexible overreliance on learned heuristic patterns in contexts where they become suboptimal. We found that strong reasoning models avoided Einstellung-based traps more often than weaker reasoning models, achieving human-level performance on mARC: physician average accuracy was 66% [95% CI: 56-76%] and the top performing model was Claude with 75% accuracy [95% CI: 74-76%]. On questions most commonly missed by physicians, the top 5 performing models answered 50% to 70% correctly with high confidence, indicating that these models may be less susceptible than humans to Einstellung effects. Our results indicate that strong reasoning models demonstrate improved flexibility in medical reasoning, achieving performance on par with humans on mARC.
Accurate prediction of pathological complete response (pCR) after neoadjuvant therapy (NAT) remains challenging in breast cancer. Conventional imaging modalities, such as ultrasound and magnetic resonance imaging (MRI), have limited accuracy when used alone. To develop and validate a machine learning model integrating ultrasound imaging features and clinicopathological information for non-invasive and individualized prediction of pCR following NAT in breast cancer patients. This retrospective study included 609 breast cancer patients who underwent NAT. Ultrasound imaging features and clinicopathological variables were collected and analyzed. Data preprocessing was performed using Python and R. The diagnostic performance of ultrasound and MRI for predicting pCR was evaluated as a baseline. Significant predictors were identified through univariate and multivariate analyses. Three machine learning models-Random Forest, Logistic Regression, and Support Vector Machine-were developed and validated. Model performance was assessed using receiver operating characteristic (ROC) curves and decision curve analysis, while SHAP analysis and feature importance rankings were used to evaluate variable contributions. The Random Forest model achieved the best performance, with an AUC of 0.85 and an accuracy of 84.7%, outperforming conventional imaging assessments. Key predictors included early NAT tumor volume reduction ≥ 80%, increased echogenicity, HER2 positivity, and higher tumor-infiltrating lymphocyte levels. The Random Forest model substantially improved prediction of pCR after NAT in breast cancer and may provide a practical, non-invasive tool to support individualized treatment planning, and clinical decision-making.
The genetic variant ALDH2*2, associated with alcohol-related flushing, is a risk factor for alcohol-related health problems. The public has been largely unaware of these risks, suggesting potential for educational interventions to reduce harms among at-risk individuals. Self-efficacy and threat perception are mechanisms of health behavior change that may explain discrepancies in how people respond to health risk information. In the current pilot study, we examined the effects of a brief feedback intervention about the health risks related to flushing, ALDH2*2, and alcohol use on participants' intention to change their drinking and their past-month heaviest week drinking quantity. We also evaluated whether self-efficacy and threat perception related to intention to change drinking. We enrolled 360 Asian American undergraduates (58% female; age 17-25). Participants were randomized to view (1) phenotype feedback about the alcohol-related cancer risk associated with flushing and ALDH2*2 (PHEN), (2) PHEN plus their own ALDH2 genotype (PHEN+GENE), or (3) an attention control session (CONTROL). Participants who completed the feedback (n = 324) reported their intention to change their drinking post-feedback and their recent alcohol consumption, self-efficacy, and threat perception at baseline and 1-, 4-, 7-, and 10-month post-feedback. Those in PHEN+GENE had significantly higher intention to change drinking compared with those in CONTROL regardless of ALDH2*2 status. A significant interaction was found between self-efficacy and threat perception in predicting intention to change drinking. Higher intention to change drinking did not relate to decreased heaviest week drinking quantity. Receiving risk feedback was associated with greater intention to change drinking among both ALDH2*2(+) and ALDH2*2(-) participants, but intention to change was not found to be associated with a decrease in heaviest week drinking quantity. Future work in larger samples will further examine self-efficacy and threat perception as potential mechanisms underlying participants' intention to change their drinking behavior. ClinicalTrials.gov: NCT04967599.
The revolution of treatment advances for children with rheumatic diseases since the advent of pediatric rheumatology has coincided with the growing recognition that many of these children will continue to require long-term rheumatology care after reaching adulthood. Moreover, it has become evident that effective, systematic approaches are needed to help adolescents and young adults (AYA) with pediatric rheumatic diseases learn to manage their health independently and succeed in an adult-oriented model of health care. In this narrative literature review, we provide a historical perspective on health care transition and its relevance to the field of rheumatology. Second, we review seminal literature on outcomes of transition and transition-related needs of AYA with pediatric-onset rheumatic diseases. Third, we describe interventions designed to improve health care transition for AYA with pediatric rheumatic diseases. Lastly, we discuss remaining knowledge gaps and future directions for the field.
This retrospective series reports outcomes and prognostic factors for advanced chordoma (AC) treatment with molecular targeted therapies (MTTs) in different treatment lines. This is a retrospective series of 57 patients with AC treated between 2004 and 2023 at one of seven participating sarcoma centres. Demographics, previous treatment, treatment details and outcomes were recorded. 57 patients were treated with 7 different MTTs. Treatment was received in first (n = 57), second (n = 16), third (n = 5) or fourth (n = 1) line. The most frequently administered agent in first line was imatinib (84.2%) and in second line imatinib + sirolimus (35.7%). Overall median progression free survival (PFS) and overall survival (OS) in first-line treatment was 6.5 (95% CI 4.0-9.0) and 29.5 months (95% CI 24.0-40.4) and in second-line 10.0 (95% CI 4.0-22.0) and 37.2 months (95% CI 9.4-45.9). Partial response according to RECIST 1.1 was seen in 5/79 treatments (6.3%). Dose reductions and interruptions were reported in 19.0% and 27.8% of treatments. PFS and response rates with these MTTs were in line with previous phase II trials and retrospective series. Although the efficacy does not meet the European Society of Medical Oncology (ESMO) Magnitude of Clinical Benefit Scale (MCBS) criteria for single arm studies in orphan diseases, MTTs are frequently used off-label due to the high unmet need and lack of other systemic treatment options. The toxicity profile and limited efficacy rate should be taken into account when counselling patients. Further research is needed to explore other systemic treatment options including (combinations with) immunotherapy.
Stenopodidea represents one of the basal lineages within Pleocyemata, yet the male reproductive system (MRS) of this group remains poorly understood, with limited information available regarding its morphology and function. This study provides the first detailed description of the MRS in four stenopodidean shrimp species from two families: Stenopodidae (Stenopus hispidus, S. scutellatus, and S. spinosus) and Spongicolidae (Microprosthema semilaeve). We analyzed the anatomy, histology, and histochemistry of the testes and vas deferens (VD), as well as spermatozoal ultrastructure, and compared these findings with data from more derived pleocyematans to identify potentially ancestral reproductive traits. Our analyses revealed two principal types of secretion in the VD of Stenopus species and three in M. semilaeve, which together form the presumptive spermatophore. Some secretions occur in small amounts and are restricted to specific VD regions. The layers surrounding the spermatozoa are relatively simple, consisting primarily of a sperm cord enclosed by thin secretory layers, suggesting a plesiomorphic reproductive condition in Stenopodidea. Spermatozoa are elliptical and characterized by a large nucleus in direct contact with the cytoplasm, numerous peripheral vesicles, and a large vesicle containing concentric membrane whorls. This structure, previously described as a lamellar body, is reinterpreted here as a putative acrosome vesicle and differs markedly from acrosome vesicles described in other Pleocyemata. Taken together, the comparatively simple spermatophore architecture and distinctive spermatozoa ultrastructure highlight Stenopodidea as an important lineage for understanding the early evolution of reproductive traits in Pleocyemata.
Light chain (AL) amyloidosis and transthyretin amyloid cardiomyopathy (ATTR-CM) are the most common types of cardiac amyloidosis. Despite similar manifestations, prognosis and treatments are distinct, emphasizing the importance of accurate and timely diagnosis. This retrospective cohort study assessed real-world diagnostic workups of adult patients suspected of having AL amyloidosis, wild-type ATTR-CM (ATTRwt-CM), or both (AL amyloidosis + ATTRwt-CM). Data were extracted from a large electronic health record and integrated claims-clinical database (January 2017-June 2023). Workups within 24 months before the first recorded diagnosis were assessed in cohorts with AL amyloidosis (International Classification of Diseases, Tenth Revision code: E85.81 only), ATTRwt-CM (E85.82 only), or AL amyloidosis + ATTRwt-CM (E85.81 and E85.82). Of 1653, 1055, and 59 patients in the AL amyloidosis, ATTRwt-CM, and AL amyloidosis + ATTRwt-CM cohorts, respectively, 53%, 61%, and 66% received any type of AL amyloidosis or ATTRwt-CM test. Across respective cohorts, 42%, 40%, and 49% received an AL amyloidosis workup, and 17%, 15%, and 17% underwent complete monoclonal protein testing (MPT) for AL amyloidosis assessment. In the ATTRwt-CM and AL amyloidosis + ATTRwt-CM cohorts, 50% and 46% received an ATTRwt-CM workup, and 9% and 5% underwent complete MPT before or ≤ 7 days after 99mtechnetium-pyrophosphate scintigraphy. Diagnostic workups were commonly done by cardiac specialists (≥ 34%) and general medicine providers (≥ 29%). Notable proportions of patients suspected of having AL amyloidosis, ATTRwt-CM, and AL amyloidosis + ATTRwt-CM did not undergo adequate guideline-recommended diagnostic testing. Due to clinical urgency, improving disease and diagnostic awareness among clinicians is necessary for early, accurate diagnosis and treatment. The authors have confirmed clinical trial registration is not needed for this submission.
Chronic pain and hazardous alcohol use are prevalent and commonly co-occur among US veterans. A growing literature highlights pain as a motivator of alcohol consumption, with evidence suggesting more intense pain is associated with an increased likelihood of drinking for pain management. Although chronic pain acceptance (i.e., willingness to experience chronic pain and its sequelae while maintaining engagement in valued life activities) has emerged as a protective factor in the context of opioid-related behavior, its role in shaping pain-alcohol relations has not been examined. The goal of this cross-sectional study was to test chronic pain acceptance as a moderator of the association between pain intensity and alcohol use severity among veterans with chronic musculoskeletal pain. Veterans (N = 429; Mage = 56.6) were recruited via Qualtrics Panels for an online survey. Measures included the Graded Chronic Pain Scale, Chronic Pain Acceptance Questionnaire, and Alcohol Use Disorders Identification Test. Hierarchical linear regression and conditional effects models were used to test associations between pain intensity, chronic pain acceptance, and alcohol use severity. Chronic pain acceptance moderated the relationship between pain intensity and alcohol use severity, with a positive association observed at low but not moderate or high levels of acceptance. Exploratory subgroup analyses among veterans scoring above threshold for hazardous drinking also revealed an interaction, though none of the conditional effects were statistically significant. The current findings suggest that higher levels of chronic pain acceptance may buffer the impact of pain on alcohol use. Additional research is needed to evaluate the utility of acceptance-based interventions for veterans with co-occurring chronic pain and hazardous drinking.
The evolution of the hominin pelvis is commonly modeled as a series of stages driven largely by the requirements of bipedal locomotion, reproduction, thermoregulation, and pelvic floor muscular support. These patterns are complicated by variation in canal dimensions in relationship with different changes in overall pelvic breadths. To quantify this complexity, we examine pelvic canal dimensions relative to body mass and bi-iliac and biacetabular breadths in a global human skeletal sample (N = 229) and 10 hominin fossils. Relative to measures of pelvic breadth and body mass, there is substantial variation in canal dimensions in hominins and both sexes of Homo sapiens, with weaker relationships with anteroposterior than mediolateral dimensions. Human females are more variable in anteroposterior dimensions than males, but not in mediolateral dimensions. While anteroposterior dimensions are relatively short in most Australopiths, canal breadths are not relatively larger than Homo (except vs. body mass). Mediolateral reduction and anteroposterior expansion are not consistent across Homo, nor within Homo sapiens. Due to substantial variation within both sexes of Homo sapiens, hominin fossils, and the reconstructions within a single assemblage, clearly no one (or 2) pelves can stand in for pelvic form for a hominin grade (e.g., Australopiths, early Homo, and so forth), or perhaps even species. Pelvic shape and "dimorphism" evolution within the hominin lineage did not follow a single trajectory. Given the dearth of Middle Pleistocene Homo pelves from warmer climates (lower latitude), and the variation produced by different pelvic reconstructions, our picture of pelvic form in later Homo remains incomplete.
Alcohol-impaired driving (AID) remains a significant public health concern, accounting for approximately 30% of vehicle fatalities annually in the United States. Despite widely negative attitudes toward AID, many adults report driving after drinking. Day-to-day changes in how people think about AID may explain this inconsistency. This study used ecological momentary assessment (EMA) to examine how both stable patterns and day-to-day changes in perceived danger of driving, willingness to drive, and subjective intoxication predict real-world driving after drinking. Participants (N = 113) from a Midwestern community completed six weeks of EMA data collection. Daily morning surveys assessed the previous night's drinking and transportation decisions, while repeated evening surveys measured perceived danger of driving, willingness to drive, subjective intoxication, and breath alcohol concentration (BrAC) using portable breathalyzer devices. Mixed-effects models examined day- and person-level cognitions as predictors of driving behavior while accounting for alcohol consumption via BrAC. Participants reported driving on nearly half of drinking days. On days when people perceived driving as more dangerous and felt more intoxicated than usual, they were less likely to drive. Moreover, on days when people were more willing to drive than usual, they were more likely to drive. These patterns held after accounting for BrAC. Additionally, people who typically experience stronger subjective effects of alcohol were less likely to drive on days when their breathalyzer readings were high (BrAC ≥ 0.05%). Day-to-day changes in how people perceive the dangers of driving and how intoxicated they feel predict whether they drive after drinking, even at high BrAC. People who typically experience strong subjective effects from alcohol appear especially responsive to objective indicators of high intoxication levels. Findings support developing real-time interventions that combine subjective feelings of intoxication with objective measures such as breathalyzers to promote safer transportation choices. ClinicalTrials.gov: NCT03846050.