To address gaps in universal, diversity-focused eating disorders prevention with early adolescents, our team co-created an evidence-informed body image intervention through a community-engaged, participatory research process. The Body Justice intervention and associated research were co-created by a team of middle school students and staff and undergraduate students and faculty in the Pacific Northwest United States. The intervention includes eight brief lessons (six hours total) with culturally-tailored content rooted in cognitive dissonance and media literacy (e.g., cultural appearance ideals, diversity representation within media, food culture). The intervention was delivered with 7th grade students over three years (N = 333; 49% students of color; 53% cisgender boys, 36% cisgender girls, 12% gender diverse; 27% sexually diverse) using college student leaders (near peers) and middle school student co-leaders. Student satisfaction immediately after the intervention was moderate overall and higher for students of color, sexually diverse students, and cisgender girls and gender diverse students compared to their peers with majority identities. Across the sample, there was a significant reduction in unhealthy weight control behaviors from baseline to two-month follow-up with similar improvement among subgroups except for students of color, who had smaller reductions over time compared to their white peers. Across the sample, there was a significant reduction in internalized appearance norms from pre to post-intervention and through follow-up. These reductions were similar across gender, but the change was significant only for white students and straight students. There was no overall improvement in perceived appearance pressure from social media over time, but subgroup analyses revealed that students of color experienced improvement over time unlike other subgroups. In general, subgroup analyses should be interpreted cautiously due to concerns about adequate power. These results suggest that the Body Justice curriculum was delivered effectively and was well-liked by middle school students with marginalized identities. While aspects of the intervention were beneficial (e.g., a reduction in unhealthy weight control behaviors over time), findings suggest potentially differential results across identity subgroups. This has implications for collaborative school-based research, body image and eating disorders prevention, and community-engaged methods to foster equity.
TIC-XNet: a structured evidence translation framework for interpretable multimodal pediatric tic event detection with improved temporal alignment and fidelity
ObjectivesThis study aimed to develop an interpretable multimodal framework for detecting tic events in children with tic disorders by translating model decisions into structured, time-aligned evidence from synchronized video and physiological signals.MethodsTIC-XNet was developed to jointly analyze synchronized video, heart rate, and electrodermal activity signals and to generate structured evidence outputs. Recordings from 417 children with clinically diagnosed tic disorders were collected during structured clinical assessments and home-based observations. TIC-XNet was compared with a prediction-only black-box model and a post-hoc explainable model under matched predictive backbones and identical training settings.ResultsWithin the evaluated internal subject-level split, TIC-XNet achieved the best performance on the pooled shared test set, with a window-level AUC of 0.915 ± 0.019, higher event-level recall and precision, fewer missed events, and lower post-buffering prediction latency than the comparator models. Its translated outputs also showed higher decision fidelity, greater stability under perturbation, and closer temporal alignment with expert-annotated tic onsets. Subject-level translated numerical signals were associated with tic severity.ConclusionsThese findings indicate that evidence translation can support more interpretable multimodal detection of tic events in children with tic disorders while remaining compatible with strong predictive performance.
Developmental high-risk criteria for severe mental illness: a neurodevelopmental framework for premorbid detection
Gender-specific symptom outcomes on cariprazine treatment: a 12-month naturalistic longitudinal follow-up study in schizophrenia
IntroductionA growing body of literature is focusing on third-generation antipsychotics and their unique characteristics, but few studies have examined gender as a crucial factor in response profiles. The present study aims to address this gap by analyzing the outcomes of 12-month naturalistic treatment with cariprazine to elucidate changes in specific psychopathological domains between men and women.MethodsThe present 12-month longitudinal naturalistic study involved a sample of individuals diagnosed with schizophrenia according to the DSM-5-TR treated with cariprazine at the outpatients’ psychiatric services of a major university and community hospitals in Italy. The assessments conducted included sociodemographic data, the Structured Clinical Interview for the DSM-5 (SCID-5), and the Positive and Negative Symptom Scale (PANSS) Total and Subscale scores, as well as the PANSS-derived Marder factors. The PANSS was administered at three time points: before starting the treatment with cariprazine (T0), after 6 months (T1), and after 12 months (T2).ResultsFifteen male and 17 female subjects were assessed at the three time points. The mean dose of cariprazine was 4.2 ± 1.3 mg for men and 4.0 ± 1.5 mg for women. Both genders exhibited improvements in all PANSS subscale symptoms after 6 and 12 months of cariprazine treatment compared to the baseline, with the only exception of the Uncontrolled hostility/excitement Marder factor among men. Progressive improvements through time points in symptom subscales were found in both sexes, reaching numerical differences in every PANSS subscale in both sexes at T2. Gender specifc response profiles emerged after 6 and 12 months of treatment in the PANSS subscales and items in men and women.DiscussionCariprazine exhibited significant efficacy in both sexes, with no significant differences between men and women despite a gender specific response profile emerged. Additional studies are needed to further investigate the efficacy profile and long-term outcome of cariprazine treatment by gender.
Mapping and engineering the human cell–cell interactome
Nature Biotechnology, Published online: 23 June 2026; doi:10.1038/s41587-026-03177-2
Di Carlo and colleagues discuss technologies required to map and engineer the human cell–cell interactome and the therapeutic avenues such an atlas could unlock.
Efficient generation of epitope-targeted antibodies with Germinal
Nature Biotechnology, Published online: 23 June 2026; doi:10.1038/s41587-026-03187-0
Germinal achieves epitope-targeted, de novo complementarity-determining region design with high experimental success rates.
Shifting the goalposts in obesity drug development
Nature Medicine, Published online: 23 June 2026; doi:10.1038/s41591-026-04462-y
Obesity drug development must move beyond an emphasis on ever-greater weight loss to prioritize tolerability, sustainable benefits and medication persistence; two recent trials exemplify this shift, with more underway.
Cytomos’ AuraCyt Digital Predictive Cell Analytics Platform Showcased at BIO Conference
Cytomos reports that it is showcasing its flagship cell analytic intelligence platform AuraCyt®, together with its novel Celledonia® benchtop technology, which is designed to boost predictive cell analytics. Current challenges in the bioprocessing space include slow, label-dependent analytical methods that are inefficient to scale-up and provide limited predictive insight, according to Cytomos.
The AuraCyt platform measures intrinsic cell physics to generate AI-ready digital fingerprints that reveal the multi-dimensional state and behavior of the cell. The benchtop cell analytics intelligence system combines the compact Celledonia analyzer with the sensors of the AuraCyt modules to transform complex cellular data into actionable insights, notes a Cytomos spokesperson, who points out that this label-free, single-cell analysis system predicts future productivity, stability, and manufacturability.
This enables earlier insights and real-time decision-making, lowering risk, providing scalable impact, optimizing process and improving product consistency, says the spokesperson. The operation reportedly provides demonstrable value across various applications, such as reducing CLD timelines by up to 40%, saving up to 65% of resources in lentivirus batch production, and reducing CAR T process time by up to 30%, comments Cytomos’ executive chair, Alan Raymond.
The company is showcasing this technology at its pod in BIO Business Forum Zone D (Exhibit Hall 2221 UK Pavillion), from 22-25th of June, 2026.
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STAT+: Cadence raises $100 million to automate chronic disease care with regulated AI
Cadence, a digital health company that cares for patients with chronic conditions, has raised $100 million as it seeks to expand its footprint and automate the work of its clinicians with artificial intelligence.
The new investment, led by Spark Capital, values Cadence at $1.23 billion and finds the company at a crossroads. Cadence’s core billing model, in which it charges insurers monthly for remote monitoring of patients, has come under scrutiny from the federal health department’s watchdog and from insurers, including UnitedHealthcare. Critics argue that the reimbursement framework is ripe for abuse and may support low-quality care.
That model currently supports a bulk of Cadence’s work with over 20 health system customers that refer patients to the company’s chronic disease management programs. Cadence uses devices such as blood pressure cuffs and an army of hundreds of clinicians to monitor and care for patients with hypertension, diabetes, and heart failure. But the foundation of Cadence’s business may change entirely with a large investment in AI. The company currently manages over 100,000 patients, and CEO and founder Chris Altchek hopes to “take it to the next level,” by automating a chunk of the human work.
STAT+: Gene-editing startup launches with $230 million and a Chinese licensing deal
A new gene-editing startup has threaded the needle of negotiating contracts with a Chinese drug company, raising $230 million in funding, and executing a reverse merger with a preexisting biotech company.
The result? Serapha Bio, which launched Tuesday to develop a one-and-done treatment for a liver and lung disease called Alpha-1 Antitrypsin Deficiency, or AATD, founding investors RA Capital and RTW Investments told STAT exclusively.
RA and RTW arranged $138 million in Series A funding for Serapha, along with $92 million in additional funds tied to the company’s reverse merger with Boundless Bio. Boundless Bio launched in 2019 to study extrachromosomal DNA and its role in cancer growth but ran into trouble with its lead program.