Tag: Academic research

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Click Chemistry Boosts Antibody–Drug Conjugates Against Heterogeneous Tumors

Antibody–drug conjugates (ADCs) have transformed cancer treatment by delivering potent cytotoxic drugs directly to tumor cells. But because each ADC recognizes only a single molecular target, many cancers become difficult to treat as tumors evolve into a patchwork of cells with different biological characteristics. A preclinical study published in Nature describes a modular strategy that enables existing antibodies and ADCs to assemble inside the body, allowing them to engage multiple tumor targets without creating entirely new drugs.

Researchers at Washington University School of Medicine modified FDA-approved antibodies and HER2-directed ADCs with complementary chemical groups that bond together through bioorthogonal “click chemistry” after sequential administration. The resulting complexes produced stronger antitumor activity than conventional ADC therapy in mouse models of pancreatic, gastric, and breast cancer.

The work addresses a longstanding obstacle for ADCs: they are most effective when nearly every tumor cell displays the same molecular target.

“Strategies that enhance ADC delivery to the tumor without requiring uniformly high antigen expression are needed to address heterogeneous and treatment-resistant tumors,” the authors write.

To test that concept, the researchers paired HER2-directed ADCs with antibodies targeting either HER2 or EGFR, a receptor frequently associated with treatment resistance. Because the molecules assemble after entering the circulation, the approach offers a modular alternative to engineering entirely new bispecific antibodies.

The strategy proved particularly effective in cancers with low, ultralow, negative, or heterogeneous HER2 expression, expanding activity into tumors that often respond poorly to existing HER2-targeted therapies.

“This strategy enabled targeted delivery of HER2-directed ADCs… to EGFR-high or EGFR-low cancer cells across the spectrum of HER2 expression,” the authors conclude.

The improved targeting translated into substantially better outcomes in the pancreatic cancer model. About 90% of treated mice survived for 120 days, whereas animals receiving conventional ADC therapy survived less than 80 days on average. The researchers also optimized the platform to reduce off-target drug accumulation in the liver, an important consideration for limiting toxicity.

Rather than relying exclusively on one receptor to deliver therapy, the system can exploit interactions between multiple tumor-associated receptors to improve drug uptake.

“The therapeutic benefit probably reflects a combination of bioorthogonal chemistry-driven ligation and tumor receptor biology rather than exclusively receptor colocalized assembly,” the authors write.

The click chemistry platform also may accelerate development of precision therapies. The linking molecules can be manufactured in as little as one to three days, making it possible to rapidly pair different clinically approved antibodies and ADCs for individual tumor profiles. Although demonstrated using HER2-targeted therapies, the researchers say the modular approach could be adapted to many receptor combinations and cancer types. They are particularly interested in applying the technology to difficult-to-treat tumors such as brain cancers, where improving drug delivery remains a major challenge.

“Beyond direct cytotoxic delivery, the modular customization of this approach offers potential for immune modulation, diagnostic imaging and combinatorial payload strategies,” the authors conclude. “As such, this approach provides a flexible foundation for the optimization of antibody-based therapeutics in oncology and other diseases.”

The post Click Chemistry Boosts Antibody–Drug Conjugates Against Heterogeneous Tumors appeared first on Inside Precision Medicine.

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Developing a Text Messaging Intervention to Increase Uptake of the Screening and Treatment for Anxiety and Depression Program Among Community College Students: Formative Study Using a Human-Centered Design Approach

Background: Community college (CC) students face significant mental health concerns but are unlikely to receive treatment. Barriers to mental health service uptake among CC students have been delineated, but few studies have identified strategies to improve uptake. Text messaging has been used to address engagement barriers to mental health services among adolescents and adults, but little research has explored this strategy for CC students. Objective: The goal of this study was to partner with CC students to co-design and conduct pilot usability testing of a text messaging intervention to address barriers and increase uptake of a mental health screening and treatment program, called Screening and Treatment for Anxiety and Depression (STAND), offered to CC students. Methods: We conducted 2 parallel sets of 4 co-design focus groups with CC students who had varying levels of engagement with STAND. We used rapid qualitative analysis to extract key themes, create text message prototypes and refine them, and present updated prototypes to gather feedback across workshops. We also assessed six usability factors on a 5-point Likert scale: satisfaction, helpfulness, attractiveness, readability, comprehension, and likelihood of getting started with STAND after receiving texts. Results: Key themes emerged about perceptions of texting, barriers to STAND, a basic framework for the text message intervention, feedback about the format of messages, and feedback about the content of messages. Students expressed positive regard for text messaging and general agreement on key barriers to STAND. Students codeveloped a framework for the intervention, including (1) delivering introductory texts to engage students in the text messages, (2) providing a personalized approach for students to select barriers most salient for them, and (3) delivering tailored content designed by students to address each barrier. Across workshops, several themes emerged with regard to how messages should be formatted and delivered, including the following: use short messages; use not too many messages; use relevant language; use images, memes, and short videos; and make messages “human-like.” Themes related to the content of messages included the following: reminders that you are not alone, knowledge that STAND has worked for other students, expressing understanding of student context and stressors, and providing an option to speak to a team member. Mean ratings on usability factors ranged from 3.88 (SD 0.64) to 4.25 (SD 0.46). Conclusions: This study describes a process for co-designing a text messaging mental health engagement intervention with CC students that is grounded in a human-centered design approach. Further research is needed to rigorously test this intervention and make iterative refinements to improve response and effectiveness.
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Exploring the Relationship Between Parental Trauma, Parenting Style, and Children’s Medical Treatment Adherence: Cross-Sectional Study

Background: Medication adherence is defined as the degree to which the medications taken reflect the prescribed intention and is influenced by various factors. Different factors, such as parental trauma or parenting style, may influence their child or children’s medical treatment adherence. Authoritative, or “flexible,” parenting is known to develop the most nurturing relationship between parent and child or children. The relationship between parental factors, such as parenting style and trauma level, and their influence on child medication adherence is being explored. Objective: This study examines the relationship between parental trauma, parenting style, and their child or children’s adherence to medical recommendations. Methods: Participants were recruited through Amazon’s Mechanical Turk, an online crowdsourcing platform. Participants were aged 18 years or older, a caregiver for at least 1 child younger than the age of 18 years, and had at least 1 child who was prescribed medication within the past 3 months. Parental trauma level was measured via the Adverse Childhood Experiences Questionnaire, and parenting style was measured via the Parental Authority Questionnaire–Revised. Descriptive statistics, including chi-square tests, 2-tailed tests, and adjusted logistic regressions, were used to determine the association between parental trauma, parenting style, and their child or children’s medical adherence. Results: A total of 720 participant responses were analyzed. Children who were medically adherent were younger (=.02). Caregivers’ mean age was 36.8 (SD 7.97) years, and 35.4% (n=255) identified as male. An increase in caregivers’ adverse childhood experiences score was marginally associated with an increased risk of medication nonadherence among their children (adjusted odds ratio 0.94; =.07). Conclusions: Similar to other studies, this study showed that parents of children who adhere to medical treatment practice an authoritative parenting style. Uniquely, it also showed that an increased adverse childhood experiences score was only marginally associated with an increased risk of medical nonadherence.
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Optimizing Treatment Strategies in the Bipolar Disorder Spectrum With Classical AI Approaches: Systematic Review of Performance, Bias, and Clinical Applicability

Background: Bipolar disorder (BD) is a complex and heterogeneous psychiatric condition, characterized by fluctuating clinical courses that affect approximately 1%‐2% of the global population in their lifetime. Despite pharmacological advances, treatment response varies significantly among patients, making the identification of individualized treatment strategies a major challenge. Artificial Intelligence (AI), through its classical approaches, has emerged as a powerful tool in precision psychiatry to identify subtle patterns in complex data and inform personalized clinical decisions. Objective: The present systematic review aimed to examine the current evidence on classical AI-supported treatment optimization in the BD spectrum. Methods: The review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Four databases (PubMed, Web of Science, Scopus, and Embase) were searched for original studies published after 2015 on the application of classical AI in the treatment of BD in adult patients. Publication bias was evaluated by visual inspection of a funnel plot. The methodological quality, risk of bias, and clinical applicability of the predictive models were assessed using the Prediction Model Risk Of Bias Assessment Tool for prediction models using regression or AI methods (PROBAST+AI; PROBAST+AI Working Group) tool. Results: A total of 35 studies were included and classified into 5 outcome-based categories, including acute symptomatic response, long-term maintenance response, relapse and readmission risk, safety and dose optimization, and brain aging and phenotyping. Acute symptomatic response models performed modestly (pooled area under the curve [AUC] 0.68), while imaging improved accuracy (74%‐77%). Long-term maintenance response models showed moderate-to-high performance (pooled AUC 0.80), with biomarker- and cellular-based models reaching 96%‐99% accuracy. Relapse and readmission prediction achieved a pooled AUC of 0.71, with digital phenotyping and rule-based methods performing best (AUC 0.85‐0.88). Safety and dose optimization models achieved 85%‐97% accuracy. Brain aging and phenotyping studies highlighted accelerated brain aging in BD, partially mitigated by lithium, and revealed novel data-driven subgroups. However, 3 studies were considered at high risk of bias due to small sample sizes associated with disproportionately high-performance estimates. An additional study was identified as potentially biased because it lay markedly distant from the funnel plot’s confidence line. Finally, the PROBAST+AI assessment revealed a high risk of bias in most studies, primarily due to data analysis limitations, small sample sizes, and lack of external validation. Conclusions: The adoption of classical AI tools in BD serves as a driver for therapeutic optimization, although current AI tools in BD should still be considered exploratory rather than ready for clinical use. Effective implementation in real-world clinical scenarios requires more robust, transparent, and externally validated models to ensure reliability and generalizability.
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10x Clinical Expansion Advances with CLIA Lab Plans, Cleveland Clinic Partnership

10x Genomics says it is on track to build out a CLIA-certified laboratory set to open next year, part of the spatial and single-cell tools developer’s expansion into clinical diagnostics launched earlier this year.

The lab will open within 10x’s headquarters campus in Pleasanton, CA, 10x co-founder and CEO Serge Saxonov, PhD, told GEN.

Serge Saxonov, PhD, 10x Genomics co-founder and CEO

“This is one great benefit that we have from the fact that we’ve got all the infrastructure here, and that’s why we feel like we can really accelerate some of these kinds of applications: Because we have the space, we have the expertise with the technology, we have the people who really know all the ins and outs of it, and we can very quickly, validate, new assays, test them, refine them, optimize them,” Saxonov said. “We have been seeing that already, in the time that we have been standing up some of these pieces, how enabling it is to have it all under one roof at this stage.

“Building a CLIA lab is definitely not a trivial undertaking, but we’ve been making really great progress,” he added. “The team has been standing up these capabilities, and definitely on track for early next year. So, very much looking forward to that.”

The CLIA lab is a key component of 10x’s move into clinical diagnostics, announced in January. Traditionally focused on research tools for academic, government, and industry customers, 10x has moved this year to launch clinical collaborations with top-tier institutions—the most recent of which was announced last month with Cleveland Clinic.

The nonprofit multispecialty academic medical center is partnering with 10x in a multi-year collaboration aimed at advancing research in novel diagnostics for bladder cancer. Cleveland Clinic has agreed to contribute patient samples with appropriate phenotypes for analysis on 10x’s Flex Apex single cell sequencing and Xenium spatial biology platforms.

“They have great access to patients and the right kinds of clinical trials and therapies that are going through their system,” Saxonov said. “We are working together to run single-cell and spatial analyses on them, collaborating on those and correlating the biology that we learn from single cell and spatial with therapeutic outcomes.”

Bladder cancer biomarkers

10x and Cleveland Clinic aim to identify biomarkers that predict how bladder cancer patients will respond to emerging therapies, such as immunotherapies and antibody-drug conjugates (ADCs).

“Those biomarkers are definitionally known already, but the actual context of their expression isn’t really that well known in terms of being able to predict response,” Saxonov explained. “The question is, if you see their expression in the context of the cancer cells, or the tumor microenvironment, or the immune compartment, it will then also inform response to therapy. And there’s plenty of evidence from scientific literature that there’s a lot of signal there, a really, really powerful signal there. What hasn’t been done is run rigorous, well-powered, clinically, really carefully well-defined studies to measure and evaluate those kinds of biomarkers.”

Oncology is one of two therapeutic areas viewed as priorities for pursuing translational applications with an eye toward potential clinical diagnostics that address therapy selection and monitoring. The other area is autoimmune disease.

Saxonov asserted that 10x’s clinical push was unrelated to its established research business, which shrank last year as its traditional base of academic and government (A&G) customers reeled from cuts in research funding. The cut prompted 10x to announce plans to eliminate about 100 jobs—8% of its workforce—though the workforce appears to have only shrunk by 18 jobs or about 4% last year, from 491 full-time employees as of December 31, 2024, to 473 at the end of last year, according to the company’s form 10-K annual filings.

“We feel our research business gives us an awesome foundation to now invest in this future of clinical applications. It is a very, very much an enabling thing,” Saxonov said. “It gives us a great foundation from which to go forward. It was always our plan, always our mission, always the strategy of the company that over time, as we develop our technologies, we want most naturally to make them actually have a direct clinical impact.”

Several recent trends have combined to support clinical expansion, Saxonov said:

  • An increasing number of therapies whose effectiveness in patients, and in what combination, remains unknown to many doctors.
  • A growing body of single-cell spatial signals, such as gene and protein expression, mapped to the exact physical coordinates of individual cells within a tissue.
  • Increased maturing of single cell, spatial, and multiomics technologies, resulting in more data and higher quality insights that enable their use in the clinic.

‘A really nice position’

“Investments around workflow, investments around logistics, being able to work with distributed collected samples, and also being able to drive the costs down and scale up these technologies—all of that progress now puts us in a really nice position to lean into, first, generating clinical evidence for all these different, therapeutic areas, then taking the resulting information and deploying that in the context of diagnostic tests in the future,” Saxonov said.

“Independent of whatever might be happening in terms of the research market, which will fluctuate over time, is that several large-scale trends have been converging.”

Is 2026 shaping up as an up year or a down year for A&G? Saxonov said he’ll offer insights when 10x releases its second quarter earnings in August.

10x announced its clinical ambitions in January during the J.P. Morgan 44th Healthcare Conference in San Francisco. The company unveiled clinical collaborations with two Boston-based institutions, Brigham and Women’s Hospital and Dana-Farber Cancer Institute, as well as the New York-based Cancer Research Institute.

The Cancer Research Institute collaboration focuses on generating “very large, AI-ready” data sets for immunotherapy, Saxonov said, while the Dana-Farber and Brigham and Women’s partnerships center more, like the Cleveland Clinic alliance, on generating clinical evidence for future diagnostics applications. Patient flows have been established, and analysis is underway in the collaborations with both Boston institutions.

“At the appropriate time, we’ll be updating the world about what we’re learning,” Saxonov added.

The post 10x Clinical Expansion Advances with CLIA Lab Plans, Cleveland Clinic Partnership appeared first on GEN – Genetic Engineering and Biotechnology News.

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Blood Cancer Therapies Informed by Spatial Remodeling of Bone Marrow

In a new study published in Leukemia titled, “Spatial remodeling of bone marrow architecture defines tissue-state signatures of disease activity and therapeutic response in myelodysplastic neoplasm,“ researchers from Weill Cornell Medicine have developed a new AI-based method to assess patients with a form of blood cancer called myelodysplastic neoplasms (MDS). The approach compares the size and shape characteristics of hematopoietic cells in the patient’s bone marrow sample with those in healthy bone marrow to generate a score that reflects disease severity. 

MDS is a form of blood cancer that usually affects older adults. About one-third of patients progress to a more aggressive cancer called acute myeloid leukemia. MDS patients must undergo frequent biopsies to identify signs of remission or worsening disease. 

“It’s fundamentally a chronic and progressive disease,” said Sanjay Patel, MD, clinical chief of hematopathology, and an associate professor of pathology and laboratory medicine at Weill Cornell Medicine. “With the current methods pathologists use to assess MDS samples, there are some clear-cut cases and a lot of gray area.” 

The researchers developed a new method using fully deidentified patient samples that may provide more clarity for patients with MDS and their physicians. 

“Using AI to assist us in looking at the spatial architecture of the bone marrow using widely available laboratory assays allows us to improve our capability to assess patients’ prognosis and perhaps triage them for precision therapies,” said David Redmond, PhD, assistant professor of computational biology research in medicine at Weill Cornell Medicine. 

The MDS-Microarchitectural Perturbation Score (MDS-MAPS) score ranks patient samples based on 82 features associated with normal tissue and different genetic subtypes of MDS. The tool uses routinely collected samples, tissue staining protocols, and imaging technologies that could be implemented in most hospital pathology departments and laboratories. 

“We can generate an MDS-MAPS value for a patient at diagnosis and track how it changes over time,” said Patel. 

The next step will be to validate the method in larger cohorts of patient samples. The researchers will collaborate with Pinkal Desai, MD, associate professor of medicine at Weill Cornell Medicine and a hematologist/oncologist at NewYork-Presbyterian/Weill Cornell Medical Center, to study how the tool performs on other forms of MDS, and increasingly recognized precursor conditions. 

“Patients with MDS and related precursor conditions have many mutations as part of the disease biology and each patient’s molecular signature is different,” said Desai. “We have always wondered if these mutations signal a different spatial pattern and whether these patterns have an impact in predicting how patients progress and respond to treatments. Together we are poised to harness technology to answer real-world clinical questions.” 

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Development and Usability Evaluation of an E-Learning Tool for Blended Learning in Pediatric Endocrinology: Formative Pilot Study

Background: Residents in pediatric endocrinology subspecialty units encounter diverse educational scenarios spanning theory, skills, and attitudes; yet, brief residencies frequently limit their exposure to certain clinical cases. Research in medical education demonstrates that e-learning can address such challenges efficiently. We implemented a blended learning model grounded in the Kolb learning cycle that uses structured, case-based e-learning. Objective: We aimed to evaluate the utility and usability of blended learning using a novel e-learning tool. Methods: We used a problem-solving approach and used the physical separation of case-based e-learning (interactive, patient scenario–based online modules) and theoretical content delivery as the educational model for residents in a pediatric endocrinology and diabetology unit. Residents worked asynchronously (on their own time, not simultaneously with others) on clinical scenarios and completed formative assessments (practice tests designed to provide feedback for learning rather than grades) with immediate feedback using a flipped classroom teaching method, in which students review material before group instruction. In addition, all cases could be discussed with specialists during face-to-face learning opportunities through a blended learning approach that combines online and in-person elements. We evaluated Kirkpatrick level 1 (reaction, how participants respond to training) and level 2 (learning, measured as an increase in knowledge or capability) outcomes using the postgraduate Medical E-learning Evaluation Survey (MEES) and the User Experience Questionnaire (UEQ), which assesses users’ perceptions of e-learning platforms. Results: Questionnaires from 12 pediatric residents and 1 questionnaire from a fourth-year medical student were evaluated. The main strengths identified were the tool’s support for applying content to daily clinical work (12/13, 92% users), provision of timely summaries (n=9, 69% users), access to reliable information sources (n=9, 69% users), and immediate feedback on responses (n=8, 62% users). Key weaknesses included device compatibility for e-learning (n=5, 38% users), limited content personalization (n=4, 31% users), and a lack of a navigation aid (n=4, 31% users). No significant functional issues were reported. The UEQ evaluation showed that dependability received the lowest rating, while attractiveness and stimulation received the highest rating. Conclusions: Our e-learning proposal provides a practical way to apply theoretical knowledge through interactive clinical cases. Evaluations show that users are highly motivated to engage with e-learning, highlighting our tool’s adaptability and effectiveness for postgraduate medical education in pediatric endocrinology. Identifying strengths and weaknesses will guide future improvements. Evaluating various aspects of e-learning remains crucial, as these aspects can affect learning outcomes. However, more longitudinal evaluations of e-learning are necessary to achieve a comprehensive understanding of its effectiveness.
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A 2-Tiered Rescue Protocol to Mitigate Difficulty-Based Failures of ChatGPT (GPT-5) and Gemini on the German M2 Medical Examination: Evaluation Study

Background: Large language models (LLMs) have demonstrated expert-level performance on medical licensing examinations, but most benchmarks focus on final accuracy. Critical gaps remain in understanding model efficiency (latency), the efficacy of tiered “rescue” protocols for error correction, and the systematic correlation between performance and human-rated question difficulty. The German M2 examination, paired with the AMBOSS platform’s user data–driven difficulty ratings, provides an opportunity to map AI performance against human cognitive load. Objective: This study aimed to move beyond singular accuracy scores by (1) evaluating and comparing the baseline (tier 1; T1) accuracy and response latency of next-generation rapid-response LLMs, (2) analyzing the efficacy of a 2-tiered rescue (tier 2; T2) protocol in correcting initial errors, and (3) correlating model performance with the user data–driven AMBOSS difficulty rating. Methods: We evaluated 4 LLMs (Gemini 2.5 Flash, Gemini 2.5 Pro, GPT-5 Instant, and GPT-5 Thinking) on the complete 316-item German M2 (Fall 2024) medical examination, including all multimodal (image-based) questions. A zero-shot copy-paste prompting strategy was used, and outputs were evaluated against ground-truth answers using a strict exact-match criterion. A 2-tiered protocol was used: T1 (Gemini Flash and GPT-5 Instant) provided baseline responses. If incorrect, a T2 (Gemini Pro and GPT-5 Thinking) model was deployed as a “rescue.” Performance was analyzed using the McNemar test, the Wilcoxon signed-rank test, the Fisher exact test, and logistic regression. Results: Baseline (T1) accuracy was identical at 91.5% (289/316; 95% CI 87.85%‐94.06%) for both Gemini 2.5 Flash and GPT-5 Instant, with 27 errors each. However, Gemini Flash (mean 1.57, SD 1.06 s) was significantly faster than GPT-5 Instant (mean 2.07, SD 1.89 s; <.001). Additionally, GPT-5 Instant expended significantly more time on incorrect answers compared with correct ones (=.002), whereas Gemini Flash showed no such hesitation (=.81). The T2 rescue rate for GPT-5 Thinking (13/27, 48.2%; 95% CI 30.74%‐66.01%) was higher, though not statistically significant (=.41), than that for Gemini 2.5 Pro (9/27, 33.3%; 95% CI 18.64%‐52.18%). This rescue protocol elevated final accuracy to 94.3% (298/316; 95% CI 91.18%‐96.37%) for the Gemini system and 95.6% (302/316; 95% CI 92.70%‐97.34%) for the GPT-5 system (=.48). A strong, inverse relationship with difficulty was found: for every 1-point increase in difficulty, the odds of a correct T1 response decreased by 42.1% (odds ratio 0.579, 95% CI 0.425‐0.788; <.001) for Gemini Flash and 47.7% (odds ratio 0.523, 95% CI 0.379‐0.720; <.001) for GPT-5 Instant. This negative correlation persisted even after the rescue (=.01 and =.006, respectively). Conclusions: Expert-level LLM performance on the German M2 examination masks a critical vulnerability: a decrease in accuracy correlated with increased question difficulty. A 2-tiered “rescue” system is an effective strategy to mitigate these difficulty-based failures and achieve >95% accuracy.
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Digital Reassurance Seeking in OCD

– by Jordan Karr, PhD

We all need reassurance once in a while. Receiving reassurance from a friend, loved one, or expert can reduce short-term distress, foster a sense of connection, and help us move forward in a productive way. On the other hand, excessive reassurance seeking can lead to a painful cycle of stress and doubt. For individuals with obsessive-compulsive disorder (OCD), reassurance is fleeting and is quickly followed by a resurgence of perceived threat and a compelling drive to seek additional reassurance.

As an OCD and anxiety specialist, I am no stranger to reassurance traps. I see them in the patient who repeatedly consults doctors but never fully trusts their answers; the partner who keeps asking, “Do you still love me?” while scrutinizing every response; and the teenager who needs her homework checked repeatedly but does not learn to tolerate uncertainty. While the content of excessive reassurance seeking may vary, its function remains the same, relieving anxiety momentarily while allowing obsessions to rebound more strongly in the long run. In each example, we see an individual desperately trying to protect something they hold dear while being misled by one of OCD’s most convincing lines: “What if this time the reassurance sticks?”

Psychologists have long argued that excessive reassurance seeking helps maintain OCD, anxiety, and depression (Abramowitz et al., 2002; Burns et al., 2006). What is new is the landscape. Today, reassurance is available instantly and endlessly through search engines, medical websites, social media, and artificial intelligence tools. Emerging research suggests that online reassurance seeking may be as prevalent as interpersonal reassurance seeking (Parsons & Alden, 2022). These digital reassurance traps present in a variety of forms, including:

  • Excessive symptom-checking on WebMD
  • Checking a loved one’s location on Find My Friends to make sure they are still alive or where they promised they would be
  • Asking Google Gemini whether an intrusive thought makes you a monster, a pedophile, or a bad Christian, Muslim, or Jew
  • Analyzing the contents of a partner’s Instagram to see whether their feelings have changed
  • Endlessly searching Reddit for answers to existential questions
  • Obsessively checking likes and read receipts to monitor the durability of a relationship
  • Finding creative ways to ask ChatGPT whether you might be responsible for spreading a virus or causing someone harm
  • Compulsively checking the news to confirm whether a feared event has taken place

Why do some individuals seek reassurance primarily from others in face-to-face contexts while others turn to the internet? Findings from one study suggest that individuals may be more likely to seek interpersonal reassurance when they desire emotional support, whereas online reassurance seeking is more likely when individuals feel ashamed or fear judgment from others (Parsons et al., 2025). In the same study, shame was reported more frequently among individuals with OCD. The perceived anonymity of the internet creates a compelling environment for seeking reassurance about our most distressing fears and the fears we feel ashamed to have.

Wait, hold on… shouldn’t having access to all the information on the internet be empowering? After all, there’s that famous saying, “Knowledge is Power.” Well I’m not sure what Francis Bacon would say if he could scroll on TikTok, but in the age of the internet, more information does not always mean more power or knowledge. In fact, information overload seems to trigger excessive reassurance seeking online (Yang & Luo, 2024). Once digital algorithms detect health-related concerns, users may be exposed to increasingly frequent and targeted content, further amplifying health anxiety and driving additional reassurance seeking online (Zhang et al., 2024).

Despite these challenges, evidence-based treatments offer hope. Exposure and response prevention (ERP), the gold-standard treatment for OCD, helps individuals tolerate uncertainty and break free from compulsive behaviors. ERP therapists are prepared to respond to clients who compulsively seek reassurance while taking care to avoid reinforcing a client’s anxiety and setting boundaries when appropriate. On the other hand, AI chatbots are available 24/7 and will continue to reassure users when it would be clear to a skilled therapist that more reassurance is harmful. Some helpful activities I have encouraged clients to try include:

  • Going for a walk and leaving your phone behind
  • When you have the urge to seek reassurance, use a timer to delay. Start with 5 minutes and gradually increase the time as you go.
  • Imaginal exposure: Writing out OCD’s worst case scenario while refraining from seeking reassurance.
  • Embracing the uncertainty: When you have the urge to seek reassurance, lean into the uncertainty by responding “maybe that will happen, maybe not.”
  • Watch a movie that triggers obsessions but leave your phone in the other room
  • Try a fast from social media. Start with a short fast and increase the length of each fast as you gain confidence.
  • Agreeing with the obsessions: Whatever your OCD throws at you, respond by saying “Sure, that is true!”

Clinicians working with youth should also attend to parental accommodations that inadvertently facilitate online reassurance seeking. Supportive Parenting for Anxious Childhood Emotions (SPACE) is an evidence-based, parent-focused intervention that emphasizes increasing supportive statements while reducing unhelpful accommodations. Setting reasonable limits on smartphone use while responding with empathy and confidence can help youth build resilience and independence (i.e. “I know it’s tough to be away from your phone and I know you got this!”).

Finally, because shame plays a central role in digital reassurance traps, incorporating self-compassion practices may be beneficial. Compassion-focused exercises help individuals respond to their struggles with kindness rather than self-criticism, complementing ERP by fostering emotional resilience. I sometimes ask clients to imagine that a close friend or loved one is feeling ashamed because they are experiencing obsessions and are stuck in an OCD loop. Then, I invite them to write down how they would support this friend while paying special attention to how compassion feels in their body. By practicing compassion for others, we strengthen the same muscles in our brains that help us turn compassion inward.

If you are getting stuck in digital reassurance traps, you are not alone! Many of these technologies are brand new and we are learning how to integrate them into our lives in a healthy way. If you need help managing compulsive online habits, finding a therapist trained in ERP could be a useful step!

References

Abramowitz, J. S., Schwartz, S. A., & Whiteside, S. P. (2002). A contemporary conceptual model of hypochondriasis. Mayo Clinic Proceedings, 77(12), 1323–1330. https://doi.org/10.4065/77.12.1323

Burns, A. B., Brown, J. S., Plant, E. A., Sachs-Ericsson, N., & Joiner, T. E., Jr. (2006). On the specific depressotypic nature of excessive reassurance-seeking. Personality and Individual Differences, 40(1), 135–145. https://doi.org/10.1016/j.paid.2005.05.019

Parsons, C. A., & Alden, L. E. (2022). Online reassurance-seeking and relationships with obsessive-compulsive symptoms, shame, and fear of self. Journal of Obsessive-Compulsive and Related Disorders, 33, 100714. https://doi.org/10.1016/j.jocrd.2022.100714

Parsons, C. A., Kim, H. J., Singh, S., Lkhagva, T., Wang, J., & Alden, L. E. (2025). Covert or connected: Motivations for online and interpersonal reassurance-seeking in OCD. Journal of Anxiety Disorders, 115, 103057. https://doi.org/10.1016/j.janxdis.2025.103057

Yang, X., & Luo, X. (2024). Unpacking cyberchondria: The roles of online health information seeking, health information overload, and health misperceptions. Telematics and Informatics, 97, 102225.

Zhang, X., Zheng, H., Zeng, Y., Zou, J., & Zhao, L. (2024). Exploring how health-related advertising interference contributes to the development of cyberchondria: A stressor–strain–outcome approach. BMC Public Health, 24, 534.

Jordan Karr, PhD, is the owner of River Falls Therapy in Portland, OR. He is a licensed psychologist in Oregon and Virginia, and specializes in evidence-based therapies for OCD and anxiety disorders. Dr. Karr has experience working in outpatient, community-based, and school-based settings.

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Curcumin attenuates α-synuclein pathology in Parkinson’s disease model mice through modulation of UBC9-associated SUMOylation signaling

BackgroundPost-translational modifications, particularly SUMOylation, plays a crucial role in α-synuclein (α-syn) aggregation, a key pathological feature of Parkinson’s disease (PD). Curcumin, a natural polyphenol, has shown neuroprotective potential, but its effects on SUMOylation-related signaling in PD remain unclear.ObjectiveThis study aimed to investigate whether curcumin modulates α-syn SUMOylation and to elucidate the underlying molecular mechanisms in PD model mice.MethodsA PD model was established in male C57BL/6 mice via unilateral intrastriatal injection of α-syn preformed fibrils (PFFs). Six months after α-syn PFFs injection, mice were treated intravenously with curcumin (25 mg/kg/day) or vehicle for 1 month. Behavioral tests (open field, rotarod) assessed motor function. Neuropathology was evaluated by immunohistochemistry and western blotting for tyrosine hydroxylase (TH), phosphorylated α-syn (p-syn), SUMOylation pathway components (SUMO1, SAE2, UBC9, PIAS1/2), and ubiquitin. Striatal dopamine levels were measured by HPLC.ResultsCurcumin treatment ameliorated motor deficits and anxiety-like behaviors in PD mice. It partially preserved dopaminergic neurons and reduced p-syn aggregation in the substantia nigra, accompanied by increased striatal dopamine levels. Mechanistically, curcumin was associated with reduced SUMO1 and increased ubiquitin levels, suggesting modulation of SUMOylation-related signaling. Among SUMOylation enzymes, UBC9 expression was decreased, whereas E1 (SAE2) and E3 (PIAS1/2) components were not substantially affected.ConclusionOur findings demonstrated that curcumin exerted neuroprotective effects in a PD model by attenuating α-syn pathology. The protective mechanism involves the inhibition of α-syn SUMOylation, primarily through the downregulation of the UBC9 enzyme. This study identifies UBC9-mediated SUMOylation as a potential target for curcumin and highlight a promising strategy for modifying α-syn-associated pathology in PD.