Surgeons’ Perceptions on the Utility of a Conceptual Novel Force Sensor at the Surgeon-Tool Interface: Formative Interview Study

Background: Real-time force feedback is essential in many surgical specialties. While previous research has focused on force measured at the tool-tissue interface, little work has explored the benefits, limitations, or opportunities of measuring force at the surgeon-tool interface. Objective: This study aims to explore scenarios in which surgeons from different medical specialties and experience levels could benefit from receiving feedback on the force exerted at the surgeon-tool (or surgeon-tissue) interface. Methods: Exploratory qualitative research was conducted through interviews with medical practitioners (N=15). This study explored perceptions of a conceptual novel force-sensing surgical glove that could provide real-time feedback in terms of usability, utility, value, and limitations. Opportunities and barriers to implement a sensor of this type in clinical practice were also explored. Participants had experience in anesthetics, dental surgery, plastic and dermatological surgery, general surgery, and obstetrics and gynecology, as these surgical fields all require precise feedback on exerted forces. Results: Participants identified two key areas where a force sensor could yield significant benefits: (1) it could enhance surgical training through objective skill assessment and quantifiable feedback, and (2) it could provide valuable insights into the forces applied during practice, particularly in scenarios where other sensory feedback is masked. Participants appreciated that a sensorized glove that can provide real-time force sensing at the surgeon-tool interface would allow for continued feedback irrespective of the instrument, and integrate seamlessly into their current surgical workflow. Furthermore, as surgeons in some specialisms, for example, dental or obstetrics and gynecology, perform manual tasks, having a sensorized glove would provide feedback in instances where they are physically manipulating tissue. However, participants expressed concerns about accurately defining safe force ranges due to the variability in patients’ anatomical structures and the potential interference with tactile sensation. Conclusions: Surgeons from various clinical practices agreed that force sensing at the surgeon-tool interface could be valuable and provide them with optimal versatility as to when they would adopt force sensing. A sensorized glove could improve decision-making and surgical outcomes when other sources of information guiding force exertion are masked. Conversely, it could be detrimental when the organic information to guide force exertion is distorted when using the sensor. While the choice between interaction modalities is dependent on the accessibility of different senses during surgery, design suggestions as to where sensors are best placed on a sensorized glove are dependent on the instrument used or the type of manual procedure conducted.
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RoBuster—Corpus Annotated With Risk of Bias Text Spans in Randomized Controlled Trials in Physiotherapy and Rehabilitation: Corpus Development and Annotation Study

Background: Risk of bias (RoB) assessment of randomized clinical trials (RCTs) is vital to answering systematic review questions accurately. Manual RoB assessment for hundreds of RCTs is a cognitively demanding and lengthy process. Automation has the potential to assist reviewers in rapidly identifying text descriptions in RCTs that indicate potential risks of bias. However, no RoB text span annotated corpus could be used to fine-tune or evaluate large language models (LLMs), and there are no established guidelines for annotating the RoB spans in RCTs. Objective: The revised Cochrane RoB 2 test (RoB 2) tool provides comprehensive guidelines for RoB assessment; however, due to the inherent subjectivity of this tool, it cannot be directly used as RoB annotation guidelines. The study aimed to develop precise RoB text span annotation instructions that could address this subjectivity and thus aid the corpus annotation. Methods: We leveraged RoB 2 guidelines to develop visual instructional placards that serve as annotation guidelines for RoB spans and risk judgments. Expert annotators used these visual placards to annotate a dataset named RoBuster, consisting of 41 full-text RCTs from the domains of physiotherapy and rehabilitation. We report interannotator agreement (IAA) between 2 annotators for text span annotations before and after applying visual instructions on a subset (n=9) of RoBuster. We also provide IAA on bias risk judgments using Cohen κ. Moreover, we used a portion of RoBuster (n=10) to evaluate an LLM using a straightforward evaluation framework. This evaluation aimed to gauge the performance of an LLM (here GPT 3.5) in the challenging task of RoB span extraction and demonstrate the utility of this corpus using a straightforward framework. Results: We present a corpus of 41 RCTs with fine-grained text span annotations comprising more than 28,427 tokens belonging to 22 RoB classes. The IAA at the text span level calculated using the F1 measure varies from 0% to 90%, while Cohen κ for risk judgments ranges between –0.235 and 1.0. Using visual instructions for annotation increases the IAA by more than 17 percentage points. LLM (GPT-3.5) shows promising but varied observed agreements with the expert annotation across the different bias questions. Conclusions: Despite having comprehensive bias assessment guidelines and visual instructional placards, RoB annotation remains a complex task. Using visual placards for bias assessment and annotation enhances IAA compared to cases where visual placards are absent; however, text annotation remains challenging for the subjective questions and the questions for which annotation data are unavailable in RCTs. Similarly, while GPT-3.5 demonstrates effectiveness, its accuracy diminishes with more subjective RoB questions and low information availability.
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Sun Pharma Aims for Top 3 in Women’s Health with $11.75B Organon Purchase

Sun Pharmaceutical Industries has agreed to acquire Organon, the women’s health drug developer spun out of Merck & Co., for $11.75 billion in a deal intended to catapult the buyer into a top 25 global biopharma—top three in women’s health—by growing its innovative medicines business and expanding its product offerings into biosimilar drugs, the companies said today.

Headquartered in Jersey City, NJ, Organon was spun out of Merck in 2021 and has since then grown its portfolio to more than 70 women’s health and general medicines products, including biosimilars, that have been commercialized in the U.S. and some 140 countries worldwide. In addition to the U.S., Organon’s largest markets include Brazil, Canada, China, and the countries of the European Union. Organon said it has six manufacturing facilities across the EU and emerging markets.

Sun Pharma said the combined company created by the deal will have annual revenue of $12.4 billion, a figure the company said would propel it into a top 25 global pharma—though the company was ranked No. 14 in GEN’s most recent A-List of Top 25 Biotech Companies Heading Into 2026, compiled last December, based on its market capitalization (share price times the number of outstanding shares) of INR 4.31 trillion ($50.8 billion).

Sun Pharma said Organon’s portfolio was similar to its own, and that the acquisition of Organon was aligned with its strategies of growing its Innovative Medicines business (to a 27% revenue share) and expanding into biosimilars as a Top 10 global company.

The combined company, Sun Pharma and Organon said, would be top three in global women’s health, creating a commercial platform for future growth; the seventh largest global biosimilar player; and a presence in 150 countries worldwide, with 18 large markets that would each generate more than $100 million in revenues.

“This transaction represents a significant opportunity for Sun Pharma to build on its vision of Reaching People and Touching Lives,” Sun Pharma executive chairman Dilip Shanghvi said in a statement. “Organon’s portfolio, capabilities, and global reach are highly complementary to our own, and we believe that bringing the two organizations together can create a stronger and more diversified platform. We have deep respect for Organon’s mission and look forward to building on its legacy while driving sustainable long‑term growth.”

Deal speculation

The deal ends two weeks of speculation that began with an April 10 report in the Indian news outlet The Economic Times stating that Sun Pharma had submitted a $12 billion all-cash offer for Organon. On Friday, the news outlet followed up with a report stating that Sun Pharma had submitted a revised $13 billion offer.

Investors appeared to support the deal, as Sun Pharma shares on India’s National Stock Exchange rose about 7% to INR 1,733.50 ($18.41) at the close of trading today.

Sun Pharma has agreed to acquire 100% of Organon’s issued and outstanding shares for cash. Sun said it planned to fund the acquisition through a combination of available cash resources and committed financing from banks.

“Together, we will become a partner of choice for acquiring and launching new products,” stated Kirti Ganorkar, managing director of Sun Pharma. “Our immediate priorities will be business continuity, disciplined integration, and responsible value creation. We see strong potential in leveraging Organon’s talent pool. In addition, there is a scope for synergies including significant revenue upside opportunities to be realized over the coming years.”

Those synergies were later quantified by Sun Pharma as approximately $350 million within two to four years of the deal’s completion.

Sun Pharma did say, however, that the acquisition of Organon will strengthen its generation of cash, with its earnings before interest, taxes, depreciation, and amortization (EBITDA) and cash flow set to nearly double, supporting future efforts to reduce the net debt/EBITDA of 2.3x resulting from the deal.

Sun Pharma finished the first nine months of its fiscal year ending March 31, 2026, with a net profit of INR 87.654 billion ($931.5 million) and EBITDA of INR 137.772 billion ($1.464 billion; up 19.2% from the year-ago period), on sales of INR 436.604 billion ($4.64 billion), up 11.3% year over year.

During its fiscal year ending March 31, 2025, Sun Pharma reported adjusted net profit (excluding one-time items) of INR 119.844 billion ($1.274 billion), up 19% from a year earlier, on sales of INR 520.412 billion (about $5.53 billion). Reported net profit for FY 2025 was INR 109.290 billion ($1.161 billion), vs. Rs. 95.764 billion ($1.017 billion) during FY 2024.

Organon finished last year with adjusted EBITDA of $1.9 billion on revenue of $6.2 billion. The company reported debt of $8.64 billion—down from the $9.5 billion in debt it reported when it separated from Merck—and a cash balance of $574 million.

Planned sale

In November, Organon announced plans to sell its JADA® System, designed to control and treat abnormal postpartum uterine bleeding or hemorrhage, to Laborie Medical Technologies for up to $465 million—$440 million to be paid at closing, subject to adjustments, and up to $25 million tied to achieving 2026 revenue targets. Net proceeds from the divestiture will contribute to Organon’s cash balance as of March 31, 2026.

Organon will merge with a subsidiary of Sun Pharma, with Organon surviving the merger. The transaction is expected to close in early 2027 subject to customary conditions, including regulatory approvals and Organon stockholder approval.

The boards of both Sun Pharma and Organon have approved the deal.

“Following a comprehensive review of strategic alternatives, our Board determined that this all‑cash transaction offers compelling and immediate value to Organon stockholders,” stated Carrie Cox, executive chair of Organon. “We believe Sun Pharma is well positioned to support Organon’s businesses, employees, and patients globally, and to further advance our commitment to delivering impactful medicines and solutions.”

The post Sun Pharma Aims for Top 3 in Women’s Health with $11.75B Organon Purchase appeared first on GEN – Genetic Engineering and Biotechnology News.

STAT+: Dems say RFK Jr. has a pattern of failing to answer their questions

WASHINGTON — Last week, Sen. Ben Ray Luján (D-N.M.) asked health secretary Robert F. Kennedy Jr. whether he would release — by Friday — the contract of a longtime vaccine critic who was hired by the Department of Health and Human Services.

“Yeah, I’m happy to,” Kennedy responded.

But Friday came and went without a response from Kennedy. On Monday, Luján’s office said they plan to follow up with HHS.

Continue to STAT+ to read the full story…

Frugal-Oriented Information and Communication Technology for Development Framework Toward Low-Cost Digital Maternal Health in Low- and Middle-Income Countries: Quantitative Descriptive Study

Background: The Sustainable Development Goals (SDGs) aim to eradicate poverty and inequality while ensuring that all individuals enjoy good health. Among these, target 3.1 seeks to reduce the global maternal mortality ratio to less than 70 per 100,000 live births. However, progress toward this target has been limited, particularly in low- and middle-income countries (LMICs), where health care delivery remains constrained by limited resources. While digital innovations have increasingly been adopted to improve health care access and service delivery, a significant proportion of populations in LMICs continues to experience inadequate access to essential maternal health services. This gap underscores the need for affordable, sustainable, and contextually appropriate strategies that are cost-effective in improving maternal health outcomes in underserved communities. Objective: This study leverages the principles of frugal innovation and information and communication technologies for development (ICT4D) to propose a frugal-oriented ICT4D framework to deliver low-cost digital maternal health solutions in LMIC settings. The framework seeks to optimize the use of available resources, foster equitable access to maternal health care, and contribute toward achieving SDG 3, particularly target 3.1. Methods: The study was conducted in both rural and urban-poor settings in Kenya using a 2-phased quantitative approach. In phase 1, eight theoretical themes relevant to maternal health uptake were explored. These themes were represented on color-coded sorting cards, which participants ranked according to perceived importance. Phase 2 involved administering structured survey questionnaires to collect empirical data. The study included a total of 32 participants, whose insights provided a foundation for analyzing the significance of contextual factors influencing maternal health service utilization. Results: The weighted scores for 3 of the 8 predetermined theoretical themes—such as resources, information services, and social support programs—emerged as the most influential factors shaping maternal health promotion (N=32). Resources ranked highest (n=6, 18.81%), followed by information services (n=6, 17.99%), while social support programs accounted for 9.64% (n=3) of the overall influence. These findings highlight critical enablers and barriers within the maternal health care landscape and provide a nuanced understanding of contextual dynamics that affect the uptake of maternal health services. The results informed the design of a frugal-oriented ICT4D framework that prioritizes low-cost digital interventions tailored to resource-limited settings. Conclusions: Despite increasing recognition of digital innovations as tools for health care transformation in LMICs, adoption of existing capital-intensive solutions remains low due to financial and infrastructural constraints. This study emphasizes the importance of adopting frugal innovation and ICT4D principles in designing low-cost, scalable digital health interventions to improve access to maternal health care. Implementing such approaches can address resource limitations, enhance maternal health outcomes, and support progress toward SDG 3, particularly target 3.1. The proposed framework provides a foundation for future research and practical interventions aimed at sustainable, equitable maternal health service delivery in LMIC contexts.
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Enhancing Sleep and Mental Health: Longitudinal, Observational, Real-World Study From a Digital Mental Health Platform

Background: Poor sleep is closely linked to mental health challenges and workplace burnout. Mental health and workplace stressors can impair sleep, while good sleep quality supports cognitive and emotional resources to cope with daily challenges. Despite positive outcomes of maintaining good sleep, many people struggle to get enough restorative sleep at night. Given the bidirectional relationship between sleep and mental health, evidence-based digital mental health solutions may offer an accessible and scalable approach to improving sleep quality. Objective: This study examines whether engagement with an employer-sponsored, multimodal digital mental health platform is associated with improvements in sleep quality over time, and whether changes in sleep quality are associated with concurrent changes in mental health and burnout outcomes. Methods: This 12-month prospective, observational study followed working adults who were newly registered to an employer-sponsored digital mental health platform (Modern Health). The platform leveraged technology (mobile and web) to connect employees with comprehensive provider-led and self-guided care through therapy, coaching, on-demand digital resources, and group psychoeducational sessions. Participants [N=578; 61.1% (n=353) women; mean age 33.88, SD 8.73 years; 40.3% (n=233) people of color] completed measures of self-rated sleep quality, depression, anxiety, and burnout (exhaustion, cynicism, and professional efficacy) at baseline and after 3 and 12 months of accessing the platform. Upon registering for the platform, participants were given an initial care recommendation, but could flexibly engage in any combination of services. Participants in this study engaged with at least one care modality, including therapy, coaching, psychoeducation sessions, and self-guided mental health resources. We examined perceived sleep quality and associations with other study variables at baseline, changes in perceived sleep quality over time, and whether changes in sleep quality correlated with concurrent changes in mental health and burnout. Results: At baseline, 42% (243/578) reported poor sleep quality and were more likely to have higher levels of depression, anxiety, and burnout. A generalized linear mixed-effects model showed that each additional month of platform access was related to an increased odds of having good sleep quality by 3.7% (=.02). Linear mixed-effects models found that higher sleep quality over time was associated with lower depression, anxiety, exhaustion, cynicism, and efficacy (all <.001). Among participants reporting poor sleep quality at baseline, 44% (62/141) reported good sleep quality at 12 months. Within this subgroup, paired sample tests showed significant reductions in depression (−48.3%) and anxiety (−38.3%), and increased cynicism, burnout, though cynicism levels remained below the cutoff for high burnout (23.9%; all <.01). Conclusions: Use of an employer-sponsored digital mental health platform was associated with meaningful improvements in self-reported sleep quality over 12 months. These gains were associated with significant reductions in depression, anxiety, and burnout symptoms, highlighting broader well-being benefits of comprehensive mental health care.

Integrating Virtual Reality Simulation, Online Learning, and Group Reflection to Strengthen Dementia Care in Nursing Homes: Mixed Methods Pilot Study

Background: Long-term care facilities are increasingly caring for persons living with dementia as this population grows. Frontline care workers provide most hands-on support, yet they often have limited access to formal dementia education and training. Traditional training formats frequently fail to support experiential learning or accommodate the linguistic, cultural, and demographic diversity of the long-term care workforce. Objective: This mixed methods pilot study examined the effects of the combined use of online learning, immersive virtual reality (VR) simulation, and facilitated group discussions on the training and preferred learning formats. In particular, this study tested whether training based on relationship-centered care (eg, emphasizing the importance of mutual respect, empathy, and shared humanity) in care relationships embodied in the immersive VR simulation allows staff to experience dementia-related cognitive and sensory changes from the perspective of persons living with dementia. Methods: A total of 21 certified nursing assistants from 1 US nursing home participated in a 3-month mixed methods intervention. Empathy and knowledge were measured using pre- and postintervention standardized tests; qualitative feedback was collected through open-ended surveys and group discussions. Results: Participants were predominantly female, Black certified nursing assistants with approximately 68% reporting 8 years or more of care experience. Among the 76.2% (16/21) of the participants who completed the pre- and postintervention surveys, empathy scores increased from pretest (mean 5.31, SD 0.74) to posttest (mean 5.51, SD 0.61). The mean difference of 0.20 (SD 0.43) did not reach statistical significance (=1.88; =.08), but the effect size was moderate (Cohen =0.47, 95% CI −0.03 to 0.43). Dementia knowledge scores also increased from pretest (mean 5.50, SD 2.37) to posttest (mean 5.94, SD 2.11), with a mean difference of 0.44 (SD 1.63), which was not statistically significant (=1.07; =.30), and demonstrated a small effect size (Cohen =0.27, 95% CI −0.43 to 1.31). Qualitative findings revealed that participants perceived the VR training as engaging and emotionally impactful. Participants described reframing their understanding of dementia, reporting reduced stigma and increased empathy toward persons living with dementia. Many noted that experiencing dementia-related symptoms through VR helped them better understand residents’ behaviors and respond with greater compassion. Participants expressed a strong preference for immersive VR and facilitated group discussions over online modules, and cultural differences in the VR scenarios were not perceived as barriers to learning. Conclusions: While preliminary, these findings suggest that combining relationship-centered care with immersive VR may enhance empathy and engagement among staff, particularly when paired with facilitated discussion and plain language explanations. This multimodal model appears particularly valuable for supporting empathic learning within diverse and experienced workforces. Larger, multisite studies with sustained follow-up are needed to determine long-term effects and optimize training for linguistically and culturally diverse workforces.
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Comparing Perceptions of ChatGPT Use in Health Attitude Contexts Among Users and Nonusers: Cross-Sectional Study

Background: In light of the growing use of artificial intelligence (AI) in health care, individuals’ access to and use of health information are transforming. ChatGPT, an AI chatbot, provides immediate responses to health queries, with the potential to influence health-related attitudes, thereby raising concerns related to privacy, reliability, and security. Objective: This study aimed to investigate the perceived usefulness, risks, anxiety, and social influence of ChatGPT on health attitudes among users and nonusers in Saudi Arabia. Methods: A cross-sectional study was conducted using an online survey based on a validated tool. In total, 337 participants aged 18 years and older responded to questions assessing their perceptions of ChatGPT on health-related attitudes. Results: Data showed that 76.1% (194/255) of the respondents used ChatGPT, with the majority being younger and more highly educated. The main uses for health-related purposes were health education (43/194, 22.2%) and physical activity guidance (31/194, 16%). The analysis showed that users considered ChatGPT useful for health-related decisions, with 45.9% (89/194) finding it easy to learn and use, but concerns about privacy (106/194, 54.7%) and reliability (87/194, 44.9%) remained. Among nonusers, security risks (39/61, 63.9%) were the major barrier to using AI-based tools for health purposes, and 68.9% (42/61) found such tools attractive and engaging. There were no statistically significant differences between users and nonusers across all examined sociodemographic characteristics (>.05). Conclusions: The study established the potential of ChatGPT in improving health decision-making and revealed cultural, privacy, and trust issues that may affect its implementation. These findings underscore the importance of strengthening the security of AI-based applications to enhance public acceptability of related health policies and to support the safe integration of tools such as ChatGPT into the health care system.

The Effectiveness and Mechanisms of Action of App-Based Interventions for Improving Mental Health and Workplace Well-Being: Randomized Controlled Trial

Background: Depression is the most common mental health disorder worldwide and frequently leads to workplace absence. As face-to-face treatment can be difficult to access, app-based interventions are a popular solution, although their effectiveness in working populations and their mechanisms of action are unclear. Deficits in executive function may contribute to the onset and maintenance of depression, and executive function training is proposed to improve symptoms by enhancing executive function. Responders to cognitive behavioral therapy (CBT) show improvements in executive function, suggesting that this may be one mechanism of action. Objective: This study investigated the effectiveness of app-based interventions (executive function or CBT-based) for reducing depressive and anxiety symptoms and improving workplace well-being, and assessed whether changes in executive function mediated improvements. Methods: A total of 228 participants (147 female participants) with mild-to-moderate symptoms of depression and anxiety were recruited online and randomly assigned to a waitlist control group, an executive function training group (NeuroNation app, Synaptikon GmbH), or a self-guided CBT group (Moodfit app, Roble Ridge LLC) for a 4-week intervention period. Participants assigned to the active intervention groups were asked to use their apps a minimum of 21 times during the intervention. Participants completed measures of depressive symptoms, anxiety symptoms, and workplace well-being, and a working memory task at baseline, postintervention, and follow-up (12 weeks). Results: Executive function training reduced anxiety (β=−2.79; =.004) and depressive (β=−2.77; =.02) symptoms at follow-up but not at postintervention, and it did not affect workplace well-being. There were no reductions in depressive or anxiety symptoms in the self-guided CBT group, though workplace well-being was improved at postintervention (β=3.72; =.02) and follow-up (β=4.46; =.02). Improvements in executive function did not mediate intervention-related changes in symptoms or workplace well-being. Self-reported adherence rates were high (executive function training: 48/54, 89%; self-guided CBT: 52/54, 96%), although attrition was high at follow-up (58% missing). Conclusions: These results suggest that app-based executive function training may be effective at managing symptoms of anxiety and depression in a working population, while self-guided CBT apps may improve workplace well-being. However, improving executive function did not appear to be a mechanism of action of either intervention. Trial Registration: ISRCTN 12730006; https://www.isrctn.com/ISRCTN12730006
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PD-L1 Inhibitors for Cancer Treatment Could Be Repurposed to Treat Bone Loss in Obesity

Bone loss related to obesity is partly caused by changes inside the bone marrow fat compartment that reshape immune signaling and increase osteoclast formation, according to researchers at the MaineHealth Institute for Research. In a study published in Bone Research, the team found that expansion of bone marrow adipose tissue in obese people changes the marrow environment toward immunosuppression through PD-L1 signaling, which in turn promotes bone-resorbing osteoclast activity that reduces bone volume.

“We discovered that bone marrow fat is not simply a passive tissue but actively reshapes immune signaling in ways that accelerate bone loss in obesity,” said senior author Clifford J. Rosen, MD, senior scientist at the MaineHealth Institute for Research.

The team noted that obesity influences bone health not just due to a higher body weight but also by altering the bone marrow environment. The increase in bone marrow fat promotes immunosuppressive PD-L1 signaling, which enhances osteoclast formation and accelerates bone loss.

The study identified a pathway in which bone marrow adipocytes increase expression of MCP-1, a signaling molecule that recruits myeloid immune cells. These recruited cells shift toward a PD-L1–expressing phenotype, with PD-L1 interacting with PD-1 receptors, which are found not only on T cells but also on osteoclast precursors. In immune biology, PD-1/PD-L1 signaling is typically known for suppressing T-cell activation and promoting immune braking. This new study shows that this same form of suppressive signaling also directly enhances osteoclast differentiation.

According to the study results, as PD-L1+ myeloid cells accumulate, they suppress T-cell activity in bone marrow, creating an immunosuppressive environment. At the same time, PD-L1 engagement with PD-1 on osteoclast precursors promotes their maturation into active osteoclasts, which break down bone tissue, increase resorption and reduce bone density.

To learn more about this mechanism, the investigators used diet-induced obese mouse models, co-culture systems, and genetic depletion approaches. An important model in this work were mice lacking bone marrow adipocytes, which allowed the researchers to isolate the role of marrow fat. The team also blocked PD-1/PD-L1 signaling during early osteoclast formation in vitro. In both cases, osteoclast differentiation decreased and bone structure improved. The mice lacking bone marrow adipocytes showed fewer PD-L1+ myeloid cells, fewer PD-1+ osteoclast precursors, and higher trabecular bone volume even under high-fat diet conditions.

Earlier research has shown a link between obesity and bone loss, but studies reported trabecular bone loss without cortical effects, while others found no significant bone changes under diet-induced obesity. The MaineHealth team noted that these earlier studies often focused on shifts in osteoblast activity as opposed to their approach which identified a pro-osteoclastic mechanism driven by immune signaling.

In addition, the Maine Health finding also added to evidence that has established that obesity is associated with impaired immune responses, including reduced vaccine effectiveness and altered macrophage activity. In this study, the marrow environment in obese mice resembled features seen in tumor-associated immune suppression, where PD-L1 expression is elevated and immune activity is dampened. The researchers wrote that “the increase in PD-L1 expression seen in OB-HFD mice is related to the increase in Mcp-1 in part because previous cancer research has suggested the recruitment of myeloid cells via Mcp-1 creates an immunosuppressive tumor microenvironment.”

The findings suggest potential strategies for preserving bone bones in obese people by targeting bone marrow adiposity or the PD-1/PD-L1 pathway. Because PD-1/PD-L1 inhibitors are already used in oncology, there is a compelling case for repurposing or adapting immune checkpoint modulation therapies already approved for cancer treatment for bone disorders linked to metabolic disease. The authors also noted another strategy could be to reduce the amount of bone marrow fat itself to restore immune balance and limit osteoclast-driven bone loss.

The post PD-L1 Inhibitors for Cancer Treatment Could Be Repurposed to Treat Bone Loss in Obesity appeared first on Inside Precision Medicine.