Reading view
Primary care detection of Alzheimer’s disease using a self-administered digital cognitive test and blood biomarkers
Nature Medicine, Published online: 15 September 2025; doi:10.1038/s41591-025-03965-4
A brief, self-administered digital cognitive test, in combination with a blood test, accurately detects clinical Alzheimer’s disease in primary care.Prognostic Value of Circulating Tumor DNA in HR+/HER2- Stage I-III Breast Cancer: A Systematic Review
Cancers (Basel). 2025 Aug 29;17(17):2831. doi: 10.3390/cancers17172831.
ABSTRACT
Background: Hormone receptor-positive (HR+), HER2-negative breast cancer accounts for the majority of breast cancer diagnoses. While outcomes have improved with neoadjuvant and adjuvant therapies, the risk of late recurrence persists, and there remains a critical need for reliable biomarkers to guide prognosis and post-treatment surveillance. Circulating tumor DNA (ctDNA), detectable via liquid biopsy, has emerged as a promising tool for monitoring minimal residual disease and predicting survival outcomes. This systematic review evaluates the association between ctDNA detection during neoadjuvant or adjuvant treatment and survival outcomes in early-stage HR+/HER2- breast cancer. Methods: This systematic review was conducted in accordance with PRISMA guidelines. A comprehensive literature search of Ovid MEDLINE and Embase was conducted to identify studies published through 3 May 2024 that evaluated ctDNA as a prognostic biomarker in stage I-III HR+/HER2- breast cancer. We included studies reporting recurrence-free survival, invasive disease-free survival, or overall survival and excluded non-original studies, conference abstracts, and non-English articles. Data extraction and qualitative synthesis were performed, and the risk of bias was qualitatively assessed across studies. No review protocol was registered. Results: Eleven studies comprising 1644 patients met the inclusion criteria. In the neoadjuvant setting, ctDNA positivity prior to treatment initiation was associated with inferior survival outcomes. In the adjuvant setting, detection of ctDNA during or after treatment was consistently linked to poorer recurrence-free and invasive disease-free survival. Across studies, ctDNA detection was a significant negative prognostic marker. Conclusions: This systematic review supports the prognostic value of ctDNA in HR+/HER2- early-stage breast cancer. Limitations include small sample sizes, observational study designs, and heterogeneity in ctDNA assays. Standardization of ctDNA testing methods and further prospective trials are needed to validate its clinical utility and explore its potential role in guiding therapeutic interventions.
PMID:40940926 | PMC:PMC12427406 | DOI:10.3390/cancers17172831
Functions of the global health system in a new era
Nature Medicine, Published online: 11 September 2025; doi:10.1038/s41591-025-03936-9
In an irrevocably changed landscape, reform of the global health system needs to answer key questions on functions, what should be delivered in different contexts and at different levels, and how the system should operate.Interventions Based on Biofeedback Systems to Improve Workers’ Psychological Well-Being, Mental Health, and Safety: Systematic Literature Review
The Impact of Artificial Intelligence on Lung Cancer Diagnosis and Personalized Treatment
Int J Mol Sci. 2025 Aug 31;26(17):8472. doi: 10.3390/ijms26178472.
ABSTRACT
Lung cancer is the leading cause of cancer mortality globally, despite the advancements in screening and management. Survival rates for lung cancer remain suboptimal, largely due to late-stage diagnoses and tumor heterogeneity. Recent advancements in artificial intelligence and radiomics provide a promising outlook for lung cancer screening, diagnosis, personalized treatment, and prognosis. These advances use large-scale clinical and imaging datasets that help identify patterns and predictive features that may be missed by human interpretation. Artificial intelligence tools hold the potential to take clinical decision-making to another level, thus improving patient outcomes. This review summarizes current evidence on the applications, challenges, and future directions of artificial intelligence (AI) in lung cancer care, with an emphasis on early diagnosis and personalized treatment. We examine recent developments in AI-driven approaches, including machine learning and deep neural networks, applied to imaging (radiomics), histopathology, biomarker analysis, and multi-omic data integration. AI-based models demonstrate promising performance in early detection, risk stratification, molecular profiling (e.g., programmed death-ligand 1 (PD-L1) and epidermal growth factor receptor (EGFR) status), and outcome prediction. These tools may enhance diagnostic accuracy, optimize therapeutic decisions, and ultimately improve patient outcomes. However, significant challenges remain, including model heterogeneity, limited external validation, generalizability issues, and ethical concerns related to transparency and clinical accountability. AI holds transformative potential for lung cancer care but requires further validation, standardization, and integration into clinical workflows. Multicenter collaborations, regulatory frameworks, and explainable AI models will be essential for successful clinical adoption.
PMID:40943394 | PMC:PMC12429163 | DOI:10.3390/ijms26178472
Fluctuating DNA methylation tracks cancer evolution at clinical scale
Nature, Published online: 10 September 2025; doi:10.1038/s41586-025-09374-4
Cancer evolutionary dynamics are quantitatively inferred using a method, EVOFLUx, applied to fluctuating DNA methylation.Using biobanks to boost research: a how-to guide
Nature, Published online: 10 September 2025; doi:10.1038/d41586-025-02813-2
From large national databases to bespoke sample collections, biobanks offer a wealth of avenues for scientific enquiry.Single-cell multiome and spatial profiling reveals pancreas cell type-specific gene regulatory programs of type 1 diabetes progression
Sci Adv. 2025 Sep 12;11(37):eady0080. doi: 10.1126/sciadv.ady0080. Epub 2025 Sep 10.
ABSTRACT
Cell type-specific regulatory programs that drive type 1 diabetes (T1D) in the pancreas are poorly understood. Here, we performed single-nucleus multiomics and spatial transcriptomics in up to 32 nondiabetic (ND), autoantibody-positive (AAB+), and T1D pancreas donors. Genomic profiles from 853,005 cells mapped to 12 pancreatic cell types, including multiple exocrine subtypes. β, Acinar, and other cell types, and related cellular niches, had altered abundance and gene activity in T1D progression, including distinct pathways altered in AAB+ compared to T1D. We identified epigenomic drivers of gene activity in T1D and AAB+ which, combined with genetic association, revealed causal pathways of T1D risk including antigen presentation in β cells. Last, single-cell and spatial profiles together revealed widespread changes in cell-cell signaling in T1D including signals affecting β cell regulation. Overall, these results revealed drivers of T1D in the pancreas, which form the basis for therapeutic targets for disease prevention.
PMID:40929272 | PMC:PMC12422192 | DOI:10.1126/sciadv.ady0080
The Impact of Artificial Intelligence on Lung Cancer Diagnosis and Personalized Treatment
Int J Mol Sci. 2025 Aug 31;26(17):8472. doi: 10.3390/ijms26178472.
ABSTRACT
Lung cancer is the leading cause of cancer mortality globally, despite the advancements in screening and management. Survival rates for lung cancer remain suboptimal, largely due to late-stage diagnoses and tumor heterogeneity. Recent advancements in artificial intelligence and radiomics provide a promising outlook for lung cancer screening, diagnosis, personalized treatment, and prognosis. These advances use large-scale clinical and imaging datasets that help identify patterns and predictive features that may be missed by human interpretation. Artificial intelligence tools hold the potential to take clinical decision-making to another level, thus improving patient outcomes. This review summarizes current evidence on the applications, challenges, and future directions of artificial intelligence (AI) in lung cancer care, with an emphasis on early diagnosis and personalized treatment. We examine recent developments in AI-driven approaches, including machine learning and deep neural networks, applied to imaging (radiomics), histopathology, biomarker analysis, and multi-omic data integration. AI-based models demonstrate promising performance in early detection, risk stratification, molecular profiling (e.g., programmed death-ligand 1 (PD-L1) and epidermal growth factor receptor (EGFR) status), and outcome prediction. These tools may enhance diagnostic accuracy, optimize therapeutic decisions, and ultimately improve patient outcomes. However, significant challenges remain, including model heterogeneity, limited external validation, generalizability issues, and ethical concerns related to transparency and clinical accountability. AI holds transformative potential for lung cancer care but requires further validation, standardization, and integration into clinical workflows. Multicenter collaborations, regulatory frameworks, and explainable AI models will be essential for successful clinical adoption.
PMID:40943394 | PMC:PMC12429163 | DOI:10.3390/ijms26178472
Liquid biopsy- A pivotal test to help navigate clinical decisions at a precision center in India!
J Liq Biopsy. 2025 Aug 9;9:100323. doi: 10.1016/j.jlb.2025.100323. eCollection 2025 Sep.
ABSTRACT
Liquid biopsy, specifically circulating tumor DNA (ctDNA) analysis, has emerged as a transformative tool in precision oncology, providing real-time, minimally invasive characterizations of the tumor and tumor dynamics. While tissue biopsy is a critical tool for baseline diagnosis of malignancy, it is often limited by sampling constraints and an inability to capture tumor heterogeneity. In this study, we explored the clinical utility of serial ctDNA testing in guiding therapeutic decisions across a cohort of 30 patients with diverse solid tumors. Our real-world analysis demonstrates that ctDNA profiling meaningfully influenced treatment escalation, de-escalation, disease monitoring, and early relapse prediction. Cases where ctDNA positivity indicated minimal residual disease prompted timely escalation of therapy, while ctDNA clearance allowed safe treatment de-intensification, minimizing toxicity without compromising outcomes. Longitudinal ctDNA monitoring provided a dynamic, non-invasive method for assessing treatment response and detecting recurrence months before radiological progression. Our study highlights the potential of integrating liquid biopsy into routine clinical practice to enable dynamic treatment monitoring, early detection of therapeutic resistance, and more informed, personalized decision-making across various cancer types.
PMID:40919127 | PMC:PMC12409318 | DOI:10.1016/j.jlb.2025.100323
The WHO global landscape of cancer clinical trials
Nature Medicine, Published online: 09 September 2025; doi:10.1038/s41591-025-03926-x
This Review of the WHO’s International Clinical Trials Registry Platform presents a snapshot of the global cancer trial landscape and provides critical empirical evidence to inform policy, practice and investment.Building the world’s first truly global medical foundation model
Nature Medicine, Published online: 08 September 2025; doi:10.1038/s41591-025-03859-5
Building the world’s first truly global medical foundation modelSTAT+: FDA greenlights trial of gene-edited pig kidneys as treatment for end-stage kidney disease
DOVER, N.H. — Not long after he woke from surgery in June, Bill Stewart made a pact with his newest organ. He wasn’t sure how long the thing would last. The doctors had been up-front from the get-go: It could be three months or six, one year or four. Still, the uncertainty hit him as he started getting back preliminary lab results, which were okay but left room for improvement. “My pig kidney and I had a little conversation while I was laying there. I just basically said, ‘I’m going to do everything I can to make sure that you stay healthy, and I appreciate you doing everything you can to keep me upright and breathing,” Stewart said.
It’s been almost three months, and Stewart is home, back to work, and has even been able to go e-biking on a lakeside trail with his wife, blessedly untethered to the grueling schedules of dialysis for the first time in years, all thanks to a gene-edited Yucatan miniature pig named Lavender.
Stewart is the most recent recipient of a pig kidney — but chances are, he won’t hold that distinction for long. On Monday, eGenesis, a Cambridge-based biotechnology company, announced that it had been cleared by the Food and Drug Administration to begin a trial of kidneys from donor pigs that have been CRISPR’d to make their organs more human-friendly. Now, Massachusetts researchers will be performing more surgeries like Stewart’s to see whether these animal parts could serve as a lifeline for people with end-stage renal disease.
Continue to STAT+ to read the full story…


© Cheryl Senter for STAT
Antibody–bottlebrush prodrug conjugates for targeted cancer therapy
Nature Biotechnology, Published online: 09 September 2025; doi:10.1038/s41587-025-02772-z
Antibody–bottlebrush conjugates expand the options for drug cargos compared to antibody–drug conjugates.Clinical applications of cell-free DNA-based liquid biopsy analysis
Transl Oncol. 2025 Nov;61:102519. doi: 10.1016/j.tranon.2025.102519. Epub 2025 Sep 6.
ABSTRACT
Liquid biopsies, particularly those involving circulating tumor DNA (ctDNA) from patient blood, have emerged as crucial and minimally invasive adjuncts to standard tissue-based testing. ctDNA testing enables the identification of actionable mutations for targeted therapy and can be routinely used when tissue samples are unavailable for genotyping. Compared to tissue-based testing, ctDNA testing has the advantages of capturing spatial or temporal genomic heterogeneity and facilitating repeated assessments. The utility of liquid biopsies extends to multiple clinical applications, including cancer diagnosis, treatment monitoring, and minimal residual disease (MRD) detection. Numerous clinical trials are currently evaluating treatment strategies using ctDNA testing. In particular, the implementation of adjuvant treatment escalation or de-escalation based on MRD detection could dramatically transform future approaches to solid tumor treatment. Various ctDNA assays have been developed, and it is important to understand their strengths and weaknesses for effective clinical applications. Furthermore, ctDNA testing faces several technical challenges, including low sensitivity in detecting copy number alterations and fusions, as well as the possibility of detecting mutations associated with clonal hematopoiesis of indeterminate potential. In this review, we comprehensively discuss the methodologies and recent advancements in cfDNA-based liquid biopsies for cancer patients, covering diagnosis, genomic profiling, and treatment monitoring. Furthermore, we explore clinical trial designs employing ctDNA testing and anticipate forthcoming changes in patient care.
PMID:40915174 | PMC:PMC12450568 | DOI:10.1016/j.tranon.2025.102519
Article: Virtual Panel: How Software Engineers and Team Leaders Can Excel with Artificial Intelligence

Artificial intelligence is impacting the individual work of software developers, how professionals work together in teams, and how software teams are being managed. In this panel, we'll discuss how artificial intelligence is reshaping software development, and what mindset and skills are required for software developers and engineering leaders to become adaptable and resilient in the age of AI.
By Ben Linders, Courtney Nash, Mandy Gu, Hien LuuScalable generation and functional classification of genetic variants in inborn errors of immunity to accelerate clinical diagnosis and treatment
STAMP: Single-cell transcriptomics analysis and multimodal profiling through imaging
Meta revises AI chatbot policies amid child safety concerns
Meta is revising how its AI chatbots interact with users after a series of reports exposed troubling behaviour, including interactions with minors. The company told TechCrunch it is now training its bots not to engage with teenagers on topics like self-harm, suicide, or eating disorders, and to avoid romantic banter. These are temporary steps while it develops longer-term rules.
The changes follow a Reuters investigation that found Meta’s systems could generate sexualised content, including shirtless images of underage celebrities, and engage children in conversations that were romantic or suggestive. One case reported by the news agency described a man dying after rushing to an address provided by a chatbot in New York.
Meta spokesperson Stephanie Otway admitted the company had made mistakes. She said Meta is “training our AIs not to engage with teens on these topics, but to guide them to expert resources,” and confirmed that certain AI characters, like highly sexualised ones like “Russian Girl,” will be restricted.
Child safety advocates argue the company should have acted earlier. Andy Burrows of the Molly Rose Foundation called it “astounding” that bots were allowed to operate in ways that put young people at risk. He added: “While further safety measures are welcome, robust safety testing should take place before products are put on the market – not retrospectively when harm has taken place.”
Wider problems with AI misuse
The scrutiny of Meta’s AI chatbots comes amid broader worries about how AI chatbots may affect vulnerable users. A California couple recently filed a lawsuit against OpenAI, claiming ChatGPT encouraged their teenage son to take his own life. OpenAI has since said it is working on tools to promote healthier use of its technology, noting in a blog post that “AI can feel more responsive and personal than prior technologies, especially for vulnerable individuals experiencing mental or emotional distress.”
The incidents highlight a growing debate about whether AI firms are releasing products too quickly without proper safeguards. Lawmakers in several countries have already warned that chatbots, while useful, may amplify harmful content or give misleading advice to people who are not equipped to question it.
Meta’s AI Studio and chatbot impersonation issues
Meanwhile, Reuters reported that Meta’s AI Studio had been used to create flirtatious “parody” chatbots of celebrities like Taylor Swift and Scarlett Johansson. Testers found the bots often claimed to be the real people, engaged in sexual advances, and in some cases generated inappropriate images, including of minors. Although Meta removed several of the bots after being contacted by reporters, many were left active.
Some of the AI chatbots were created by outside users, but others came from inside Meta. One chatbot made by a product lead in its generative AI division impersonated Taylor Swift and invited a Reuters reporter to meet for a “romantic fling” on her tour bus. This was despite Meta’s policies explicitly banning sexually suggestive imagery and the direct impersonation of public figures.
The issue of AI chatbot impersonation is particularly sensitive. Celebrities face reputational risks when their likeness is misused, but experts point out that ordinary users can also be deceived. A chatbot pretending to be a friend, mentor, or romantic partner may encourage someone to share private information or even meet in unsafe situations.
Real-world risks
The problems are not confined to entertainment. AI chatbots posing as real people have offered fake addresses and invitations, raising questions about how Meta’s AI tools are being monitored. One example involved a 76-year-old man in New Jersey who died after falling while rushing to meet a chatbot that claimed to have feelings for him.
Cases like this illustrate why regulators are watching AI closely. The Senate and 44 state attorneys general have already begun probing Meta’s practices, adding political pressure to the company’s internal reforms. Their concern is not only about minors, but also about how AI could manipulate older or vulnerable users.
Meta says it is still working on improvements. Its platforms place users aged 13 to 18 into “teen accounts” with stricter content and privacy settings, but the company has not yet explained how it plans to address the full list of problems raised by Reuters. That includes bots offering false medical advice and generating racist content.
Ongoing pressure on Meta’s AI chatbot policies
For years, Meta has faced criticism over the safety of its social media platforms, particularly regarding children and teenagers. Now Meta’s AI chatbot experiments are drawing similar scrutiny. While the company is taking steps to restrict harmful chatbot behaviour, the gap between its stated policies and the way its tools have been used raises ongoing questions about whether it can enforce those rules.
Until stronger safeguards are in place, regulators, researchers, and parents will likely continue to press Meta on whether its AI is ready for public use.
(Photo by Maxim Tolchinskiy)
See also: Agentic AI: Promise, scepticism, and its meaning for Southeast Asia
Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and co-located with other leading technology events. Click here for more information.
AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.
The post Meta revises AI chatbot policies amid child safety concerns appeared first on AI News.
