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Quantum cryptography and data protection for medical devices before and after they meet Q-Day

npj Digital Medicine, Published online: 21 October 2025; doi:10.1038/s41746-025-02082-3

Although still at a nascent state, quantum computing promises advances in healthcare, from drug discovery to personalised treatments. But it also threatens current cryptographic systems that protect medical data and infrastructure. The concept of “Q-Day” highlights risks such as “harvest now, decrypt later” attacks, with particular concerns for medical devices and sensitive applications in fields like femtech. Preparing for this future requires the rapid adoption of post-quantum cryptography, the coordination of time-phased and scalable “technology rollout” strategies, and revised regulatory frameworks to safeguard patient safety, privacy, and trust.
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Effectiveness of a Digital Therapy on 6-Month Weight Loss in People With Obesity: The Digital Therapy to Promote Weight Loss in Patients With Obesity by Increasing Their Adherence to Treatment (DEMETRA) Randomized Clinical Trial

Background: Obesity is a chronic, relapsing disease influenced by environmental, lifestyle, biological, and genetic factors, affecting over 1 billion people globally. Treatment for adults typically involves multicomponent lifestyle interventions—diet, physical activity, and behavior change—for at least 6-12 months. However, adherence is often low, and in-person sessions can be time-consuming and costly. Digital therapeutics (DTx), which enhance patient engagement and support long-term outcomes, have proven effective in managing chronic and mental health conditions. DTx offer scalable, evidence-based solutions with the potential to improve obesity management. Objective: The Digital Therapy to Promote Weight Loss in Patients With Obesity by Increasing Their Adherence to Treatment (DEMETRA) study is a prospective, multicenter, pragmatic, randomized, double-arm, single-blind, placebo-controlled trial evaluating the 6-month efficacy of an innovative, multicomponent digital intervention for obesity, which combines dietary, physical activity, and behavioral strategies in people with obesity (primary objective). Secondary objectives were assessing changes in BMI, waist circumference, blood pressure, glucose metabolism, lipid profile, adherence, and factors associated with absolute 6-month weight loss. Methods: The trial was conducted at 2 obesity centers in Italy with 246 participants aged 18-65 years (BMI 30-45 kg/m2), randomly assigned to either the Digital Therapeutics for Obesity (DTxO) app or a placebo app. DTxO offered personalized diet plans, exercise routines, and psycho-behavioral support, while the placebo app only allowed users to log data without feedback. Both groups followed a Mediterranean-style low-calorie diet with an 800 kcal/day deficit. On average, participants used the DTxO app for 42 minutes/day and the placebo app for 35 minutes, primarily for physical activity tracking. Univariable and multivariable generalized linear models were used to assess associations with 6-month absolute weight change (primary end point) and percent weight change (secondary end point). Results: Overall, 207 participants (84.1%) completed the 6-month visit. Both arms achieved a statistically significant absolute (DtxO: –3.2 kg, IQR –6.0 kg to –0.9 kg; placebo: –4.0 kg, IQR –6.9 kg to –0.5 kg; P<.001) and percent loss in body weight (DtxO: –3.0%, IQR –5.7% to –0.8%; placebo: –4.0%, IQR –8.5% to –0.5%; P<.001) after 6 months, without significant between-group differences (univariable generalized linear models: P=.34 and P=.17, respectively). Univariable regression analyses showed a significant association between adherence to app use and 6-month absolute weight loss (β=–.06, SE 0.02, P=.01) as well as percent weight loss (β=–.05, SE 0.01, P=.01). Adherent participants, defined as those with overall adherence at or above the 75th percentile of daily usage, included 35 individuals in the intervention group and 10 in the placebo group. In this subgroup, the estimated 6-month mean absolute weight change was –7.02 kg (95% CI –9.45 to –4.59) in the DTxO-adherent group and –3.50 kg (95% CI –7.01 to 0.01) in the placebo-adherent group (P=.02). The estimated 6-month mean percent change in weight was –6.31% (95% CI –8.86 to –3.76) in the DTxO-adherent group and –2.78% (95% CI –6.48 to 0.92) in the placebo-adherent group (P=.03). A significantly greater weight loss (P=.01 for study arm, either on absolute or percent change in weight from baseline) among adherent participants randomized to the DTxO app was also confirmed by analyses using mixed linear models for repeated measures. Conclusions: Although overall weight loss did not differ significantly between the DTxO and placebo groups, participants who used the DTxO app for at least 40% of the expected time achieved significantly greater weight loss. These results suggest that higher engagement with DTx can improve obesity outcomes. Further research should explore combining DTxO with pharmacological treatments or bariatric surgery. Trial Registration: ClinicalTrials.gov NCT05394779; https://clinicaltrials.gov/ct2/show/NCT05394779
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Multi-omics analyses inform mechanisms of immunotherapy response in pancreatic cancer

Front Immunol. 2025 Oct 2;16:1673098. doi: 10.3389/fimmu.2025.1673098. eCollection 2025.

ABSTRACT

INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) continues to exhibit resistance to immunotherapy. In this study, we evaluated the efficacy of combining immunotherapy with chemotherapy for the treatment of advanced pancreatic cancer. Additionally, we employed a multimodal analytical approach to elucidate the immune landscape and conduct transcriptomic profiling in PDAC.

METHODS: A retrospective analysis was conducted on the clinical data of 52 patients diagnosed with advanced PDAC who underwent a combined treatment regimen of immunotherapy and chemotherapy. The study evaluated the objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). To characterize the immune landscape in treatment-naive pancreatic ductal adenocarcinoma (PDAC) tumors and in the systemic circulation, flow cytometry, multiplex immunohistochemistry (mIHC), and whole transcriptome sequencing were employed.

RESULTS: The study reported an ORR of 32.7%, a DCR of 67.3%, and a 6-month PFS rate of 38.5%, with a median PFS of 5.5 months. Patients treated with a combination of immunotherapy and gemcitabine achieved the longest PFS. The first-line treatment cohort exhibited a significantly higher DCR (79.3% vs. 52.2%, P = 0.038) and a longer median PFS (6.6 vs. 3.5 months, P = 0.032) compared to the second-line treatment cohort. The efficacy of treatment varied depending on the drug combinations used. Flow cytometry analysis revealed a greater frequency of CD45- CD64+ cells in the peripheral blood of patients with progressive disease (PD) compared to those with a partial response (PR). Multiplex immunofluorescence (MIF) analysis indicated an increased intratumoral infiltration of CD8+ T cells and CD137+ CD8+ T cells in patients with PR. Whole transcriptome sequencing (WTSS) identified key genes involved in immune regulation, signal transduction, and digestive function. Hemopexin (HPX) and regulatory factor X-associated protein (RFXAP) were upregulated in PR patients and showed a positive correlation with survival, whereas Interleukin-6 (IL-6) expression was linked to poor prognosis.

CONCLUSIONS: These findings indicate that immunochemotherapy shows potential for the treatment of advanced PDAC. Our study elucidates the immune landscape associated with PDAC and provides critical insights for the identification of prospective therapeutic targets, which could guide the development of innovative combination immunotherapy strategies.

PMID:41112307 | PMC:PMC12528169 | DOI:10.3389/fimmu.2025.1673098

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STAT+: Duke data scientist launches startup to help hospitals adopt AI

Mark Sendak was getting tired of seeing the toil of so many colleagues go to waste.

At Duke University, he was part of a team of data scientists and engineers who built artificial intelligence tools to help make better health care decisions, and to more effectively treat patients with serious and life-threatening conditions. 

But even when one of their inventions appeared to help patients and generated positive results in scientific studies, it never gained uptake beyond Duke’s walls. Patients and doctors in other health systems didn’t get the opportunity to benefit.

Continue to STAT+ to read the full story…

© Courtesy Vega Health

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Pan-Cancer Analyses of Shared and Distinct Gene Expression in 17 Cancers: Rethinking Cancer Classification and Moving Beyond "One Drug, One Disease" Paradigm of Pharmaceutical Innovation

OMICS. 2025 Oct 17. doi: 10.1177/15578100251387873. Online ahead of print.

ABSTRACT

Cancer is a disease with heterogenous molecular signatures that ought to be unpacked to achieve the overarching aim of precision oncology. A pan-cancer omics approach provides a systems science framework to explore shared and distinct mechanisms across cancers. We report here pan-cancer analyses of gene expression data from 17 cancers, for example, adrenocortical cancer, lung cancer, kidney cancer, and colorectal cancer, and 26 tissue types, using public datasets to construct disease-specific transcriptional networks. Using the hypergeometric test, 1005 microRNAs (miRNAs), 314 transcription factors (TFs), and 332 receptors were identified as regulatory molecules interacting with differentially expressed genes. Kyoto Encyclopedia of Genes and Genomes pathway analysis was performed to explore their functional roles. Accordingly, we found miR-124-3p, miR-6799-5p, and miR-7106-5p as common miRNAs; Specificity Protein 1 (SP1), RELA Proto-Oncogene, NF-κB Subunit (RELA), and Nuclear Factor Kappa B Subunit 1 (NFKB1) as shared TFs; Cyclin-Dependent Kinase 2 (CDK2), Histone Deacetylase 1 (HDAC1), and ABL Proto-Oncogene 1, Non-Receptor Tyrosine Kinase (ABL1) as common receptors; and pathways in cancer, PI3K-Akt signaling, and p53 signaling as commonly enriched. Survival analysis in an independent dataset confirmed these findings: SP1 and NFKB1 were significant in 9 cancers, RELA in 6, whereas CDK2, HDAC1, and ABL1 were significant in 11, 10, and 10 cancers, respectively, out of the 17 cancers researched herein. In conclusion, these findings provide system-level insights on tumor heterogeneity and inform future cancer classification, for example, according to shared and distinct molecular signatures and development of therapies that might prove effective across several cancers. We underline that unpacking molecular signatures across multiple cancers also offers new prospects to move beyond the "One Drug, One Disease" paradigm of pharmaceutical innovation.

PMID:41111411 | DOI:10.1177/15578100251387873

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Alternatives to animal testing are the future — it’s time that journals, funders and scientists embrace them

Nature, Published online: 20 October 2025; doi:10.1038/d41586-025-03344-6

Biomedical research techniques that don’t involve the use of animals are gaining momentum, but those using innovative approaches still face resistance from some quarters.
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Circulating tumor DNA in Non-Viral head and neck squamous cell Carcinoma: A systematic review and Meta-Analysis

Oral Oncol. 2025 Nov;170:107760. doi: 10.1016/j.oraloncology.2025.107760. Epub 2025 Oct 17.

ABSTRACT

Non-viral head and neck squamous cell carcinoma (HNSCC) has poor survival and high recurrence rates. Circulating tumor DNA (ctDNA) is a promising biomarker for understanding tumor biology, assessing treatment response, and monitoring disease progression. While extensively studied in virally mediated HNSCC, its role in non-viral HNSCC remains underexplored. This systematic review and meta-analysis consolidates evidence on the diagnostic, prognostic, and therapeutic value of ctDNA in non-viral HNSCC. A systematic search across Medline, PubMed, Embase, and the Cochrane Library identified 1,915 records, of which 47 were included. Data extraction followed PRISMA guidelines, with overall survival (OS), progression-free survival (PFS), and recurrence-free survival (RFS), pooled as hazard ratios (HRs) with 95% confidence intervals (CIs) using a fixed-effect model. Among 3,574 patients, the most common tumor sites were the oral cavity (35 %) and oropharynx (22 %), with the majority presenting with stage IVA/IVB disease (29 %). Pre-treatment ctDNA detection rates ranged from 50 % to 100 % (median: 83 %), while post-treatment detection rates varied between 28 % and 100 % (median: 48 %). ctDNA detected recurrence in 80 % of patients, with a median lead time of 4.6 months. ctDNA detection was significantly associated with worse OS (HR 10.26, 95 % CI 3.58-29.40; P < 0.0001). Residual ctDNA was strongly correlated with worse PFS (HR 7.32, 95 % CI 4.17-12.86; P < 0.00001) and RFS (HR 7.33, 95 % CI 2.75-19.58; P < 0.0001). ctDNA holds potential for improving diagnostic accuracy, monitoring progression, and predicting survival outcomes in non-viral HNSCC. However, further large-scale studies and standardized guidelines are needed for validation and clinical implementation.

PMID:41108912 | DOI:10.1016/j.oraloncology.2025.107760

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Systematic benchmarking of high-throughput subcellular spatial transcriptomics platforms across human tumors

Nat Commun. 2025 Oct 17;16(1):9232. doi: 10.1038/s41467-025-64292-3.

ABSTRACT

Recent advancements in spatial transcriptomics technologies have significantly enhanced resolution and throughput, underscoring an urgent need for systematic benchmarking. Here, we generate serial tissue sections from colon adenocarcinoma, hepatocellular carcinoma, and ovarian cancer samples for systematic evaluation. Using these uniformly processed samples, we generate spatial transcriptomics data across four high-throughput platforms with subcellular resolution: Stereo-seq v1.3, Visium HD FFPE, CosMx 6K, and Xenium 5K. To establish ground truth datasets, we profile proteins on tissue sections adjacent to all platforms using CODEX and perform single-cell RNA sequencing on the same samples. Leveraging manual nuclear segmentation and detailed annotations, we systematically assess each platform's performance across capture sensitivity, specificity, diffusion control, cell segmentation, cell annotation, spatial clustering, and concordance with adjacent CODEX. The uniformly generated and processed multi-omics dataset could advance computational method development and biological discoveries. The dataset is accessible via SPATCH, a user-friendly web server for visualization and download.

PMID:41107232 | PMC:PMC12534522 | DOI:10.1038/s41467-025-64292-3

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R-loops in hepatocellular carcinoma: Bridging genomic instability and therapeutic opportunity (Review)

Mol Med Rep. 2026 Jan;33(1):6. doi: 10.3892/mmr.2025.13716. Epub 2025 Oct 17.

ABSTRACT

R‑loops, three‑stranded nucleic acid structures composed of an RNA:DNA hybrid and displaced single‑stranded DNA, have emerged as important regulators of gene expression and genome maintenance. Although physiological R‑loops participate in normal cellular processes, their dysregulation can threaten genomic integrity by inducing DNA damage and replication stress. The present review explores the role of R‑loops in hepatocellular carcinoma (HCC), a malignancy characterized by marked genomic instability. In the present review, the formation mechanisms of R‑loops, their dual functions in transcriptional regulation and DNA damage, and their specific implications for HCC pathophysiology were discussed. HCC cells exhibit altered R‑loop homeostasis with aberrant accumulation linked to hepatitis B virus infection, inflammatory signaling and oncogene activation. The present review highlighted how HCC cells exploit or manage R‑loops to promote tumor progression, particularly through the epigenetic silencing of differentiation genes and modulation of replication stress responses. Furthermore, emerging therapeutic strategies targeting R‑loop biology were examined, including small molecules that induce synthetic lethality, gene‑based interventions and combination approaches that exploit R‑loop vulnerabilities. Challenges in targeting R‑loops and future directions, including multi‑omics profiling and biomarker development, were also addressed. Understanding the complex interplay between R‑loops and HCC offers promising avenues for novel diagnostic and therapeutic approaches for this malignancy.

PMID:41104860 | DOI:10.3892/mmr.2025.13716

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When helpfulness backfires: LLMs and the risk of false medical information due to sycophantic behavior

npj Digital Medicine, Published online: 17 October 2025; doi:10.1038/s41746-025-02008-z

When helpfulness backfires: LLMs and the risk of false medical information due to sycophantic behavior
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Semi-automated surveillance of surgical site infections using machine learning and rule-based classification models

npj Digital Medicine, Published online: 17 October 2025; doi:10.1038/s41746-025-01989-1

Semi-automated surveillance of surgical site infections using machine learning and rule-based classification models
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Use of Artificial Intelligence-Assisted Conversational Agents to Improve Patient Experience Related to Physicians: Cross-Sectional Study in China

Background: Artificial intelligence-assisted conversational agents have been applied and developed in outpatient departments to improve health services in China. However, there has been little research that evaluates the effect of artificial intelligence-assisted conversational agents on the patient experience related to physicians during outpatient visits. Objective: This aim of this study was to examine whether the use of artificial intelligence-assisted conversational agents improves the patient experience related to physicians during outpatient visits and to further find out the difference in the patient experience between conversational agent users and nonusers. Methods: We used the Chinese Outpatient Experience Questionnaire to survey the patient experience related to physicians during outpatient visits. A sample of 392 adult residents who sought outpatient services from tertiary public hospitals in China was selected by random sampling. The t tests were used to test the mean difference in the patient experience scores between conversational agent users and nonusers. Multiple linear regression analysis was further performed to determine whether the use of artificial intelligence-assisted conversational agents during outpatient visits was associated with a better patient experience related to physicians. Results: Conversational agent user reported significantly higher scores than nonusers in the total patient experience scores (t392=5.589, P<.001 the items and dimensions of physician-patient communication p=".006)," health information short-term outcome general satisfaction multiple linear regression results further showed that after controlling for other factors on participant characteristics use artificial intelligence-assisted conversational agents during outpatient visits significantly influenced total patient experience scores related to physicians averagely increased by conclusions: could improve especially in terms making better accessing more targeted ameliorating outcomes increasing satisfaction. therefore we suggest public hospitals should consider benefits actively deploy departments so as continuously visits.>
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Codon specific readthrough as a mechanism of BRCA2 restoration in acquired PARP inhibitor and chemotherapy resistance

Nucleic Acids Res. 2025 Oct 14;53(19):gkaf990. doi: 10.1093/nar/gkaf990.

ABSTRACT

BRCA2 mutations contribute to the pathogenesis and treatment sensitivity of a subset of ovarian, breast, prostate, and pancreatic cancers. When these cancers become therapy resistant, secondary mutations that restore the BRCA2 open reading frame are found in half the cases, but other causes of resistance remain incompletely understood. Here, we identified translational readthrough of a premature termination codon (PTC) as a cause of resistance to poly(ADP-ribose) polymerase inhibitors (PARPis) and cisplatin in cells derived from the BRCA2-mutated ovarian cancer line PEO1 by PARPi selection. Despite persistence of the signature 4965C > G (p.Y1655X) BRCA2 mutation, low-level expression of full-length BRCA2 protein was detectable in these cells by immunoblotting and tandem mass spectrometry. Either BRCA2 knockdown or gene interruption 5' or 3' to the PTC restored treatment sensitivity, implicating BRCA2 in the resistance. Reporter assays demonstrated UAG-selective readthrough in the resistant clones but not parental cells. Moreover, custom searching of global proteomic data indicated readthrough of stop codons, particularly UAGs, in additional proteins in the resistant clones. Finally, multi-omic analysis identified multiple changes in the nonsense-mediated decay and termination machineries that favor readthrough. Accordingly, the present results identify PTC readthrough as a potential mechanism of drug resistance in cells with BRCA2 nonsense mutations.

PMID:41099700 | PMC:PMC12526053 | DOI:10.1093/nar/gkaf990

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