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PubMed2026

Engineered MXene-based nanozyme platform: NIR-II photothermal and dual enzyme-mimetic potentiated chemodynamic synergy for precision tumor eradication.

The antioxidant defense barrier in the tumor microenvironment, particularly glutathione (GSH), considerably restricts the therapeutic efficacy of chemodynamic therapy (CDT). Moreover, CDT generally exhibits relatively mild therapeutic efficacy owing to its intrinsic reaction kinetics, making it difficult to achieve complete tumor eradication within a short time. To address these issues, we construct a functionalized nanotherapeutic platform, Nb2CTx@Ru-PEG2000-FA (NCRPF), for tumor photothermal ablation and enhanced CDT resulting from GSH depletion. NCRPF possesses three key advantages: 1. Efficient near-infrared II photothermal conversion (η = 42.08%), raising the tumor temperature above 45 °C within 90 s for rapid ablation; 2. Dual peroxidase-like and glutathione peroxidase-like activities, simultaneously depleting GSH and generating a burst of ·OH to eliminate residual tumors; 3. Targeted tumor accumulation with 2.9-fold higher efficiency than passive diffusion. Both in vitro and in vivo results confirm that this combined strategy achieves complete tumor eradication with favorable biosafety. Collectively, the NCRPF nanotherapeutic system provides a powerful new paradigm with high translational potential for the complete eradication of breast cancer.

Animals↗

PubMed2025

Implementation of a Face-To-Face Vs Virtual Peer-Integrated Collaborative Care Intervention for Mental Health Treatment of Physical Trauma Survivors: A Qualitative Study of Lessons from the COVID-19 Pandemic.

OBJECTIVE: We assessed the impact of the COVID-19 pandemic on the implementation of a peer-integrated enhancement of integrated clinical care intervention to address the mental health needs of 450 patients undergoing treatment for a physical injury. METHODS: Qualitative data were collected by 7 clinician investigators of a randomized controlled trial acting as participant observers in a trauma care setting of a major U.S. metropolitan hospital and analyzed in collaboration with an external mixed methods specialist. RESULTS: The pandemic created or exacerbated several implementation barriers, including increased risk of infection, homelessness, hospitalizations and comorbid conditions such as fentanyl overdoses that increased demand on emergency department and Trauma Center services, imposition of safety measures to reduce risk of infection in clinical settings, transition from face-to-face to virtual interactions with study patients, shortages of specialty mental health providers, suspension of recruitment of patients into the study, scheduling calls with patients, and an increased workload for the study clinical interventionists. Peer specialists perceived the transition to virtual interactions with patients reduced their effectiveness; however, this was not reflected in assessments of patient satisfaction with services received and may have inadvertently increased adoption by Trauma Center staff. Reduction in reach of the intervention to target population was temporary. CONCLUSIONS: The COVID-19 pandemic exacerbated existing barriers and created new barriers to successfully implementing evidence-based practices in trauma care settings, resulting in an attenuation of their effectiveness. However, the shift from face-to-face to virtual services delivery may have actually led to improved implementation outcomes. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03569878. Registered June 15, 2018.

Humans↗

PubMed2026

Access Block and Ambulance Ramping: The Canaries of the Healthcare System.

OBJECTIVE: To identify evidence-based factors leading to the global challenge of hospital access block and inform strategies to improve emergency access performance. METHODS: A mixed methods approach was followed comprising an umbrella review of published systematic reviews, qualitative analysis of the perspectives of patients and healthcare workers, and quantitative analysis of contextual factors and 6 years of ambulance, emergency inpatient and ward movement records for the 25 largest public hospitals in Queensland, Australia. RESULTS: A key set of findings and recommendations were identified to improve emergency access that are practical and actionable. These comprise the introduction of inpatient discharge metrics and monitoring to shift focus from the front door of hospitals to the 'back door'; increasing support for primary care, community care, aged care, NDIS and vulnerable groups; maintaining demand-side strategies such as increasing inpatient-equivalent care alternatives (e.g., hospital in the home, acute care within nursing home services); investment in prehospital flow; improving hospital processes such as extended-hour discharge lounges; improving workforce; and revising funding policies. CONCLUSIONS: The study findings fill a gap in the evidence regarding challenges and recommendations for improving patient flow within hospital emergency departments and across the broader health system. Focussing efforts at the 'back end' of the inpatient journey is a critical step to improve emergency care outcomes.

Humans↗

PubMed2026

Effectiveness of Embedded Social Media Content on E-cigarette Attitudes and Behaviors: Results from a Randomized Control Trial.

BACKGROUND: This longitudinal randomized controlled trial examined the effects of anti-vaping social media content on e-cigarette attitudes and intentions among U.S. young adults (ages 18-24; n=3,400). METHODS: Targeted content was embedded directly into participants' social media feeds, with varying levels of impressions. RESULTS: Results indicate that increased exposure to anti-vaping messages significantly elevated perceived risk of harm (β=0.11, 95% CI: 0.03-0.20, p < .01) and social unacceptability of e-cigarette use (β=0.10, 95% CI: 0.03-0.18, p < .01), while decreasing intentions to vape (RRR = 0.59, 95% CI: 0.36-0.97, p < .05). Notably, these attitudinal shifts occurred even with relatively low ad exposure and over an extended intervention period, while controlling for the e-cigarette use status (never, former, or current) of participants. Discussion These findings support the effectiveness of digital media campaigns in influencing health-related behaviors and attitudes among young adults. Specifically, embedding anti e-cigarette content directly in the feed of young adults is shown to be effective in shifting attitudes in a space where these young adults are already engaged. Limitations include limited ad impressions and minimal change in ad awareness recall, suggesting future research should explore longer interventions and broader nicotine product messaging.

Humans↗

PubMed2026

Integration of ear and hearing care services in low- and middle-income health systems: a systematic review and qualitative synthesis.

Hearing loss is a global public health burden and mostly affects those living in low- and middle-income countries (LMICs). One approach to address ongoing challenges is the World Health Organization's recommendation for the integration of ear and hearing care (EHC) services into healthcare packages. However, little is known about EHC integration approaches, particularly in LMICs additionally, these approaches have not been investigated through a health systems lens. This qualitative review aimed to describe the various approaches to the EHC service integration in LMICs and to identify enabling and constraining factors. We reviewed 17 studies, with a focus on LMICs, using adaptations of the Valentijn integration and World Health Organization EHC frameworks, following the PRISMA guidelines. Our investigation showed that most integration approaches were at micro or individual level. Enabling factors for integration of EHC services were training, mentorship, collaboration, technology, inclusion of EHC in healthcare packages and investment in EHC services. Barriers were challenges with training, facilities and equipment, policy implementation and resourcing of EHC services. We further described factors influencing healthcare seeking behaviour and the use of integrated EHC services, such as access and ability to pay, referral systems and communication and awareness. This study describes the complex nature of EHC integration and ways to support integration. Key considerations are the level of integration, training to address workforce issues and factors influencing service utilisation as we work towards health system strengthening.

Humans↗

PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

PubMed2026

Probiotic-derived extracellular vesicles as food-based nanocarriers: Mechanisms, functional applications, and future perspectives in food systems.

Probiotic-derived extracellular vesicles (PDEVs) are a promising type of postbiotic nanoparticle derived by fermentation of probiotics, and have gained growing interest as a potential application in food science and nutrition. These are lipid bilayer vesicles of nanoscale, which are naturally released by probiotic cells and contain a wide variety of bioactive molecules, such as proteins, nucleic acids, and metabolites. Moreover, PDEVs are highly stable, biocompatible, and can be easily engineered to have surfaces with high functionality, which makes them good candidates in functional engineering. In contrast to traditional live probiotics, PDEVs overcome the difficulties of preserving microbial viability during processing and storage, thus providing superior safety, stability, and predictable biological performance. This is a systematic review of the various functions of PDEVs in food systems. We conclude on the processes through which PDEVs control intestinal barrier integrity, alter gut microbiota composition, and alter host immune responses, and their potential to enhance gut health when added to functional foods. In addition to their health-promoting effects, PDEVs have shown significant potential as natural antimicrobial agents to preserve food and as effective nanocarriers of hydrophobic bioactive compounds, including fucoxanthin, to improve their stability, bioavailability, and targeted delivery. Moreover, PDEVs can be used as new regulators of microbial fermentation. However, it should be noted that a lot of the evidence that is available is still preliminary and the effectiveness of these applications in real food-processing and storage conditions has not been fully proven. Although they have potential, there are a number of challenges that still hinder the widespread use of PDEVs in the food industry. These involve the creation of scalable and cost-effective production processes, batch-to-batch consistency, vesicle stability in a variety of food matrices, and regulatory and safety considerations. Other emerging engineering approaches, such as surface functionalization and cargo loading, are also discussed in this review and could further increase the specificity, functionality, and application versatility of PDEVs in food systems. Moving forward, the incorporation of PDEVs into the next generation functional foods, novel food preservation methods, and customized nutrition plans should be prioritized in future studies. Further developments in these fields can make PDEVs useful platforms at the interface of food microbiology, nanotechnology, and human health.

Probiotics↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗

PubMed2026

Patterns and implications of co-use between vaping and hallucinogens: a systematic review and meta-analysis.

BACKGROUND: The co-occurrence use of e-cigarettes and hallucinogens has become increasingly common, particularly among youth and young adults. However, evidence regarding the association between these behaviors remains limited and fragmented. This systematic review and meta-analysis aimed to synthesize current evidence, examining the correlation between hallucinogen use and the likelihood of being an e-cigarette user. METHODS: A comprehensive search was conducted in PubMed, Scopus, Web of Science, EMBASE, and Cochrane CENTRAL up to June 2025. Eligible studies measured both hallucinogen and e-cigarette use and reported quantitative associations between these behaviors. Data extraction and risk-of-bias assessments were performed independently by three reviewers using the Newcastle-Ottawa Scale. Pooled effect sizes were calculated using a random-effects model (REML). Certainty of evidence was evaluated with the GRADE approach. RESULTS: Eleven studies met the inclusion criteria (n = 247,904), and seven were included in the meta-analysis (n = 217,478). The pooled analysis demonstrated that hallucinogen users had 4.47 times higher odds of being e-cigarette users (OR: 4.47, 95% CI 2.72 to 7.34; p < 0.001; I2 = 95.7%, n = 7). The certainty of evidence was rated as low. CONCLUSIONS: Hallucinogen use is directionally and strongly associated with e-cigarette use across diverse populations. Although the direction of association was consistent across studies, the magnitude of effect was heterogeneous. These behaviors likely share psychosocial and environmental determinants, although alternative explanations, including shared genetic liability, recall bias, and residual confounding, cannot be excluded. Further longitudinal studies are needed to clarify the underlying mechanisms of this association and establish temporality. The findings also support integrating hallucinogen-use screening into e-cigarette prevention and harm-reduction programs targeting youth and young adults.

Humans↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans↗

PubMed2026

Ten-Year Update of Nurse Practitioner Service Impact on Patient and Health Service Outcomes in Emergency Care Settings-A Systematic Review.

AIMS: To provide a 10-year update on the best available evidence evaluating the impact of nurse practitioner services on cost, waiting times, patient satisfaction, representation rates, and length of stay in emergency and urgent care settings. DESIGN: Systematic review. DATA SOURCES: The search was completed on January 28, 2025, in Embase (Elsevier), Medline (EBSCOhost), CINAHL (EBSCOhost), Cochrane Library (Wiley), Emcare (Ovid), Web of Science Core Collection (Clarivate) and Scopus (Elsevier). The data range (2014-2024) was used to limit the search. METHODS: The search was conducted with results imported into Covidence. In Covidence, two reviewers conducted screening, data extraction, and quality appraisal of articles, and findings were analysed using a narrative synthesis approach. Eligible studies examined nurse practitioner services in emergency or urgent care settings, reporting outcomes of cost, waiting times, patient satisfaction, representation rates, and length of stay. RESULTS: Title and abstract screening were performed on 2329 records. Of these, 236 full-text articles were reviewed, and 17 underwent critical appraisal and data extraction. Narrative analysis of outcome measures yielded mixed results, with both favourable and unfavourable findings reported regarding nurse practitioner services. CONCLUSIONS: Global evaluation of nurse practitioner services in emergency care remains inconsistent. Nevertheless, emerging evidence supports their positive impact, particularly in improving patient outcomes. To effectively inform policy, workforce planning and clinical integration, there is a need for professional benchmarks that provide clear frameworks for the evaluation of patient-centred outcomes and operational impacts in emergency departments. IMPLICATIONS: Evidence related to nurse practitioner services in emergency and urgent care clinics highlights the positive impact of nurse practitioner services on patient wait times and satisfaction; however, there is limited and variable evidence of impact on health care costs and outcomes. IMPACT: This paper recommends that evaluating emergency nurse practitioner services requires homogeneous research using consistent professional benchmarks and evaluation frameworks. REPORTING METHOD: This systematic review follows the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. PATIENT OR PUBLIC CONTRIBUTION: This study did not include patient or public involvement in its design, conduct, or reporting. TRAIL REGISTRATION: PROSPERO 2025 CRD420250645148.

Humans↗

PubMed2026

"It was good because they have a relationship with us": A qualitative study on low-threshold buprenorphine treatment at syringe services programs.

INTRODUCTION: Syringe service programs (SSPs) reach people who inject drugs with opioid use disorder (OUD) and are novel "low-threshold" venues to initiate buprenorphine treatment. The study investigated patients' experiences with SSP-initiated buprenorphine treatment, which could aid in improving buprenorphine treatment delivery at SSPs. METHODS: The study included 12 participants who completed qualitative exit interviews after a randomized controlled trial of buprenorphine treatment at SSPs. In the parent study, participants received buprenorphine treatment through an onsite model at an SSP or enhanced referral to a community health center based on the randomization sequence. Most participants started taking buprenorphine at home. Exit interviews included participants from both study arms, and the semi-structured interview guide focused on their experiences with clinicians, experiences initiating buprenorphine, prior experiences with OUD treatment, and perceptions about continuing buprenorphine treatment. Four researchers iteratively read, coded, and discussed each transcript, then they derived recurring themes using thematic analysis. RESULTS: Participants were mostly male, middle-aged, and 50% identified as Latino. Four main themes related to buprenorphine treatment initiation: 1) Onsite treatment facilitated buprenorphine prescription, but some participants also expressed a need for additional support; 2) Precipitated withdrawal complicated participants' buprenorphine initiation in both arms; 3) Participants largely experienced the SSPs as affirming and welcoming; and 4) Developing strong relationships with healthcare providers was critical to successful buprenorphine treatment initiation. CONCLUSIONS: The SSP-based model provided rapid access to buprenorphine prescriptions, but precipitated withdrawal was a common complication. Some participants desired additional support and guidance when they started taking buprenorphine at home. The findings point to a "low-threshold, high-touch" approach where participants receive expedited access to buprenorphine providers at SSPs but also additional support throughout the initiation process to avoid and/or manage precipitated withdrawal. Despite some challenges, SSP-based buprenorphine treatment was highly valued by study participants.

Humans↗

PubMed2025

Improving Community-Based Care for Adolescents with ADHD: a Randomized Controlled Trial of Artificial Intelligence-Assisted Fidelity Supports.

Cognitive-behavioral treatments (CBTs) for adolescents with ADHD demonstrate promise of long-term effects on outcome. However, their implementation in routine care community clinics faces barriers that impact quantity, efficiency, and quality of delivery, as well as client outcomes. This study is a randomized controlled trial designed to evaluate the impact of an AI-assisted service delivery model on therapist implementation of Supporting Teens' Autonomy Daily (STAND), a CBT blended with Motivational Interviewing (MI) for adolescents with ADHD. Adolescents with ADHD (N = 51), who were clients at three community mental health agencies, received treatment from 23 therapists. There was randomization of adolescents and therapists to AI-assisted or standard implementation supports. In addition to standard supports (i.e., training, standard facilitation resources, technical assistance, case supervision), AI-assisted support package included digitized facilitation resources housed in a clinical dashboard (Care4), feedback on content fidelity, and AI-generated feedback on MI implementation quality. The AI-assisted group was associated with more efficient treatment delivery and lower number of appointments attended by the adolescent. There was also a significant decrement in MI quality over time in the AI-assisted group compared to the standard support group. Feedback in focus groups indicated that therapists perceived a task-oriented mindset to be associated with receipt of the AI-assisted support package, leading therapists to prioritize efficiency over relational aspects of therapy. Following the results of this trial, a future, larger RCT should examine the impact of the AI-assisted implementation model on mental health outcomes and cost savings to organizations, third party payers, and clients. Trial registration number: NCT05135065; https://www.clinicaltrials.gov ; Registered September 2021.

Humans↗

PubMed2026

Morbidity and mortality from local anesthetics: localized and systemic toxicity.

PURPOSE OF THE REVIEW: Local anesthetics remain vital to modern medicine, yet their narrow therapeutic window continues to result in complications. This review synthesizes recent literature to define the current landscape of local anesthetic-associated adverse events. RECENT FINDINGS: Perioperative mortality attributable to local anesthetics persists despite sustained safety initiatives and professional society recommendations. Pharmacovigilance and case data identify lidocaine (oropharyngeal, topical, and via local infiltration) as the predominant contributor to adverse outcomes, including death. Local anesthetic systemic toxicity remains an issue, with a recent shift in epidemiology: an increasing proportion of toxic events originates from surgeon- and proceduralist-administered analgesia. Anesthesiologist-controlled methods also cause toxicity via catheter-based delivery and nerve blocks in highly vascular regions. Localized toxicity in the form of high neuraxial contributes to morbidity, with recent reviews reinforcing known risk factors; whereas localized neurotoxicity appears less troublesome when managed appropriately. SUMMARY: The cumulative evidence identifies shifts in the patterns of systemic and localized toxicities. Bupivacaine-based peripheral nerve blocks no longer represent the principal cause of complications because of the advent of ultrasound guidance and lipid emulsion therapy. In contrast, high neuraxial techniques persist as a cause of morbidity, accompanied by intravenous/oropharyngeal lidocaine, proceduralist-administered local infiltration analgesia, and catheter-based delivery.

Humans↗

PubMed2026

Beyond Glycaemia: Fear of Hypoglycaemia, Cognition and Functional Mobility After Advanced Hybrid Closed-Loop Therapy in Older Adults With Type 1 Diabetes: A Prespecified Secondary Analysis of a Randomised, Single-Centre Study.

BACKGROUND: Evidence on psychological, cognitive and functional outcomes of advanced diabetes technologies in older adults with long-standing type 1 diabetes (T1D) remains limited. We evaluated whether initiation of advanced hybrid closed-loop (AHCL) therapy was associated with changes in fear of hypoglycaemia, diabetes distress, psychological well-being, cognition, frailty-related measures and mobility-related function in adults aged ≥ 65 years with T1D. METHODS: This prespecified, exploratory secondary analysis was conducted within a single-centre, open-label, randomised, controlled, parallel-group trial including adults aged ≥ 65 years with long-standing T1D. Participants were randomly assigned (1:1) to initiate AHCL therapy using the MiniMed 780G system or to continue standard diabetes treatment. The secondary outcomes included WHO-5, the 17-item Diabetes Distress Scale (DDS), Hypoglycemia Fear Survey-II (HFS-II), Montreal Cognitive Assessment, Digit Symbol Substitution Test, Fried frailty phenotype and performance-based functional measures. No formal sample-size calculation was performed for these secondary outcomes. RESULTS: Thirty-one participants were randomised and 29 completed 12 months of follow-up and were included in the treatment-effect analyses. In the baseline-adjusted primary analysis, AHCL therapy was associated with a lower HFS-II score than standard treatment (adjusted mean difference -18.9; 95% CI: -32.4 to -5.4; nominal p = 0.008), although this finding did not remain statistically significant after Holm correction (adjusted p = 0.104) or in an exploratory model additionally adjusted for sex (difference -13.6; 95% CI: -32.2 to 5.0; p = 0.145). Diabetes distress, psychological well-being, global cognition and processing speed did not differ between groups. In sex-adjusted sensitivity analyses, the between-group differences remained statistically significant for 6-min walk distance (92.6 m; 95% CI: 36.8 to 148.3; p = 0.002) and Timed Up and Go performance (-2.27 s; 95% CI: -4.28 to -0.27; p = 0.028), but not for gait speed (0.27 m/s; 95% CI: -0.05 to 0.59; p = 0.099). At 12 months, 12 of 14 AHCL participants were robust and 2 were pre-frail; in the control group, 11 of 15 were robust and 4 were pre-frail. No participant was classified as frail at follow-up. CONCLUSIONS: In this small, selected cohort, AHCL therapy was associated with a nominally lower fear-of-hypoglycaemia score and better performance on selected mobility-related tests over 12 months. The fear-of-hypoglycaemia finding did not remain statistically significant after correction for multiple comparisons or additional adjustment for sex. Six-minute walk distance and Timed Up and Go remained statistically significant in the exploratory sex-adjusted sensitivity analyses, whereas the gait-speed difference did not. No measurable between-group deterioration in global cognition or processing speed was observed. These exploratory findings require confirmation in larger studies with balanced representation by sex and direct measurement of physical activity. These findings also support a person-centred clinical message: older age alone should not be regarded as a barrier to AHCL when treatment is introduced with individualised education and appropriate ongoing support.

Humans↗

PubMed2026

Surveilled subjectivation: narratives of drug policing among people who use prohibited drugs in Sweden.

In Sweden, possession and personal use of drugs are criminalized since 1988, resulting in police work being directed towards minor drug offenses. Despite this, police and other authorities are encouraged to protect the health and wellbeing of people who use prohibited drugs (PWUPD). Knowledge is scarce on how this drug policy plays out in practice. This study therefore analyzes interviews with 20 PWUPD who visited harm reduction services and interacted with policing agents in Stockholm, Sweden. The analysis is based on the participants' narratives of drug policing, and it concerns how they produced themselves as subjects through relations between materiality and discourse. We utilize the concept of surveilled subjectivation to elucidate what the participants could do, what they knew and who they could be or become under drug policing. Four themes were identified illustrating the link between discourse and materiality in PWUPD's surveilled subjectivation: "Material aspects of surveillance"; "Resisting the 'drug abuser' identity"; "Fighting power with power"; and "Crossing boundaries and becoming-other". The participants described nonstop efforts to prevent their bodies, activities, belongings and environments from being enfolded by drug law enforcement, which otherwise would fuel even more surveillance. They therefore disassociated themselves from the "drug abuser" identity, and managed encounters with policing agents by keeping a low profile or acting compliantly. While the study highlights the skills and knowledges the participants deployed to navigate omnipresent drug policing, we conclude that their production of autonomous and empowered subjectivities would be facilitated if possession and use of drugs were no longer criminalized.

Humans↗

PubMed2026

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans↗