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PURPOSE OF REVIEW: A critical evaluation of contemporary literature regarding the role of big data, artificial intelligence, and digital technologies in precision cardio-oncology care and survivorship, emphasizing innovative and groundbreaking endeavors. RECENT FINDINGS: Artificial intelligence (AI) algorithm models can automate the risk assessment process and augment current subjective clinical decision tools. AI, particularly machine learning (ML), can identify medically significant patterns in large data sets. Machine learning in cardio-oncology care has great potential in screening, diagnosis, monitoring, and managing cancer therapy-related cardiovascular complications. To this end, large-scale imaging data and clinical information are being leveraged in training efficient AI algorithms that may lead to effective clinical tools for caring for this vulnerable population. Telemedicine may benefit cardio-oncology patients by enhancing healthcare delivery through lowering costs, improving quality, and personalizing care. Similarly, the utilization of wearable biosensors and mobile health technology for remote monitoring holds the potential to improve cardio-oncology outcomes through early intervention and deeper clinical insight. Investigations are ongoing regarding the application of digital health tools such as telemedicine and remote monitoring devices in enhancing the functional status and recovery of cancer patients, particularly those with limited access to centralized services, by increasing physical activity levels and providing access to rehabilitation services. SUMMARY: In recent years, advances in cancer survival have increased the prevalence of patients experiencing cancer therapy-related cardiovascular complications. Traditional cardio-oncology risk categorization largely relies on basic clinical features and physician assessment, necessitating advancements in machine learning to create objective prediction models using diverse data sources. Healthcare disparities may be perpetuated through AI algorithms in digital health technologies. In turn, this may have a detrimental effect on minority populations by limiting resource allocation. Several AI-powered innovative health tools could be leveraged to bridge the digital divide and improve access to equitable care.
- Publikační typ
- časopisecké články MeSH
Alexander disease (AxD) is a rare and severe neurodegenerative disorder caused by mutations in glial fibrillary acidic protein (GFAP). While the exact disease mechanism remains unknown, previous studies suggest that mutant GFAP influences many cellular processes, including cytoskeleton stability, mechanosensing, metabolism, and proteasome function. While most studies have primarily focused on GFAP-expressing astrocytes, GFAP is also expressed by radial glia and neural progenitor cells, prompting questions about the impact of GFAP mutations on central nervous system (CNS) development. In this study, we observed impaired differentiation of astrocytes and neurons in co-cultures of astrocytes and neurons, as well as in neural organoids, both generated from AxD patient-derived induced pluripotent stem (iPS) cells with a GFAPR239C mutation. Leveraging single-cell RNA sequencing (scRNA-seq), we identified distinct cell populations and transcriptomic differences between the mutant GFAP cultures and a corrected isogenic control. These findings were supported by results obtained with immunocytochemistry and proteomics. In co-cultures, the GFAPR239C mutation resulted in an increased abundance of immature cells, while in unguided neural organoids and cortical organoids, we observed altered lineage commitment and reduced abundance of astrocytes. Gene expression analysis revealed increased stress susceptibility, cytoskeletal abnormalities, and altered extracellular matrix and cell-cell communication patterns in the AxD cultures, which also exhibited higher cell death after stress. Overall, our results point to altered cell differentiation in AxD patient-derived iPS-cell models, opening new avenues for AxD research.
- MeSH
- Alexanderova nemoc * genetika patologie metabolismus MeSH
- astrocyty * metabolismus patologie MeSH
- buněčná diferenciace * fyziologie MeSH
- gliový fibrilární kyselý protein * metabolismus genetika MeSH
- indukované pluripotentní kmenové buňky * metabolismus MeSH
- kokultivační techniky MeSH
- kultivované buňky MeSH
- lidé MeSH
- mutace MeSH
- nervové kmenové buňky metabolismus MeSH
- neurony metabolismus patologie MeSH
- organoidy metabolismus patologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Optimal management of outpatients with heart failure (HF) requires serially updating the estimates of their risk for adverse clinical outcomes to guide treatment. Patient-reported outcomes (PROs) are becoming increasingly used in clinical care. The purpose of this study was to determine whether the inclusion of PROs can improve the risk prediction for HF hospitalization and death in ambulatory patients with HF. METHODS AND RESULTS: We included consecutive patients with HF with reduced ejection fraction (HFrEF) and HF with preserved EF (HFpEF) seen in a HF clinic between 2015 and 2019 who completed PROs as part of routine care. Cox regression with a least absolute shrinkage and selection operator regularization and gradient boosting machine analyses were used to estimate risk for a combined outcome of HF hospitalization, heart transplant, left ventricular assist device implantation, or death. The performance of the prediction models was evaluated with the time-dependent concordance index (Cτ). Among 1165 patients with HFrEF (mean age 59.1 ± 16.1, 68% male), the median follow-up was 487 days. Among 456 patients with HFpEF (mean age 64.2 ± 16.0 years, 55% male) the median follow-up was 494 days. Gradient boosting regression that included PROs had the best prediction performance - Cτ 0.73 for patients with HFrEF and 0.74 in patients with HFpEF, and showed very good stratification of risk by time to event analysis by quintile of risk. The Kansas City Cardiomyopathy Questionnaire overall summary score, visual analogue scale and Patient Reported Outcomes Measurement Information System dimensions of satisfaction with social roles and physical function had high variable importance measure in the models. CONCLUSIONS: PROs improve risk prediction in both HFrEF and HFpEF, independent of traditional clinical factors. Routine assessment of PROs and leveraging the comprehensive data in the electronic health record in routine clinical care could help more accurately assess risk and support the intensification of treatment in patients with HF.
- MeSH
- hodnocení rizik metody MeSH
- hodnocení výsledků péče pacientem * MeSH
- hospitalizace statistika a číselné údaje MeSH
- kvalita života * psychologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- následné studie MeSH
- retrospektivní studie MeSH
- senioři MeSH
- srdeční selhání * patofyziologie psychologie terapie diagnóza mortalita MeSH
- tepový objem fyziologie MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
The honeybee (Apis mellifera) is a key pollinator critical to global agriculture, facing threats from various stressors, including the ectoparasitic Varroa mite (Varroa destructor). Previous studies have identified shared bacteria between Varroa mites and honeybees, yet it remains unclear if these bacteria assemble similarly in both species. This study builds on existing knowledge by investigating co-occurrence patterns in the microbiomes of both Varroa mites and honeybees, shedding light on potential interactions. Leveraging 16S rRNA datasets, we conducted co-occurrence network analyses, explored Core Association Networks (CAN) and assess network robustness. Comparative network analyses revealed structural differences between honeybee and mite microbiomes, along with shared core features and microbial motifs. The mite network exhibited lower robustness, suggesting less resistance to taxa extension compared to honeybees. Furthermore, analyses of predicted functional profiling and taxa contribution revealed that common central pathways in the metabolic networks have different taxa contributing to Varroa mites and honeybee microbiomes. The results show that while both microbial systems exhibit functional redundancy, in which different taxa contribute to the functional stability and resilience of the ecosystem, there is evidence for niche specialization resulting in unique contributions to specific pathways in each part of this host-parasite system. The specificity of taxa contribution to key pathways offers targeted approaches to Varroa microbiome management and preserving honeybee microbiome. Our findings provide valuable insights into microbial interactions, aiding farmers and beekeepers in maintaining healthy and resilient bee colonies amid increasing Varroa mite infestations.
- MeSH
- Bacteria * klasifikace genetika izolace a purifikace MeSH
- mikrobiota * MeSH
- RNA ribozomální 16S genetika MeSH
- Varroidae * mikrobiologie MeSH
- včely mikrobiologie parazitologie MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Type 2 diabetes and prediabetes represent significant global health challenges, with physical activity (PA) being essential for disease management and prevention. Despite the well-documented benefits, many individuals with (pre)diabetes remain insufficiently active. General practitioners (GP) provide an accessible platform for delivering interventions; however, integrating PA interventions into routine care is hindered by resource constraints. OBJECTIVES: The ENERGISED trial aims to address these barriers through an innovative GP-initiated mHealth intervention combining wearable technology and just-in-time adaptive interventions. METHODS: The ENERGISED trial is a pragmatic, 12-month, multicentre, randomised controlled trial, assessing a GP-initiated mHealth intervention to increase PA and reduce sedentary behaviour in patients with type 2 diabetes and prediabetes. The primary outcome is daily step count, assessed via wrist-worn accelerometry. The primary analysis follows the intention-to-treat principle, using mixed models for repeated measures. Missing data will be handled under the missing-at-random assumption, with sensitivity analyses exploring robustness through reference-based multiple imputation. The trial incorporates the estimand framework to provide transparent and structured treatment effect estimation. DISCUSSION: This statistical analysis plan outlines a robust approach to addressing participant non-adherence, protocol violations, and missing data. By adopting the estimand framework and pre-specified sensitivity analyses, the plan ensures methodological rigour while enhancing the interpretability and applicability of results. CONCLUSIONS: The ENERGISED trial leverages innovative mHealth strategies within primary care to promote PA in individuals with (pre)diabetes. The pre-specified statistical framework provides a comprehensive guide for analysing trial data and contributes to advancing best practices in behavioural intervention trials for public health. TRIAL REGISTRATION: ClinicalTrials.gov NCT05351359 . Registered on April 28, 2022.
- MeSH
- akcelerometrie MeSH
- cvičení * MeSH
- diabetes mellitus 2. typu * terapie psychologie diagnóza MeSH
- fitness náramky MeSH
- lidé MeSH
- multicentrické studie jako téma MeSH
- nositelná elektronika MeSH
- pragmatické klinické studie jako téma MeSH
- praktické lékařství * metody MeSH
- prediabetes * terapie psychologie diagnóza MeSH
- sedavý životní styl * MeSH
- telemedicína * statistika a číselné údaje MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- protokol klinické studie MeSH
T-cell engagers represent a transformative approach to cancer immunotherapy leveraging bispecific and multispecific antibody constructs to redirect T-cell cytotoxicity toward malignant cells. These molecules bridge T cells and tumor cells by simultaneously binding CD3 on T cells and tumor-associated antigens on cancer cells, thereby enabling precise immune targeting even in immunologically "cold" tumors. Recent advancements include conditional T-cell engagers activated by tumor microenvironment proteases to minimize off-tumor toxicity as well as T-cell receptor-based engagers targeting intracellular antigens via MHC presentation. Clinical successes, such as Kimmtrak in metastatic uveal melanoma, underscore good potential of these modalities, while challenges persist in the management of cytokine release syndrome, neurotoxicity, and tumor resistance. Emerging multispecific engagers are aimed at enhancing efficacy via incorporation of costimulatory signals, thus offering a promising trajectory for next-generation immunotherapies. T-cell engagers are also gaining attention in the treatment of autoimmune disorders, where they can be designed to selectively modulate pathogenic immune responses. By targeting autoreactive T or B cells, T-cell engagers hold promise for restoring immune tolerance in such conditions as HLA-B*27-associated autoimmunity subtypes, multiple sclerosis, rheumatoid arthritis, and type 1 diabetes mellitus. Engineering strategies that incorporate inhibitory receptors or tissue-specific antigens may further refine T-cell engagers' therapeutic potential in autoimmunity, by minimizing systemic immunosuppression while preserving immune homeostasis.
- MeSH
- imunoterapie * metody MeSH
- lidé MeSH
- nádorové mikroprostředí imunologie MeSH
- nádory * imunologie terapie MeSH
- protilátky bispecifické terapeutické užití imunologie MeSH
- receptory antigenů T-buněk imunologie metabolismus MeSH
- T-lymfocyty * imunologie metabolismus MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
Uroteliální karcinom patří v raných stadiích k nejčastějším nádorovým onemocněním, onkolog se však častěji setkává s pacienty s pokročilým onemocněním. Právě metastatický uroteliální karcinom zůstává velkou terapeutickou výzvou. Tradiční léčba byla a stále je postavena na chemoterapii obsahující platinový derivát, avšak za poslední roky i tato diagnóza prošla velkým vývojem a do léčby přibyly nové léky ze skupiny moderní imunoterapie. Zcela zásadní zlom pak přinesly kombinované režimy imunoterapie s konjugovanými protilátkami, kdy kombinace pembrolizumabu s enfortumab vedotinem přepsala doporučené postupy léčby uroteliálního karcinomu v první linii. Právě kombinovaná terapie se stane budoucností managementu uroteliálního karcinomu, tak jako je to patrné i u jiných nádorových onemocnění.
Muscle-invasive bladder cancer (MIBC) is an aggressive malignancy with a high risk of metastases and recurrence. The standard treatment involves neoadjuvant cisplatin-based chemotherapy followed by radical cystectomy, yet approximately 50 % of patients relapse within three years. Neoadjuvant chemotherapy improves overall survival (OS) and pathological complete response (pCR). Emerging treatment strategies include neoadjuvant immunotherapy, with phase II trials demonstrating increased pCR rates with pembrolizumab and atezolizumab. The recently published NIAGARA trial established that perioperative durvalumab combined with chemotherapy reduces disease progression risk by 32 % (HR = 0.68) and mortality risk by 25 % (HR = 0.75). This supports perioperative immunotherapy as the new standard of care. Ongoing studies focus on combining ADCs and ICIs and leveraging ctDNA to refine patient selection. These advancements drive personalized oncology and optimize neoadjuvant therapy.
- MeSH
- cirkulující nádorová DNA MeSH
- imunoterapie metody MeSH
- lidé MeSH
- nádory močového měchýře * farmakoterapie MeSH
- neoadjuvantní terapie MeSH
- peroperační péče MeSH
- protokoly protinádorové kombinované chemoterapie MeSH
- randomizované kontrolované studie jako téma MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
INTRODUCTION: The provision of optimal care for older adults with complex chronic conditions (CCCs) poses significant challenges due to the interplay of multiple medical, pharmacological, functional and psychosocial factors. To address these challenges, the I-CARE4OLD project, funded by the EU-Horizon 2020 programme, developed an advanced clinical decision support tool-the iCARE tool-leveraging large longitudinal data from millions of home care and nursing home recipients across eight countries. The tool uses machine learning techniques applied to data from interRAI assessments, enriched with registry data, to predict health trajectories and evaluate pharmacological and non-pharmacological interventions. This study aims to pilot the iCARE tool and assess its feasibility, usability and impact on clinical decision-making among healthcare professionals. METHODS AND ANALYSIS: A minimum of 20 participants from each of the seven countries (Italy, Belgium, the Netherlands, Poland, Finland, Czechia and the USA) participated in the study. Participants were general practitioners, geriatricians and other medical specialists, nurses, physiotherapists and other healthcare providers involved in the care of older adults with CCC. The study design involved pre-surveys and post-surveys, tool testing with hypothetical patient cases and evaluations of predictions and treatment recommendations. Two pilot modalities-decision loop and non-decision loop-were implemented to assess the effect of the iCARE tool on clinical decisions. Descriptive statistics and bivariate and multivariate analysis will be conducted. All notes and text field data will be translated into English, and a thematic analysis will be performed. The pilot testing started in September 2024, and data collection ended in January 2025. At the time this protocol was submitted for publication, data collection was complete but data analysis had not yet begun. ETHICS AND DISSEMINATION: Ethical approvals were granted in each participating country before the start of the pilot. All participants gave informed consent to participate in the study. The results of the study will be published in peer-reviewed journals and disseminated during national and international scientific and professional conferences and meetings. Stakeholders will also be informed via the project website and social media, and through targeted methods such as webinars, factsheets and (feedback) workshops. The I-CARE4OLD consortium will strive to publish as much as possible open access, including analytical scripts. Databases will not become publicly available, but the data sets used and/or analysed as part of the project can be made available on reasonable request and with the permission of the I-CARE4OLD consortium.
BACKGROUND: The combination of ibrutinib and venetoclax leverages complementary mechanisms of action and has shown promising clinical activity in mantle cell lymphoma (MCL). This study evaluated the efficacy and safety of ibrutinib-venetoclax compared with ibrutinib-placebo in patients with relapsed or refractory MCL. METHODS: SYMPATICO is a multicentre, randomised, double-blind, placebo-controlled, phase 3 study performed at 84 hospitals in Europe, North America, and Asia-Pacific. Eligible patients were adults (aged ≥18 years) with pathologically confirmed relapsed or refractory MCL after one to five previous lines of therapy and an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2. Patients were randomly assigned (1:1) to receive oral ibrutinib 560 mg once daily concurrently with oral venetoclax (5-week ramp-up to 400 mg once daily) or placebo for 2 years, then single-agent ibrutinib 560 mg once daily until disease progression or unacceptable toxicity. Randomisation and treatment assignment occurred via interactive response technology using a stratified permuted block scheme (block sizes of 2 and 4) with stratification by ECOG performance status, previous lines of therapy, and tumour lysis syndrome risk category. Patients and investigators were masked to treatment assignment. The primary endpoint was investigator-assessed progression-free survival in the intention-to-treat population. Safety was assessed in all patients who received at least one dose of study treatment. This study is registered with ClinicalTrials.gov, NCT03112174, and is closed to enrolment. FINDINGS: Between April 26, 2018, and Aug 28, 2019, 267 patients were enrolled and randomly assigned; 134 to the ibrutinib-venetoclax group and 133 to the ibrutinib-placebo group. 211 (79%) of 267 patients were male and 56 (21%) were female. With a median follow-up of 51·2 months (IQR 48·2-55·3), median progression-free survival was 31·9 months (95% CI 22·8-47·0) in the ibrutinib-venetoclax group and 22·1 months (16·5-29·5) in the ibrutinib-placebo group (hazard ratio 0·65 [95% CI 0·47-0·88]; p=0·0052). The most common grade 3-4 adverse events were neutropenia (42 [31%] of 134 patients in the ibrutinib-venetoclax group vs 14 [11%] of 132 patients in the ibrutinib-placebo group), thrombocytopenia (17 [13%] vs ten [8%]), and pneumonia (16 [12%] vs 14 [11%]). Serious adverse events occurred in 81 (60%) of 134 patients in the ibrutinib-venetoclax group and in 79 (60%) of 132 patients in the ibrutinib-placebo group. Treatment-related deaths occurred in three (2%) of 134 patients in the ibrutinib-venetoclax group (n=1 COVID-19 infection, n=1 cardiac arrest, and n=1 respiratory failure) and in two (2%) of 132 patients in the ibrutinib-placebo group (n=1 cardiac failure and n=1 COVID-19-related pneumonia). INTERPRETATION: The combination of ibrutinib-venetoclax significantly improved progression-free survival compared with ibrutinib-placebo in patients with relapsed or refractory MCL. The safety profile was consistent with known safety profiles of the individual drugs. These findings suggest a positive benefit-risk profile for ibrutinib-venetoclax treatment. FUNDING: Pharmacyclics (an AbbVie Company) and Janssen Research and Development.
- MeSH
- adenin * analogy a deriváty MeSH
- bicyklické sloučeniny heterocyklické * aplikace a dávkování terapeutické užití škodlivé účinky MeSH
- doba přežití bez progrese choroby MeSH
- dospělí MeSH
- dvojitá slepá metoda MeSH
- lidé středního věku MeSH
- lidé MeSH
- lokální recidiva nádoru farmakoterapie patologie MeSH
- lymfom z plášťových buněk * farmakoterapie patologie mortalita MeSH
- piperidiny * aplikace a dávkování MeSH
- protokoly protinádorové kombinované chemoterapie * terapeutické užití škodlivé účinky MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- sulfonamidy * aplikace a dávkování terapeutické užití škodlivé účinky MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- klinické zkoušky, fáze III MeSH
- multicentrická studie MeSH
- randomizované kontrolované studie MeSH
Respiratory viruses represent a significant public health threat. There is the need for robust and coordinated surveillance to guide global health responses. Established in 2012, the Global Influenza Hospital Surveillance Network (GIHSN) addresses this need by collecting clinical and virological data on persons with acute respiratory illnesses across a network of hospitals worldwide. GIHSN utilizes a standardized patient enrolment and data collection protocol across its study sites. It leverages pre-existing national infrastructures and expert collaborations to facilitate comprehensive data collection. This includes demographic, clinical, epidemiological, and virologic data, and whole genome sequencing (WGS) for a subset of viruses. Sequencing data are shared in the Global Initiative on Sharing All Influenza Data (GISAID). GIHSN uses financing and governance approaches centered around public-private partnerships. Over time, GIHSN has included more than 100 hospitals across 27 countries and enrolled more than 168,000 hospitalized patients, identifying 27,562 cases of influenza and 44,629 of other respiratory viruses. GIHSN has expanded beyond influenza to include other respiratory viruses, particularly since the COVID-19 pandemic. In November 2023, GIHSN strengthened its global impact through a memorandum of understanding with the World Health Organization, aimed at enhancing collaborative efforts and data sharing for improved health responses. GIHSN exemplifies the value of integrating scientific research with public health initiatives through global collaboration and public-private partnerships governance. Future efforts should enhance the scalability of such models and ensure their sustainability through continued public and private support.
