Multiple computer-aided detection (CADe) systems have been developed to improve adenoma detection during colonoscopy, but their comparative efficacy and consistency of effect remain uncertain. This network meta-analysis aimed to compare the efficacy of different CADe systems across multiple detection outcomes. MEDLINE, Embase, Scopus, and the Cochrane Library were systematically searched for randomized controlled trials (RCTs) comparing CADe-assisted colonoscopy versus colonoscopy without CADe or other CADe systems. The primary outcome was adenoma detection rate (ADR). Secondary outcomes were adenomas per colonoscopy (APC) and adenoma miss rate (AMR). A random-effects network meta-analysis was performed to synthesize direct and indirect evidence. Forty-one RCTs (31,789 patients; 14 CADe systems) were included. In the exploratory complete-network analysis, 10 of 14 systems significantly improved ADR (RR range 1.12-1.76), 9 increased APC, and 3 reduced AMR. In the FDA-cleared systems analysis, 3 of 6 improved ADR (RR range 1.14-1.25), whereas 3 did not. Several systems retained a significant benefit in studies meeting the control-arm ADR thresholds recommended by ESGE (≥25%) and ASGE/ACG (≥35%), although effects varied across platforms and attenuation at higher baseline ADR was not uniform. Baseline ADR was not associated with treatment effects in meta-regression. The effectiveness of CADe-assisted colonoscopy is not uniform across platforms and varies according to the specific product. These findings support a system-specific rather than class-based evaluation of CADe technologies. However, comparative estimates should be interpreted cautiously given the low certainty of evidence for several outcomes and the absence of head-to-head comparisons and closed loops within the network.
Regulation and screening of biomacromolecule (e.g., enzyme) activity is one of the core tasks in disease treatment and drug discovery. Natural products are an important source of enzyme inhibitors, but their complex composition makes it difficult to develop effective candidate drug molecules. As a typical biomacromolecular target, chymotrypsin (CHT) exhibits aberrant activity closely associated with diseases such as wound healing, chronic pancreatitis, and emphysema. Therefore, efficient screening of enzyme inhibitors from natural products holds significant importance for clinical diagnosis, treatment, and drug development. This study establishes an integrated screening platform for enzyme inhibitors by combining a Cu2+-casein-mediated fluorescence-enhanced biosensing system with targeted ligand capture technology, enabling highly sensitive screening and precise identification of chymotrypsin inhibitors from natural products. In this platform, Cu2+-casein functions as a biomacromolecular substrate while also acting as a peroxidase-mimetic enzyme, significantly enhancing the fluorescence signal amplification effect of o-phenylenediamine oxidation. When chymotrypsin hydrolyzes casein, the structure of casein is disrupted, reducing its copper ion-binding capacity. Which leads to decreased catalytic activity and subsequent changes in fluorescence intensity, allowing quantitative detection of chymotrypsin activity with a detection limit as low as 13.6 ng mL-1. In the targeted fishing module, immobilized chymotrypsin (CHT@NH2-SiO2) is employed as an affinity medium, and combined with HPLC and LC-MS analysis, enables precise identification of active components in complex samples. This integrated strategy mitigates certain limitations of individual techniques, providing a feasible approach for efficient, high-throughput screening of inhibitors targeting biomacromolecules from complex systems.
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Prostate cancer (PCa) remains one of the most prevalent and lethal cancers in men, particularly in its metastatic form. Despite therapeutic advancements, resistance to therapy often leads to a castration-resistant state with genetic and molecular alterations that promote immune evasion and disease progression. Chronic inflammation and the immunosuppressive tumor microenvironment (TME) further exacerbate immune dysfunction. The suboptimal clinical success of current immunotherapies in advanced PCa underscores the urgent need to better understand the mechanisms underlying immune escape during disease progression and in response to therapeutic interventions. This review explores the key immune-evasive features of PCa, the contribution of the TME, and the immunotherapeutic strategies that have been clinically evaluated to improve outcomes in patients with advanced disease.
This study explored the interactions between emotional and behavioral symptoms in preschool children with autism spectrum disorder (ASD) and identified potential clinical subtypes based on these interrelationships. A total of 1886 preschool children with ASD and 285 age-matched typically developing (TD) children were assessed using the Child Behavior Checklist for ages 1.5-5. Symptom networks were estimated using the EBICglasso algorithm, and group differences were evaluated via network comparison tests. Subgroups within the ASD sample were identified using Individual Difference Symptom Networks (IDSN) with k-means clustering. The results revealed distinct network structures between the ASD and TD groups, with emotional reactivity demonstrating the highest centrality in the ASD network. Two distinct ASD subgroups (ASD-A and ASD-B) were identified, which showed significant differences from the TD group across all emotional and behavioral dimensionsin the CBCL 1.5-5. The subgroups differed significantly in overall network strength and specific edge connections, particularly between aggressive behavior and withdrawal problems. The findings indicate that emotional reactivity may play a central role in the symptom network of preschool children with ASD. The identification of two clinical subgroups with distinct symptom connectivity patterns provides valuable insights for developing more individualized and targeted intervention strategies. ASD-A subgroup points to the potential value of comprehensive early intervention programs, whereas ASD-B subgroup highlights the need for functional communication training and social engagement strategies.
Patient-centered care, emphasizing autonomy and shared decision-making, is essential in palliative cancer care. The increasing prevalence of cancer requires optimized health care use, and given patients' preference for home-based care, traditional time-based follow-up appointments may not adequately address their needs. We have developed a digital patient-controlled follow-up intervention at the acute palliative care unit in Norway. The digital app is integrated into the existing national health service platform, MyHealth, and facilitates symptom monitoring, self-management support, and patient-controlled access to palliative care services. This pilot study will evaluate the feasibility and acceptability of the intervention and study procedures prior to examining the intervention's effect in a future randomized controlled trial. Applying a mixed methods design, we plan to recruit 20 patients to participate in a 6-week intervention period, during which they will complete weekly electronic versions of the revised Edmonton Symptom Assessment System to monitor symptom burden and enable tailored follow-up. Participants will have access to a dedicated website providing self-management guidance and will also be able to electronically book appointments with the palliative care team. Health-related quality of life will be assessed at baseline and after the intervention using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C-15-Palliative. Following the intervention, patients will complete a satisfaction questionnaire. Semistructured interviews with patients and family carers will explore experiences, benefits, and barriers, while a focus group with health care professionals will assess feasibility from a clinical perspective. Quantitative and qualitative data will be analyzed separately before being integrated to identify convergence, complementarity, or divergence. Findings from this pilot study will inform the design and feasibility of a future RCT. The recruitment of patients will start in October 2026, and the recruitment period and the intervention will last until April 2027 or until 20 patients have been recruited. We subsequently anticipate completing data analyses, manuscript writing, and submission of the stage 2 manuscript by October 2027. In January 2026, we received funding for the 4-year project (including a randomized controlled trial). This project is funded by the Dam Foundation (grant research [2025] #SDAM_FOR701622), supported by the Norwegian Cancer Society. Digital, need-based follow-up may offer a sustainable, patient-centered model for palliative cancer care. The findings of this feasibility study will inform the design of a randomized controlled trial to examine the effect of this intervention. PRR1-10.2196/92046.
To investigate the efficacy and safety of a novel dual-sided composite defocus (DSCD) lens for pediatric myopia control. Prospective, randomized, double-masked, three-arm, parallel-controlled clinical trial with 1-year follow-up. A total of 225 children aged 6-14 years with myopia ranging from -0.50 D to -6.00 D were randomized 1:1:1 to DSCD, single-surface defocus (SSD), or single-vision spectacle (SVS) lenses. Overall, 194 participants (86.2%) completed the 1-year follow-up. Participants were randomly assigned to the DSCD, SSD, or SVS lens group. The DSCD lens incorporated a front-surface microlens array and a posterior freeform aspheric design intended to generate an asymmetric peripheral myopic defocus profile. Outcomes were measured at baseline and during the 12-month follow-up. Statistical analyses included analysis of covariance, Pearson correlation, and exploratory subgroup analyses. The primary outcomes were 12-month changes in axial length (AL) and spherical equivalent refraction (SER). At 12 months, the DSCD group exhibited significantly less SER progression than the SVS group (-0.22 ± 0.37 D vs -0.83 ± 0.47 D; P < 0.001) and the SSD group (-0.22 ± 0.37 D vs -0.45 ± 0.43 D; P = 0.005). Axial elongation was also significantly slower with DSCD than with SVS lenses (0.19 ± 0.14 mm vs 0.42 ± 0.18 mm; P < 0.001). No statistically significant difference in axial elongation was observed between the DSCD and SSD groups. The DSCD lens reduced SER progression by 73.6% and AL elongation by 55.2% relative to SVS lenses. Exploratory subgroup analyses suggested less progression in children aged 8-12 years, those with baseline AL of 24-25 mm, and those with low myopia. No lens-related adverse events were observed, and all groups demonstrated high compliance and good adaptation. Over 12 months, DSCD lenses resulted in significantly less SER progression and axial elongation than SVS lenses. Compared with the SSD lenses tested in this study, DSCD lenses showed significantly less SER progression, whereas the difference in axial elongation was not statistically significant. DSCD lenses were generally well tolerated and may represent a spectacle-based option for pediatric myopia control.
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Cefepime is recommended for treating severe pulmonary infections caused by P. aeruginosa using intravenous route that limits sufficient deposition in the bronchi and alveoli of the lungs. To address this, we developed a cefepime dry powder while enabling lower total administered doses using an inhaler. A factorial design (Xn + 1) with two additives, L-leucine and L-tryptophan, was used to prepare inhalable and physicochemical stable powders via spray drying. The preparation parameters retained drug contents above 90 % across all cefepime powder formulations (CPF; n = 10). The particles were spherical with a mean geometric particle diameter 1-2 µm. Leucine significantly improved the aerodynamic properties by increasing the number of dimples on the particles' surfaces. The optimized formulation, CPF-3 (10 % leucine-only), produced the highest fine particle dose (FPD), corresponding to a fine particle fraction (FPF) of approximately 80 %. The minimum inhibitory concentrations (MIC) and 90 % minimum biofilm inhibitory concentrations (MBIC90) of the formulations were comparable to those of the cefepime raw material and safe on the lung epithelial cell line (A549). The powder exhibited moisture-sensitivity and therefore requires storage in a dry environment at room temperature. Overall, this study establishes a robust formulation strategy of inhalable fourth generation β‑lactams.
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Methylaluminoxane (MAO) is the most widely used cocatalyst in single-site olefin polymerization, yet its molecular structures have decisively resisted characterization. Computational chemistry has played an indispensable role throughout the characterization efforts, from the earliest cage-based structural proposals inspired by tert-butylaluminoxane analogs through systematic hydrolysis-based modeling to the identification of two-dimensional sheet structures as the thermodynamically preferred motif. This review traces that computational journey, with particular attention to the methodological advances and failures that shaped it. The discovery that widely used density functional theory methods for MAO carry systematic errors for four-coordinate aluminum-oxygen environments, and that vibrational entropy rather than electronic energy is the decisive thermodynamic quantity in the experimentally relevant size domain, fundamentally redirected the field. The resulting ovalene-based sheet model for the dominant [(AlOMe)16(AlMe3)6Me]- anion is simultaneously consistent with electrospray ionization mass spectrometry, solid-state NMR, X-ray crystallography, and synchrotron pair distribution function data, and yields catalyst activation barriers in reasonable agreement with experiment. The structural foundation now established for the dominant anionic component of fresh MAO opens a realistic path toward understanding the full complexity of the MAO mixture and toward rational design of next-generation aluminum-based cocatalysts.
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Photodynamic therapy (PDT) is a promising therapeutic modality based on the combined use of light and photosensitizers (PSs) and approved for treating several types of cancers. Thio-heterocyclic naphthalimide-based PSs are particularly attractive as phototheranostic agents, combining fluorescence imaging for diagnosis with reactive oxygen species (ROS)-mediated cytotoxicity for treatment. However, no effective conjugation strategy for simultaneously endowing naphthalimides with water solubility and efficient ROS production ability currently exists. Herein, novel water-soluble, heavy atom-free thioxanthene-fused naphthalimide-polyamine conjugates 1-4 have been developed. Structural variation in the polyamine moiety, including chain length and nitrogen content, allowed the fine-tuning of key properties. Conjugates 2 and 3 exhibited (i) favorable photophysical and fluorescent properties, (ii) enhanced water solubility, (iii) improved photodynamic efficacy against MCF-7 breast cancer cells, and (iv) negligible dark toxicity. This novel class of thioxanthene-fused naphthalimide-polyamine conjugates provides a promising conjugation strategy for improving the drug-like properties of PSs.
On a population level, mental health apps are accessible and effective. However, nondigitally native adults with chronic pain are a large and growing population who have been neglected during the development process of these interventions. Although technology use is rapidly growing among this population, their engagement with mobile health-related apps is lagging because usability is often not optimized for their needs and preferences. This study aimed to identify design preferences and determinants of engagement with mental health apps by nondigitally native adults who have chronic pain and coexisting symptoms of depression or anxiety. In this qualitative study, participants completed a semistructured interview regarding their experience with, and perceptions of, mobile devices, apps, and digital health interventions. Participants were 45 years or older; scored ≥10 on the 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder, or both; endorsed pain on most days or every day in the past 3 months; and were living in the United States. The interview guide was informed by the Consolidated Framework for Implementation Research and the Behavioral Intervention Technology model. Codes were organized into themes. Recruitment continued until thematic saturation was achieved. A total of 42 participants were interviewed (mean age 57, SD 8 years; n=32, 76% women). Participants strongly preferred apps that are free, describe strong privacy policies, and add functional value to their lives. They were more motivated by "real-life" goal achievement and tangible health improvements than by gamification within an app, and many were wary of allowing apps to passively collect certain types of data, especially to make inferences about their mental health. Most participants were unaware of apps designed to address chronic pain, but they were interested in the concept, particularly to help track their mood and pain and then identify associations between their symptoms, app activity, and other life events. Despite their daily use of apps, many participants described frequent challenges related to app navigation. While on-demand access to app tools was preferred, most participants appreciated the potential value of occasional push notifications if their timing was thoughtful and customizable. Participants cautioned against an overly cheerful, "infantile," or informal tone for an app that addresses serious issues such as mental health and chronic pain. Mental health apps for nondigitally native adults should highlight tangible health improvements that can be achieved from app engagement (more so than gamification), potentially using a multidomain tracking feature, if appropriate. This population is available to receive just-in-time adaptive interventions, but the frequency and timing should be thoughtful, customizable, and not wholly reliant on passively collected personal data. Health-related apps designed to address conditions that are more common with increasing age should account for these preferences.
Clinical practice guidelines are a cornerstone of evidence-based medicine, yet their implementation in routine care remains inconsistent. Large language models (LLMs), particularly with Retrieval-Augmented Generation (RAG), have shown strong performance in medical question answering, but their ability to use knowledge from German-language guidelines has not been systematically evaluated due to a lack of a dedicated benchmark. We therefore developed such a benchmark and evaluated guideline-based question answering with different LLMs and retriever configurations. We developed cpgQA-DE, an expert-validated benchmark dataset of 200 multiple-choice questions derived from 10 current German clinical practice guidelines across five specialties. All questions were reviewed for correctness, relevance and complexity. The dataset includes case-based and knowledge-based questions with metadata on guideline source, specialty, relevance and difficulty. We evaluated LLM performance using a RAG-based pipeline built on a corpus of German guidelines, comparing multiple model-retriever combinations. RAG integration substantially improved accuracy across all tested models and for most retrievers. The best-performing configuration, GPT-5 combined with the multilingual-e5-large retriever, achieved an accuracy of 95%. Notably, the open-weight model gpt-oss-120b reached 90% accuracy when used with RAG. cpgQA-DE enables systematic and reproducible offline evaluation of guideline-aware question answering systems in the German healthcare context. The observed performance gains with RAG support the use of LLMs augmented with quality-assured external knowledge. Such systems may help bridge the evidence-practice gap by providing guideline-based recommendations at the point of care, while strong performance of open-weight models suggests potential for on-premises deployment in privacy-sensitive clinical environments.
With increasing emphasis on extending healthy lifespan, aging research requires vertebrate models that permit efficient mechanistic investigation and intervention testing within practical time and cost constraints. The African turquoise killifish (Nothobranchius furzeri) has attracted growing attention because it combines an exceptionally short life cycle with an intact vertebrate physiological context and an expanding genetic toolkit, enabling relatively rapid evaluation of candidate aging interventions and mechanistic analysis across molecular, tissue, and organismal levels. This review assesses N. furzeri from an integrative-physiology perspective, focusing on germline-soma interactions, gut microbiota-host crosstalk, nutrient sensing and metabolic remodeling, temperature responsiveness, and AMPK-mTOR-linked programs. It also examines expanding genome-engineering and reporter approaches that support mechanistic and tissue-resolved investigation of these physiological processes. Building on recent reviews of killifish biology, disease modeling, regeneration, and the hallmarks of aging, we synthesize evidence across major intervention domains, distinguish established phenotypic effects from incompletely resolved mechanisms, and highlight functional endpoints, methodological standardization, and the appropriate interpretation of the model's translational relevance. Together, these features position N. furzeri as a strategically useful vertebrate platform for rapid mechanistic testing, intervention evaluation, and prioritization of aging-related pathways. Future progress will require improved methodological standardization, tissue-resolved causal studies, and question-driven cross-species validation where appropriate.
Older adults with type 1 diabetes are clinically heterogeneous, with variable cognition, dexterity, comorbidity burden, caregiver support, and prior technology experience. Evidence on automated insulin delivery systems (AIDs) in this population remains limited and largely observational. We performed a systematic review and meta-analysis of contemporary AIDs in adults aged ≥60 years with type 1 diabetes. We searched PubMed, Embase, Web of Science, Cochrane Library, and ClinicalTrials.gov through February 2026. Nine studies (7 observational studies and 2 randomized crossover trials; 8,765 participants) were included. We pooled outcomes during AID use using single-arm random-effects meta-analyses. When baseline data were available, we performed change-from-baseline analyses. With AIDs, pooled mean time in range (TIR) was 77.95% (95% CI 75.31-80.59), HbA1c was 6.95% (52 mmol/mol) (95% CI 6.67-7.24), and time below range (TBR) < 70 mg/dL was 1.35% (95% CI 1.12-1.57). From baseline, AID use was associated with higher TIR, lower hyperglycemia, lower HbA1c (MD - 0.36%; 95% CI - 0.63 to - 0.09), and lower diabetes distress, without increased hypoglycemia. Findings were consistent in direction with broader AID literature. Older age alone should not preclude individualized AID use.
Largemouth bass ranavirus (LMBV) is a DNA virus that threatens various aquatic animals, yet the mechanism by which it attaches to host cells to initiate infection remains poorly understood. Here, we report that the major capsid protein (MCP) of LMBV interacts with host protein disulfide-isomerase A3 (PDIA3). Subsequently, PDIA3 was also found to be localized on the host cell membrane, which may play a critical role in mediating virus adhesion and infection. Further investigation demonstrated that blocking the viral MCP protein with recombinant PDIA3 significantly reduced LMBV adhesion and infection. Similarly, adhesion and infection were markedly impaired when cell surface PDIA3 was blocked with specific antibodies. To further confirm the role of PDIA3 in LMBV adhesion, PDIA3 was expressed in human embryonic kidney 293T (HEK 293T) cells that were originally insensitive to LMBV. The results showed that PDIA3 expression in HEK 293T cells enhanced LMBV adhesion and infection. In addition, it was found that suppression of pdia3 expression could inhibit LMBV infection in largemouth bass. These results indicated that the interaction between MCP protein and PDIA3 plays a crucial role in promoting LMBV adhesion during virus entry and infection, deepening our understanding of the mechanism of LMBV infection and offering a potential target for controlling LMBV.