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PubMed2026

Proteomic insights into the immunomodulatory effects of Ca/Sr co-doped sol-gel coatings for titanium implants.

Ionic functionalization of biomaterial coatings has emerged as a powerful strategy to regulate early host responses at the implant interface. However, how combined Ca/Sr incorporation governs the adsorbed proteome and downstream immune signaling remains poorly understood. This study analyses, employing in vitro tests and proteomics, the effect of adding Sr and Ca to Si-based coatings designed to bioactivate Ti implants. Hybrid Si-based coatings were synthesized by the sol-gel route with a fixed Ca content (0.5 wt%) and increasing Sr contents (0.5, 1.0, 1.5 wt%), and their physicochemical properties, ion release kinetics, and hydrolytic stability were characterized. The coatings remained highly crosslinked despite Ca/Sr incorporation, whereas the highest Sr content increased hydrolytic degradation to around 70% after 56 days. Proteomic analysis identified 183 adsorbed proteins, of which 56 were differentially adsorbed on Ca/Sr-coatings, mainly associated with immune and coagulation pathways. In vitro, RAW 264.7 showed increased gene expression of TNF-α and TGF-β; with an enhanced TNF-α secretion by the addition of Ca and Sr. In parallel, MC3T3-E1 indicated that Ca/Sr-coatings were not cytotoxic and did not impair cell proliferation. However, ALP activity was reduced in the co-doped groups, indicating that the immunomodulatory effects induced by Ca/Sr incorporation were not accompanied by enhanced early osteogenic differentiation. The Ca/Sr combination induced alterations in the adsorption of immune-related proteins, which correlated with the in vitro findings. The deeper insight into how Ca/Sr mixtures modulate protein adsorption on biomaterial surfaces may be key to understanding the immunomodulatory capacity of these bioactive cations.

Animals↗
PubMed2026

A Multimethod Evaluation to Assess Feasibility, Acceptability, and Preliminary Efficacy of HPVVaxFacts, a Tailored Mobile Web App, for Parents With Unvaccinated Children: Pilot 2-Arm Randomized Controlled Trial.

BACKGROUND: Mobile health (mHealth) interventions may improve provider-parent communication on human papillomavirus (HPV) vaccination to reduce concerns, and increase intention and uptake. HPVVaxFacts (233 Analytics) is a novel, mobile web app delivering tailored education based on the Health Belief Model and Theory of Reasoned Action, addressing parental concerns preclinic visit. OBJECTIVE: This study aimed to assess the feasibility, acceptability, and preliminary efficacy of HPVVaxFacts among parents of adolescents aged 9-17 years. METHODS: We conducted a pilot, randomized controlled trial in 2 urban Tennessee clinics from June to September 2023 comparing 2 groups: tailored education via HPVVaxFacts mobile web app (intervention, n=27), and nutrition education (attention control, n=30). Eligible parents had or were caregivers to a child aged 9 to 17 years unvaccinated against HPV, had a mobile phone, had an upcoming clinic visit, and spoke English. The recruitment strategy was patient intake software-Phreesia (Phreesia, Inc) and eClinicalWorks (eClinicalWorks). Although unblinded, parents could deduce their study arm assignment. Providers were blinded. Feasibility, acceptability, and preliminary efficacy (HPV vaccine knowledge, concerns, intentions, and vaccination rates) were assessed using multimethod evaluation. Parents were assessed at baseline and immediately post intervention via surveys. Vaccination rates were assessed at 12 months post intervention via electronic health records. Nineteen parent interviews were conducted up to 9 months post intervention. A clinic staff consultation (n=6) was 1 month post intervention. RESULTS: Of 57 enrolled parents, most were female (52/57, 91%), non-Hispanic White (44/57, 77%), had ≤US $80,000 household income (32/57, 56%), and had some college or less (27/57, 47%). In total, 81% (29/36) of parents viewed HPVVaxFacts. Post intervention, HPV vaccine initiation was higher in the intervention group compared to the attention control group (48% vs 17%; difference 0.24; 95% CI 0.03-0.46; P=.01). Parents in the HPVVaxFacts arm demonstrated a greater reduction in knowledge (ie, knowledge increase; mean change: -0.6 vs 0.1) and concern scores (mean change: -3.4 vs -1.4) than those in the nutrition education arm. However, between-arm differences were not statistically significant (P=.13 and P=.14, respectively). The majority found the study protocol and HPVVaxFacts acceptable. Benefits of HPVVaxFacts include confirming their decision to vaccinate, supporting parent-child discussion on the vaccine, and answering questions preclinic visit or offering questions for the provider. Study protocol delivery and mobile web app instructions were suggested areas for improvement. Barriers for HPVVaxFacts use include content in English only and digital format. CONCLUSIONS: Our study suggests HPVVaxFacts was feasible and acceptable among parents to provide previsit, tailored information on HPV vaccination. Outcomes offer a positive trajectory but need more exploration. Next steps include a well-powered efficacy trial to determine the impact of HPVVaxFacts on initiation vaccine rates and parental hesitancy factors, as well as to explore an interaction, effect modification, and mediation among different variables.

Humans↗
PubMed2026

Nasopharyngeal Carriage Rate, Risk Factors, and Co-Resistance Patterns of Methicillin-Resistant Staphylococcus aureus in Ethiopia: Systematic Review and Meta-Analysis.

Methicillin-resistant Staphylococcus aureus (MRSA) nasopharyngeal carriage is a major global health concern linked to severe infections and transmission. However, comprehensive evidence on the burden of MRSA carriage, antimicrobial resistance, and associated risk factors in Ethiopia remains limited. This study aimed to estimate pooled prevalence, resistance pattern, and determinants of nasopharyngeal MRSA carriage. PubMed, ScienceDirect, Scopus, Web of Science, Google Scholar, and gray literature were searched for cross-sectional studies published between January 2015 and December 2025. Two groups of reviewers screened studies based on predefined criteria. The risk of bias was assessed using the Joanna Briggs Institute tool. Pooled prevalence and resistance proportions were estimated using a random-effects model, and pooled odds ratios (ORs) were calculated using the Mantel-Haenszel method. Heterogeneity and publication bias were assessed, and a sensitivity analysis was conducted. A total of 1040 records were identified, and 20 studies (6869 participants) were included. The pooled carriage prevalence was 7.3% (95% CI, 5.0-10.8), with substantial heterogeneity (I2 = 95.5%). Resistance was highest to tetracycline (55.75%) and lowest to clindamycin (12.66%). Increased odds of carriage were associated with prior hospitalization (OR, 3.49) and antibiotic use (OR, 2.35). Inconsistent variable coding across included studies limited the inclusion of other potential risk factors. Evidence of publication bias was detected, suggesting that the pooled prevalence should be interpreted with appropriate caution. The findings indicate a considerable burden of MRSA and highlight the need for strengthened antimicrobial stewardship, improved surveillance, and targeted prevention efforts in higher-risk populations. This review was registered in PROSPERO (CRD420251047192).

Ethiopia↗
PubMed2026

First identification and molecular subtyping of Blastocystis spp. in donkeys in Aksaray province, Türkiye.

Blastocystis is a common intestinal protist worldwide that can infect humans and animals. Although its molecular epidemiology in Türkiye is mostly focused primarily on humans and livestock, equids have received limited attention despite their traditional roles and frequent contact with humans and other animals in rural environments. This study aimed to determine the molecular prevalence and subtype (ST) distribution of Blastocystis spp. in donkeys in Aksaray Province, providing the first molecular data on donkeys in Türkiye. A total of 182 fresh fecal samples were collected from donkeys in nine villages within Aksaray province. Genomic DNA was extracted, and the small subunit ribosomal RNA (SSU rRNA) gene fragment of Blastocystis spp. was amplified via PCR analysis. Positive isolates were sequenced bidirectionally for identification and subsequent phylogenetic analysis of Blastocystis in donkeys. The overall molecular prevalence of Blastocystis spp. in donkeys was 4.4% (8/182). The infection rate was higher in young donkeys (under 3 years old; 8.33%) than in adults (3 years or older; 2.46%). However, this difference was not statistically significant. Sequence analysis of the positive PCR products revealed the presence of one known livestock-specific subtype, ST10. Phylogenetic analysis showed that the ST10 isolates characterized in this study clustered with isolates identified from different hosts. This study provides the first molecular data on Blastocystis presence in donkeys in Türkiye. The exclusive detection of ST10 suggests potential cross-species transmission, likely facilitated by the traditional practice of co-housing donkeys with other animals in confined barns. These findings indicate that donkeys may contribute to Blastocystis transmission, underscoring the importance of a "One Health" approach in future epidemiological surveillance.

Animals↗
PubMed2026

ADAM10's combined influence on the diagnostic usefulness of IL 22, IL 10, IL-17 A, and IL-17D in autism spectrum disorders: Predicted role on gut leakiness as co-morbidity.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing global prevalence but a lack of reliable diagnostic biomarkers. Emerging evidence suggests that immune dysregulation, gut-brain axis dysfunction, and increased intestinal permeability play key roles in ASD pathophysiology. This study investigated the combined diagnostic value of ADAM10 and cytokines (IL-10, IL-22, IL-17 A, and IL-17D). Multivariable logistic regression produces an improved ROC curve that improves diagnostic accuracy over individual markers by combining numerous predictors into a single risk score (linear predictor). The technique, which frequently raises individual marker AUCs, entails modelling a binary result, calculating the probability, and visualizing ROC based on the projected probabilities. In this case-control study, plasma levels of ADAM10, IL-10, IL-22, IL-17 A, and IL-17D were measured in 37 male children with ASD and 37 age-matched controls. Group comparisons, correlation analyses, and receiver operating characteristic (ROC) curve analyses, including combined ROC models, were performed. ADAM10, IL-22, and IL-17 A levels were significantly reduced in children with ASD compared to controls, whereas IL-10 and IL-17D showed no significant differences. ADAM10, IL-17 A, and IL-22 demonstrated good diagnostic performance, with AUC values of 0.886, 0.855, and 0.812, respectively. In contrast, IL-10 and IL-17D showed poor discriminatory ability, with AUC values of 0.524 and 0.599, respectively. Combined ROC analysis markedly improved diagnostic accuracy, with all panels including ADAM10 achieving AUC values above 0.90, and some reaching as high as 0.988, with high sensitivity and specificity. The combination of ADAM10 with selected cytokines significantly enhances diagnostic performance compared to individual markers, supporting a link between immune dysregulation, barrier dysfunction, and gut permeability in ASD.

Humans↗
PubMed2026

AI Health message intervention: The role of message customization and message source in breast cancer screening among women of color.

OBJECTIVES: To examine the effectiveness of breast cancer screening messages with varying levels of customization (generic, targeted, and tailored) and to compare AI-generated versus human-generated messages. METHODS: A between-subjects experimental design with a control condition was employed. Message content followed a standardized structure and varied by level of customization: generic, targeted (demographic-based), and tailored (perceived susceptibility- and barrier-based). Messages were developed by either the authors or GenAI (ChatGPT-4o). A total of 391 participants recruited via Prolific were randomly assigned to five groups (generic, targeted-human, targeted-AI, tailored-human, and tailored-AI). Self-efficacy, behavioral intentions, attitudes, and message believability were measured using different scales. RESULTS: Customized (tailoring and targeting) health messages performed comparably to generic messages in shaping positive health outcomes. GenAI-generated messages also produced outcomes comparable to those of human-generated messages under standardized conditions. Significant negative indirect effects through message believability for the human-tailored condition was found relative to the generic condition. CONCLUSIONS: GenAI may be a useful tool for developing and customizing scalable health messages. Its effectiveness depends not only on customization but also on maintaining message quality, including readability, clarity, coherence, naturalness, and credibility. PRACTICAL IMPLICATIONS: GenAI may support health practitioners in developing customized and scalable breast cancer messages. However, professional review remains necessary to ensure that the message is culturally appropriate, responsive to patient concerns, and suitable for use alongside patient-provider communication.

Humans↗
PubMed2026

Critical insights on the application of the theory of planned behaviour to food handlers' food safety practices.

Foodborne diseases remain a significant public health concern, often linked to unsafe food-handling practices. The Theory of Planned Behaviour (TPB) is widely used to predict and explain food safety behaviours, yet its application in this field has not been systematically and in-depth evaluated. This review evaluated how the TPB has been applied to study food handlers' behaviour, focusing on methodological approaches, use of the TACT (Target, Action, Context, and Time) framework, validity, elicitation studies, and reliability. Seventeen studies were included following a systematic search of four databases (Scopus, Web of Science, Wiley Online Library, and Taylor & Francis Online). Data were extracted on behaviour definition, aim of study, main findings, use of indirect and direct TPB measures, use of elicitation studies, internal consistency, content validation, analytical methods used, and any extensions to the original TPB framework. Key elements related to adherence to core TPB principles and measurement practices were extracted using a Checklist. Most studies used direct measures of TPB constructs, and only a few reported procedures for content validation. Considerable variability was found in the reporting of key measurement and psychometric practices. Five studies fully applied the TACT framework, while nine incorporated additional factors such as knowledge and moral norms. Elicitation studies were conducted in five cases where indirect measures were employed. Analytical approaches were mainly based on multiple linear regression, with limited use of more advanced techniques such as structural equation modeling. Twelve studies reported internal consistency results. Overall, the review highlights opportunities to strengthen methodological practices in future TPB research on food safety. Greater attention to conducting and reporting content validation, full application of the TACT framework, reporting of internal consistency, and consistent inclusion of elicitation studies when using indirect measures may enhance transparency, reinforcing the credibility and trustworthiness of research findings. A major methodological limitation of this review was that screening and data extraction were conducted by a single reviewer and no formal quality or risk-of-bias assessment of the included studies was performed. Despite these limitations, the findings provide practical guidance for the development and validation of TPB-based questionnaires and may support more robust food safety research, interventions, and policy initiatives aimed at improving food handlers' practices.

Humans↗
PubMed2026

Risk of mortality and complications in people with depressive disorder and co-occurring diabetes mellitus: a systematic review and meta-analysis.

AIMS: People with depressive disorder have increased premature mortality and higher rates of diabetes mellitus than general population. Evidence shows that diabetes may further increase their risk of premature death from diabetes-related complications, especially cardiovascular diseases (CVDs). Earlier studies examining depression-associated outcomes in diabetes patients have shown mixed results and were hindered by important limitations, especially the use of self-reported questionnaires to ascertain depression, causing misclassification bias by identifying subclinical symptoms or diabetes distress. Associations of depression with specific diabetes complications have not been systematically evaluated. This meta-analysis aimed to investigate the risk of mortality and complications among patients with depression and co-occurring diabetes (depression-diabetes group) relative to patients with diabetes-only (diabetes-only group), on their all-cause mortality rates, and if applicable cause-specific mortality rates, and occurrence of specific diabetes complications. METHODS: We systematically reviewed and quantitatively synthesized diabetes-related outcomes in patients with depression by searching Embase, MEDLINE, PsycInfo and Web-of-Science from inception to 20 December 2024, and included studies that examined mortality and complication outcomes in depression-diabetes group relative to diabetes-only group. Results were synthesized by random-effects meta-analytic models, with stratified-analyses (subgroup analyses and meta-regression) by study-level characteristics, including age, gender, study period, geographic region, follow-up duration and nature of diabetes sample. The study was registered with PROSPERO (CRD42024595145). RESULTS: Twenty-six studies were identified from nine geographic regions. Regarding mortality risk, depression-diabetes group exhibited increased risks of all-cause mortality (RR = 1.30 [95% CI: 1.21-1.39]) and CVD-specific mortality (1.15 [1.02-1.29]) relative to diabetes-only group. Regarding complication risk, depression-diabetes group showed increased risk of complications (1.28 [1.18-1.40]) relative to diabetes-only group, especially in incident-diabetes sample signifying advanced disease stage upon presentation, with stratified-analyses showing higher risk of metabolic complications (1.63 [1.33-1.99]) and cardiovascular complications (1.20 [1.11-1.29]), and lower likelihood of retinopathy (0.84 [0.76-0.94]), albeit comparable rates of cerebrovascular complications (1.36 [0.99-1.87]), nephropathy (1.09 [0.93-1.27]) and peripheral-vascular complications (0.97 [0.79-1.18]). Both overall mortality and complication risks were present in various regions and persisted over time. Heterogeneities were noted and could not be entirely explained by stratified analyses. CONCLUSIONS: Our study demonstrated that patients with depression and co-occurring diabetes were associated with elevated overall mortality risk and complication risk (particularly metabolic and cardiovascular-complications) than non-depressed counterparts, suggesting an overall poorer glycemic control that might eventually drive their earlier death. Comprehensive and multipronged interventions are needed for individualized risk estimation of diabetes-related outcomes, with consequent early interventions to minimize the avoidable physical morbidity and premature mortality in this vulnerable population.

Humans↗
PubMed2026

Rational design of high-productivity perfusion processes for CHO Cells: From growth inhibitory strategies to model-driven optimization.

While perfusion culture for Chinese hamster ovary (CHO) cells offers advantages such as continuous operation and flexibility, it suffers from product loss through cell bleeding and difficulties in reaching high productivity due to sustained rapid cell growth. Growth inhibitory strategies are widely used to enhance productivity in fed‑batch processes; however, their practical implementation and comparative effectiveness in perfusion processes remain insufficiently explored. Meanwhile, process development often relies on costly trial‑and‑error approaches. Here, we systematically compared three growth inhibitory strategies in perfusion culture-low cell‑specific perfusion rate (CSPR), sodium butyrate, and mild hypothermia-with respect to cell growth, metabolism, productivity, and product quality. Genome‑scale metabolic flux sampling analysis revealed that low‑CSPR and sodium butyrate induce a convergent up‑regulation of energy metabolism, correlating with greater gains in specific productivity (qp). Building on this insight, we developed a growth‑kinetic model for the combined low‑CSPR + butyrate strategy, incorporating parameter uncertainty. This model‑guided framework enabled the rational design of two distinct high‑productivity perfusion processes: a sustained mode that achieved robust long‑term stability alongside substantial productivity gains, and a high‑intensity mode that pushed qp and daily volumetric titer to their maxima, with increases of up to 108.94% and 190.36%, respectively, in a model CHO cell line with a moderate baseline productivity. Our study provides a proof‑of‑concept framework for perfusion intensification, from strategy selection to rational process design.

Animals↗
PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗
PubMed2026

In situ product monitoring in heterogeneous reaction of gaseous trimethylamine on Fe2O3/Fe(NO3)3: Effect of environmental factor and particle property.

Gas-particle reactions represent an important atmospheric heterogeneous transformation process for organic amines (OAs). Environmental factors and particle properties may impact the gas-particle reaction products. Although the products from gas-particle reactions can be monitored by various in situ techniques, related data remain scarce. Here, the interfacial and gaseous products from the reaction of trimethylamine on Fe2O3/Fe(NO3)3 particles under light irradiation with mixed NO2, O2, SO2 and H2O were monitored using in-situ diffuse reflectance Fourier transform infrared spectroscopy and proton transfer reaction time-of-flight mass spectrometry. Dark reaction of gaseous trimethylamine on Fe2O3/Fe(NO3)3 generated two interfacial products types: N-containing ones (CH3NCH2, CH3NO2, (CH3)2NCHO, and CH3N(OH)CHO) and N-free ones (alcohols, aldehydes and acids), both accumulating with reaction progression. Light irradiation and O2 oxidation enhanced formation of these products, while NO2 promoted the production of CH3NO2 and (CH3)2NCHO. H2O and SO2 occupied the active sites of particles to inhibit the formation of all products. Compared to Fe(NO3)3, Fe2O3 showed absolute dominance in contribution to the formation of products. Considering the smaller particle size of Fe2O3 and excess Fe(NO3)3, the physical mixing of them reduced the generation of interfacial products. Furthermore, gaseous products of CH3OH, HCHO, CH3CHO, HCOOH and CH3COOH detection clarified the N-free interfacial products. The presence of Fe(NO3)3 inhibited the formation of HCOOH and favored the formation of CH3CHO in the gas phase. By combining product information with thermodynamic calculations, the heterogeneous reaction pathways of trimethylamine were tentatively proposed. These findings provide a guiding significance for the migration of OAs in real atmospheric environment.

Methylamines↗
PubMed2026

Misalignment between ultra-processed status and 'better for you' claims on premix alcohol products.

BACKGROUND: Premix alcohol products (also known as ready-to-drink beverages) are a rapidly expanding alcohol category and frequently marketed using 'better for you' claims (e.g., 'Low sugar', 'Natural'). Little is known about the extent to which these products are ultra-processed or whether marketing claims align with ultra-processed status. This study aimed to address this evidence gap by auditing ingredient disclosure on premix products, assessing the ultra-processed status of these products, and determining the prevalence of 'better for you' claims with a particular focus on claims relating to ultra-processed status. METHODS: 534 premix alcohol products sold in major Australian retail outlets were assessed. Products were evaluated for compliance with mandatory ingredient disclosure, classified according to ultra-processed status based on the presence of indicators of ultra-processing (additives and other industrial ingredients), and analysed to determine the prevalence and types of 'better for you' marketing claims. RESULTS: Only 79% of assessed products displayed an ingredients list. Among compliant products, 98% contained at least one additive or ingredient indicative of ultra-processing, most commonly flavours, carbonating agents, colours, and sweeteners. One-third (33%) of products containing an ultra-processing indicator displayed a claim suggesting naturalness or minimal processing. Substantially higher proportions of ultra-processed products than non-ultra-processed products carried health-related claims. DISCUSSION AND CONCLUSIONS: Premix beverages available in Australia are overwhelmingly ultra-processed, yet many are marketed in ways that may mislead consumers about their composition and healthfulness. Stronger regulatory oversight of ingredient disclosure and marketing claims in this sector is urgently needed to support informed consumer decision-making.

Alcoholic Beverages↗
PubMed2026

How to assess different types of abstract concepts in brain disorders: A systematic review.

The clinical evaluation of semantic knowledge has predominantly relied on tools targeting concrete concepts, whereas abstract knowledge has historically received limited attention despite its importance in everyday communication. Only a few instruments have explored the internal subdivision of abstract knowledge, likely due to the intrinsic difficulty of defining specific types of concepts or dimensions, resulting in a fragmented and heterogeneous neuropsychological assessment framework that limits our understanding of this domain. This systematic review examined the tools used to assess various types of abstract concepts in clinical populations. A literature search has been performed on the electronic databases of PubMed and Google Scholar (last update: October 2025). A total of 17 tests is reviewed, differing in the test characteristics, i.e. ranging from automatic to controlled processes and varying in ecological validity, the type of stimuli employed, and the abstract dimensions explored. Most studies have focused on neurodegenerative patients, while comparatively few have examined other clinical conditions. The risk of bias of the reviewed studies was assessed using an ad hoc developed instrument. This review highlights the need for future research to extend investigations to additional abstract domains and clinical populations, while also identifying key challenges related to stimulus selection and the determination of the most appropriate assessment framework.

Humans↗
PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗
PubMed2026

Effectiveness of artificial intelligence in nursing simulation education: A systematic review, meta-analysis and bibliometric visualization analysis.

OBJECTIVES: To synthesize the roles and core functions of AI in nursing simulation education for nursing students via systematic review, quantitatively evaluate its effects on students' knowledge and skill outcomes through meta-analysis, and map the research landscape and development trends of this field through bibliometric visualization analysis. DESIGN: Systematic review, meta-analysis and bibliometric visualization analysis. DATA SOURCES: Eight electronic databases: PubMed, Web of Science, MEDLINE, ERIC, Academic Search Complete, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Science and Technology Journal Database (VIP) were employed to search studies from the time of construction to 16 December 2025. REVIEW METHODS: Studies meeting the inclusion criteria were screened. The revised Cochrane Risk of Bias tool (ROB 2) and Joanna Briggs Institute (JBI) critical appraisal checklists were used for quality assessment. Meta-analysis was performed with Review Manager 5.4, and bibliometric visualization analysis was conducted using VOSviewer 1.6.20 and Bibliometrix (based on R4.4.3). RESULTS: A total of 61 studies were included. AI primarily played two roles in nursing simulation education: peer-type new subject (n = 24) and direct mediator (n = 22). Meta-analysis showed that AI interventions significantly improved nursing students' knowledge (SMD = 1.49, 95% CI [0.55,2.43], p = 0.002) and skills (SMD = 0.66, 95% CI [0.02,1.31], p = 0.04). Bibliometric analysis identified that the United States of America and China were the two main contributing countries in this field, and the key motor themes included generative artificial intelligence, virtual patients, and geriatric care. CONCLUSIONS: AI exerts positive effects on nursing students' knowledge acquisition and skill enhancement in simulation education, with peer-type new subject and direct mediator as the dominant roles. Future research should focus on expanding AI applications in multi-specialty simulation scenarios, activating the data-driven value of machine learning, and strengthening international collaboration and standardization construction, so as to promote the sustainable development of AI-integrated nursing simulation education.

Humans↗
PubMed2026

Natural products alleviate exercise-induced fatigue by modulating gut microbiota: a systematic review.

BACKGROUND: Exercise-induced fatigue critically impairs athletic performance and training quality. The gut microbiota, as a key regulator of the "gut-muscle axis," has emerged as a promising anti-fatigue target. Natural products - owing to their diverse sources, structural complexity, and favorable safety profiles - have attracted growing research interest. However, a systematic synthesis comparing their anti-fatigue effects via gut microbiota modulation across different sources is lacking. SCOPE AND APPROACH: We systematically searched PubMed, Web of Science, the Cochrane Library, and CNKI for original studies that administered natural products and concurrently assessed gut microbiota changes and anti-fatigue outcomes. Twenty-six studies (25 animal experiments and 1 human trial) were included and categorized into seven groups by source and chemical characteristics. A descriptive systematic review was conducted to identify common mechanisms and source-specific differentiations. KEY FINDINGS AND CONCLUSIONS: The enrichment of short-chain fatty acid (SCFA)-producing bacteria and the activation of the SCFA-AMPK/PGC-1α axis were shared core events across all product categories. However, source-dependent mechanistic divergences emerged: polysaccharides acted primarily as fermentable substrates with an optimal dose window; polyphenols and saponins exerted dual modulation on both microbiota and host signaling pathways; compound extracts achieved systemic synergy through functional complementation; marine- and animal-derived products exhibited unique targeting profiles and rapid action. Intestinal barrier maintenance and brain-gut axis regulation further extended the anti-fatigue repertoire. Collectively, natural products possess a solid mechanistic basis for alleviating exercise-induced fatigue via gut microbiota remodeling. The differentiated characteristics of these methods in targeting precision and pathway engagement provide a theoretical foundation for designing precision intervention strategies tailored to specific fatigue contexts.

Humans↗
PubMed2026

Inducible flocculation in Komagataella phaffii enables enhanced biomass separation for biopharmaceutical production.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50 % create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (ScFLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation or gravity sedimentation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY® VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

Flocculation↗
PubMed2026

Identification and formation pathways of oxidation products of chlorinated paraffins during ozonation in municipal wastewater.

Chlorinated paraffins (CPs) cannot be efficiently removed by conventional water treatment processes and are continually discharged into the aqueous environment. Ozonation can effectively remove lipophilic and persistent pollutants. However, the degradation behaviors of short-chain CPs (SCCPs), medium-chain CPs (MCCPs), and long-chain CPs (LCCPs) in wastewater during the ozonation process remained unknown. In this study, ozonation treatment achieved removal efficiencies of 61 % for SCCPs, 66 % for MCCPs, and 51 % for LCCPs from wastewater within 30 min. Approximately 147 oxidative products of SCCPs, MCCPs, and LCCPs were non-targeted identified through Ph4PCl-enhanced ionization with ultra-high performance liquid chromatography-Orbitrap mass spectrometry. These oxidation products were structurally classified into three categories: carbon chain breakage (53 products), HCl-elimination (27 products), and hydroxylation (67 products). Twenty-three di-hydroxylated CPs were newly identified among the products. Hydroxylation was the predominant pathway for SCCPs, producing di-hydroxylated SCCPs ((OH)₂-SCCPs) with a higher generation rate constant (KG = 22.28 × 10⁻² min⁻¹) compared to other products. MCCPs and LCCPs mainly underwent carbon chain breakage and hydroxylation, generating shorter carbon chain congeners, (OH)2-SCCPs, and di-hydroxylated MCCPs ((OH)2-MCCPs). The KG values of (OH)2-SCCPs (10.56 × 10-2 min-1) and (OH)2-MCCPs (12.05 × 10-2 min-1) generated from the MCCPs were the highest, and the KG values of MCCPs (6.49 × 10-2 min-1), SCCPs (6.27 × 10-2 min-1), and (OH)2-SCCPs (4.74 × 10-2 min-1) generated from the LCCPs were higher than those of other products. These results comprehensively clarify the oxidation efficiencies and pathways of CPs during ozonation. Future studies must explore the potential risks associated with the oxidation products.

Water Pollutants, Chemical↗