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PubMed2026

Diagnostic accuracy of nuclear STAT6 immunohistochemistry for solitary fibrous tumour: a systematic review and meta-analysis.

Nuclear STAT6 immunohistochemistry is the diagnostic surrogate for the NAB2::STAT6 fusion of solitary fibrous tumour (SFT); its sensitivity is established, but specificity varies for unexamined reasons. This review quantified pooled accuracy and tested whether antibody clone and nuclear threshold govern specificity. PubMed, Scopus and Web of Science were searched to 29 June 2026 for studies reporting nuclear STAT6 immunohistochemistry against a reference standard (NAB2::STAT6 confirmation and/or expert consensus) in SFT and comparators, with extractable two-by-two data. Two reviewers screened, extracted data and applied QUADAS-2. A bivariate generalised linear mixed model gave summary sensitivity and specificity, and exploratory subgroup analysis and meta-regression tested antibody clone, anatomical site and reference-standard type. Twenty-three studies (1216 SFT and 4715 comparators) were included. Summary sensitivity was 98.7% (95% confidence interval 96.7-99.5) and specificity 99.1% (97.8-99.6); the diagnostic odds ratio was approximately 8656. The monoclonal YE361 subgroup (8 studies) reached specificity 99.9% (99.3-100), with one false positive among 861 comparators, versus 98.1% (96.0-99.1) for polyclonal and other antibodies. False positives concentrated in dedifferentiated liposarcoma and prostatic stromal tumours. Estimates were stable after removing studies at higher risk of bias (98.9%/99.1%) and on leave-one-out analysis; the Deeks test was non-significant (p = 0.08). Nuclear STAT6 immunohistochemistry is therefore highly sensitive and specific for SFT, and the residual specificity loss is structured and largely avoidable: the monoclonal YE361 read at a strict nuclear threshold is preferred, with MDM2 and CDK4 applied to exclude dedifferentiated liposarcoma when nuclear STAT6 is unexpectedly positive.

Humans↗

PubMed2026

Getting to the Core of the Matter-Assessing the Role of Replication in Metabarcoding-Based sedaDNA.

Replication is central to most experimental and sampling designs, increasing inferential power and capturing fine-scale data heterogeneity. However, its importance remains poorly evaluated in some ecological and evolutionary settings. This is the case of metabarcoding studies using DNA recovered from sedimentary archives, in which biological signals integrate ecological information through depositional and burial processes, yet are commonly inferred from a single sediment core per site. Here, we evaluated the effect of different types of replication using sedimentary DNA metabarcoding data from two genetic markers (mitochondrial COI and nuclear 18S) using a nested sampling design. The design included three intertidal sites, three spatially separated sediment cores per site (biological replicates), two sediment horizons per core, and eight PCR (technical) replicates per sediment sample. Variance partitioning showed that site identity and sediment age group together explained > 70% of the variation in beta diversity, indicating that among-site spatial and stratigraphic differences were the dominant drivers of community composition. PERMANOVA likewise identified non-significant effects of biological replication. Among PCR replicates from the same sediment sample, richness varied substantially, whereas Shannon diversity was more consistent. Despite this variability, differences in community composition among technical replicates remained smaller than those associated with biological replication or site identity, indicating a limited influence on broader ecological patterns. Community composition was highly similar among replicate cores within sites, consistent with stratigraphic coherence. These results indicate limited within-site heterogeneity and suggest that, under stratigraphically coherent conditions, increasing biological replication may provide little additional information, whereas enhancing technical replication and stratigraphic resolution can improve ecological inference from sedimentary DNA metabarcoding datasets.

DNA Barcoding, Taxonomic↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

Adjuvant CDK4/6 inhibitors in early-stage breast cancer: Clinical evidence and considerations for risk stratification and treatment selection.

Hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer is the most common biologic subtype and carries a persistent risk of recurrence, particularly in patients with high-risk, early-stage disease. Cyclin-dependent kinase 4 and 6 inhibitors, initially established as a standard component of first-line therapy in the metastatic setting based on improvements in progression-free and overall survival, have since been evaluated in the adjuvant setting. While adjuvant palbociclib did not improve invasive disease-free survival, the monarchE and NATALEE trials demonstrated that abemaciclib and ribociclib, respectively, reduce recurrence risk in patients with high-risk, early-stage disease, with emerging overall survival data further supporting their use. However, the absolute magnitude of benefit varies substantially with baseline risk, and treatment-related toxicity and adherence challenges must be considered, as approximately 20% to 25% of patients discontinue therapy before completion. The integration of these agents into clinical practice also intersects with ongoing efforts to deescalate axillary surgery, as treatment eligibility has been largely defined by anatomic staging, particularly nodal status. Available data suggest that the incremental impact of axillary surgery on identifying candidates for cyclin-dependent kinase 4 and 6 inhibition is modest, especially among the favorable-risk populations now eligible for surgical deescalation. As the field evolves, advances in molecular risk stratification, genomic profiling, and dynamic biomarkers are poised to shift treatment selection from anatomic staging toward biologically driven approaches. Multidisciplinary decision-making that integrates tumor biology, anticipated absolute benefit, toxicity, patient preferences, and surgical considerations will be essential to ensure individualized care.

Humans↗

PubMed2026

An oxidative stress - and immunotherapy-related six-gene signature defines immune subtypes and predicts prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Oxidative stress and the tumor immune microenvironment jointly shape hepatocellular carcinoma (HCC) progression and response to immunotherapy, yet integrated biomarkers linking these processes are lacking. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify oxidative stress- and immunotherapyrelated differentially expressed genes (OSIRDEGs). Functional enrichment, weighted gene co-expression network analysis (WGCNA) and LASSO-Cox regression were used to construct a prognostic signature. Consensus clustering, TIDE, CIBERSORT and ssGSEA characterized immune phenotypes. Somatic mutation, copy-number and drug-response data were integrated to assess genomic alterations and drug sensitivity. Expression of model genes was validated by qRT-PCR and western blotting in HCC cell lines. RESULTS: We identified 24 OSIRDEGs enriched in cell-cycle and mitotic pathways. WGCNA intersection yielded 18 module genes, from which a six-gene signature (BUB1B, CDKN2A, CENPE, HMMR, PTTG1, SPP1) was derived. The signature robustly stratified patients into high- and low-risk groups with significantly different progression-free and disease-free survival in both TCGA-LIHC and GSE14520. Based on signature expression, two molecular subtypes were defined, exhibiting distinct survival, immune landscapes and predicted immunotherapy responsiveness. Model genes harbored recurrent alterations and showed significant correlations with anticancer agents. All six genes were upregulated at mRNA and protein levels in metastatic HCC cell lines versus normal hepatocytes. CONCLUSIONS: We systematically explored the landscape of OSIRDEGs in HCC, and proposed a validated six-gene signature that refines prognostic stratification, delineates immunerelevant HCC subtypes and highlights candidate biomarkers for therapeutic selection and mechanistic investigation.

Humans↗

PubMed2026

From commensal to pathobiont: The emergence of virulence-enhanced Escherichia coli in China's food-animal systems - insights with future implications.

A fundamental shift in Escherichia coli epidemiology is being driven by convergence of virulence determinants and antimicrobial resistance within linked human-animal-environment systems. In China, the rapid growth of food-animal production, extensive antimicrobial use, and complex food networks are accelerating the emergence and dissemination of virulence-enhanced E. coli pathobionts. This review synthesizes recent epidemiological, genomics, and outbreak data to characterize China's evolving landscape of food-animal-associated E. coli. We highlight a significant shift from classical pathotypes to hybrid lineages that simultaneously carry virulence factors and last-resort antibiotic resistance determinants, including mcr-1, tet(X4), and blaNDM. These traits disseminate rapidly via plasmid-mediated horizontal gene transfer, facilitating rapid adaptation and enabling cross-sectoral One Health transmission. National surveillance, foodborne outbreak investigations, and whole-genome sequencing data show that food-animal reservoirs are active evolutionary niches that drive pathogen diversity and fitness, rather than serving merely as contamination sources. Whole-genome sequencing also pinpoints high-risk clones (e.g., ST394) and plasmid-mediated co-selection of virulence and AMR. The emergence of hybrid pathotypes (e.g., STEC/ETEC) and AMR-virulence co-selection challenges traditional classification and limits the effectiveness of conventional surveillance approaches. The 2017 colistin ban reduced mcr-1, yet ongoing resistance and emerging tet(X4) demand integrated surveillance. Collectively, these findings call for reconceptualizing E. coli as a dynamic genomic entity embedded within a unified ecological network. Addressing this threat requires an integrated One Health strategy including genomic surveillance, agricultural antimicrobial stewardship, and coordinated food-environment-clinical monitoring to prevent high-risk clone emergence and global spread.

Animals↗

PubMed2026

A qualitative study of cancer survivors' exercise behaviour 4 months after a telerehabilitation program.

PURPOSE: Although telerehabilitation can improve access to exercise programs for cancer survivors, it is not known if these programs lead to ongoing change in exercise habits. This study explored participant experiences of exercise 4 months after finishing specialized cancer exercise-based telerehabilitation. METHOD: A qualitative study embedded in a randomized controlled trial evaluated exercise-based cancer telerehabilitation delivered in groups. Data were collected via semistructured interviews that were audio-recorded and transcribed verbatim. Seventeen adult cancer survivors (age 21 to 80) were purposively sampled 4 months after completing exercise-based cancer telerehabilitation. Data were coded independently by two researchers and analyzed inductively within an interpretive description framework. RESULTS: The overarching theme was telerehabilitation was perceived to facilitate positive exercise intentions. Participants said they were empowered to exercise through knowledge, opportunity, and connection gained through telerehabilitation. They described acting on their positive intentions to exercise to varying degrees following telerehabilitation, depending on their context. A subtheme was that exercise was challenging in their new reality created by cancer. Comorbidities, ongoing side effects, previous exercise experience, and personal factors were considered by some to influence their ability to exercise. CONCLUSION: Telerehabilitation may facilitate positive intent to maintain exercise. Cancer survivors may need ongoing support after telerehabilitation to act on positive exercise intentions due to health-related difficulties. IMPLICATIONS FOR CANCER SURVIVORS: Participation in telerehabilitation may be a positive first step to initiate exercise, but ongoing support to maintain positive behavior changes is likely to be needed for people without previous exercise experience.

Humans↗

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

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans↗

PubMed2026

Costs of surgeries in low- and middle-income countries: a systematic literature review.

BACKGROUND: Surgical care is essential for achieving global health equity, yet low- and middle-income countries (LMICs) face major gaps in access and planning, partly due to limited evidence on the costs and resource requirements of surgical interventions. Understanding these costs is vital for designing efficient and equitable health systems. METHODS: We conducted a systematic literature review (covering MEDLINE, EMBASE, Global Health, EconLit and grey literature) to identify studies reporting the costs of surgeries in LMICs from January 2000 to June 2023. Minor and major surgical procedures were considered, focusing on therapeutic procedures (excluding diagnostic interventions). Studies that clearly identified, quantified and costed hospital resources and services deployed in the provision of surgical care, and included at least two of the surgical production factors (ie, consumables, diagnostics, personnel, infrastructure and overhead) in the costing were included. Costs were standardised to 2023 International dollars (I$) for comparability. RESULTS: A total of 74 studies from 29 countries met the inclusion criteria, with 210 cost estimates across 65 procedure groups. Costs varied widely: from I$1.54 for a caesarean section in Tanzania to I$618 098 for paediatric cataract surgery in Zambia. Full costing studies reported higher estimates than partial costing studies. Most studies (60%) originated from upper-middle-income countries, with limited data (10%) from low-income settings. CONCLUSION: This review provides a reference list of surgical procedure costs across LMICs, highlighting considerable cost variation by procedure, specialty and country. The findings underscore the need for better-quality, standardised cost data-especially from low-income countries-to inform national surgical plans, universal health coverage benefit packages and reimbursement policies.

Developing Countries↗

PubMed2026

Genomic science and the nurse educator's role: Promoting integration from curriculum to clinical practice.

BACKGROUND: Registered nurses and nurse educators play a critical role in preparing future clinicians to translate genomic discoveries into practice. However, emerging evidence suggests that both groups may lack sufficient knowledge and confidence in genomics, potentially limiting their ability to teach, mentor, and apply genomics in real-world settings. This gap is especially concerning in Aotearoa New Zealand, where the genomic literacy of nurse educators and clinicians remains underexplored. OBJECTIVE: This study aims to: (1) assess nurse educators' genomic literacy and confidence in teaching genomics; and (2) evaluate registered nurses' knowledge and confidence in applying and teaching genomics in clinical practice. DESIGN: Exploratory descriptive qualitative. SETTING: This study was conducted in the greater Auckland area. PARTICIPANTS: A total of 17 participants were recruited using purposive sampling to ensure a diverse range of perspectives across varying levels of teaching experience, disciplinary backgrounds, and exposure to genomic content. METHODS: Data were collected using semi-structured focus group interviews, a method well-suited for generating in-depth discussion and facilitating interaction among participants with shared professional interests. The collected data were analysed using thematic analysis methods. RESULTS: The findings offer insight into the preparedness of New Zealand's nursing workforce to engage with genomic-informed healthcare and inform strategies for integrating genomics into nursing curricula and continuing professional development. Given the interdisciplinary nature of genomic healthcare, these insights may also be relevant to other health professionals-including midwives, pharmacists, and allied health practitioners-who increasingly encounter genomic information in clinical practice and require foundational competencies to support patient care. CONCLUSION: Addressing this educational gap is critical to ensuring that nurses-key facilitators of patient care and public health-are equipped to deliver safe, equitable, and evidence-based genomic healthcare.

Humans↗

PubMed2026

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence↗

PubMed2026

Retinal microstructural alterations as early phenotypes of depression in radiogenomics analysis.

BACKGROUND: With the increasing prevalence of depression, there is an urgent clinical need for early screening in depression. The retina offers a promising window for early screening in depression due to its rapid, non-invasive, objective, eye-brain correlated characteristics, but previous research has yielded conflicting alterations in retinal microstructure in depression. METHODS: We screened retinal optical coherence tomography and brain magnetic resonance imaging data in the UK Biobank to enroll 23,225 participants for retinal study of depression occurrence, and 1475 participants for the eye-brain association study. We also used genetic data (ID: ebi-a-GCST90014267 and ukb-d-20,448) from the Integrative Epidemiology Unit Open Genome-Wide Association Study for Mendelian randomization analysis. We used Cox regression to assess the association between retinal microstructure and depression risk, Mendelian randomization to infer causality, and mediation analysis to explore retina-brain pathway association. RESULTS: The Cox regression analysis showed that retinal ganglion cell-inner plexiform layer (GCIPL) thickness remained a significant predictor of depression. The Mendelian randomization analysis indicated a positive statistical association between GCIPL thickness and depression. Moreover, there was a significant positive correlation (all p < 0.001) between the volume of specific depression-related brain regions and the GCIPL thickness. Adjusting for age, sex, and head size, the mediation analysis provided preliminary evidence for a potential anatomical pathway linking retinal GCIPL thickness to depression-related brain regions through primary visual cortex and secondary visual cortex volumes. CONCLUSION: Thickened retinal GCIPL is a potential early phenotype of depression and has a potential association pathway with depression-related brain regions using a radiogenomics approach.

Humans↗

PubMed2026

Role of nicotine metabolite ratio in pharmacological interventions on smoking cessation: A systematic review and meta-analyses of randomized controlled trials.

BACKGROUND AND OBJECTIVES: Emerging evidence suggests that the nicotine metabolite ratio (NMR) may influence the efficacy of smoking cessation, yet its role across pharmacotherapies remains unclear. This study aims to investigate how NMR affects cessation outcomes under different medications to guide personalized treatment. METHODS: We searched PubMed, Medline, EMBASE, and the Cochrane Central Register of Controlled Trials (inception to September 30, 2024) for randomized controlled trials on pharmacotherapy for smoking cessation with NMR data. Data were synthesized using random-effects models, with heterogeneity assessment. The primary outcome was verified smoking cessation rate at the end of treatment or the closest time-point. RESULTS: Eleven RCTs with accessible full text were included in the qualitative analyses and nine were included in the quantitative synthesis. For non-titratable nicotine replacement therapy (NRT), normal/fast metabolizers demonstrated lower odds of smoking cessation than slow metabolizers (Odds Ratio, OR=0.81, 95% confidence interval, CI=0.68-0.96; 5 studies, I²=62.5%). No significant associations were shown between normal/fast and slow metabolizers using titratable NRT (OR=1.04, 95% CI=0.95-1.14; 2 studies, I²=0%), bupropion (OR=0.67, 95% CI=0.38-1.16; 2 studies, I²=51.4%), or varenicline (OR=1.17, 95% CI=0.79-1.74; 4 studies, I²=59.8%). CONCLUSION: Current evidence demonstrates that NMR moderates' treatment efficacy among those who smoke using non-titratable NRT, with slow metabolizers achieving significantly better cessation outcomes than normal/fast metabolizers. Substantial further research is needed to determine optimal medication hierarchies across metabolic profiles.

Humans↗

PubMed2026

Complementary feeding patterns in preterm and term infants.

Complementary feeding is essential for infants' nutritional status and development, marking the transition to solid foods when breast milk or formula alone is insufficient. Despite its importance, clear recommendations on which foods to introduce when initiating complementary feeding in preterm infants are lacking. By using data from our previously published randomized controlled trial on the timing of complementary feeding in preterm infants, the current study explores the complementary feeding patterns of preterm infants and compares them with those of term-born infants, providing insights into parental decision-making and potential long-term health impacts. Complementary feeding practices differed significantly between preterm (n = 255) and term (n = 159) infants, with preterm infants more often receiving vegetables as their first solid food (85.4% versus 68.8%, difference 17.6% with 95% CI 12-35%). The group with early introduction of vegetables had a lower BMI-for-age z-scores (β -0.28 [95% CI -0.55 - 0.02]) and weight-for-height z-scores (β -0.27 [95% CI -0.53 to -0.01]) at two years of age. Additionally, preterm infants showed a greater variety in the numbers of different fruits and vegetables consumed by six months (corrected) age than term-born counterparts (8.29 (SD 3.65) versus 6.26 (SD 3.47), p < 0.001). These results indicate that complementary feeding patterns in preterm infants differ from term-born infants, with potential positive implications on growth. These data contribute to the development of accurate feeding protocols for preterm infants. Given that feeding practices are culturally influenced, further multinational research is essential to refine complementary feeding guidelines for preterm infants and support caregivers in informed decision-making.

Humans↗

PubMed2026

Relational care in community mental health: Evaluating staff experiences in Intensive Community Care Services (ICCS) vs treatment as usual.

BACKGROUND: The quality of healthcare delivery relies heavily on building strong relationships between healthcare providers (HCPs) and clients. This study presents the results of a process evaluation for a Randomised Controlled Trial (RCT) examining the effectiveness of Intensive Community Care Service (ICCS) vs Treatment as Usual (TAU; inpatient or core community CAMHS). METHODS: Thirty-four semi-structured interviews were conducted with staff across various services, including 20 from ICCS and 14 other TAU services. A thematic decomposition analysis was conducted on the data, and specific themes relevant to staff experiences of young people's engagement with services and overall recovery. RESULTS: Three main themes were observed in the HCP data (1. Relational Ecologies: barriers and enablers to engagement, 2. flexibility of approach amidst systemic pressures and 3. the web of trust in the relationship-building process). HCPs highlighted the necessity of developing trust and rapport through non-clinical engagement strategies, such as informal visits and personalised interactions. HCPs emphasised that without trust, treatment effectiveness diminishes, necessitating a tailored approach rather than a one-size-fits-all model. The flexibility in duration of treatment and methods of engagement was noted as crucial in accommodating individual client needs and fostering an open, trusting environment necessary for long-term recovery. CONCLUSION: The findings highlight the vital importance of relational care models, especially ICCS, in addressing the complex needs of Children and Young People (CYP). Flexible, family-centred approaches improve trust, engagement, and long-term recovery outcomes. Recommendations include tackling systemic barriers and expanding relational care models within CAMHS to meet increasing mental health demands effectively. Further research should investigate scalable strategies for integrating these insights into wider mental health service frameworks.

Humans↗

PubMed2026

Genetic Ancestry and Carrier Variant Frequency Enrichment in a Colombian Andean Population: Insights From the Eje Cafetero.

Colombia is one of the most genetically diverse populations in Latin America, and its demographic process has promoted the persistence and local enrichment of deleterious alleles, increasing the frequency of autosomal recessive disorders, particularly in semi-isolated Andean populations such as the Eje Cafetero. However, exome-based reference data from this region remain scarce, limiting ancestry-aware variant interpretation and carrier screening strategies. We aimed to characterize the ancestry proportions of this population using exome data, and to estimate the carrier frequency and distribution of pathogenic and likely pathogenic (P/LP) variants in clinically relevant recessive genes. We conducted a cross-sectional study with whole-exome sequencing (WES) in 316 unrelated individuals from the Colombian Eje Cafetero. P/LP variants were evaluated in 454 genes associated with autosomal recessive disorders. The global ancestry proportions were estimated using a validated panel of 250 exome-compatible ancestry-informative markers. Carrier frequencies were compared against Non-Finnish Europeans (NFE) and Admixed Americans (AMX) from gnomAD v4. The cohort showed predominant European ancestry (mean 51%), followed by Native American (36%) and African (13%) components. We identified 151 carriers of 89 distinct pathogenic variants across autosomal recessive genes. The most frequent variants were SERPINA1 c.863A>T (5.5%), CFTR c.1210-11T>G (3.5%), and PYGM c.1094C>T (1.5%). Also, recurrent variants were significantly enriched compared with both NFE and AMX populations, supporting regional founder effects. This study represents one of the most comprehensive exome-based genetic characterizations of the Colombian Eje Cafetero, revealing ancestry-specific enrichment of clinically relevant autosomal recessive variants driven by founder effects.

Female↗

PubMed2026

Water intake, switching between bites and sips, and drinking behavior are associated with food intake across meals varying in spiciness: A secondary analysis of two randomized crossover studies.

Widespread nutrition advice instructs consumers to drink water with meals to increase fullness and reduce energy intake. However, recent data indicates greater water intake is associated with more food intake at a meal, not less. Switching between meal components (e.g., alternating between food and water), has also been associated with increased food intake at a pasta meal, but it remains unclear whether this applies to other foods. In a secondary analysis, we pooled existing data from 2 crossover experiments (total n = 86) where adults ate an ad libitum lunch consisting of 650 g of beef chili (n = 52) or chicken tikka masala (n = 34) with 450 g of water twice in the laboratory while being video-recorded. For both experiments, the spiciness of the lunch was varied by adding different ratios of hot:sweet paprika. Videos were coded to measure sip number, sip size (g/sip), drinking rate (g/min), and number of switches between bites of food and sips of water. As we previously reported, increasing spiciness slowed eating rate and reduced food intake; in secondary analyses described here, the reduction in food intake was not moderated by water intake, switching, or drinking behaviors (all p > 0.73). Notably, across all meals, greater water intake (p < 0.001) and switching (p = 0.02) associated with greater food intake. Overall, individuals ate more when they drank more and switched between bites and sips more often, highlighting the potential influence of water and drinking behaviors on food consumption. This finding challenges the widespread dietary advice to drink water with meals to reduce food intake.

Humans↗