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PubMed2026

Perinatal depression, maternal thyroid status and fetus/infant health and development: A systematic review.

BACKGROUND: Thyroid hormones are known to influence both maternal depression and child developmental outcomes, while maternal depression independently affects child outcomes. The potential interaction between thyroid dysfunction and depression in shaping child development remains insufficiently explored. The present study addresses such interplay. METHODS: Following PRISMA 2020 and JBI guidelines, three databases were searched through December 2025 for primary studies on maternal thyroid status, perinatal depression, and child development. Risk of bias (RoB) was assessed using validated tools. Due to clinical and methodological heterogeneity, data were synthesized narratively following SWiM guidelines. RESULTS: Eleven studies were included. Beyond independent risks for preterm birth and behavioral problems, limited evidence supports a synergistic model, while most studies likely reflect the simple co-occurrence of risks. Maternal thyroid peroxidase antibodies (TPO-Ab) were associated with child externalizing problems exclusively in the presence of clinical depression. High depressive symptoms also attenuated the cognitive benefits of prenatal iodine supplementation. Thyroid status appears to function as a risk moderator rather than a mediator. However, 50% of observational studies presented high RoB, primarily due to participant attrition. CONCLUSION: Findings are still scarce to support a synergistic risk model where specific maternal thyroid parameters (i.e. thyroid autoimmunity and iodine status) may moderate the impact of depressive symptoms on child development. Despite the high RoB in half of the studies, results highlight the need for integrated screening protocols. Simultaneously assessing mental health and thyroid status may optimize risk stratification for high-risk mother-infant dyads.

Female↗

PubMed2026

The knee-ankle link: impact of knee varus severity on distal joint malalignment and concomitant pathologies.

BACKGROUND: Knee varus deformity is traditionally managed as an isolated joint pathology; however, persistent distal symptoms following proximal realignment suggest a more extensive kinetic chain dysfunction. The degree to which knee varus severity dictates distal malalignment and secondary pathologies remains poorly quantified in the current literature. METHODS: This systematic review and meta-analysis were conducted in accordance with PRISMA 2020 guidelines (PROSPERO: CRD420261363327). A comprehensive search of PubMed, Embase, Web of Science, and the Cochrane Library was performed from inception to April 2026. Studies examining the relationship between knee varus (HKA angle) and radiographic distal alignment or pathologies were included. Data synthesis utilized random-effects models, with prevalence analyzed via generalized linear mixed models (GLMM). RESULTS: Fourteen studies were included in the final synthesis. While pooling of continuous radiographic parameters was limited by high statistical heterogeneity in Talar Tilt (I2 = 96.5%), individual large-cohort data (Huang et al.) indicated that severe knee varus (HKA > 10°) was associated with increased odds of concomitant ankle osteoarthritis (OR 2.29; 95% CI 1.28-4.11) and a specific cohort prevalence of 37.1%. Furthermore, single-arm prevalence data revealed divergent trends across different study populations, with compensatory hindfoot valgus reaching 69.9% in some cohorts and rigid varus up to 63.9% in others. CONCLUSIONS: Severe genu varum is associated with distal kinetic chain alterations and concomitant ankle pathologies. However, due to the extreme heterogeneity and divergent distal adaptations observed across different cohorts, standardized knee-centric protocols may be insufficient. Further longitudinal and interventional studies are required to establish phenotype-specific rehabilitation guidelines.

Humans↗

PubMed2026

Care navigation for older adults after stroke - A systematic review and meta-analyses to guide social prescribing.

INTRODUCTION: Stroke affects many older people worldwide, and patient navigation and social prescribing (e.g., care navigation) may help recovery. We aimed to synthesize evidence on the effect of care navigation for people living with the effects of a stroke (PLWS) on anxiety, depression, quality of life, and well-being. Our secondary focus was to explore these models in rural settings. METHODS: We conducted a systematic review following guidelines, and searched for peer-reviewed randomized controlled trials for older adults (60 years+ or group mean age in this range) who had a stroke and received patient navigation or social prescribing. Two authors independently screened citations at Level 1 (title and abstract) and Level 2 (full text). The date of the last updated search was December 5, 2025. We synthesized data quantitatively using meta-analyses (random effects model and standard mean difference). RESULTS: We identified 11 studies using patient navigation, but no social prescribing interventions. The total number of PLWS participants at baseline was 7829 with an average mean age of 68 years (43% women). There were no differences between groups for anxiety or quality of life for PLWS, but there was a difference favouring the intervention for depression, although the findings were no longer significant with sensitivity analyses. Thus, results should be interpreted with caution. Only two studies provided data for caregivers, with mixed findings. No studies focused on well-being or rural settings. CONCLUSIONS: Care navigation for PLWS needs more research, including testing social prescribing within stroke rehabilitation in rural and urban locations. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2025 CRD420251077958.

Aged↗

PubMed2026

Evaluating a coaching intervention for Dementia Care Practice Recommendations in care communities: a cluster randomized controlled trial.

BACKGROUND AND OBJECTIVES: Within care communities, including nursing home and assisted living settings, person-centered dementia care, outlined by the 2018 Alzheimer's Association Dementia Care Practice Recommendations (DCPR), is foundational to quality care and improving staff outcomes. This study evaluates the effectiveness of a 6-month Care Community Coaching Program in enhancing person-centered dementia care and staff outcomes in alignment with the DCPR. RESEARCH DESIGN AND METHODS: A cluster randomized controlled trial was conducted with 77 care communities and 434 staff members-227 from 38 intervention communities and 207 from 39 control communities. Outcomes included employee satisfaction (areas: job satisfaction, team building and communication, scheduling and staffing, training, and management and leadership), person-centered care practices (areas: workplace practices, individualized care and services, caregiver-resident relationships), and dementia care confidence, measured pre- and post-intervention and at 3-month follow-up. A generalized Estimating Equations model was used to estimate intervention effects. RESULTS: Care communities assigned to the coaching intervention showed statistically significant improvements in employee satisfaction and staff perceptions of workplace practices and individualized care. No statistically significant effects on staff perceptions of caregiver-resident relationships or on dementia care confidence were noted. DISCUSSION AND IMPLICATIONS: Findings provide direction for future research and intervention development, including examining coaching's impact on resident quality outcomes, and incorporating skills training into future models. Collectively, findings provide evidence of the effectiveness of a Care Community Coaching Program in improving staff outcomes and person-centered practices, offering a practical path towards improving the lived experience of residents and staff in care communities.

Humans↗

PubMed2026

Modulating sentence comprehension in people with aphasia through anodal tDCS: A double-blind randomized cross-over study.

This double-blind randomized cross-over study investigated the effects of perilesional anodal transcranial direct current stimulation (AtDCS) combined with speech-language therapy on sentence comprehension in eight individuals with chronic nonfluent agrammatic aphasia. The behavioral therapy consisted of an intensive comprehension treatment including drilling in sentence-to-picture matching and Mapping Therapy. Each participant underwent both the anodal tDCS and sham stimulation conditions (five received sham first followed by real stimulation, and the remaining three the reverse sequence), with each condition paired with the same behavioral treatment and separated by a four-month washout period. Stimulation was applied over the perilesional area (left BA6) for 20 min during daily 40-min therapy sessions over four consecutive weeks. Sentence comprehension was assessed with the RiComprendo battery and functional communication with the Communicative Effectiveness Index (CETI). Data were analyzed using paired t-tests, Bayesian analyses, and linear mixed-effects models to control for baseline performance and individual variability. Both stimulation conditions produced significant pre-to-post improvements in sentence comprehension, particularly for syntactically complex structures such as passives and center-embedded object relatives. However, gains were overall greater following AtDCS, as reflected in larger effect sizes, stronger Bayes factors, and a significant treatment effect in the mixed-effects models. Only the AtDCS condition yielded significant improvements in self-perceived comprehension abilities on the CETI. These findings suggest that AtDCS over perilesional cortical areas may boost the effects of traditional language therapy on sentence comprehension, supporting its feasibility and potential as an adjuvant intervention in post-stroke aphasia rehabilitation.

Humans↗

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

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

Impact of Integrated Continuous Team Midwifery Care on Breastfeeding Success within the Iranian Health System: A Randomized Controlled Trial.

INTRODUCTION: Supporting women during the perinatal period helps build confidence, strengthens early bonding between mother and baby, and encourages successful breastfeeding. Continuous midwifery care models are one of the ways that support women in this periods. OBJECTIVE: This study aimed to evaluate the effect of integrated continuous team midwifery care (ICTMC) in enhancing breastfeeding success in the Iranian health system. METHODS: In this randomized controlled trial, 200 low-risk primiparous women with a gestational age of less than 12 weeks were recruited from public health centers. Participants were randomly assigned to either the intervention group, which received continuous midwifery care throughout pregnancy, childbirth, and postnatal follow-up, or the control group, which received routine care. The primary outcomes were early skin-to-skin contact and breastfeeding success at the time of discharge and at 4-6 weeks postpartum. Data were analyzed using Stata, employing descriptive statistics, Chi-square, independent t-test, Phi/Cramer's V, and Cohen's d. The p < 0.05 is significant. Data were analyzed with SPSS 26. RESULTS: ICTMC groups were significantly more likely to initiate skin-to-skin contactearly skin-to-skin contact immediately after birth (92% vs. 74%, p < 0.001) and achieve successful breastfeeding at the discharge time (88% vs. 70%, p = 0.002) compared to the control group. At 6 weeks postpartum, breastfeeding success remained higher in the intervention group (82% vs. 65%, p = 0.004). CONCLUSION: Women with ICTMC, effectively support skin-to-skin contactearly mother-infant bonding and enhance breastfeeding success among low-risk primiparous women. Integrating this model into routine maternal care may improve perinatal outcomes.

Humans↗

PubMed2026

Integrative machine learning and transcriptomic analysis reveals molecular mechanisms underlying low survival rate in larval Chinese Bahaba (Bahaba taipingensis).

Chinese Bahaba (Bahaba taipingensis) is a Class I protected marine fish endemic to China. Low larvae survival during artificial breeding severely hinder population recovery. To investigate the molecular mechanism of high mortality in larval fish, this study performed RNA-seq on liver from naturally deceased (ND) and mass-dead (MD) individuals, combined with least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms to screen for core signature genes. A total of 873 differentially expressed genes (DEGs) were identified, including 112 upregulated and 761 downregulated genes. GO and KEGG enrichment analyses revealed significant enrichment in amino acid metabolism disorders, one‑carbon folate pool impairment, PPAR signaling abnormalities, ECM-receptor interaction, focal adhesion pathway, indicating widespread metabolic suppression accompanied by extracellular matrix remodeling and signaling disturbances in the livers of MD fish. MAD pre-filtering combined with dual machine learning algorithms yielded 18 robust core signature genes, among which SLC38A4, MMP1, FADD, FKBP5, and APOB were consistently identified as high-frequency core genes by both algorithms. SLC38A4 exhibited the highest importance score in the RF model and was significantly downregulated, making it the primary molecule distinguishing ND from MD phenotypes. ROC curve analysis showed that both models achieved an AUC of 1.000 (95% CI lower bound: 0.610), confirming the precise discriminatory ability of the core genes. GSEA further demonstrated significant enrichment of this core gene set in ND samples. This study provides the first systematic elucidation of the molecular mechanisms underlying liver dysfunction in low survival rate B. taipingensis, characterized by amino acid transport impairment, metabolic reprogramming, and structural remodeling, offering theoretical foundations for health assessment, early mortality risk warning, and artificial breeding conservation of this species.

Animals↗

PubMed2026

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

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

Humans↗

PubMed2026

Diagnostic accuracy of bronchoalveolar lavage fluid-based testing for pulmonary cryptococcosis: A systematic review and meta-analysis.

BACKGROUND: Pulmonary cryptococcosis(PC) presents diagnostic challenges because of its non-specific clinical and radiological manifestations. Bronchoalveolar lavage fluid (BALF)-based testing, which includes latex agglutination (LA) and lateral flow assay (LFA), offers a minimally invasive diagnostic method, yet its pooled diagnostic accuracy remains unclear. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Scopus from inception to May 2026. Studies evaluating BALF-based testing for PC with extractable 2 × 2 data were included. The methodological quality of relevant studies was assessed by the QUADAS-2 tool. Pooled sensitivity, specificity, likelihood ratios, and diagnostic odds ratio (DOR) were estimated using a bivariate random-effects model. Subgroup analyses were performed by testing method and reference standard type. Heterogeneity was evaluated through paired forest plots, HSROC visualization, and exploratory bivariate meta-regression. RESULTS: The pooled sensitivity was 0.87 (95% CI: 0.81-0.91), and the specificity was 0.99 (95% CI: 0.982 - 0.995). The pooled positive likelihood ratio (PLR) was 88.00 (95% CI: 47.39 - 163.42), the negative likelihood ratio (NLR) was 0.13 (95% CI: 0.09 -0.20), and the DOR was 658.50 (95% CI: 285.36-1519.55). No significant threshold effect or publication bias was detected. Exploratory meta-regression suggested a possible assay-method effect in the joint model (P = 0.03), mainly driven by specificity (P = 0.01). CONCLUSIONS: The study demonstrates the high accuracy of CrAg in BALF for the diagnosis of pulmonary cryptococcosis, supporting its role as an important adjunctive diagnostic tool, particularly when tissue biopsy is not feasible or rapid results are needed. Larger prospective studies with standardized protocols are needed to validate these estimates.

Humans↗

PubMed2026

Temporal Trends and Spatial Variation in Preterm Prelabour Rupture of Membranes: A Population-Based Study.

OBJECTIVE: To describe the temporal trends in Preterm prelabour rupture of membranes (PPROM) in metropolitan France and the geographical distribution at the administrative division level. DESIGN: Exploratory population-based study using administrative data of the French National Health Data System. SETTING: Metropolitan France, 2015 to 2023. POPULATION: Pregnancy with a diagnosis of PROM before 37 SA. METHODS: Annual crude incidence of PPROM was calculated by dividing the number of pregnancies with PPROM diagnosis by the number of live births recorded during the same period. Annual trend was estimated by a binomial negative mixed model. Smoothed standardised incidence ratios were estimated based on a BYM2 model, which accounts for spatial variability between departments. MAIN OUTCOME: PPROM cases, defined as pregnancies with first hospitalizations with a diagnosis of PROM before 37 weeks. RESULTS: Over the study period, we included 150 615 PPROM cases representing 16 735 (±596) per year. Incidence of PPROM cases showed an ascending trend over time (incidence rate ratio 1.023 per year; 95% CI: 1.017-1.030) with an annual crude incidence ranging from 2.2% in 2015 to 2.7% in 2023. A decrease in the incidence was observed in 2020 relative to other years (incidence rate ratio 0.903, 95% CI: 0.887-0.920). A map of smoothed SIRs of PPROM cases at the French administrative division level revealed geographical inequalities. CONCLUSIONS: This first population-based study describing PPROM cases in metropolitan France paves the way for further studies to explore environmental hypotheses. Identifying temporal and geographical disparities in PPROM incidence is relevant to public health policy and practice as such disparities argue for the development of targeted prevention strategies in high-risk areas.

French national health data system↗

PubMed2026

Meniscal preservation in the age of biologics: toward a quantitative decision algorithm for personalized repair.

BACKGROUND: Despite advances in arthroscopic repair and biologic augmentation, surgical indication for meniscal tears remains heterogeneous. No standardized framework currently integrates biomechanical, clinical, and biological determinants to guide repair versus resection. PURPOSE: To develop a quantitative decision model-the Meniscal Preservation Score (MPS)-that unifies biomechanical and biological evidence to stratify reparability potential and standardize treatment selection in meniscal surgery. METHODS: A systematic evidence synthesis conducted in accordance with PRISMA 2020 reporting standards of studies published from 2000 to 2025 in PubMed, Embase, and Scopus identified key determinants of meniscal healing. Five consistent predictors-patient age, vascularity, tear morphology, associated pathology, and activity profile-were weighted through a two-round modified Delphi consensus among ten experienced knee surgeons. The resulting 0-9-point MPS was incorporated into a stepwise decision tree linking lesion morphology, biological context, and surgical strategy. Conceptual validation used 50 simulated cases and a retrospective cohort of 45 patients to test agreement between algorithm recommendations and expert surgical decisions. RESULTS: The MPS achieved 86% concordance with expert judgment in simulation and 84% agreement in clinical validation. In this retrospective exploratory cohort, cases in which surgical management was concordant with MPS recommendations demonstrated higher mean IKDC scores at 24 months and lower observed reoperation rates. These findings should be interpreted as associative rather than causal, as treatment allocation was not controlled and discordant cases may have represented inherently more complex pathology. CONCLUSION: The MPS represents an evidence-informed decision-support framework designed to systematize reparability assessment. While exploratory analyses suggest structural coherence with expert reasoning, prospective implementation and external validation are required before clinical adoption as a predictive tool. LEVEL OF EVIDENCE: conceptual model with exploratory validation.

Humans↗

PubMed2026

The combined and independent influence of food texture and a 'mindful eating' instruction on eating rate and food intake among Dutch primary schoolchildren.

Eating rate (ER), the amount of food consumed per unit of time, is a key determinant of food intake, with faster ER associated with larger meal size. Research in adults has shown that both sensory properties like texture, and instructions can influence ER and intake. However, their independent and combined effect on ER and intake in children remain poorly understood. This study examined the effects of food texture and a 'mindful eating' instruction on ER and food intake in children. Children (N = 73), 38 boys, aged 4-12 years, participated in a 4-week cluster-randomized incomplete cross-over study conducted during regular school lunches. Using a 2×3 factorial design, children were exposed to two levels of food texture (softer vs. harder whole-grain buns) and three types of instructions (none, control, 'mindful'). Linear mixed models with repeated measures were used, adjusting for sex and group. As the interaction between food-texture and type of instructions was non-significant, it was excluded from the final models. Results revealed a strong main effect of food texture on ER and food intake (all p < 0.001), where compared with softer buns, harder buns were associated with a slower eating rate (Δ = -6.67 g/min, SE = 0.59) and reduced food intake (Δ = -70 g, SE = 8). In contrast, type of instruction had no significant effect on ER or intake (p = 0.85). Our findings demonstrate that food texture exerts a dominant influence on children's eating rate and food intake, highlighting texture modification as a potential leverage point for influencing ER and intake in children.

Humans↗

PubMed2026

Trends in the Prevalence of Foods High in Saturated Fats, Sodium, and Added Sugars among U.S. adults, NHANES 2007-2018.

BACKGROUND: Foods and beverages high in saturated fats, sodium, and added sugars (HFSS) are often ultra-processed and linked to poor health outcomes, but few studies have investigated their intake. OBJECTIVE: To describe the trends in the intake of HFSS foods and beverages between 2007 and 2018 in a nationally representative sample of U.S. adults, by sociodemographic characteristics and What We Eat in America food groups. DESIGN: This is a secondary, cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2018. PARTICIPANTS/SETTING: The final sample included 27,984 adults 19 years of age or older from NHANES with at least one complete dietary recall. MAIN OUTCOME MEASURES: The primary outcomes are the percentage of total energy intake from foods classified as HFSS according to the Pan American Health Organization (PAHO) Nutrient Profile Model. STATISTICAL ANALYSES PERFORMED: To estimate the percentage of energy intake from foods and beverages HFSS, linear regression models with interaction terms between cycles and covariates were used. RESULTS: The overall intake of foods and beverages HFSS did not change, representing over 60% of the total energy intake between 2007-2010 and 2015-2018. The intake of foods and beverages high in sodium increased by 2.0 percentage points (95% CI: 0.5, 3.5) and 3.5 percentage points (95% CI: 1.1, 5.8), respectively. The intake of foods and beverages high in saturated fats increased by 6.1 percentage points (95% CI: 4.5, 7.6) and 6.1 percentage points (95% CI: 3.9, 8.2), respectively. The intake of foods and beverages high in added sugars did not change. CONCLUSION: In the U.S., intake of HFSS foods and beverages is high. Future research should focus on whether public health interventions and policies might reduce the intake of foods high in nutrients of concern.

Added sugars↗

PubMed2025

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

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

Humans↗

PubMed2026

Effectiveness and moderators of PE and CPT in adult PTSD treatment: a systematic review and meta-analysis.

Background: Posttraumatic Stress Disorder (PTSD) is a prevalent and debilitating condition that challenges mental health services worldwide. Effective psychological interventions are crucial for treatment, among which Prolonged Exposure (PE) and Cognitive Processing Therapy (CPT) are prominent. Comparative analyses of these treatments, considering moderators such as patient demographics and treatment specifics, are necessary to tailor interventions effectively.Objective: This meta-analysis synthesised findings from 175 treatment arms across 163 studies to evaluate the comparative effectiveness of PE and CPT for PTSD. Effect sizes were calculated as Hedges' g for between-group (treatment vs. control) and within-group (pre-post) comparisons.Results: Using a random-effects model, the overall pooled effect size was large (Hedges' g = 1.67, 95% CI [1.56, 1.79]), suggesting substantial treatment-related symptom improvement. Multivariate meta-regression revealed, across the full sample, none of the main effects or interactions was significant. A sensitivity analysis excluding 10 influential outliers reduced the overall effect size (g = 1.55), indicating that PE was associated with larger effects than CPT among non-military samples, and larger effects were observed in studies with a higher proportion of female participants, military samples, and samples with lower proportions of sexual trauma. Treatment-by-sample-characteristic interactions were not significant in the trimmed model.Conclusions: Findings suggest that PE and CPT produce large effects in reducing PTSD symptoms, with some variation across treatment type and sample characteristics. Results underscore the importance of examining contextual moderators such as treatment setting and population type and highlight the need for transparent reporting of key sample features to improve future meta-analytic precision.

Humans↗

PubMed2026

Estrone disrupts early reproductive development in juvenile male Siniperca chuatsi and is associated with brain and gonadal responses.

Whether estrone (E1)-associated disruption of early reproductive development in fish is accompanied by brain responses in addition to direct gonadal effects remains unclear. Here, juvenile Siniperca chuatsi, a non-model but economically important freshwater species, were exposed for 60 d to 0, 0.01, 0.1, and 1.0 μg/L E1, spanning environmentally reported and elevated concentrations. By integrating waterborne concentration monitoring, histopathology, transcriptomics, and quantitative real-time PCR (qPCR) validation, we evaluated E1-associated changes in brain and gonadal tissues during early reproductive development. Waterborne E1 concentrations remained generally stable throughout the exposure period. At the highest tested concentration (1.0 μg/L), E1 caused neuronal vacuolation and pyknosis in the hypothalamic region and induced distinct ovarian-like structures in the gonads of genetic males. In the brain, cyp19a1, crhr1, and adcy2a were significantly upregulated, whereas egr1 was significantly downregulated, indicating transcriptional changes in genes associated with local estrogen conversion, stress-response/cAMP signaling, and neuronal activity-related regulation within a broader injury/stress-response background. In the gonad, RNA-seq analysis showed significant downregulation of star2, hsd3b1, cyp17a1, and cyp11b and significant upregulation of hsd17b1, suggesting alterations in steroidogenesis-related gene expression at the transcriptomic level. qPCR analysis of selected gonadal candidate genes showed expression directions generally consistent with the RNA-seq results, and these molecular patterns were consistent with the feminized histological phenotype. Together, these results indicate that E1 can disrupt early reproductive development in juvenile S. chuatsi and support a cautious working model in which E1 exposure is accompanied by concurrent brain and gonadal responses. This study provides new evidence for understanding the toxic effects and ecological risk implications of natural estrogen E1 during early fish development.

Animals↗