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Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

Humans

Visualizing the future: impact of holographic visualization on teaching minimally invasive veneer preparation: a randomized controlled trial.

BACKGROUND: Minimally invasive veneer preparation in prosthodontic education requires advanced spatial understanding and psychomotor precision. Although immersive technologies are increasingly used in dental education, evidence regarding the educational effectiveness of holographic visualization in prosthodontics remains limited. This randomized controlled trial evaluated the impact of holographic visualization on preparation quality and student-reported educational outcomes during preclinical training in minimally invasive veneer preparation. METHODS: Sixty undergraduate dental students were randomly assigned to receive either conventional two-dimensional photographic visualization (n&#x2009;=&#x2009;30) or holographic three-dimensional visualization (n&#x2009;=&#x2009;30). Following a standardized calibration session and baseline preparation, participants performed a second veneer preparation after exposure to the assigned visualization modality. Preparations were independently assessed by two blinded evaluators using a predefined scoring rubric. Within-group changes were analysed using Wilcoxon signed-rank tests, and between-group differences were assessed using analysis of covariance adjusted for baseline performance. Student-reported outcomes were compared using Mann-Whitney U tests with false discovery rate correction. RESULTS: Both groups showed significant improvements in preparation quality from baseline to post-intervention (both p&#x2009;<&#x2009;0.001). However, no significant between-group differences were observed (adjusted mean difference: 0.60 points; 95% confidence interval: -0.48 to 1.67; p&#x2009;=&#x2009;0.269). Overall student-reported outcomes were comparable between groups. Spatial understanding showed the largest between-group effect in favour of holographic visualization, although this difference was not significant after correction for multiple comparisons. Holographic visualization was highly accepted by students, and 70% supported its future integration into dental education. CONCLUSIONS: Although holographic visualization did not significantly improve immediate preparation quality compared with conventional two-dimensional photographs, it was highly accepted by students and showed the largest observed effect for perceived spatial understanding. These findings suggest that holographic visualization may primarily support spatial understanding and represent a valuable adjunct for teaching complex three-dimensional concepts in preclinical prosthodontic education. TRIAL REGISTRATION: German Clinical Trials Register (DRKS), DRKS00040713, prospectively registered on 22 June 2026.

Humans

Open Dialogue versus treatment as usual for adults presenting in crisis to mental health services in England (the ODDESSI Trial): a multisite cluster-randomised trial.

BACKGROUND: Open Dialogue is a person-centred, transdiagnostic model of mental health care that emphasises continuity, therapeutic relationships, and collaboration with the service user's social network. Open Dialogue is a service-wide approach to care involving network meetings with the service user, members of their social network, and usually two practitioners who support the network throughout the duration of care. In this cluster-randomised trial, we aimed to evaluate the clinical effectiveness of Open Dialogue versus treatment as usual for adults presenting in crisis to community mental health services in England. METHODS: This multicentre, parallel two-arm, cluster-randomised, controlled superiority trial was conducted in mental health services in five National Health Service trusts in London and the South of England. Clusters were defined at the level of primary care practices within service catchment areas. Participants were adults aged 18 years or older presenting in crisis to mental health services and registered with a practice within trial clusters. Randomisation was done at the cluster level (1:1), stratified by catchment area, and balanced on average general practice (GP) list size and Index of Multiple Deprivation (2015). The chief investigator, senior statistician, and assessors of the primary outcome were masked in the study. Participants either received Open Dialogue or treatment as usual, which refers to the functional team model currently implemented throughout English mental health services. The primary outcome was time (days) to first relapse following initial recovery from the index crisis censored at the end of the 2-year follow-up period. Participant-reported secondary outcomes were EuroQol Visual Analogue Scale, Social Provisions Scale, Lubben Social Network Scale, Questionnaire about the Process of Recovery, and the Client Satisfaction Questionnaire, measured at five timepoints over 2 years, and clinical measures were extracted from electronic health records. People with relevant lived experience were involved in the design and execution of the study. Fidelity to the model of care in Open Dialogue and treatment as usual, and adherence to the delivery of Open Dialogue, were measured prior to each site starting participant recruitment, then every 6 months thereafter until the final participant follow-up in that site. The trial was retrospectively registered (ISRCTN52653325) and is complete. FINDINGS: 185 general practices associated with six mental health Trusts across England were identified for screening. 105 practices were excluded, and 80 were included in cluster formation, forming 32 clusters that were randomly assigned (16 to treatment as usual and 16 to the Open Dialogue intervention). One mental health trust (two clusters) withdrew, resulting in five mental health trusts (30 clusters) participating in the trial. Between June 25, 2019, and Dec 9, 2021, 494 participants (266 [54%] female gender, 221 [45%] male gender, 341 [69%] White British) with a mean age of 38&#xb7;1 years (SD 13&#xb7;4) provided consent for study inclusion (223 in the treatment as usual group and 271 in the Open Dialogue group). Of these, 174 (78%) in the treatment as usual group and 225 (83%) in the Open Dialogue group recovered and had data enabling relapse determination; there was no significant difference between groups on the primary outcome of time to relapse following initial recovery (marginal hazard ratio 0&#xb7;95 [95% CI 0&#xb7;67-1&#xb7;32]). For secondary outcomes, Open Dialogue was associated with significantly lower probabilities of psychiatric inpatient admission and re-referral to crisis care or secondary mental health services, and with improvements in self-rated recovery, health-related quality of life, and satisfaction with services. There were no significant differences in social network quality or size. There were 386 serious adverse events (281 in the treatment as usual group and 105 in the Open Dialogue group); 376 (97%) were deemed to be unrelated to the intervention. INTERPRETATION: Open Dialogue did not reduce time to first relapse compared with treatment as usual, the primary outcome, but it reduced acute inpatient bed use, improved service user reported outcomes and experience, and there were no significant safety concerns. Further investigation is required to determine whether Open Dialogue can enhance the effectiveness and acceptability of crisis care and continuing care in community mental health services. FUNDING: National Institute for Health Research.

Humans

A Qualitative Analysis of Cancer Survivors' Experience in a Time-Restricted Eating vs Control Clinical Trial to Address Cancer-Related Fatigue.

PURPOSE: To describe cancer survivors' lived experiences in a clinical trial that tested an individualized nutrition counseling with or without time-restricted eating to address cancer-related fatigue. METHODS: The Fatigue REDuction After cancer study was a two-arm, randomized controlled trial. Participants were adult cancer survivors who were 2 months to 2 years post-treatment. All participants received individualized nutrition counseling; those in the time-restricted eating group self-selected a consistent 10-hour eating window for 12 weeks. After the study, semi-structured exit interviews were conducted to gauge participants' experiences in the trial. Interviews were transcribed and two independent coders thematically analyzed the interviews using inductive and deductive coding. NVivo software was used for data organization and analysis. RESULTS: Participants (n&#x202f;=&#x202f;24; TRE&#x202f;=&#x202f;11; Control&#x202f;=&#x202f;13) were 55 &#xb1; 13 years old, 75% were female, and they had a variety of cancer types. The majority of participants found that being in the study helped them to set and achieve lifestyle goals and would therefore recommend the study to others. Participants in the time-restricted eating group noted that time-restricted eating helped them set a better routine, providing a positive sense of control. However, some noted difficulty switching to a 14-hour fasting schedule, as it can interfere with their regular routine or employment schedules. Many participants noted they were happy that cancer-related fatigue was gaining more attention, hoping to find solutions for persistent cancer-related fatigue. CONCLUSION: The majority of participants found the study useful and, regardless of their group assignment or the intervention's impact on their fatigue, found the study helped them to gain better control of their dietary habits.

Humans

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans

Interventions to Reduce Loneliness in Informal Caregivers of People With Dementia: A Systematic Review.

AIM: To summarize the current evidence on reducing loneliness among informal caregivers of people with dementia, such as family members or friends. DESIGN: A systematic review. METHODS: The methodological quality was evaluated using the revised Cochrane risk-of-bias tool for randomized controlled trials and the revised JBI critical appraisal checklist for quasi-experimental studies. Data were extracted as predefined and synthesized narratively. The Template for Intervention Description and Replication checklist was used to report the intervention characteristics. DATA SOURCES: Six electronic databases (MEDLINE via PubMed, EMBASE, Cochrane Library, PsycINFO, CINAHL Plus, and Web of Science Core Collection) were searched for studies published in peer-reviewed English journals from the inception of each database until 28 January 2024. RESULTS: Eight studies were included in this review, published between 2002 and 2023, with three being randomized controlled trials. All included interventions were psychosocial. Only one study reported significant improvements in loneliness. Five studies utilized remote and online interventions, such as social networking, psychotherapy, and online social support. Interventions varied in their impact on secondary outcomes, including stress, depressive symptoms, anxiety, and caregiver burden. Four studies demonstrated a positive effect on caregiver stress levels. One pilot trial reported a positive impact on depressive symptoms, and another study noted potential improvements in anxiety. One pilot study reported an average improvement in caregiver burden. CONCLUSION: While the evidence is insufficient for conclusive statements, this systematic review suggests potential benefits of interventions to reduce loneliness and improve mental health among these caregivers. It highlights the promise of remote interventions in addressing loneliness among dementia caregivers. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: The findings suggest that tailored interventions, especially those delivered remotely, can enhance the support provided to caregivers, potentially improving their mental health and overall well-being. REPORTING METHOD: This systematic review adhered to the PRISMA statement. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Humans

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models

How do women with a history of childhood sexual abuse experience the preconception and perinatal period? A qualitative systematic review.

CONTEXT: Child sexual abuse (CSA) is a public health issue that predominantly affects women and has both short- and long-term consequences. The perinatal period can represent a challenge, but also an opportunity to identify a history of CSA and to provide sensitive care that may help prevent the intergenerational transmission of trauma. AIM: To describe and understand the experiences and coping strategies of women who are survivors of child sexual abuse and are transitioning to motherhood. METHOD: We conducted a systematic review of qualitative studies according to a protocol registered in PROSPERO, following methodological standards and reporting the results according to the ENTREQ guideline. A search was conducted on five databases up to July 2025. Two authors independently selected the articles and assessed their methodological quality. Data were analysed using thematic synthesis and the confidence in the findings was evaluated according to GRADE-CERQual. RESULTS: We included 21 qualitative studies that resulted in six themes. The findings reveal how women who experienced child sexual abuse and are transitioning to motherhood may experience this stage with ambivalence-ranging from revictimisation to identity reconstruction-where perinatal care emerges as a potential healing vehicle throughout this process. CONCLUSIONS: The perinatal period becomes a window of opportunity to heal deep wounds, with perinatal care playing a key role. The findings support trauma-informed perinatal care, underpinned by reflective practice and a holistic approach. Further work is needed to improve the identification of child sexual abuse, enhance professional training and review current practices to ensure sensitive care.

Humans

Applications of metal-organic frameworks in smart packaging for food freshness indication: a comprehensive review.

Smart packaging is extensively studied for its multifunctional capabilities in antimicrobial activity, preservation, and atmosphere modification. Recently emerged metal-organic frameworks (MOFs) freshness-indicating packaging becomes a key research direction in smart packaging owing to its distinctive functions and physicochemical properties. As multifunctional materials, the unique porous structure and tunable properties of MOFs provide a distinctive approach for developing food packaging applications dedicated to food freshness indication. Existing MOFs-based smart packaging still faces potential safety risks and technical challenges in practical applications, and there remains a lack of integrated discussion that combines synthesis strategies, packaging design, optimization, and safety assessment. This review elaborates on the application of MOFs in freshness-indicating smart packaging, focusing on diverse MOFs synthesis strategies, the formats of smart packaging, types of indicator signals, and qualitative/quantitative analytical methods. It also delves into the methodology concepts of MOFs-based smart packaging and evaluates MOFs safety in food packaging by addressing potential risks. Studies show that MOFs-based smart packaging achieves qualitative and semi-quantitative analysis of food freshness through multiple signal modalities such as visible color change, fluorescence, and photothermal effects. This review emphasizes that safe MOFs design is critically important and should comply with the overall migration limit of <10 mg/dm2 specified in Regulation (EC) No 1935/2004, lanthanide element limit of <0.05 mg/kg, and FDA threshold of 1.5 &#x3bc;g/person/day. Comprehensive safety assessment and intelligent sensing platforms will constitute pivotal directions for advancing MOFs-based smart packaging toward practical application.

Food Packaging

Effectiveness of Internet-Delivered Cognitive Behavioural Therapy (ICBT) in Improving Weight-Loss and Psychosocial Well-Being Among Adults With High BMI: A Systematic Review.

AIM: To examine the effectiveness of Internet-delivered Cognitive Behaviour Therapy (ICBT) in improving psychosocial well-being and promoting weight-loss in adults &#x2265;&#x2009;18&#x2009;years with BMI &#x2265;&#x2009;25&#x2009;kg/m2. BACKGROUND: Global obesity engenders significant physical and psychosocial health consequences. Second-wave ICBT focused on restructuring negative thoughts and behaviours has been explored as a potential intervention for elevated BMI and mental health concerns, but its effectiveness remains to be fully established, making further evaluation essential. METHODS AND DATA SOURCES: Eight databases were searched from inception to January 2025 for randomised controlled trials (RCTs), including participants &#x2265;&#x2009;18&#x2009;years with BMI &#x2265;&#x2009;25&#x2009;kg/m2 and second-wave ICBT evaluating BMI, weight, depression, eating behaviours, and self-esteem. This review followed PRISMA 2020. Study quality was assessed using the Cochrane Risk of Bias (ROB 2) and GRADE. Data were extracted using a modified Cochrane form. Random-effects meta-analysis calculated Standardised Mean Differences (SMD) with 95% confidence intervals, with subgroup analyses exploring heterogeneity. RESULTS: Nine trials with 2278 participants were included. Significant improvements were seen in BMI, weight, and depressive symptoms while self-esteem effects were small and non-significant. Compared with passive controls, ICBT showed greater improvements in BMI and weight, whereas differences versus active control were smaller and inconsistent. Face-to-face CBT demonstrated superior outcomes for depression and self-esteem. Male-tailored interventions showed greater improvements. Shorter programmes yielded larger short-term weight loss, while longer programmes supported more sustained effects. Narrative synthesis indicated improvements in emotional and external eating, with increased mindful and restrictive eating behaviours. CONCLUSION: ICBT improved weight, BMI, and depressive symptoms, with limited evidence for self-esteem. Male-tailored interventions and longer programmes may enhance sustainable outcomes. IMPACT: Future ICBT programs should integrate strategies targeting sustainable weight loss and psychosocial well-being to support long-term outcomes. NO PATIENT OR PUBLIC CONTRIBUTION: Patients or members of the public were not involved, as this study synthesised previously published data. TRIAL REGISTRATION: PROSPERO registration number: CRD42024497961.

Humans

An expanded breakfast buffet increases daily energy and protein intakes in hospitalised patients: A prospective crossover quality improvement study.

BACKGROUND & AIMS: Inadequate dietary intake remains common during hospitalisation. Ordinary hospital meals are central to nutritional intake, but their contribution depends on what is offered and what patients are able and willing to eat. We evaluated whether a preference-informed, limited expansion of the hospital breakfast buffet could increase total daily energy and protein intakes. METHODS: This prospectively structured, ward-based crossover quality-improvement study was conducted in seven inpatient wards at a tertiary university hospital. Each ward was observed for four consecutive days and randomly allocated to begin with standard or expanded breakfast, after which conditions alternated daily. The expanded buffet consisted of standard breakfast supplemented with familiar energy- and protein-rich foods selected from previous patient-choice data. Twenty-four-hour intake was registered using component-level weighed food records during the day and nursing registration overnight. Primary outcomes were total daily energy and protein intakes. Linear mixed-effects models adjusted for observation day and ward-level starting sequence and accounted for repeated patient observations and ward-level clustering. Analyses used data from patients who consumed breakfast and contributed analysable observations under both breakfast conditions. RESULTS: The primary crossover population included 71 patients contributing 188 analysable patient-days. Compared with standard breakfast, the expanded breakfast increased total daily energy intake by +198 kcal/day (95% CI 44 to 352) and protein intake by +6.8 g/day (95% CI 1.0 to 12.5), without a statistically significant increase in total food weight. Daily energy and protein adequacy increased by +8.7 and + 6.8 percentage points, respectively. The increase was driven mainly by breakfast intake, with no measurable reduction in non-breakfast intake. CONCLUSIONS: A limited expansion of the ordinary hospital breakfast buffet increased total daily energy and protein intakes in the primary crossover population of hospitalised adults who consumed breakfast. This increase occurred without a statistically significant increase in total food weight or a measurable reduction in non-breakfast intake. Small, preference-informed additions of familiar energy- and protein-rich foods at breakfast may improve daily intake by increasing the nutrient yield of foods patients are able or willing to eat.

Humans

Molecular mechanisms of natural de novo shoot organogenesis and their applications.

Natural de novo shoot organogenesis (DNSO) is the spontaneous regeneration of shoots from wound sites outside the shoot apical region through endogenous developmental programs. This regenerative capacity enables plants to recover from severe tissue damage by re-establishing the shoot-root axis. Here, we review current knowledge about the molecular mechanisms of natural DNSO, focusing on transcriptomic and physiological studies in model plants. Accumulating evidence suggests that natural DNSO proceeds through three sequential phases: (i) early wound responses, characterized by the activation of the WIND1-ESR1 module and the establishment of apical-basal auxin asymmetry; (ii) cellular proliferation driven by metabolic and cell-cycle reprogramming; and (iii) cytokinin-mediated establishment of shoot apical meristem identity. We also discuss how these mechanistic insights have been harnessed for practical applications, including tissue culture-free transformation systems such as the cut-dip-budding (CDB) method, and developmental reprogramming strategies that employ ectopic expression of developmental regulator (DR) genes to induce DNSO in otherwise recalcitrant species. Together, these advances illustrate how understanding natural regeneration can guide the development of simplified, broadly applicable plant transformation technologies.

Plant Shoots

Examining Behavioral Interventions for Infancy and Early Toddlerhood: A Systematic Review of Intervention Effects, Parameters, and Participants.

Rapid advancement is paving the way to identify children who would likely benefit from early intervention during the first years of life, prior to the onset of significant delays in development. With the widely acknowledged benefits of early intervention, key questions arise: Does behavioral intervention targeted to infancy and early toddlerhood improve developmental outcomes? What procedures might be used, and under what circumstances? Who do these interventions work for? The current review comprehensively examined the literature on behavioral interventions based in operant learning, focused on key developmental areas with children in the first two years of life. We located and synthesized 69 studies with unique participant cohorts that included 1735 children. The search revealed many studies focused on the first year of life, of which a large proportion investigated approaches to increase communication. We provide implications, limitations, and future directions on how behavioral interventions for infants and young toddlers can inform current practice and future intervention research this population.

Humans

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans

Externally validated risk prediction models for gestational diabetes mellitus: A systematic review and meta-analysis.

INTRODUCTION: Risk prediction models for gestational diabetes mellitus (GDM) offer potential for early identification and targeted prevention. External validation is crucial to assess model performance across diverse populations. Despite the availability of numerous GDM prediction models, limited evidence exists on their external validation frequency, methodological quality, and clinical applicability. This systematic review evaluated externally validated GDM prediction models, focusing on methodological rigor, reporting standards, and clinical relevance to inform future research and implementation. MATERIAL AND METHODS: Databases including Ovid MEDLINE, Embase, Scopus, Emcare, and CINAHL were searched up to May 1, 2025. Studies reporting external validation of GDM risk prediction models were included. Two reviewers independently screened studies. Data were extracted using the CHARMS framework, and risk of bias and applicability were assessed using PROBAST+AI. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251125758). RESULTS: Twenty-six studies validated 33 models, with validation sample sizes ranging from 50 to 75&#x2009;161. Over half used the IADPSG criteria to define GDM. Discrimination metrics were commonly reported, but calibration, overall performance, and clinical utility were often lacking. Meta-analysis was feasible for only four models: Teede et&#xa0;al., Nanda et&#xa0;al., Naylor et&#xa0;al., and Van Leeuwen et&#xa0;al., each showing fair discrimination. The Teede et&#xa0;al. model was the most widely validated, with 11 external validations across six continents and a pooled AUC of 0.72 (95% CI: 0.67-0.76). Despite fewer validations, the Nanda et&#xa0;al. model achieved the highest pooled discrimination (5 validations; pooled AUC 0.77, 95% CI: 0.74-0.80). The Naylor et&#xa0;al. and van Leeuwen et&#xa0;al. models also underwent meta-analysis, as sufficient external validation studies were available to support comparative performance assessment. Notably, 69.23% of studies had a high risk of bias. CONCLUSIONS: While many models showed acceptable predictive performance, most validations were methodologically weak. Future studies should follow best-practice guidelines and promote scalable validation strategies, such as algorithm sharing, to enhance clinical utility.

Humans

Feasibility of implementation, diagnostic accuracy, and end-user impact of an electronic health record (EHR)-based ureteral stent tracking tool in a pediatric population.

INTRODUCTION & OBJECTIVES: Ureteral stent tracking systems have reduced stent retention in adults, but their accuracy and impact in pediatrics have been minimally explored. With low event rates in children, such tools may yield high false positives, raising questions on balancing event prevention with provider burden. We aimed to evaluate the feasibility, diagnostic accuracy, and end-user impact of an Electronic Surveillance Tool for Evaluating Nephroureteral stent Tracking (eSTENT) at our institution. STUDY DESIGN: eSTENT, implemented in 1/2024, flags ureteral stents at risk for retention based on implant documentation, expected explant date, and explant documentation. Monthly reports are generated for stents missing explant documentation. We retrospectively evaluated the diagnostic performance of eSTENT from 1/2024-8/2025 at our pediatric hospital. A usability survey including a validated 1-7 implementation score (higher = easier implementation) was distributed to pediatric urologists and operating room nurses. RESULTS: Of 172 cases with ureteral stent placement, eSTENT flagged 28 events (16%) in 24 patients. Of these, 26 represented documentation gaps where explant had been appropriate. Two flags had no documentation of explant, representing near miss events that were identified. No retained stents occurred, consistent with high sensitivity and modest specificity. There were no flags in the last 6 months of the study period. Survey response rate was 100% for surgeons and 55% for nurses. Before eSTENT, stents were not routinely tracked. All surgeons and 93% of nurses reported no added burden, despite occasional misidentification of retained stents. Three surgeons found eSTENT beneficial, four were neutral, and free-text responses generally cited eSTENT's "fail safe" nature as positive. Nurses suggested improvements, including user support and integrated documentation reminders. The average implementation score among both groups was 6/7, indicating easy adoption. DISCUSSION: While the impact of stent tracking tools in adult literature has been positive, our study emphasizes the feasibility of broader adoption at a pediatric hospital. Integration of eSTENT may avoid the potentially devastating consequences of a retained stent. Prioritizing sensitivity over specificity appears acceptable for a "never event" in patient safety. Our study is limited by the retrospective nature of data collection and survey bias. CONCLUSIONS: Though no stents were retained in the study period, eSTENT appropriately flagged two cases without added burden to most end-users. Further optimization is warranted, but adoption in pediatric centers may enhance care reliability.

Humans

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

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