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PubMed2026

The value of international collaborations for supporting neuroanesthesia practice, education, and research in resource-constrained settings.

PURPOSE OF REVIEW: Neuroanesthesia practice in low- and middle-income countries is constrained by workforce shortages, limited infrastructure, and variability in clinical practice. Growing global interest in collaboration makes it timely to evaluate how international partnerships can address these gaps and improve equity in care, education, and research. RECENT FINDINGS: Recent literature highlights substantial variability in neuroanesthesia practice and limited access to context-appropriate guidelines and advanced technologies. International collaborations, including training partnerships, scholarship programs, and research networks, have improved knowledge exchange, workforce development, and the adoption of standardized practices. Evidence suggests that specialized training is associated with improved clinical outcomes. However, persistent inequities in research participation, authorship, and leadership, as well as concerns regarding sustainability and 'parachute research', remain. SUMMARY: International collaboration is a key strategy for advancing neuroanesthesia in resource-constrained settings. Sustainable, equitable partnerships that prioritize local ownership, capacity building, and contextual adaptation are essential to improving clinical practice, strengthening education, and enhancing global research representation.

Humans↗

PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2026

Nociception-guided opioid administration within multimodal analgesia for laparoscopic endometriosis surgery: a randomized controlled trial.

Women with endometriosis are at increased risk of severe postoperative pain due to nociceptive sensitization. While multimodal analgesia reduces opioid use, the added value of objective nociception monitoring remains unclear. This study evaluated whether NOL®-guided opioid titration improves perioperative outcomes within a standardized multimodal regimen. In this prospective, randomized, single-blinded trial, premenopausal women undergoing laparoscopic surgery for suspected endometriosis or adenomyosis were assigned to NOL®-guided analgesia or standard care based on clinical assessment. All patients received a standardized multimodal protocol. The primary outcome was total perioperative opioid consumption. Secondary outcomes included postoperative pain scores (NRS) and PACU length of stay. Exploratory analyses assessed the association between preoperative pain (Mankoski Pain Scale, MPS) and postoperative outcomes. A total of 111 patients were analyzed (NOL®: n = 54; control: n = 57). Total perioperative opioid consumption did not differ significantly between groups (adjusted mean difference = 14 μg for Fentanyl and 52 μg for Remifentanil; p = 0.8). Surgery duration was an independent predictor of opioid use (p < 0.001) and PACU length of stay (p = 0.01), whereas treatment group had no significant effect. Postoperative pain scores were comparable between groups at all time points. NOL®-derived metrics were not associated with opioid consumption or pain. Higher preoperative MPS scores independently predicted higher pain scores in the late PACU phase. NOL®-guided opioid titration did not reduce perioperative opioid consumption or improve early postoperative outcomes compared with standard multimodal analgesia in women undergoing laparoscopic surgery for endometriosis.

Humans↗

PubMed2026

Predicting training outcomes for developmental dyslexia from EEG data.

Developmental dyslexia (DD) is characterised by lower-than-average reading abilities and is diagnosed in approximately 10% of individuals. The societal barriers may limit professional fulfilment and psychological wellbeing of individuals with DD, calling for the development of effective interventions to counteract them. As DD is associated with challenges in both phonological and visuo-attentional domains, different longitudinal training approaches were developed to strengthen them. However, they require a considerable amount of personal, social and economic resources and the outcomes may vary depending on individual differences in behavioural and neurophysiological functionality. Hence, predicting training outcomes might help in developing personalised treatment protocols and optimising the use of resources. In the present work we applied machine learning to resting-state EEG to predict longitudinal training outcomes in adults with DD enrolled in a randomized clinical trial. In particular, one group received a visuo-attentional training combined with transcranial alternating current stimulation (tACS), another group received visuo-attentional training with sham/placebo stimulation, and the third group received a phonological training with sham/placebo stimulation. The improvement in text reading speed was associated with spectral power in low-beta and individual frequencies in the alpha (IAF) and beta (IBF) bands, while the improvement in pseudoword reading was associated with IBF. The findings highlight the potential of capturing neural markers of treatment responsiveness in DD. Future studies should focus on the generalisability of predictive models to real-world settings, while investigating whether specific EEG markers predict responsiveness to distinct remediation protocols, thus supporting the development of personalised interventions.

Humans↗

PubMed2026

Culturally adapted post-diagnostic dementia support for South Asian people living with dementia and caregivers: a rapid review.

BACKGROUND: The number of minority ethnic people living with dementia (PLWD) in the UK is predicted to rise to 50 000 by 2026 and 172 000 by 2051. As the global population ages, there is a greater need to develop culturally appropriate post-diagnostic support for PLWD from minority ethnic backgrounds. METHODS: A rapid review was conducted of culturally adapted post-diagnostic dementia support for South Asian people with dementia and carers. Eight electronic databases were searched from inception until 16 September 2025. Databases included Cumulative Index to Nursing and Allied Health Literature, Excerpta Medica Database, MEDical Literature Analysis and Retrieval System Online, Psychological Information, Turning Research Into Practice, Allied and Complementary Medicine Database, Social Policy and Practice and the Cochrane Database of Systematic Reviews. Two reviewers independently screened the studies. Consistent with rapid review methods, no formal quality assessment of included studies was undertaken. The rapid review adhered to Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. RESULTS: Twelve studies were included. These included seven carer support programmes focusing on raising awareness and education on dementia and care. These interventions increased carers' knowledge of dementia and confidence in caregiving. Four studies reported on psychosocial interventions: Cognitive Stimulation Therapy, Cognitive Behaviour Therapy and Meditation Therapy, demonstrating benefits for caregiver burden and mental health. One study reported on service-level innovations through a South Asian link nurse, which improved access to services and facilitated the development of culturally appropriate information materials. CONCLUSION: The findings of this rapid review demonstrate the feasibility and perceived value of culturally sensitive psychoeducation, carer training and psychosocial interventions. However, research remains small-scale, methodologically limited, with little focus given to interventions directly supporting PLWD.

Humans↗

PubMed2026

An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.

OBJECTIVES: To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL). METHODS: Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds. CONCLUSION: This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.

Humans↗

PubMed2026

Clinical accuracy and short-term outcomes of intraoral photogrammetry for complete-arch implant rehabilitation: A retrospective multicentre study on 35 patients.

OBJECTIVES: To evaluate the clinical accuracy and short-term outcomes of complete-arch implant-supported fixed dental prostheses (ISFDPs) fabricated using an intraoral photogrammetry (IPG) based digital workflow in completely edentulous patients. METHODS: This multicenter retrospective clinical study included 35 patients rehabilitated with 52 complete-arch ISFDPs (10 FP1, 18 FP2 and 24 FP3 restorations) supported by 221 implants. All definitive prostheses were designed and fabricated using a fully digital workflow initiated by IPG acquisition with the Aoralscan Elite IPG® (SHINING 3D). The primary outcome was clinical accuracy, assessed at definitive prosthesis delivery through evaluation of passive fit using the Sheffield test and radiographic verification. Secondary outcomes included biologic and prosthetic complications, as well as implant and prosthesis survival rates during the follow-up. RESULTS: Passive fit was achieved in all definitive restorations (100%). Radiographic evaluation confirmed accurate marginal adaptation at the implant-prosthesis interface in all cases. No statistically significant differences in clinical accuracy were observed according to treated arch, number of supporting implants, or prosthetic design (P > .05). During a mean follow-up period of 12.1 ± 3.5 months, biologic and prosthetic complications were limited and generally minor. Implant survival was 99.5%, and prosthesis survival was 100%. CONCLUSIONS: Within the limitations of this retrospective clinical study, the IPG based workflow demonstrated high clinical accuracy and predictable short-term outcomes for complete-arch implant rehabilitation, consistently enabling passive fit and favorable prosthetic performance. CLINICAL RELEVANCE: IPG may represent a clinically reliable and predictable approach for complete-arch digital implant impression acquisition. The high rates of passive fit, together with the low incidence of biologic and prosthetic complications observed in this multicenter clinical study, support the use of IPG based workflows for the fabrication of complete-arch ISFDPs.

Humans↗

PubMed2026

A point-of-use SERS assay for rapid detecting difenoconazole and flusilazole residues in fruit juices using Au/COF substrate.

We developed a ready-to-use surface-enhanced Raman scattering (SERS) sensor for rapid, pretreatment-free detection of difenoconazole (DIF) and flusilazole (FLU) in peach and lychee juices. The substrate combines Au nanoparticles (AuNPs) with covalent organic frameworks (COF) and is implemented on a portable 25-well plate, enabling in situ testing. Juices can be directly applied to the SERS-active Au/COF composite, allowing simultaneous adsorption and signal generation. The correlation between SERS intensity and logarithmic concentration yielded R-values between 0.925 and 0.986, meeting the monitoring needs of non-laboratory scenarios. The entire workflow completes within 12 min, offering a faster alternative to conventional methods while maintaining high sensitivity and reproducibility. Detection limits reach 0.96-1.22 ppb for DIF and FLU, both of which are below the regulatory maximum residue limits. Distinct SERS fingerprints enable reliable discrimination of mixed residues across juice matrices, supporting rapid on-site monitoring and cost-effective pesticide surveillance.

Triazoles↗

PubMed2026

The Effect of Pain Catastrophizing on Acupuncture Treatment for Chronic Pain in Cancer Survivors.

CONTEXT: Pain catastrophizing (PC) predicts worse pain outcomes in cancer survivors. However, little is known whether PC influences pain outcomes of nonpharmacological treatments such as acupuncture. OBJECTIVES: This study aimed to assess the impact of PC on acupuncture efficacy for chronic pain in cancer survivors. METHODS: This secondary analysis of PEACE trial used two-sample t-test and Pearson's chi-squared test to analyze the pain outcomes of cancer survivors who received electroacupuncture (EA) or battlefield acupuncture (BFA). PC was measured using Pain Catastrophizing Scale (PCS). The Brief Pain Inventory (BPI) was used to measure pain severity and interference at the primary endpoint (week 12). RESULTS: Among 266 participants, 41 (15.41%) had a high baseline PC. Among those receiving EA, high PC patients had greater reductions in pain severity (-3.9 vs. -2.1, P = 0.006) and pain interference (-3.8 vs. -2.6, P = 0.04) than low PC. PC was not associated with pain outcomes in BFA group (P > 0.05 for both severity and interference). Among patients with high PC, a greater proportion were responders in the EA group than those in BFA group (83.3% vs. 43.5%, P = 0.009). Among low PC patients, there was no significant difference in the proportion of responders between the EA and BFA groups (66.1% vs. 64.5%, P = 0.8). CONCLUSION: We found that cancer survivors with high baseline PC had greater pain reductions with EA than BFA and compared to low PC patients. These findings suggest that EA may serve as a targeted treatment option for vulnerable patients with high PC and further support precision pain management.

Humans↗

PubMed2026

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine↗

PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗

PubMed2026

Diagnostic Value and Limitations of Dermoscopy in Humans and Animals: A Critical Comparative Analysis.

BACKGROUND: Dermoscopy is a noninvasive imaging technique that is well-established in human dermatology, where it enhances the diagnosis of neoplastic, inflammatory, infectious, and alopecic skin disorders. In veterinary dermatology, its use is expanding yet remains heterogeneous and largely descriptive, despite growing evidence of conserved dermoscopic patterns across species. HYPOTHESIS/OBJECTIVES: To review the applications of dermoscopy in veterinary dermatology, and to provide a comparative analysis of dermoscopic features observed in dogs, cats, and horses in relation to corresponding findings in human dermatology. MATERIALS AND METHODS: A systematic review of the literature reporting dermoscopic findings in veterinary dermatology was conducted in accordance with PRISMA guidelines. PubMed, Scopus and Google Scholar were searched for studies published up to 30 July 2025. Eligible studies included original articles describing dermoscopic features in dogs, cats, or horses. Extracted data included species, dermatological condition, dermoscopic findings, device type and histopathological correlation, when available. Levels of evidence were assessed using the Oxford Centre for Evidence-Based Medicine criteria. RESULTS: Thirty studies met the inclusion criteria. Most were descriptive case reports or case series. Dermoscopy was applied to a wide range of conditions, including alopecias, parasitic infestations, dermatophytosis, neoplastic and sebaceous lesions, inflammatory dermatoses, and congenital vascular anomalies. Recurrent dermoscopic features showed strong similarities to those described in human dermatology, although species-specific anatomical differences influenced interpretation. CONCLUSIONS: Dermoscopy represents a valuable adjunct diagnostic tool in veterinary dermatology, with clear translational relevance. Standardisation of terminology and further prospective studies are required to support its broader clinical integration.

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PubMed2026

Health Literacy and Capecitabine Adherence in a Remote Monitoring Pilot Trial for Breast Cancer: Post Hoc Exploratory Analysis.

BACKGROUND: Oral anticancer therapy enables convenient, home-based cancer care but can introduce adherence challenges, particularly with complex dosing schedules. Capecitabine is commonly used in breast cancer, often as adjuvant therapy or in advanced disease, and typically requires twice-daily dosing on cyclical schedules, increasing the risk of missed or incorrect doses. Low health literacy may exacerbate these difficulties, and emerging remote monitoring tools may help close this gap. OBJECTIVE: In this post hoc exploratory analysis, we evaluated whether health literacy (1) was associated with capecitabine adherence and (2) modified a remote monitoring intervention's effectiveness. METHODS: We conducted post hoc analyses of a 2-arm pilot trial that randomized women with breast cancer treated with capecitabine to enhanced usual care (EUC) or remote patient monitoring (RPM). Adherence was captured with a smart pill bottle, Nomi by SMRxT, that recorded dose timing and quantity. Participants in the RPM group received messages for missed or incorrect doses and weekly symptom assessments. Incorrect or missed doses and severe symptoms triggered alerts to the oncologist. Health literacy was assessed at enrollment. To evaluate moderation, we used linear regression with an interaction term (health literacy × intervention arm) predicting adherence (proportion of days). Marginal effects quantified differences in adherence by study arm and health literacy. RESULTS: Among 28 participants (EUC, n=15 and RPM, n=13), 9 (32.1%) had lower health literacy, 16 (57.1%) identified as Black, 10 (35.7%) identified as White, and 15 (53.6%) had income below 200% of the federal poverty level. In the regression model, the health literacy × randomized group interaction did not reach statistical significance (-16.3 percentage points, 95% CI -35.5 to 2.9; P=.09). Predicted adherence among lower health literacy participants was 87.5% in the RPM group and 65.5% in the EUC group (difference: +22.1 percentage points, 95% CI 6.2-37.9; P=.008). Among participants with higher health literacy, adherence was 89.9% in the RPM group and 84.1% in the EUC group (difference: +5.7 percentage points, 95% CI -5.2 to 16.7; P=.29). Within the EUC group, predicted adherence was 18.6 percentage points lower among those with lower versus higher health literacy (95% CI -32.4 to -4.9; P=.01); within the RPM group, this difference was 2.3 percentage points lower among those with lower versus higher health literacy (95% CI -15.8 to 11.1; P=.73). CONCLUSIONS: In this post hoc exploratory analysis, the estimated difference in capecitabine adherence between the RPM and EUC groups was larger among participants with lower health literacy. Although the formal interaction test was not statistically significant, the magnitude and direction of the observed difference support further investigation of RPM as a potential approach to improve adherence among patients facing health literacy-related adherence barriers. Larger, prospectively powered studies are needed to confirm these findings and evaluate downstream clinical outcomes.

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PubMed2026

The clinical value of adding immune checkpoint inhibitors to radiotherapy for cancer: a systematic review and meta-analysis.

BACKGROUND: While several randomized clinical trials (RCTs) have explored the addition of immune checkpoint inhibitor (ICI) treatment for patients undergoing radiotherapy, studies systematically assessing the clinical value of such interventions are lacking. METHODS: PubMed, Embase, and Cochrane Library databases were searched for relevant RCTs of cancers that received ICIs plus radiotherapy or radiotherapy. Eligible studies were those published in English as of 14 April 2024. Two independent reviewers screened the included studies and extracted relevant data, then selected the random or fixed-effects model based on the I2 statistic. The main outcomes were hazard ratios (HRs) with 95% confidence intervals (CIs) for overall survival (OS) and progression-free survival (PFS); Odds ratios (ORs) with 95% CIs for objective response rate (ORR), disease control rate (DCR), and adverse events (AEs). Stratified analysis was performed based on cancer type, ICI type, and the timing of ICI addition. The study was registered on PROSPERO (CRD42024551008). RESULTS: 15 RCTs with 7947 patients were included. Pooled HRs were 0.865 (95% CI, 0.730-1.000; I2 = 72.1%) for OS and 0.799 (0.677-0.922; I2 = 82.0%) for PFS in cancer patients. In cancer types, adding immunotherapy to radiotherapy significantly improved patients with non-small-cell lung cancer (OS: 0.544 [0.371-0.717]; PFS: 0.527 [0.438-0.617]) and cervical cancer (OS: 0.722 [0.578-0.867] and PFS: 0.754 [95%CI, 0.621-0.887]). Regarding the ICIs schedule, adjuvant ICI therapy with pooled HRs was 0.742 (0.649-0.834) for OS and 0.638 (0.579-0.697) for PFS. In addition, the pooled ORs for the incidence of grade 3 or higher treatment-related and immune-related adverse events were 1.227 (1.059-1.421; I2 = 71.9%) and 2.217 (1.743-2.821; I2 = 74.0%), respectively. CONCLUSION: Adding immunotherapy to radiotherapy can provide significant clinical benefits for patients with NSCLC and cervical cancer, and the addition of these ICIs in the adjuvant stage is supported.

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PubMed2026

MicroRNAs in Oral Bio-Fluids as Predictive Biomarkers of Orthodontic Tooth Movement: A Systematic Review.

This systematic review was designed to assess scientific evidence of the association of microRNA expression during orthodontic tooth movement through various time points. A systematic review was performed in accordance with the PRISMA checklist. A search strategy was developed in electronic databases including Med Line, Scopus, EBSCO Host and ProQuest Dissertations & Theses Global until June 2025. Eligibility criteria included studies that investigated microRNA expression in saliva/GCF during orthodontic treatment. The risk of bias of the included studies was analysed using the QUADAS-2 and RoB-2 tools. The search retrieved 2800 records, of which nine studies were selected. Minor variations in GCF collection were noted, while stimulated saliva was collected in one study. RT-PCR and the Fluro meter accounted for the majority of miRNA estimation. Thirteen miRNAs were identified as target biomarkers for OTM regulation. Despite the high risk of bias, the evidence from the current systematic review indicates that microRNAs can be considered as potential biomarkers of orthodontic tooth movement in oral biofluids. Trial Registration: Prospero ID-CRD420251153064.

Humans↗

PubMed2026

Paediatric penile length: a systematic review and meta-analysis.

OBJECTIVE: To assess geographical variation in stretched penile length among prepubertal boys and evaluate temporal trends over the past two decades, as defining reference values for genital organ size remains crucial for early identification of development disorders. METHODS: The PubMed, Cochrane and Scopus databases (no deadlines for publishing were imposed) were searched according to the Preferred Reporting Items for Systematic Review and Meta-analyses statement. Five authors independently extracted individual participant data and assessed the risk of bias. Studies with quantitative penile lengths were included; those involving congenital malformations were excluded. The review protocol was prospectively registered in the International Prospective Register of Systematic Reviews (registration number CRD42022335643). RESULTS: A total of 55 studies from 2000 to 2024 were evaluated, including data from 31 915 boys. Pooled mean stretched penile length estimates were 3.07 cm (95% confidence interval [CI] 2.88-3.26 cm) for the 1-week-old boys, 3.73 cm (95% CI 3.53-3.93 cm) for the 1-year-old boys, 4.69 cm (95% CI 4.49-4.88 cm) for the 2-5 year-old boys, and 5.43 cm (95% CI 5.20-5.66 cm) for the 5-10 year- old boys. When comparing data from the 2000s to the 2020s, stretched penile length decreased by 16.2% (from 3.46 to 2.90 cm), 16.3% (from 4.17 to 3.49 cm), 21.5% (from 5.31 to 4.17) and 26.2% (from 6.46 to 4.77 cm) in the 1-week-old, 1-year-old, 2-5-year-old and 5-10-year-old boys, respectively. Subgroup analysis for those aged >2 years showed significant variations by geographical region (P < 0.001). CONCLUSIONS: The present study observed large variations in penile length across geographical regions and among prepubescent boys of different ages, while also suggesting a possible decline over the past two decades.

Humans↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n = 11), persistent FGR (n = 9), and healthy controls (n = 13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n = 69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p < 0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular signatures reflecting the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans↗