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PubMed2026

The Interrelationship between Cadmium, Smoking, and Migraine in the ELSA-Brasil Study.

This study explored the relationship between serum cadmium (Cd), smoking exposure, and migraine in the ELSA-Brasil cohort (2008-2010). The analysis included 2,750 participants whose serum Cd levels were measured using inductively coupled plasma mass spectrometry. Smoking exposure was assessed using self-report data of active smoking and second-hand smoke. Migraine, including definite and probable migraine, was diagnosed according to the International Classification of Headache Disorders, 3rd edition (ICHD-3). Logistic regression was used to estimate the odds of migraine across serum Cd quintiles, using the third quintile as the reference category, while linear regression examined the relationship between smoking exposure and Cd levels. Polynomial contrasts tested linear trends. Participants had a mean (SD) age of 53.2 (9.0) years and 53.1% were women. Migraine prevalence was 29.1% (including probable migraine). Individuals with migraine had slightly higher median serum Cd levels than controls [0.050 µg/L (IQR 0.035-0.077) vs. 0.048 µg/L (0.035-0.066); p = 0.021], although smoking exposure scores did not differ between groups. Smoking exposure showed a strong positive association with serum Cd concentrations (p-trend < 0.001). Participants in the highest Cd quintile had greater odds of migraine [aOR 1.51 (95% CI 1.09-2.08), p = 0.011] after adjustment for smoking exposure and sociodemographic and clinical confounders. Sex-stratified analysis yielded even stronger associations among males [aOR 1.84 (95% CI 1.07-3.16), p = 0.027]. However, in the sensitivity analysis including definite migraine cases only, this association was no longer significant [aOR: 1.14 (0.71, 1.83), p = 0.579]. Main findings suggest that Cd exposure from smoking may contribute to migraine occurrence, particularly in males. However, other sources of Cd that could influence migraine should not be disregarded, and future investigation in this field is warranted.

Cadmium↗

PubMed2026

Nutrikinetics and bioavailability of Promunel®, a standardized poplar-type propolis phenolic extract: a double-blinded, placebo-controlled, cross-over, randomized trial.

Brown poplar-type propolis has been recognized and used for centuries to help prevent upper respiratory tract infections (URTIs). However, the scarce, incomplete information in humans on the nutrikinetics and bioavailability of its phenolic constituents, combined with a lack of standardization in its phenolic content and profile pose major challenges to develop bioactive ingredients. Thus, the aim of this study was to establish the nutrikinetics and total bioavailability (NKBA) parameters of brown poplar-type propolis phenolics in humans using the Standardized Propolis Extract (SPE) Promunel®. To achieve this, a 48 h NBKA study was conducted following a double blinded, randomized, placebo-controlled, cross-over design in healthy humans (n = 10) with two doses of SPE (1X = 400 mg or 4X = 1600 mg). Phenolic compounds were detected, identified and quantified in the extract, plasma and urine through different LC-MS/UV technologies. The SPE used is a rich (304.44 ± 15.61 µmol mg-1) and diverse source of phenolic compounds (5 sub-families). A total of 63 and 85 phenolic metabolites were identified and quantified in plasma and urine, mostly in the form of glucuronides and sulfates. In plasma, phenolic metabolites reached Cmax (1.22 ± 0.20 for 1X and 4.80 ± 0.48 µM for 4X) after 1 h of SPE intake, while urinary excretion occurred mostly during the first 3 h after. The total net bioavailability of SPE phenolic compounds at 48 h was 57.16 ± 5.71% for 1X and 43.82 ± 6.77% for 4X. Generally, the data between SPE 1X and 4X were proportional, indicating that a higher dose does not substantially modulate total net bioavailability. Overall, our data shows that brown poplar-type SPE phenolic compounds are highly bioavailable in the form of cinnamic acid and flavonoid conjugates, and that these compounds are rapidly absorbed and eliminated through the urine. Our results suggest that, for a sustained presence in circulation, brown poplar-type propolis supplements should be consumed more than once a day.

Humans↗

PubMed2026

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

Humans↗

PubMed2026

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗

PubMed2026

Role of External Vibratory Lithoclast (Lithecbole) in Improving Lower Pole Stone Clearance After Extracorporeal Shock Wave Lithotripsy (ESWL).

Background and Objective: Extracorporeal shock wave lithotripsy (ESWL) is a widely used non-invasive treatment for renal stones. However, its effectiveness in clearing stones located in the lower pole of the kidney is often limited due to the anatomical challenges that impede the spontaneous passage of fragmented stones. This study evaluate the efficacy and safety of External Physical Vibration Lithecbole (EPVL) when used as an adjunctive therapy following ESWL in patients with lower pole renal stones, with a focus on improving stone clearance rates. Materials and Methods: This prospective interventional study was conducted at Al Yarmouk Teaching Hospital over two years and included 100 patients with 10-15 mm lower pole renal stones. Patients were randomized into two groups: The ESWL alone and ESWL plus EPVL. All patients received two ESWL sessions (3000 shocks/session). The treatment group additionally received EPVL therapy using a flank-applied vibration device. Follow-up was performed using ultrasound and KUB radiography. Statistical analysis was conducted using appropriate tests with significance set at p<0.05. Results: Baseline characteristics, including age, gender, weight, stone size and location, were statistically comparable between groups. The mean stone size was 12.4±1.7 mm. A significantly higher stone-free rate was observed in the ESWL+EPVL group compared to the ESWL-only group (66% vs. 48%, p = 0.027). Although the residual stone size showed a numerical difference favoring EPVL, it was not statistically significant (p = 0.11). Complication rates were low, mild and similar in both groups (p = 0.3). Logistic regression analysis revealed that smaller stone size (p<0.001) and lower patient weight (p = 0.030) were significantly associated with successful stone clearance. Subgroup analysis further confirmed that patients with stones <11 mm or a weight <70 kg had the highest stone-free rates. Conclusion: In this initial evaluation, EPVL demonstrated a safe and effective adjunct to ESWL in enhancing stone clearance for lower-pole renal stones. Its application was associated with improved treatment outcomes without increasing complication rates. Further studies with extended EPVL sessions and longer follow-up are warranted.

Humans↗

PubMed2026

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

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

Mass Spectrometry↗

PubMed2026

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation↗

PubMed2026

Longitudinal Repeated Protein Measurements in a Multiethnic Cohort Identify Novel Diabetes Biomarkers That Reveal Unique Disease Pathways.

There is up to a fourfold increase in diabetes biomarkers identified with longitudinal repeated versus single time point proteomic measurements. The increase in biomarkers identified with longitudinal repeated measurements is supported by a similar proportion being nominated as causal for type 2 diabetes with Mendelian randomization. Proteins unique to the longitudinal repeated analyses highlighted biological pathways (e.g., posttranslational protein modification and cellular structure and cycle regulation) that were distinct from pathways enriched among the shared proteins (e.g., small-molecule metabolic and catabolic processes). Longitudinal protein measurements identify additional novel disease biomarkers and disparate biological pathways compared with single measurement analyses.

Journal Article↗

PubMed2026

Clinical and psychological characteristics of adolescents at risk of mood disorders compared with adolescents with suicidal behavior.

Suicide is one of the leading causes of death among adolescents, yet little is understood about the biopsychosocial factors related to suicidality. The demographic, clinical, and biological characteristics of adolescents with and without psychiatric histories may help inform mechanistic approaches to treatment of mood disorders and suicidality. The 'characterizing the inflammatory profile and suicidal behavior in adolescents' and 'RAD arm of the Texas Resilience Against Depression' studies aimed to characterize the clinical and biological profiles of youth with suicidal behavior and youth at risk for mood disorders, compared to healthy adolescents (n = 75 in each group). Here, we report the descriptive baseline clinical and psychological characteristics of adolescents at risk of mood disorders and those with suicidal behavior. The adolescents with suicidal behavior reported 3.53 lifetime suicidal events on average, predominantly reported moderate to very severe depression (34.7%, 24%, to 9.3%), moderate to severe anxiety (58.6%), low optimism (91.9%), and mild (39.2%) to moderate (28.4%) degree of hopelessness. The at-risk adolescents predominantly reported no depression (60%) or anxiety (68.9%), moderate optimism (50%), and a positive outlook (85.7%). Healthy adolescents predominantly reported no depression (88.3%) or anxiety (93.2%), moderate optimism (59%), and a positive outlook (87%). The adolescents with suicidal behavior and those at risk of mood disorders exhibited significantly higher irritability and borderline personality disorder features (uncorrected p = 0.02 to p < 0.001) and lower resilience compared to healthy adolescents. Ongoing investigations using the longitudinal clinical and biological data will help identify the immune biosignatures of suicidality in youth.

Humans↗

PubMed2026

Trade-offs in avian parental care: a review of theory and meta-analysis of brood size manipulations.

The selective forces shaping parental care have been studied for over 50 years. While theoretical and experimental work has yielded qualitative progress, the large body of empirical work testing predictions about parental investment based on life-history trade-offs has yet to be synthesized. We first provide an overview of the core life-history theory exploring how selection might shape parental care. We then conduct a systematic review and meta-analysis on studies that experimentally manipulated brood size in birds, a widely used experimental approach to manipulate parental investment. We extracted 313 estimates from 62 studies representing 31 species of birds from 19 different families and tested key predictions on trade-offs in parental care derived from theory. Our analysis provides strong support for some predictions about life-history trade-offs in parental care, but weak or equivocal support for others. Specifically, we found that overall, avian parents respond to brood size manipulations as predicted by life-history theory: they increased care in response to brood enlargement, and decreased care in response to brood reductions. Furthermore, for the same relative manipulation size, responses to brood reductions were greater than responses to brood enlargements. This finding is consistent with predictions derived from life-history theory based on some types of non-linear utility curves. However, many predictions derived from theory are not well supported by our comparative analysis. Species' life-history traits such as clutch size (a measure of current reproduction), adult survival, and broods per year (two measures of future reproduction), explained little, if any, among-species variation in response to brood size manipulations. Several factors may explain this. We highlight that brood size manipulations may affect more than just perception of the value of current reproduction, such as altering parents' perception of predation risk. Importantly, these unintended consequences could lead to asymmetric responses like those we observed. Other common experimental approaches - such as hormone manipulations, altering a partner's effort, and food supplementation - often affect multiple traits or fitness components simultaneously, or may involve cues that poorly match the evolved mechanisms guiding parental behaviour. Our review of both theory and experimental approaches suggests that there are multiple opportunities for more precise experiments. We offer several recommendations for effective designs. One is improved understanding of the biology underlying the functions relating to costs and benefits, with careful consideration of not only how the manipulation will affect only one of those, but also the mechanisms that might alter how parents perceive the manipulation. We also emphasize general principles, such as assessing alternative hypotheses and devising multiple independent tests. Armed with these recommendations, we believe there are new opportunities to increase the strength of inference achieved from studies aimed at understanding the trade-offs affecting the evolution of parental care.

Animals↗

PubMed2026

Comparative Bioavailability of Trimodal (CTx-1301) Versus Bimodal Dexmethylphenidate Modified-Release Formulations in Adults with Attention-Deficit/Hyperactivity Disorder: A Randomized, Single-Dose, Crossover Study.

BACKGROUND AND OBJECTIVES: Attention-deficit/hyperactivity disorder (ADHD) is a chronic neurodevelopmental disorder that often requires sustained symptom control throughout the day. Although bimodal extended-release dexmethylphenidate (d-MPH XR) formulations provide initial and intermediate drug release, they may not consistently maintain therapeutic exposure into the late afternoon and evening. Trimodal formulations with an additional delayed release component may extend drug exposure later in the day, although this remains to be established. To explore differences in pharmacokinetic (PK) profiles between trimodal (CTx-1301) and bimodal delivery of d-MPH XR, a comparative bioavailability study was conducted at the highest and lowest doses for both formulations. METHODS: In this randomized, 4-period, crossover study, adults with ADHD received single doses of CTx-1301 (50 mg and 6.25 mg) and d-MPH XR (40 mg and 5 mg). Comparative bioavailability was assessed through adjusted geometric mean ratios for exposure parameters (maximum observed plasma concentration [Cmax], area under plasma concentration-time curve to last measurable concentration [AUClast] and extrapolated to infinity [AUC0-inf]), with a prespecified bioequivalence range of 0.80 to 1.25. Secondary endpoints included partial AUCs and safety assessments. RESULTS: The study population (N = 45) was predominantly male (88.9%) and White (55.6%), with mean age of 29.6 ± 8.01 years. Adjusted geometric mean ratios comparing the primary exposure parameters (Cmax, AUClast, and AUC0-inf) for CTx-1301 versus d-MPH XR were within the bioequivalence range (0.80-1.25) at both the high and low doses. The CTx-1301-to-d-MPH XR partial AUC ratios were within the bioequivalence range from 0 to 9 hours post-dose. At later intervals (AUC9-12 and AUC12-16), adjusted geometric mean ratios exceeded the upper bioequivalence threshold, consistent with the expected contribution of the third medication release component. Dose proportionality was observed between the two CTx-1301 doses and two d-MPH XR formulations. CTx-1301 was generally well tolerated. The most commonly reported adverse events included tachycardia, insomnia, headache, nausea, and euphoric mood. The incidence of treatment-emergent adverse events was numerically lower with CTx-1301 than with d-MPH XR; however, no statistical analysis was performed. CONCLUSIONS: Key exposure parameters including Cmax, AUClast, and AUC0-inf for trimodal CTx-1301 were statistically bioequivalent to bimodal d-MPH XR. Interval‑specific PK analyses demonstrated higher exposure with CTx‑1301 during later post-dose intervals (9-16 h), consistent with the formulation's third release component. However, the clinical relevance of these PK differences requires further evaluation. CTx-1301 demonstrated dose proportionality and was well tolerated at high and low doses. REGISTRATION: ClinicalTrials.gov, NCT04138498; 19 September 2019.

Humans↗

PubMed2026

Diagnostic value of blood p-tau subtypes in Alzheimer's disease progression and pathology: systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disease and the most likely to lead to dementia. With the availability of the latest therapies, the need for Alzheimer's disease diagnosis is now gradually increasing. Whereas blood phosphorylated-tau (p-tau) has demonstrated excellent performance in the prediction and diagnosis of disease progression and Aβ positivity in AD, there are differences between different p-tau subtypes. Therefore, a pooled analysis of different blood p-tau subtypes is of more important clinical value. METHOD: Relevant literature was screened by complete search in four databases, Pubmed, Embase, Cochrane Library and Scopus. Relevant data and AUC and their confidence intervals of the included literature were extracted and analyzed by classification according to p-tau subtypes. Quality assessment was performed using the QUADAS-2 tool. RESULT: Our results reveal that p-tau217 performs better in the diagnostic performance in most stages of AD, which is consistent with the guidelines. However, our results concluded that p-tau217 has poorer diagnostic performance in the stages of cognitive unimpaired or less cognitively impaired, especially in the Aβ positivity diagnosis of SCD and CU. Head-to-head meta-analyses formally confirmed that p-tau217 significantly outperforms p-tau181 across AD dementia, Aβ positivity, tau positivity, and biological staging (all P < 0.05), whereas no significant difference was observed between p-tau231 and p-tau181. CONCLUSION: By integrating single-arm pooled AUC estimates with formal head-to-head statistical comparisons, our study provides evidence-based support for plasma p-tau217 as the subtype with the most robust diagnostic performance across AD pathology and biological staging. Head-to-head analyses formally confirmed that p-tau217 significantly outperforms p-tau181 in Aβ positivity, Tau positivity, and biological staging.

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

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans↗

PubMed2026

Clinical performance of monolithic and veneered zirconia three-unit posterior FDPs: A five-year multicenter randomized controlled trial.

AIM: This randomized controlled clinical study compared monolithic, partially veneered, and fully veneered zirconia FDPs over a 5-year period with respect to survival, technical and biological complications, and patient-reported outcome measures (PROMs). MATERIALS AND METHODS: Sixty-four patients requiring three-unit posterior FDPs were randomly allocated to monolithic (MONO-FDP), partially veneered (PV-FDP), or fully veneered (FV-FDP) groups. All FDPs were fabricated from 4 mol% Y₂O₃ partially stabilized zirconia (4Y-TZP). Follow-up examinations were conducted at baseline, 1, 3, and 5 years. Technical parameters were evaluated using modified USPHS criteria. Periodontal measurements (PPD, BOP, PI) and patient satisfaction were assessed at all time points. RESULTS: A total of 63 FDPs were evaluated at baseline, 57 at 3 years, and 54 at 5 years. Survival at 5 years was 94.7% for MONO-FDPs, 100% for FV-FDPs and 100% for PV-FDPs. Technical complications occurred exclusively in PV-FDP (33%) and FV-FDP (38%) groups and consisted of minor, polishable chipping; no chipping or fractures were recorded in MONO-FDPs (0%) with statistically significant difference between MONO-FDP and the other two groups (p ≤ 0.014). Biological parameters remained stable across all groups, with no significant differences in PPD, BOP, or PI. PV-FDPs and FV-FDPs tended to receive more favorable professional color ratings, whereas PROMs were similar among the groups. CONCLUSIONS: All three FDP designs-monolithic, partially veneered, and fully veneered-fabricated from 4Y-TZP zirconia demonstrated excellent 5-year clinical performance. Technical complications were limited to PV- and FV-FDPs and consisted of minor chipping. Biological outcomes and patient satisfaction were similar across groups. CLINICAL SIGNIFICANCE: The five-year outcomes suggest that veneered, partially veneered, and monolithic FDPs can be used with high clinical reliability; however, restorations incorporating veneering ceramic may present an elevated risk of ceramic chipping.

Humans↗

PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗

PubMed2026

From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer's disease.

Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n = 727; 216 CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys Aβ42, Aβ40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations. Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954-0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14-3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q = 2 × 10-6), and CSF YWHAG correlated strongly with total tau (ρ = 0.87). Cross-fluid directional concordance was modest overall (54-57%) but increased to 73-80% among mapped analyte/protein rows reaching q < 0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication.

Alzheimer Disease↗

PubMed2026

The hidden threat from food-derived carbon dots: Formation, biodistribution, and potential health risks.

Food-derived carbon dots (CDs) are a new class of carbon-based nanoparticles generated during the thermal processing of food matrices. These nanomaterials have been extensively studied for their unique fluorescence, good biocompatibility, and tunable surface chemistry in food detection, intelligent packaging, and biomedical applications. However, their nanoscale size and high surface activity have raised safety concerns regarding biological interactions, in vivo biodistribution, and potential long-term health hazards. Although CDs have traditionally been regarded as low-toxicity materials due to their favorable biocompatibility, the potential hidden risks of CDs have not received sufficient attention. CDs exhibit dose-dependent toxicity, not only accumulating in various tissues and organs but also potentially inducing oxidative stress and interfering with cellular metabolic functions. Therefore, this review summarizes the advances in sources, synthetic strategies, and core properties of CDs, with a special focus on in vivo biological interactions, fates, and potential safety challenges. In addition, it is proposed that the standardized detection and risk assessment system should be established to further explore the long-term health effects of CDs under real dietary exposure, thereby ensuring their safety and sustainable application.

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