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PubMed2026

The science of Arabic coffee (Qahwa): from phytochemistry and nutritional profile to health benefits and safety evaluation.

Arabic coffee (Qahwa), a traditional beverage widely consumed in the Middle East, has attracted increasing scientific attention due to its distinctive phytochemical composition and associated health effects. This review provides an integrated analysis of Qahwa's nutritional profile, focusing on its key bioactive constituents, including chlorogenic acids, caffeine, diterpenes (cafestol and kahweol), and phenolic compounds. These constituents contribute to a range of biological activities, notably antioxidant, anti-inflammatory, hepatoprotective, and metabolic regulatory effects. The influence of technological variables, including roasting degree, brewing method, and bean origin, on the chemical composition and functional properties is critically examined. Safety concerns, particularly acrylamide formation and mycotoxin contamination, are also discussed. Although emerging data support Qahwa's potential as a functional beverage, further research is required to clarify dose-response relationships, synergistic interactions, and long-term health outcomes. This work highlights Qahwa as a promising candidate for food and nutraceutical applications, warranting standardized compositional profiling and toxicological evaluation.

Humans↗

PubMed2026

Diffusion MRI radiomics in meningiomas: imaging correlates of tumor grade and intraoperative consistency.

OBJECTIVE: Despite advancements in imaging studies, the preoperative prediction of the biological behavior and intraoperative consistency of intracranial meningiomas remains limited. This study evaluated the association of volumetric diffusion-based and texture-derived radiomic features extracted from routine MRI with histopathological aggressiveness and intraoperative tumor consistency. METHODS: Ninety-seven intracranial meningiomas resected at two tertiary centers were retrospectively analyzed. Volumetric segmentation was performed on contrast-enhanced T1-weighted MRI and coregistered to apparent diffusion coefficient (ADC) maps. Data on first-order diffusion metrics and selected texture features were collected. The associations between World Health Organization (WHO) grade and Ki-67 index were assessed using nonparametric tests and Spearman correlation analysis. Independent factors associated with intraoperative tumor consistency (Zada grades 1-5) were evaluated via multivariate ordinal logistic regression analysis that adjusted for tumor volume, skull base location, calcification status, and WHO grade. Secondary receiver operating characteristic (ROC) curve analyses were performed to differentiate solid (Zada grades 4-5) from soft (Zada grades 1-2) tumors. ROC analyses were performed within the study cohort and were intended as exploratory assessments of discriminative performance. RESULTS: The mean ADC (ADCmean) and the 10th percentile of the ADC decreased significantly with increasing WHO grade (p < 0.001). ADCmean had a moderate inverse correlation with the Ki-67 index (r = -0.42, p < 0.001) and intraoperative tumor consistency (r = -0.45, p < 0.001). In the multivariate analysis, the ADCmean remained independently associated with increasing tumor firmness. Each 0.1 × 10-3 mm2/sec increase corresponded to a 38% reduction in the odds of belonging to a higher consistency category (OR 0.62, 95% CI 0.51-0.74, p < 0.001). The ROC analysis showed good discrimination for solid tumors (area under the curve 0.847, 95% CI 0.742-0.953) and soft tumors (area under the curve 0.824, 95% CI 0.714-0.935). Texture features had weaker associations with intraoperative tumor consistency. CONCLUSIONS: Volumetric diffusion-derived metrics, particularly ADCmean, are associated with both histopathological aggressiveness and intraoperative tumor firmness in meningiomas. Diffusion imaging may reflect a graded microstructural continuum rather than a purely dichotomous property, providing complementary preoperative insights into surgical complexity.

Humans↗

PubMed2026

Addressing racism as a clinical competence: Robert Wilson, Jr. (1867-1946).

Addressing health inequity is now recognized as a clinical competency in medical education. We examined the career and writings of Robert Wilson Jr. (1867-1946), longtime dean of the Medical College of the State of South Carolina during the Jim Crow Era, using primary and secondary sources within the context of systemic and structural racism, particularly in South Carolina. Wilson used public health data to refute the "Black Extinction Hypothesis" rooted in social Darwinism. He challenged assumptions of inherent Black susceptibility to tuberculosis, linking disease instead to social determinants of health. He also identified disproportionate mortality from kidney and cardiovascular disease among Black populations, anticipating modern health disparities research. Wilson further acknowledged systemic injustice and implicated structural conditions, including housing, in shaping outcomes. In an era of continuing health inequity and racial health disparities, Wilson applied empirical evidence to reject biological determinism, identify outcomes disparities, and advocate for racial justice.

History, 20th Century↗

PubMed2026

Open repairs with biceps rerouting does not impact retears in large to massive rotator cuff tears compared to conventional open repair: a randomized clinical trial.

BACKGROUND: The treatment of large to massive rotator cuff tears leads to a high failure rate and several techniques have been proposed to improve these results. Rerouting the long head of the biceps tendon (LHBT) appears to be a biological reinforcement to increase tendon healing. Therefore, this study aimed to compare the clinical and radiological outcomes of open repair for large and massive rotator cuff tears reinforced with the LHBT to conventional open repair. METHODS: A prospective randomized study was conducted with patients diagnosed with large to massive rotator posterosuperior rotator cuff tear and intact LHBT, randomized into 2 groups: biceps rerouting and conventional open repair. The functional outcomes were assessed by the American Shoulder and Elbow Surgeon score, University of California at Los Angeles score, and SF-12 questionnaire preoperatively and at 6, 12, and 24 months postoperatively. Pain level was also assessed by the visual analog scale including the first day and 2 weeks postoperatively. Structural outcomes were rotator cuff and LHBT healing with magnetic resonance imaging and acromiohumeral distance (AHD) through radiography. RESULTS: We evaluated 58 patients, 29 in each group. At the end of the follow-up there were no statistically significant differences between groups in American Shoulder and Elbow Surgeon (76.1 vs. 80.4, P = .761), University of California at Los Angeles (27.1 vs. 29.1, P = .634), or visual analog scale scores (1.3 vs. 1.1, P = .781). Additionally, rotator cuff healing rates (48.3% vs. 44.8%, P = .402) and LHBT healing rates (79.3% vs. 82.7%, P = .738) were similar. AHD increased in both groups, with no significant difference in delta AHD (P = .513). Both groups showed significant clinical improvement over time in all evaluated outcomes (P < 0,01). No postoperative complications were reported. CONCLUSIONS: We could not identify an advantage of open repair with LHBT rerouting as reinforcement over conventional open repair. Nonetheless, all clinical scores improved at the end of the 24 months of follow-up in both groups.

Humans↗

PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗

PubMed2026

Beyond risk factors: A capacity framework for cancer survivorship research.

Cancer survivorship research has identified numerous biological, behavioral, psychosocial, health care, and structural factors that influence recovery. However, these factors are typically studied as separate determinants rather than interacting influences. This commentary proposes available survivorship capacity as a unifying framework that explains how these diverse determinants collectively shape recovery and survivorship outcomes. Concepts from geroscience, health care delivery, rehabilitation, occupational therapy, and human factors science were synthesized to develop a conceptual framework of available survivorship capacity. The framework conceptualizes recovery as a function of the capacity remaining after competing health care and life demands draw upon survivors' finite physical, cognitive, emotional, social, financial, temporal, and health care resources. It generates testable propositions for measurement, intervention research, health care delivery, and implementation science while positioning available survivorship capacity as a common mechanism linking diverse determinants of recovery and identifying actionable targets for intervention. Available capacity offers a unifying conceptual framework for understanding heterogeneity in survivorship outcomes and intervention effectiveness while generating a research agenda for future survivorship science. Measuring and strengthening survivors' available capacity, while reducing unnecessary demands, may improve engagement in care, health behaviors, and long-term recovery.

Humans↗

PubMed2026

Diagnostic performance of intraoperative in vivo hyperspectral imaging for meningioma grading and molecular alterations: results from a prospective feasibility study.

OBJECTIVE: Hyperspectral imaging (HSI) is an emerging intraoperative, noninvasive, contrast agent-free imaging modality that enables quantitative assessment of tissue composition. The present study aimed to investigate whether HSI-derived tissue parameters correlate with WHO grade and molecular markers of aggressiveness in cranial meningiomas. METHODS: In this prospective study, intraoperative in vivo HSI was performed using the TIVITA tissue system, capturing spectral signatures between 500 and 1000 nm. Quantitative tissue parameters included tissue oxygen saturation (StO2), near-infrared perfusion index, organ hemoglobin index (OHI), and tissue water index (TWI). HSI parameters were correlated with histopathological WHO grade and molecular alterations, including CDKN2A/B deletion, TERT promoter mutation, and 1p/22q loss. Group differences were analyzed using one-way ANOVA, and diagnostic performance was assessed using receiver operating characteristic (ROC) analysis. RESULTS: Forty-six meningiomas were included, comprising WHO grade 1 (n = 35) and WHO grade 2-3 (n = 11) tumors. TWI was significantly higher in WHO grade 2-3 meningiomas compared with WHO grade 1 tumors (mean 0.49 [SD 0.12] vs 0.38 [SD 0.17], p = 0.048). ROC analysis demonstrated an area under the ROC curve (AUC) of 0.71 (95% CI 0.56-0.86, p = 0.036) for TWI in discriminating higher-grade disease. A TWI cutoff ≥ 0.367 identified all WHO grade 2-3 meningiomas with 100% sensitivity and 100% negative predictive value. In a molecular subgroup (n = 15), OHI appeared higher in tumors with homozygous CDKN2A/B deletion than in nondeleted tumors (mean 0.77 [SD 0.04] vs 0.62 [SD 0.10]). However, only 3 CDKN2A/B-deleted cases were available, and these findings should be considered descriptive. ROC analysis yielded an AUC of 0.89 (95% CI 0.71-1.00). An OHI cutoff ≥ 0.712 identified all three CDKN2A/B-deleted tumors (100% sensitivity), with 83.3% specificity and 86.7% accuracy. CONCLUSIONS: The present investigation demonstrated that HSI-derived tissue water and hemoglobin metrics provide biologically meaningful information in meningiomas. Low tissue water content appeared to rule out higher-grade diseases in this first subset cohort, while elevated hemoglobin showed a potential association with CDKN2A/B deletion in a small exploratory subgroup. These findings support the potential of HSI as a real-time noninvasive tool for intraoperative risk stratification and should be evaluated in large-scale studies. German Clinical Trials Register no. DRKS00036771 (www.drks.de).

Humans↗

PubMed2026

New Evidence in Heart Failure: 2026 Update.

Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of HF continues to increase due to population aging, improved survival, and the growing prevalence of cardiovascular, renal, and metabolic comorbidities. Simultaneously, the pace of scientific progress in HF has accelerated considerably. Recent advances have refined our understanding of HF epidemiology, prognosis, and disease trajectories, including emerging concepts of HF improvement, remission, and recovery. The Second Universal Definition of HF has also updated the classification framework, moving beyond the traditional ejection fraction-based categories. HF is now broadly classified into two major phenotypes: heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Novel mechanistic insights highlight the role of inflammation, immune activation, metabolic dysfunction, mitochondrial biology, and multisystem interactions in HF progression. There has also been significant progress in the characterization and management of major comorbidities, including chronic kidney disease (CKD), diabetes, obesity, atrial fibrillation (AF), pulmonary hypertension, frailty, malnutrition, and cancer. Diagnostic innovations include novel biomarkers, multi-omics technologies, artificial intelligence-based approaches, advanced imaging techniques, congestion assessment tools, and emerging digital health solutions. Important advances have occurred in specific HF aetiologies, including cardiomyopathies, cardiac amyloidosis (CA), myocarditis, arrhythmia-induced cardiomyopathy (AiCM), and Chagas cardiomyopathy. Therapeutic developments continue to reshape HF management across the spectrum of left ventricular ejection fraction. Recent evidence has focused on optimization of guideline-directed medical therapy in HFrEF, expansion of evidence-based therapies in HFpEF, and growing roles for sodium-glucose cotransporter-2 inhibitors, finerenone, incretin-based therapies, and transcatheter valve interventions. Collectively, these advances support the transition from a predominantly phenotype-based approach towards a more personalized and biologically informed model of HF care, with the potential to further improve outcomes across the entire HF spectrum.

Journal Article↗

PubMed2026

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans↗

PubMed2026

The interplay between circadian misalignment or sleep disturbances and cognition and brain function in individuals with different degrees of insulin resistance - a systematic review.

Disruption of sleep increases the risk of type 2 diabetes and worsens cognitive outcomes, yet few studies have evaluated the interaction between insulin resistance and sleep parameters in relation to cognitive outcomes or the risk of dementia. This systematic review examines how circadian misalignment and sleep disturbances affect cognition and neuroimaging findings in individuals with varying degrees of insulin resistance. Across 27 studies, disrupted circadian rhythmicity and sleep disturbances were negatively associated with brain health, possibly through its effects on insulin sensitivity, whereas the impact of sleep duration and quality were inconclusive. Methodological heterogeneity, reliance on cross-sectional designs, and limited control for confounders restricted definitive conclusions and highlighted the need for longitudinal and interventional studies with objective measurements. Nonetheless, the findings support circadian rhythmicity as a potentially modifiable risk factor for preserving cognition in insulin-resistant populations. Future research should prioritise prospective and interventional studies and focus on biological markers rather than self-reported outcomes.

Humans↗

PubMed2026

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants↗

PubMed2026

CAR-T Cell Therapy: Manufacturing Platforms and Clinical Consequences.

Chimeric antigen receptor (CAR) T-cell therapy has transformed hematological cancer care, yet variability in efficacy, durability, and safety cannot be explained solely by antigen selection or patient factors. We propose that manufacturing platforms are active biological determinants of outcome. Viral vectors, used in all licensed products, provide stable genomic integration and durable expression but are limited by cost, cargo capacity, and centralized production. Nonviral strategies, including transposons, CRISPR knock-ins, and messenger RNA delivery, enable faster, less-expensive manufacturing with larger payloads, while introducing distinct safety and persistence profiles. This review presents a three-layer mechanistic framework that reframes manufacturing as biology: integration biology determines genomic risk and transgene stability; clonal fitness shapes persistence, dominance, and exhaustion; and epigenomic imprinting, influenced by gene transfer method, cytokines, and culture stress, preconfigures functional trajectories. Clinical observations link platform choice to immune recovery, where prolonged B-cell aplasia and delayed T-cell reconstitution contribute to infection-related nonrelapse mortality, and hematopoietic reserve at apheresis emerges as a practical predictor. Finally, manufacturing is positioned as the key to democratizing cell therapy. Decentralized, nonviral production aligned with regulatory standards may enable equitable access and transition CAR-T therapy from innovation to sustainable global care.

Humans↗

PubMed2026

Targeting TP53 in triple-negative breast cancer: Molecular pathogenesis, therapeutic implications, and emerging pharmacological strategies.

Triple-negative breast cancer (TNBC) remains a highly aggressive and therapeutically challenging subtype, defined by the absence of oestrogen, progesterone, and HER2 expression. Tumour Protein 53 (TP53) mutations represent the most frequent genetic alteration, occurring in over 80% of cases and driving tumour initiation, progression, and therapeutic resistance. Mutant p53 proteins not only lose canonical tumour-suppressive functions but also often acquire gain-of-function (GOF) oncogenic properties that promote metastasis, genomic instability, and resistance to mechanisms like ferroptosis. This review examines the biological role of TP53 in TNBC pathogenesis and evaluates emerging pharmacological strategies aimed at targeting these vulnerabilities. Key approaches include the pharmacological reactivation of mutant p53 using small molecules such as APR-246, COTI-2, and the mutation-specific reactivator rezatapopt (PC14586), which has shown significant clinical tumour reduction in Y220C-mutant patients. Other strategies involve targeted protein degradation, the exploitation of synthetic lethal interactions (e.g., Chk1 or Aurora kinase B inhibition), and the use of natural products like cryptolepine or piperine derivatives. Recent clinical evidence further highlights the potential of combining epigenetic agents like decitabine with chemotherapy in TP53-mutant populations. Integrating TP53 mutation status into biomarker-driven treatment paradigms is a pivotal step toward achieving precision oncology and improving clinical outcomes for patients with TNBC.

Precision oncology↗

PubMed2026

Functional and Nutritional Potential of Chickpea Protein Hydrolysates: A Systematic Review and Plant-protein Network Analysis.

Chickpea is a protein-rich legume increasingly explored as a substrate for functional plant-based ingredients. Chickpea protein hydrolysates (CPHs) and chickpea-derived peptides (CPs), obtained through enzymatic hydrolysis or simulated gastrointestinal digestion, may provide technological and biological properties while supporting the valorization of chickpea fractions and by-products. This review integrates a network analysis of title-abstract terms from 5,728 unique Scopus and PubMed records on plant protein hydrolysates with a systematic review of 72 studies focused on CPH production, peptide characterization, bioactivity, and translational gaps. The evidence indicates that CPHs and CPs show promising antioxidant, antihypertensive, antidiabetic, anti-inflammatory, lipid-lowering, immunomodulatory, antimicrobial, and anticancer-related activities, mainly supported by biochemical assays, cell models, and animal studies. However, heterogeneous hydrolysis protocols, incomplete peptide characterization, inconsistent bioactivity methods, limited scale-up evidence, and the absence of human intervention trials restrict translation. Future studies should prioritize standardized protocols, mechanistic validation, bioavailability, sensory and regulatory assessment, food-matrix validation, and clinical trials.

Cicer↗

PubMed2026

Effects of apple phenolics on the human metabolome: modulation of key metabolic pathways.

Apples are widely recognized for their potential health benefits, partly attributed to their phenolic compounds. However, their impact on human metabolism remains incompletely understood. This study investigated metabolic effects of apple-derived phenolic compounds using untargeted metabolomics approach across multiple biofluids. In a crossover intervention study, 30 healthy men consumed a phenolic-rich apple juice or a placebo for two weeks. Blood, urine and saliva samples were collected before and after each intervention and analyzed by direct infusion ultra-high resolution mass spectrometry. Consumption of apple phenolic compounds resulted in significant alterations of the human metabolome, including increased levels of phenolic-derived degradation products and microbial-associated metabolites across all biofluids. Pathway enrichment analysis revealed pronounced effects on phenylalanine and tyrosine metabolism, as well as linoleic and arachidonic acid metabolism, Overall, these findings demonstrate that apple phenolic compounds induce measurable, microbiota-associated and systemic metabolic changes, providing new insights into their metabolic fate and biological relevance.

Humans↗

PubMed2026

Thermal analysis techniques for microplastic mass quantification: Methodological challenges and standardization needs.

Microplastics (MPs, 1 μm-5 mm) and nanoplastics (NPs, <1 μm) are ubiquitous contaminants requiring standardized quantification methods. This systematic review evaluates thermal analysis techniques for mass-based MP detection, including pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS), thermogravimetry-MS (TGA-MS), thermal extraction desorption-GC-MS (TED-GC-MS), and differential scanning calorimetry (DSC). Database searches (Web of Science, from inception to December 1, 2025) following PRISMA guidelines identified studies across seven environmental matrices (water, soil/sediment, atmosphere, biota, human tissues). We identify critical standardization gaps: inconsistent marker ion selection, unvalidated conversion factors for tire and road wear particles (TRWPs), and the absence of certified reference materials for complex matrices. Py-GC-MS demonstrates versatility but suffers from lipid interference in biological samples; TED-GC-MS offers superior sensitivity (sample capacity ∼200× Py-GC-MS) but lacks real-time chromatographic monitoring. To advance data comparability, we propose: (i) harmonized ion selection hierarchies based on specificity-sensitivity balance, (ii) matrix-specific TRWP quantification protocols, and (iii) inter-laboratory validation using environmental reference materials. This review provides a methodological roadmap for standardizing thermal analysis in MP research.

Humans↗

PubMed2026

Sitosterolemia: evolving strategies for earlier diagnosis.

PURPOSE OF REVIEW: Sitosterolemia is a rare autosomal recessive lipid disorder caused by biallelic pathogenic variants in ABCG5 or ABCG8 , resulting in excessive intestinal absorption and impaired biliary excretion of plant sterols. Although historically considered exceptionally rare, recent genetic studies suggest the disorder is substantially underdiagnosed, with marked phenotypic heterogeneity ranging from xanthomas and premature atherosclerosis to hematologic abnormalities, and frequently mimics familial hypercholesterolemia. This review summarizes recent advances in the clinical, biological, and genetic diagnosis of sitosterolemia, with a focus on strategies that may facilitate earlier detection. RECENT FINDINGS: Phytosterol quantification, particularly sitosterol, campesterol, and stigmasterol, remains indispensable for accurate diagnosis. Hematologic abnormalities, including hemolytic anemia, stomatocytosis, and macrothrombocytopenia, are increasingly recognized as valuable diagnostic clues complementing the biochemical approach. Expanded variant catalogs for ABCG5/ABCG8 and genome-wide association studies have revealed potentially polygenic contributions to phytosterol metabolism extending beyond these two genes. However, no specific guidelines have yet been established for cascade screening. SUMMARY: Earlier diagnosis requires integration of clinical, biochemical, hematologic, and genetic data. Plasma phytosterol measurement remains the diagnostic cornerstone. Improved disease awareness, broader access to sterol testing, and expanded genetic screening may reduce diagnostic delays and enable timely management, including ezetimibe and dietary phytosterol restriction.

Humans↗

PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗