Previous
Endocrine treatment in combination with CDK4/6 inhibitors represents the mainstay of first-line palliative treatment in HR+/HER2– breast cancer. The treatment landscape after progression on CDK4/6 inhibitors has evolved into a complex and rapidly evolving field, driven by novel endocrine and targeted agents, new combination therapies, and increasing implementation of biomarker-directed approaches. Recent randomized trials have shown that new therapeutic strategies significantly prolong progression-free survival in this setting, with some treatments reaching notable numerical improvements. Translating these options into routine clinical practice remains challenging due to heterogeneous trial designs, lack of head-to-head comparisons, suboptimal comparator treatments, and limited overall survival data. While the increasing implementation of biomarkers holds the potential for more personalized treatments, their clinical utility depends on their mechanistic and contextual biological relevance, methodological reliability of detection, and proven predictive value in clinical trials. Based on the current evidence, optimal treatment selection and sequencing in the post-CDK4/6 inhibitor setting remain insufficiently defined, and optimization of biomarker-guided treatment requires further mechanistic understanding and methodological refinement. This narrative review provides an overview of the most recent randomized clinical trial evidence shaping current clinical practice and discusses persistent uncertainties regarding its implementation in routine care.
Endocrine treatment in combination with CDK4/6 inhibitors represents the mainstay of first-line palliative treatment in HR+/HER2– breast cancer. The treatment landscape after progression on CDK4/6 inhibitors has evolved into a complex and rapidly evolving field, driven by novel endocrine and targeted agents, new combination therapies, and increasing implementation of biomarker-directed approaches. Recent randomized trials have shown that new therapeutic strategies significantly prolong progression-free survival in this setting, with some treatments reaching notable numerical improvements. Translating these options into routine clinical practice remains challenging due to heterogeneous trial designs, lack of head-to-head comparisons, suboptimal comparator treatments, and limited overall survival data. While the increasing implementation of biomarkers holds the potential for more personalized treatments, their clinical utility depends on their mechanistic and contextual biological relevance, methodological reliability of detection, and proven predictive value in clinical trials. Based on the current evidence, optimal treatment selection and sequencing in the post-CDK4/6 inhibitor setting remain insufficiently defined, and optimization of biomarker-guided treatment requires further mechanistic understanding and methodological refinement. This narrative review provides an overview of the most recent randomized clinical trial evidence shaping current clinical practice and discusses persistent uncertainties regarding its implementation in routine care.
DOI: https://doi.org/10.37349/etat.2026.1002400
This article belongs to the special issue Breaking Boundaries in Breast Cancer Care: Emerging Controversies and Innovation in Surgical and Medical Approaches
Aim:
This study examines the interactions of climate change, economic, and social factors on food security, by way of a three -decade impact and threat assessment of Nigeria.
Methods:
The study employs annual time-series data covering 32 observations and applies the Autoregressive Distributed Lag (ARDL) modeling approach to examine both the long-run and short-run relationships among the variables. Prior to estimation, the Augmented Dickey-Fuller (ADF) unit root test was conducted to determine the stationarity properties of the variables, while the ARDL bounds test was used to verify the existence of a long-run cointegration relationship.
Results:
The findings confirm a long-run equilibrium relationship between food security and the selected climatic and socio-economic variables. Both the long-run and short-run estimates show that temperature, rainfall variability, relative humidity, population growth, poverty rate, migration, and limited access to credit significantly reduce per capita food expenditure, thereby worsening food security. The error correction model is negative and statistically significant, indicating rapid adjustment to long-run equilibrium following short-run disturbances. Diagnostic tests further confirm that the estimated model is statistically robust, free from multicollinearity, heteroskedasticity, and serial correlation, and stable over the study period.
Conclusions:
The study demonstrates that food security in Nigeria is shaped by the combined effects of climate change and socio-economic vulnerabilities, underscoring the need for integrated adaptation and development policies. Strengthening climate-resilient agricultural practices, expanding access to credit, reducing poverty, and enhancing social protection measures are essential to improving household food security and building resilience to future climatic and economic shocks.
Aim:
This study examines the interactions of climate change, economic, and social factors on food security, by way of a three -decade impact and threat assessment of Nigeria.
Methods:
The study employs annual time-series data covering 32 observations and applies the Autoregressive Distributed Lag (ARDL) modeling approach to examine both the long-run and short-run relationships among the variables. Prior to estimation, the Augmented Dickey-Fuller (ADF) unit root test was conducted to determine the stationarity properties of the variables, while the ARDL bounds test was used to verify the existence of a long-run cointegration relationship.
Results:
The findings confirm a long-run equilibrium relationship between food security and the selected climatic and socio-economic variables. Both the long-run and short-run estimates show that temperature, rainfall variability, relative humidity, population growth, poverty rate, migration, and limited access to credit significantly reduce per capita food expenditure, thereby worsening food security. The error correction model is negative and statistically significant, indicating rapid adjustment to long-run equilibrium following short-run disturbances. Diagnostic tests further confirm that the estimated model is statistically robust, free from multicollinearity, heteroskedasticity, and serial correlation, and stable over the study period.
Conclusions:
The study demonstrates that food security in Nigeria is shaped by the combined effects of climate change and socio-economic vulnerabilities, underscoring the need for integrated adaptation and development policies. Strengthening climate-resilient agricultural practices, expanding access to credit, reducing poverty, and enhancing social protection measures are essential to improving household food security and building resilience to future climatic and economic shocks.
DOI: https://doi.org/10.37349/eff.2026.1010189
Aim:
To investigate the associations between the digital neurobehavioral signature (DNS) score, cognitive function, and psychological resilience among adults, and to explore the potential mediating role of psychological resilience in the association between digital behavioral patterns and cognitive performance.
Methods:
A cross-sectional study was conducted at Abbasi Shaheed Hospital, Karachi, among 400 adults. DNS was assessed using a composite DNS score derived from screen time, sleep, physical activity, and digital engagement. Cognitive function was measured using the Montreal Cognitive Assessment, while psychological resilience and depressive symptoms were assessed using validated scales. Multivariable regression and mediation analyses were performed to evaluate independent associations and indirect effects. For continuous outcomes, differences across DNS profiles were assessed using one-way ANOVA, followed by Bonferroni-adjusted post-hoc pairwise comparisons when the ANOVA was significant. A p < 0.05 was considered statistically significant.
Results:
Participants with maladaptive DNS demonstrated significantly lower cognitive performance and psychological resilience compared with those with adaptive profiles, with significant differences confirmed by Bonferroni-adjusted post-hoc pairwise comparisons (p < 0.001). Higher DNS composite scores were independently associated with lower cognitive scores (β = −0.34, p < 0.001). Psychological resilience was positively associated with cognitive function and partially mediated the association between digital behavioral patterns and cognition.
Conclusions:
These findings suggest that the exploratory DNS composite behavioral index is associated with cognitive function and psychological resilience and may provide a framework for investigating relationships between digital lifestyle behaviors and neurocognitive and psychological outcomes.
Aim:
To investigate the associations between the digital neurobehavioral signature (DNS) score, cognitive function, and psychological resilience among adults, and to explore the potential mediating role of psychological resilience in the association between digital behavioral patterns and cognitive performance.
Methods:
A cross-sectional study was conducted at Abbasi Shaheed Hospital, Karachi, among 400 adults. DNS was assessed using a composite DNS score derived from screen time, sleep, physical activity, and digital engagement. Cognitive function was measured using the Montreal Cognitive Assessment, while psychological resilience and depressive symptoms were assessed using validated scales. Multivariable regression and mediation analyses were performed to evaluate independent associations and indirect effects. For continuous outcomes, differences across DNS profiles were assessed using one-way ANOVA, followed by Bonferroni-adjusted post-hoc pairwise comparisons when the ANOVA was significant. A p < 0.05 was considered statistically significant.
Results:
Participants with maladaptive DNS demonstrated significantly lower cognitive performance and psychological resilience compared with those with adaptive profiles, with significant differences confirmed by Bonferroni-adjusted post-hoc pairwise comparisons (p < 0.001). Higher DNS composite scores were independently associated with lower cognitive scores (β = −0.34, p < 0.001). Psychological resilience was positively associated with cognitive function and partially mediated the association between digital behavioral patterns and cognition.
Conclusions:
These findings suggest that the exploratory DNS composite behavioral index is associated with cognitive function and psychological resilience and may provide a framework for investigating relationships between digital lifestyle behaviors and neurocognitive and psychological outcomes.
DOI: https://doi.org/10.37349/ent.2026.1004168
Aim:
Valvular heart disease (VHD) is an important factor in cardiovascular mortality. While early diagnosis is essential, existing methods often lack accuracy, leading to misdiagnosis. This study explores the use of deep learning (DL) for multi-class classification of VHD using phonocardiograph (PCG) signals.
Methods:
The dataset includes normal PCG heart signals and nine VHD classes such as severe and mild aortic stenosis, mild and moderate mitral stenosis, mild, moderate, and severe mitral regurgitation, and moderate and severe tricuspid regurgitation. A novel convolutional neural network (CNN) is developed to classify these ten classes, demonstrating high accuracy even in noisy data acquisition. Unlike traditional machine learning, which relies on handcrafted features such as spectral, wavelet, and mel-frequency cepstral coefficients, the CNN model automatically learns patterns from raw signals, thereby reducing the need for manual feature engineering. The model is further validated using real-time PCG data from heart clinics diagnosed by heart specialists.
Results:
It achieves excellent performance with 99.81% accuracy, 99.84% precision, 99.82% recall, 99.85% F1-score, and an area under the curve of the receiver operating characteristic of 1.0.
Conclusions:
This DL model eliminates segmentation and manual pre-processing, enabling early, accurate VHD detection while outperforming existing methods and supporting clinical decisions and patient care.
Aim:
Valvular heart disease (VHD) is an important factor in cardiovascular mortality. While early diagnosis is essential, existing methods often lack accuracy, leading to misdiagnosis. This study explores the use of deep learning (DL) for multi-class classification of VHD using phonocardiograph (PCG) signals.
Methods:
The dataset includes normal PCG heart signals and nine VHD classes such as severe and mild aortic stenosis, mild and moderate mitral stenosis, mild, moderate, and severe mitral regurgitation, and moderate and severe tricuspid regurgitation. A novel convolutional neural network (CNN) is developed to classify these ten classes, demonstrating high accuracy even in noisy data acquisition. Unlike traditional machine learning, which relies on handcrafted features such as spectral, wavelet, and mel-frequency cepstral coefficients, the CNN model automatically learns patterns from raw signals, thereby reducing the need for manual feature engineering. The model is further validated using real-time PCG data from heart clinics diagnosed by heart specialists.
Results:
It achieves excellent performance with 99.81% accuracy, 99.84% precision, 99.82% recall, 99.85% F1-score, and an area under the curve of the receiver operating characteristic of 1.0.
Conclusions:
This DL model eliminates segmentation and manual pre-processing, enabling early, accurate VHD detection while outperforming existing methods and supporting clinical decisions and patient care.
DOI: https://doi.org/10.37349/ec.2026.1012121
Alzheimer’s disease, a neurodegenerative disease, is caused by the accumulation of amyloid-β (Aβ) protein and hyperphosphorylation of Tau protein in the brain, resulting in decreased cognitive function and memory. Neuroinflammation, which is the body’s defense mechanism in the brain, is one of the factors that can worsen the condition of Alzheimer’s patients. The activity of glial cells, such as microglia and astrocytes, causes the release of proinflammatory cytokines that can damage the neurons. However, currently available therapies can only address the symptoms of Alzheimer’s disease. Therefore, alternative strategies are needed that can be used to overcome Alzheimer’s disease, such as the use of natural compounds that have therapeutic potential. The purpose of this article is to discuss the potential of natural substances, such as curcumin, resveratrol, and luteolin, in modulating neuroinflammation. Curcumin, a compound contained in rhizome plants, has been shown to inhibit neuroinflammation by inhibiting the activation of innate immune signalling pathways and suppressing microglia activity. Resveratrol, a polyphenol in plants, has been reported to reduce neuroinflammation by modulating the Sirtuin 1 signalling pathway and polarizing microglia. Luteolin, a plant secondary metabolite belonging to the flavonoid group, is reported to be effective in reducing the production of reactive astrocytes and inhibits the p38 MAPK pathway to reduce neuroinflammation. Overall, preclinical evidence suggests that these natural substances show potential as therapeutic candidates for Alzheimer’s disease, although further clinical studies are still needed to confirm their efficacy and safety.
Alzheimer’s disease, a neurodegenerative disease, is caused by the accumulation of amyloid-β (Aβ) protein and hyperphosphorylation of Tau protein in the brain, resulting in decreased cognitive function and memory. Neuroinflammation, which is the body’s defense mechanism in the brain, is one of the factors that can worsen the condition of Alzheimer’s patients. The activity of glial cells, such as microglia and astrocytes, causes the release of proinflammatory cytokines that can damage the neurons. However, currently available therapies can only address the symptoms of Alzheimer’s disease. Therefore, alternative strategies are needed that can be used to overcome Alzheimer’s disease, such as the use of natural compounds that have therapeutic potential. The purpose of this article is to discuss the potential of natural substances, such as curcumin, resveratrol, and luteolin, in modulating neuroinflammation. Curcumin, a compound contained in rhizome plants, has been shown to inhibit neuroinflammation by inhibiting the activation of innate immune signalling pathways and suppressing microglia activity. Resveratrol, a polyphenol in plants, has been reported to reduce neuroinflammation by modulating the Sirtuin 1 signalling pathway and polarizing microglia. Luteolin, a plant secondary metabolite belonging to the flavonoid group, is reported to be effective in reducing the production of reactive astrocytes and inhibits the p38 MAPK pathway to reduce neuroinflammation. Overall, preclinical evidence suggests that these natural substances show potential as therapeutic candidates for Alzheimer’s disease, although further clinical studies are still needed to confirm their efficacy and safety.
DOI: https://doi.org/10.37349/ent.2026.1004167
This article belongs to the special issue Neuro-Inflammation as a Target in the Design of Multifunctional Drug Candidates for Neurodegenerative Diseases
Aim:
Antimicrobial resistance poses a major global health crisis, with some bacterial strains now resistant to nearly all available antibiotics. Carbon quantum dots (CQDs) have emerged as promising nanomaterials for broad-spectrum infection prevention owing to their multiple antibacterial mechanisms, biocompatibility, and cost-effectiveness. Many reported CQD fabrication methods rely on synthetic chemicals, which increase production costs and potentially compromise the biocompatibility of the resulting CQDs. Although green-synthesized CQDs have attracted considerable attention for antibacterial applications, limited studies have investigated the use of natural, food-derived components to tune CQD surface charge and its influence on antibacterial activity and mammalian cell compatibility. This study aims to develop CQDs with tunable surface charges from natural food-derived carbon sources for broad-spectrum antibacterial applications.
Methods:
Whole-meal bread and soybean flour were used as biogenic precursors to synthesize negatively charged CQDs via a simple hydrothermal method. Surface charge was adjusted to neutral and positive by incorporating lemon juice and chitosan during synthesis. Antibacterial activity and mammalian cell viability were evaluated.
Results:
Bread- and soybean-derived CQDs exhibited negative surface charges (–15 mV) due to abundant carboxyl and hydroxyl groups formed during precursor decomposition. Addition of lemon juice altered the surface chemistry by introducing balanced protonated and deprotonated species, producing zwitterionic CQDs with near-neutral charge (–0.1 mV). Further incorporation of chitosan introduced protonated amine groups (–NH3+), yielding positively charged CQDs (+10 mV). At an optimal concentration of 10 µg/mL, both neutral and positively charged CQDs demonstrated moderate broad-spectrum antibacterial activity (30–40% inhibition) against Gram-negative and Gram-positive bacteria. Their antibacterial effect was attributed to favorable electrostatic interactions with negatively charged bacterial cell envelopes, causing membrane disruption, reactive oxygen species (ROS)-induced damage, and intracellular interference. In contrast, mammalian cells maintained 100% viability, likely due to their flexible cholesterol-rich membranes, stronger antioxidant defense systems, and intracellular compartmentalization.
Conclusions:
This study demonstrates a reagent-free and sustainable approach for producing CQDs with controlled surface charges from natural precursors. The resulting CQDs show strong potential as safe and effective antibacterial nanomaterials for biomedical applications.
Aim:
Antimicrobial resistance poses a major global health crisis, with some bacterial strains now resistant to nearly all available antibiotics. Carbon quantum dots (CQDs) have emerged as promising nanomaterials for broad-spectrum infection prevention owing to their multiple antibacterial mechanisms, biocompatibility, and cost-effectiveness. Many reported CQD fabrication methods rely on synthetic chemicals, which increase production costs and potentially compromise the biocompatibility of the resulting CQDs. Although green-synthesized CQDs have attracted considerable attention for antibacterial applications, limited studies have investigated the use of natural, food-derived components to tune CQD surface charge and its influence on antibacterial activity and mammalian cell compatibility. This study aims to develop CQDs with tunable surface charges from natural food-derived carbon sources for broad-spectrum antibacterial applications.
Methods:
Whole-meal bread and soybean flour were used as biogenic precursors to synthesize negatively charged CQDs via a simple hydrothermal method. Surface charge was adjusted to neutral and positive by incorporating lemon juice and chitosan during synthesis. Antibacterial activity and mammalian cell viability were evaluated.
Results:
Bread- and soybean-derived CQDs exhibited negative surface charges (–15 mV) due to abundant carboxyl and hydroxyl groups formed during precursor decomposition. Addition of lemon juice altered the surface chemistry by introducing balanced protonated and deprotonated species, producing zwitterionic CQDs with near-neutral charge (–0.1 mV). Further incorporation of chitosan introduced protonated amine groups (–NH3+), yielding positively charged CQDs (+10 mV). At an optimal concentration of 10 µg/mL, both neutral and positively charged CQDs demonstrated moderate broad-spectrum antibacterial activity (30–40% inhibition) against Gram-negative and Gram-positive bacteria. Their antibacterial effect was attributed to favorable electrostatic interactions with negatively charged bacterial cell envelopes, causing membrane disruption, reactive oxygen species (ROS)-induced damage, and intracellular interference. In contrast, mammalian cells maintained 100% viability, likely due to their flexible cholesterol-rich membranes, stronger antioxidant defense systems, and intracellular compartmentalization.
Conclusions:
This study demonstrates a reagent-free and sustainable approach for producing CQDs with controlled surface charges from natural precursors. The resulting CQDs show strong potential as safe and effective antibacterial nanomaterials for biomedical applications.
DOI: https://doi.org/10.37349/ebmx.2026.101373
The clinical significance of neutrophil activation and NETosis in patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is the focus of ongoing research. In the presented clinical case of active granulomatosis with polyangiitis (GPA) with multi-organ damage associated with ANCA-proteinase 3 (PR3), a high proportion of neutrophils transitioning to NETosis (97.9%) was detected. This case report aimed to characterize spontaneous NETosis and neutrophil functional activity in a patient with severe active PR3-positive GPA in order to determine whether a distinct pattern of neutrophil activation could be identified. In this case, NETosis was completely represented by the suicidal variant, with no evidence of vital NETosis or extracellular DNA structures formed by other leukocytes. This observation adds to the current understanding of the key role of neutrophils and NETs in the pathogenesis of AAV. Unlike previous studies that mainly quantified circulating NET markers or stimulated NET formation in vitro, this report provides an integrated assessment of spontaneous NETosis phenotype together with neutrophil chemotaxis and thromboinflammatory behavior in an individual patient with active GPA.
The clinical significance of neutrophil activation and NETosis in patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is the focus of ongoing research. In the presented clinical case of active granulomatosis with polyangiitis (GPA) with multi-organ damage associated with ANCA-proteinase 3 (PR3), a high proportion of neutrophils transitioning to NETosis (97.9%) was detected. This case report aimed to characterize spontaneous NETosis and neutrophil functional activity in a patient with severe active PR3-positive GPA in order to determine whether a distinct pattern of neutrophil activation could be identified. In this case, NETosis was completely represented by the suicidal variant, with no evidence of vital NETosis or extracellular DNA structures formed by other leukocytes. This observation adds to the current understanding of the key role of neutrophils and NETs in the pathogenesis of AAV. Unlike previous studies that mainly quantified circulating NET markers or stimulated NET formation in vitro, this report provides an integrated assessment of spontaneous NETosis phenotype together with neutrophil chemotaxis and thromboinflammatory behavior in an individual patient with active GPA.
DOI: https://doi.org/10.37349/emd.2026.1007136
Aim:
Kinetoplastids are flagellated protozoa encompassing multiple parasitic species responsible for severe neglected diseases. Although treatments exist, therapeutic failure and toxic side effects underscore the need for innovative drug development. Recent advances in protein design have accelerated the creation of small protein modules with specific functions, known as miniproteins, with broad pharmacological applications. However, their intrinsic inability to cross biological membranes limits their use against intracellular targets. This work aims to propose and computationally explore a modular delivery strategy that exploits the flagellar pocket (FP) as an entry route to deliver protein-based therapeutics into the parasites.
Methods:
Using experimentally determined structures of three FP receptors, we applied a motif-scaffolding pipeline combining RFdiffusion, ProteinMPNN, and AlphaFold2-multimer to design de novo miniprotein modules capable of mimicking the natural cargo recognized by each receptor. Candidate designs were evaluated using a scoring function integrating minimum interaction predicted aligned error (miPAE) and backbone root mean square deviation (RMSD) across five predicted models per design.
Results:
The design campaign yielded different outcomes depending on the target. For the transferrin receptor, 67 candidates surpassed the established in silico success thresholds, a pool expected to contain multiple experimentally validated binders. For the invariable surface glycoprotein 65, 17 candidates met the criteria, constituting a tractable experimental panel. Lastly, the haptoglobin-hemoglobin receptor proved a challenging target, with no candidates clearly surpassing both thresholds, likely due to the hydrophilic nature of its binding interfaces and the requirement for direct heme coordination.
Conclusions:
This work provides a structural rationale for a novel receptor-mediated intracellular delivery paradigm in kinetoplastid parasites, offering a computational pipeline for generating miniprotein modules ready for experimental validation. We further outline how these delivery modules could be integrated into modular protein-based drugs incorporating protease recognition sequences, cell-penetrating peptides, and subcellular localization signals, laying the conceptual ground for a new therapeutic approach against these neglected diseases.
Aim:
Kinetoplastids are flagellated protozoa encompassing multiple parasitic species responsible for severe neglected diseases. Although treatments exist, therapeutic failure and toxic side effects underscore the need for innovative drug development. Recent advances in protein design have accelerated the creation of small protein modules with specific functions, known as miniproteins, with broad pharmacological applications. However, their intrinsic inability to cross biological membranes limits their use against intracellular targets. This work aims to propose and computationally explore a modular delivery strategy that exploits the flagellar pocket (FP) as an entry route to deliver protein-based therapeutics into the parasites.
Methods:
Using experimentally determined structures of three FP receptors, we applied a motif-scaffolding pipeline combining RFdiffusion, ProteinMPNN, and AlphaFold2-multimer to design de novo miniprotein modules capable of mimicking the natural cargo recognized by each receptor. Candidate designs were evaluated using a scoring function integrating minimum interaction predicted aligned error (miPAE) and backbone root mean square deviation (RMSD) across five predicted models per design.
Results:
The design campaign yielded different outcomes depending on the target. For the transferrin receptor, 67 candidates surpassed the established in silico success thresholds, a pool expected to contain multiple experimentally validated binders. For the invariable surface glycoprotein 65, 17 candidates met the criteria, constituting a tractable experimental panel. Lastly, the haptoglobin-hemoglobin receptor proved a challenging target, with no candidates clearly surpassing both thresholds, likely due to the hydrophilic nature of its binding interfaces and the requirement for direct heme coordination.
Conclusions:
This work provides a structural rationale for a novel receptor-mediated intracellular delivery paradigm in kinetoplastid parasites, offering a computational pipeline for generating miniprotein modules ready for experimental validation. We further outline how these delivery modules could be integrated into modular protein-based drugs incorporating protease recognition sequences, cell-penetrating peptides, and subcellular localization signals, laying the conceptual ground for a new therapeutic approach against these neglected diseases.
DOI: https://doi.org/10.37349/eds.2026.1008179
Inulin is a naturally occurring water-soluble fructan-type polysaccharide composed primarily of β (2→1)-linked D-fructose units, typically terminated by a glucose residue. Inulin is widely used as a functional ingredient due to its technological and health-promoting benefits. This review provides a comprehensive, up-to-date evaluation of inulin, focusing on its structural characteristics, physicochemical properties, extraction techniques, and applications in food. Conventional and emerging green extraction methods, such as microwave-assisted, ultrasound-assisted, and enzyme-assisted methods, are compared with respect to efficiency, yield, and sustainability. The functionality of inulin as a fat replacer, sugar substitute, and texturizing agent is critically examined, particularly with respect to its degree of polymerization. In addition, the prebiotic and immunomodulatory effects of inulin are addressed, emphasizing its role in modulating gut microbiota and associated health outcomes. Advanced analytical techniques, such as Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), and thermogravimetric analysis and differential scanning calorimetry (TGA-DSC), are also discussed to determine the structure-function relationships of inulin. This review summarizes recent advances and identifies key research gaps to support the effective, targeted use of inulin in functional foods and health applications.
Inulin is a naturally occurring water-soluble fructan-type polysaccharide composed primarily of β (2→1)-linked D-fructose units, typically terminated by a glucose residue. Inulin is widely used as a functional ingredient due to its technological and health-promoting benefits. This review provides a comprehensive, up-to-date evaluation of inulin, focusing on its structural characteristics, physicochemical properties, extraction techniques, and applications in food. Conventional and emerging green extraction methods, such as microwave-assisted, ultrasound-assisted, and enzyme-assisted methods, are compared with respect to efficiency, yield, and sustainability. The functionality of inulin as a fat replacer, sugar substitute, and texturizing agent is critically examined, particularly with respect to its degree of polymerization. In addition, the prebiotic and immunomodulatory effects of inulin are addressed, emphasizing its role in modulating gut microbiota and associated health outcomes. Advanced analytical techniques, such as Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), and thermogravimetric analysis and differential scanning calorimetry (TGA-DSC), are also discussed to determine the structure-function relationships of inulin. This review summarizes recent advances and identifies key research gaps to support the effective, targeted use of inulin in functional foods and health applications.
DOI: https://doi.org/10.37349/eff.2026.1010188
Aim:
To investigate interobserver variability in programmed cell death ligand 1 (PD-L1) combined positive score (CPS) assessment in head and neck squamous cell carcinoma (HNSCC) and to develop an artificial intelligence (AI)-based model for predicting PD-L1 expression and patient prognosis from hematoxylin and eosin (H&E)-stained slides.
Methods:
Fifty HNSCC specimens were independently evaluated for PD-L1 by pathologists with different experience levels. Agreement was assessed using Fleiss’ and Cohen’s κ. Whole-slide images were processed into tiles for deep learning using DenseNet121. Tile-level features were integrated via two machine learning pipelines to construct whole-slide prediction models. Multiple algorithms were tested, with performance evaluated in validation and testing cohorts. Prognostic value was analyzed using AI-derived risk stratification.
Results:
Interobserver agreement was low (Fleiss’ κ = 0.34), indicating substantial variability in CPS assessment. DenseNet121 achieved moderate predictive performance (AUC 0.641 in validation, 0.616 in testing). AI models significantly improved prediction accuracy, with logistic regression demonstrating the best performance (AUC 0.900 in validation, 0.851 in testing). AI-derived prediction scores effectively stratified overall survival, with multiple models showing significant prognostic discrimination (P < 0.05).
Conclusions:
AI models integrating deep learning and machine learning can accurately predict PD-L1 expression and stratify prognosis in HNSCC, outperforming tile-level deep learning alone.
Aim:
To investigate interobserver variability in programmed cell death ligand 1 (PD-L1) combined positive score (CPS) assessment in head and neck squamous cell carcinoma (HNSCC) and to develop an artificial intelligence (AI)-based model for predicting PD-L1 expression and patient prognosis from hematoxylin and eosin (H&E)-stained slides.
Methods:
Fifty HNSCC specimens were independently evaluated for PD-L1 by pathologists with different experience levels. Agreement was assessed using Fleiss’ and Cohen’s κ. Whole-slide images were processed into tiles for deep learning using DenseNet121. Tile-level features were integrated via two machine learning pipelines to construct whole-slide prediction models. Multiple algorithms were tested, with performance evaluated in validation and testing cohorts. Prognostic value was analyzed using AI-derived risk stratification.
Results:
Interobserver agreement was low (Fleiss’ κ = 0.34), indicating substantial variability in CPS assessment. DenseNet121 achieved moderate predictive performance (AUC 0.641 in validation, 0.616 in testing). AI models significantly improved prediction accuracy, with logistic regression demonstrating the best performance (AUC 0.900 in validation, 0.851 in testing). AI-derived prediction scores effectively stratified overall survival, with multiple models showing significant prognostic discrimination (P < 0.05).
Conclusions:
AI models integrating deep learning and machine learning can accurately predict PD-L1 expression and stratify prognosis in HNSCC, outperforming tile-level deep learning alone.
DOI: https://doi.org/10.37349/emed.2026.1001426
Pathogenic variants in the tumor suppressor gene NF1 cause neurofibromatosis type 1 (NF1), one of the most common hereditary cancer predisposition syndromes. Pathogenic NF1 variants have been associated with an increased risk of several cancers; however, the relationship between NF1 variation and colon cancer remains underreported. We report a 41-year-old woman with a mosaic monoallelic germline pathogenic NF1 variant, NM_000267.3:c.1756_1759del (p.Thr586Valfs*18), previously detected on germline multigene panel testing in saliva at a variant allele frequency of approximately 35%. She later presented with fatigue, dyspnea on exertion, and iron-deficiency anemia. Computed tomography, colonoscopy, biopsy, mismatch repair immunohistochemistry, surgical pathology, and tumor next-generation sequencing led to the diagnosis of right-sided colon adenocarcinoma that was mismatch repair deficient (dMMR) and microsatellite instability-high (MSI-H). She underwent right hemicolectomy, recovered postoperatively, and entered standard surveillance; at the time of manuscript development, she was also receiving systemic therapy. This case highlights the co-occurrence of an NF1 variant and dMMR colorectal cancer and underscores the need for further studies to determine whether this represents a coincidental finding or a biologically meaningful association.
Pathogenic variants in the tumor suppressor gene NF1 cause neurofibromatosis type 1 (NF1), one of the most common hereditary cancer predisposition syndromes. Pathogenic NF1 variants have been associated with an increased risk of several cancers; however, the relationship between NF1 variation and colon cancer remains underreported. We report a 41-year-old woman with a mosaic monoallelic germline pathogenic NF1 variant, NM_000267.3:c.1756_1759del (p.Thr586Valfs*18), previously detected on germline multigene panel testing in saliva at a variant allele frequency of approximately 35%. She later presented with fatigue, dyspnea on exertion, and iron-deficiency anemia. Computed tomography, colonoscopy, biopsy, mismatch repair immunohistochemistry, surgical pathology, and tumor next-generation sequencing led to the diagnosis of right-sided colon adenocarcinoma that was mismatch repair deficient (dMMR) and microsatellite instability-high (MSI-H). She underwent right hemicolectomy, recovered postoperatively, and entered standard surveillance; at the time of manuscript development, she was also receiving systemic therapy. This case highlights the co-occurrence of an NF1 variant and dMMR colorectal cancer and underscores the need for further studies to determine whether this represents a coincidental finding or a biologically meaningful association.
DOI: https://doi.org/10.37349/en.2026.1006148
Parturients with pulmonary arterial hypertension (PAH) face an increased risk of morbidity and mortality surrounding the peripartum period. Patients with severe PAH and Eisenmenger syndrome have the highest risk for perioperative mortality and provide a significant perioperative challenge for anesthesiologists, necessitating a multidisciplinary approach throughout pregnancy. We present a case of an urgent cesarean section at 37 weeks of gestation in a patient with Eisenmenger syndrome, a large atrial septal defect, and supra-systemic pulmonary hypertension. Due to the patient’s severity of PAH, cardiothoracic surgery was present and placed femoral arterial and venous catheters in preparation for possible extracorporeal membrane oxygenation (ECMO) cannulation in the event of hemodynamic collapse. The procedure was performed under a carefully titrated epidural, thus avoiding general anesthesia and the dangers associated with inducing a patient with her comorbid conditions. An arterial line, internal jugular central line, and Swan-Ganz catheter were placed while the patient was awake to aid in monitoring. Additionally, transthoracic echocardiography (TTE) was used to assist in cardiac monitoring while the epidural level was gradually increased. She was maintained on vasopressin, epinephrine, and phenylephrine infusions in addition to inhaled nitric oxide. She tolerated the procedure well, and the fetus was delivered safely. Careful management across pre-epidural, post-epidural, intraoperative, and postoperative stages illustrates the dynamic adjustments and multidisciplinary communication required in this patient population. Advanced medical therapy optimization, careful neuraxial anesthesia titration, and early consideration of extracorporeal cardiopulmonary resuscitation (ECPR) together capture the critical elements of management in this complex setting.
Parturients with pulmonary arterial hypertension (PAH) face an increased risk of morbidity and mortality surrounding the peripartum period. Patients with severe PAH and Eisenmenger syndrome have the highest risk for perioperative mortality and provide a significant perioperative challenge for anesthesiologists, necessitating a multidisciplinary approach throughout pregnancy. We present a case of an urgent cesarean section at 37 weeks of gestation in a patient with Eisenmenger syndrome, a large atrial septal defect, and supra-systemic pulmonary hypertension. Due to the patient’s severity of PAH, cardiothoracic surgery was present and placed femoral arterial and venous catheters in preparation for possible extracorporeal membrane oxygenation (ECMO) cannulation in the event of hemodynamic collapse. The procedure was performed under a carefully titrated epidural, thus avoiding general anesthesia and the dangers associated with inducing a patient with her comorbid conditions. An arterial line, internal jugular central line, and Swan-Ganz catheter were placed while the patient was awake to aid in monitoring. Additionally, transthoracic echocardiography (TTE) was used to assist in cardiac monitoring while the epidural level was gradually increased. She was maintained on vasopressin, epinephrine, and phenylephrine infusions in addition to inhaled nitric oxide. She tolerated the procedure well, and the fetus was delivered safely. Careful management across pre-epidural, post-epidural, intraoperative, and postoperative stages illustrates the dynamic adjustments and multidisciplinary communication required in this patient population. Advanced medical therapy optimization, careful neuraxial anesthesia titration, and early consideration of extracorporeal cardiopulmonary resuscitation (ECPR) together capture the critical elements of management in this complex setting.
DOI: https://doi.org/10.37349/ec.2026.1012119
This article belongs to the special issue Cardiovascular Risk for Mothers and Offspring Resulting from Complicated Pregnancy
Aim:
This study aimed to analyze the entrapment processes of polyphenols using sodium alginate and gelatin for the development of potential food supplements and to evaluate biological properties.
Methods:
Entrapment beads containing pomegranate peel polyphenols were prepared by ionic gelation with sodium alginate and calcium chloride to achieve the optimal concentrations, while the gelatin gums were made artisanally according to the manufacturer’s recipe. To characterize the supplements, total polyphenol content, entrapment efficiency, antioxidant capacity, and prebiotic, antimicrobial, and hemolytic activities were assessed.
Results:
After the entrapment processes, the polyphenol content was 22.03 ± 0.39 mg/L for alginate beads and 67.00 ± 0.76 mg/L for gums, with entrapment efficiencies of 2.20% and 6.70%, respectively. Regarding biological activities, the antioxidant activity was 77.92% acid 2,2-azino-bis(3-etilbenzotiazolina-6-sulfónico) (ABTS) and 50.06% 1,1-diphenyl-2-picrylhydrazyl (DPPH) for alginate beads, and 39.66% for ABTS and 22.60% DPPH for gums. For prebiotic activity, gums with polyphenols favored the growth of Levilactobacillus brevis (4.10 × 109 cells/mL) and Lacticaseibacillus paracasei (2.49 × 109 cells/mL) strains.
Conclusions:
These findings suggest that it is possible to develop food supplements with biological properties using naturally occurring bioactive compounds from non-conventional sources through entrapment processes, although process optimization is necessary.
Aim:
This study aimed to analyze the entrapment processes of polyphenols using sodium alginate and gelatin for the development of potential food supplements and to evaluate biological properties.
Methods:
Entrapment beads containing pomegranate peel polyphenols were prepared by ionic gelation with sodium alginate and calcium chloride to achieve the optimal concentrations, while the gelatin gums were made artisanally according to the manufacturer’s recipe. To characterize the supplements, total polyphenol content, entrapment efficiency, antioxidant capacity, and prebiotic, antimicrobial, and hemolytic activities were assessed.
Results:
After the entrapment processes, the polyphenol content was 22.03 ± 0.39 mg/L for alginate beads and 67.00 ± 0.76 mg/L for gums, with entrapment efficiencies of 2.20% and 6.70%, respectively. Regarding biological activities, the antioxidant activity was 77.92% acid 2,2-azino-bis(3-etilbenzotiazolina-6-sulfónico) (ABTS) and 50.06% 1,1-diphenyl-2-picrylhydrazyl (DPPH) for alginate beads, and 39.66% for ABTS and 22.60% DPPH for gums. For prebiotic activity, gums with polyphenols favored the growth of Levilactobacillus brevis (4.10 × 109 cells/mL) and Lacticaseibacillus paracasei (2.49 × 109 cells/mL) strains.
Conclusions:
These findings suggest that it is possible to develop food supplements with biological properties using naturally occurring bioactive compounds from non-conventional sources through entrapment processes, although process optimization is necessary.
DOI: https://doi.org/10.37349/eff.2026.1010186
Background:
Chronic kidney disease (CKD) is linked to high cardiovascular morbidity and mortality. Many patients remain at risk despite standard treatment. This review assessed the renal, cardiovascular, safety, and primary care implementation outcomes of sodium-glucose cotransporter-2 (SGLT2) inhibitors in CKD, including patients with and without diabetes.
Methods:
This systematic review followed PRISMA 2020 guidelines. PubMed, Scopus, and Google Scholar were searched for English-language human studies published between 2016 and 2026. Reference lists of eligible articles were also manually screened. Eligible studies included randomized controlled trials and primary observational studies evaluating SGLT2 inhibitors in patients with CKD, with or without diabetes. Studies reporting renal, cardiovascular, safety, or primary care implementation outcomes were included. Data were extracted using a standardized form and synthesized qualitatively because of clinical and methodological heterogeneity.
Results:
Fifteen primary studies were included, comprising randomized controlled trials and observational studies. Across landmark clinical trials and real-world studies, SGLT2 inhibitors slowed eGFR decline, reduced albuminuria, and lowered the risk of kidney and heart failure hospitalization. Renal and cardiovascular benefits were observed in patients with and without diabetes. SGLT2 inhibitors were generally well tolerated, with genital mycotic infections and volume depletion being the most reported adverse events, while serious adverse events were uncommon. Real-world studies consistently identified underprescription and implementation barriers in primary care.
Discussion:
SGLT2 inhibitors are foundational therapies for CKD, providing consistent renal and cardiovascular benefits with an acceptable safety profile in patients with and without diabetes. However, substantial gaps remain in their implementation in primary care. Improving early identification of eligible patients, clinician awareness, and integration of guideline-directed prescribing into routine practice may help reduce CKD progression and cardiovascular events.
Background:
Chronic kidney disease (CKD) is linked to high cardiovascular morbidity and mortality. Many patients remain at risk despite standard treatment. This review assessed the renal, cardiovascular, safety, and primary care implementation outcomes of sodium-glucose cotransporter-2 (SGLT2) inhibitors in CKD, including patients with and without diabetes.
Methods:
This systematic review followed PRISMA 2020 guidelines. PubMed, Scopus, and Google Scholar were searched for English-language human studies published between 2016 and 2026. Reference lists of eligible articles were also manually screened. Eligible studies included randomized controlled trials and primary observational studies evaluating SGLT2 inhibitors in patients with CKD, with or without diabetes. Studies reporting renal, cardiovascular, safety, or primary care implementation outcomes were included. Data were extracted using a standardized form and synthesized qualitatively because of clinical and methodological heterogeneity.
Results:
Fifteen primary studies were included, comprising randomized controlled trials and observational studies. Across landmark clinical trials and real-world studies, SGLT2 inhibitors slowed eGFR decline, reduced albuminuria, and lowered the risk of kidney and heart failure hospitalization. Renal and cardiovascular benefits were observed in patients with and without diabetes. SGLT2 inhibitors were generally well tolerated, with genital mycotic infections and volume depletion being the most reported adverse events, while serious adverse events were uncommon. Real-world studies consistently identified underprescription and implementation barriers in primary care.
Discussion:
SGLT2 inhibitors are foundational therapies for CKD, providing consistent renal and cardiovascular benefits with an acceptable safety profile in patients with and without diabetes. However, substantial gaps remain in their implementation in primary care. Improving early identification of eligible patients, clinician awareness, and integration of guideline-directed prescribing into routine practice may help reduce CKD progression and cardiovascular events.
DOI: https://doi.org/10.37349/ec.2026.1012120
Aim:
Animal streptococci surviving thermization of raw milk prior to traditional Greek cheese processing may include both harmless and potentially harmful strains with multiple antibiotic resistances. Therefore, the aims of this study were to biotype and evaluate the antibiotic resistance and primary technological and safety properties of wild streptococci occurring in Greek sheep milk before and after mild thermization.
Methods:
Sixteen Streptococcus isolates previously isolated from two raw/thermized (65oC; 30 s) counterpart milks of native Epirus sheep breeds and identified by 16S ribosomal RNA (rRNA) gene sequencing were biochemically characterized using conventional methods (phenotypic tests, sugar fermentation patterns, API 20 STREP and API ZYM profiles) and assessed for susceptibility to eight antibiotics by the disk diffusion method, and for their milk acidification capacity, bacteriocin activity, enzymatic activity profiles, and biogenic amine (BA) formation in vitro.
Results:
Tetracycline-resistant (57% of the total 7 isolates) Streptococcus parauberis and ciprofloxacin-resistant Streptococcus gallolyticus subsp. pasteurianus (1 isolate) and Streptococcus lutetiensis (2 isolates) strains occurring in raw milk were not recovered post-thermally. Instead, thermization selected for a tetracycline-resistant (50% of the total 6 isolates) thermophilic group previously genotyped as Streptococcus equinus, herein biotyped as Streptococcus pneumoniae. None of the Streptococcus isolates was resistant to ampicillin, chloramphenicol, erythromycin, gentamycin, penicillin, or vancomycin, or β-hemolytic, or produced histamine and tyramine. The milk acidifying activity rate (final skimmed milk pH 4.79 to 5.47 after growth at 37oC for 6 h, gradually decreasing to 22oC for a total of 48 h) of the isolates was species-dependent and increased in the order S. equinus > S. gallolyticus > S. lutetiensis > S. parauberis.
Conclusions:
Except for the two bacteriocin-producing and α-galactosidase-positive S. lutetiensis antilisterial strains (KFM 55 and KFM 60), which show promise, all animal streptococci derived from Epirus sheep milk should be considered a priori unsafe for inclusion in complex natural cheese starter cultures because they belong to pathogenic, mastitis-causing species or subspecies. The two promising S. lutetiensis strains require further safety evaluations for streptococcal virulence and antibiotic resistance genes, mainly to ciprofloxacin, before their commercial use as natural cheese starters.
Aim:
Animal streptococci surviving thermization of raw milk prior to traditional Greek cheese processing may include both harmless and potentially harmful strains with multiple antibiotic resistances. Therefore, the aims of this study were to biotype and evaluate the antibiotic resistance and primary technological and safety properties of wild streptococci occurring in Greek sheep milk before and after mild thermization.
Methods:
Sixteen Streptococcus isolates previously isolated from two raw/thermized (65oC; 30 s) counterpart milks of native Epirus sheep breeds and identified by 16S ribosomal RNA (rRNA) gene sequencing were biochemically characterized using conventional methods (phenotypic tests, sugar fermentation patterns, API 20 STREP and API ZYM profiles) and assessed for susceptibility to eight antibiotics by the disk diffusion method, and for their milk acidification capacity, bacteriocin activity, enzymatic activity profiles, and biogenic amine (BA) formation in vitro.
Results:
Tetracycline-resistant (57% of the total 7 isolates) Streptococcus parauberis and ciprofloxacin-resistant Streptococcus gallolyticus subsp. pasteurianus (1 isolate) and Streptococcus lutetiensis (2 isolates) strains occurring in raw milk were not recovered post-thermally. Instead, thermization selected for a tetracycline-resistant (50% of the total 6 isolates) thermophilic group previously genotyped as Streptococcus equinus, herein biotyped as Streptococcus pneumoniae. None of the Streptococcus isolates was resistant to ampicillin, chloramphenicol, erythromycin, gentamycin, penicillin, or vancomycin, or β-hemolytic, or produced histamine and tyramine. The milk acidifying activity rate (final skimmed milk pH 4.79 to 5.47 after growth at 37oC for 6 h, gradually decreasing to 22oC for a total of 48 h) of the isolates was species-dependent and increased in the order S. equinus > S. gallolyticus > S. lutetiensis > S. parauberis.
Conclusions:
Except for the two bacteriocin-producing and α-galactosidase-positive S. lutetiensis antilisterial strains (KFM 55 and KFM 60), which show promise, all animal streptococci derived from Epirus sheep milk should be considered a priori unsafe for inclusion in complex natural cheese starter cultures because they belong to pathogenic, mastitis-causing species or subspecies. The two promising S. lutetiensis strains require further safety evaluations for streptococcal virulence and antibiotic resistance genes, mainly to ciprofloxacin, before their commercial use as natural cheese starters.
DOI: https://doi.org/10.37349/eff.2026.1010187
The neurodegenerative condition known as Alzheimer’s disease (AD) is defined chiefly by intraneuronal tangles, large-scale neuronal death, and dementia. Although much progress has been made in Alzheimer’s research, early diagnosis of the disease and effective treatment are difficult; conventional diagnostic tests fail to detect the pathology until there is significant neurodegeneration, and many treatments do not penetrate the blood-brain barrier and have poor target specificity. Nanotechnology has the ability to completely transform neurodegenerative disease diagnosis and treatment. Sensitive molecule detection, efficient drug targeting, and integration are possible through nanotechnology-based diagnostic tools, drug delivery mechanisms, and medicines. A great deal has been achieved in the last decade with respect to this, and favorable outcomes in the therapy of AD have been witnessed. The objective of this review is to critically assess the novel potential of nanobiomaterials for early detection and treatment of AD, highlighting their contributions to sensitive biomarker detection, targeted drug delivery, multimodal imaging, and the challenges of clinical translation.
The neurodegenerative condition known as Alzheimer’s disease (AD) is defined chiefly by intraneuronal tangles, large-scale neuronal death, and dementia. Although much progress has been made in Alzheimer’s research, early diagnosis of the disease and effective treatment are difficult; conventional diagnostic tests fail to detect the pathology until there is significant neurodegeneration, and many treatments do not penetrate the blood-brain barrier and have poor target specificity. Nanotechnology has the ability to completely transform neurodegenerative disease diagnosis and treatment. Sensitive molecule detection, efficient drug targeting, and integration are possible through nanotechnology-based diagnostic tools, drug delivery mechanisms, and medicines. A great deal has been achieved in the last decade with respect to this, and favorable outcomes in the therapy of AD have been witnessed. The objective of this review is to critically assess the novel potential of nanobiomaterials for early detection and treatment of AD, highlighting their contributions to sensitive biomarker detection, targeted drug delivery, multimodal imaging, and the challenges of clinical translation.
DOI: https://doi.org/10.37349/en.2026.1006147
This article belongs to the special issue Progress in Alzheimer's disease research: etiology, molecular mechanisms involved in disease progression, and advances in therapies aimed at slowing or reversing neurodegeneration
Aim:
Neuropathic pain (NP) is common in cancer patients, but its relationship with haematological inflammatory markers remains poorly understood. This study explored the association between NP and haematological parameters in Nigerian cancer patients.
Methods:
This cross-sectional study enrolled 90 patients with solid tumours from the University of Ilorin Teaching Hospital. Pain severity was assessed using the Numerical Rating Scale, while NP was evaluated with the painDETECT questionnaire. Complete blood count parameters were analysed, and derived inflammatory indices were calculated. Statistical analyses employed chi-square tests, Spearman’s correlation, and binary logistic regression.
Results:
NP was present in 21.1% of patients. Significant associations with NP were observed for haemoglobin (p = 0.006), absolute lymphocyte count (p = 0.003), platelet-to-lymphocyte ratio (PLR, p = 0.015), haemoglobin-to-platelet ratio (HPR, p = 0.001), and systemic immune-inflammation index (SII, p < 0.001). Correlation analysis showed NP positively correlated with platelet count (ρ = 0.23, p = 0.029), absolute neutrophil count (ρ = 0.263, p = 0.012), neutrophil-to-lymphocyte ratio (NLR, ρ = 0.248, p = 0.019), SII (ρ = 0.215, p = 0.045), and neutrophil-platelet score (NPS, ρ = 0.248, p = 0.018), while correlating negatively with haemoglobin (ρ = –0.223, p = 0.034). Logistic regression identified haemoglobin, platelet count, absolute lymphocyte count, absolute neutrophil count, NLR, and HPR as independent predictors of NP.
Conclusions:
Haematological parameters reflecting systemic inflammation are significantly associated with NP in cancer patients. These readily available indices may serve as useful adjuncts for identifying at-risk patients, particularly in resource-limited settings. Prospective studies are warranted to validate these findings.
Aim:
Neuropathic pain (NP) is common in cancer patients, but its relationship with haematological inflammatory markers remains poorly understood. This study explored the association between NP and haematological parameters in Nigerian cancer patients.
Methods:
This cross-sectional study enrolled 90 patients with solid tumours from the University of Ilorin Teaching Hospital. Pain severity was assessed using the Numerical Rating Scale, while NP was evaluated with the painDETECT questionnaire. Complete blood count parameters were analysed, and derived inflammatory indices were calculated. Statistical analyses employed chi-square tests, Spearman’s correlation, and binary logistic regression.
Results:
NP was present in 21.1% of patients. Significant associations with NP were observed for haemoglobin (p = 0.006), absolute lymphocyte count (p = 0.003), platelet-to-lymphocyte ratio (PLR, p = 0.015), haemoglobin-to-platelet ratio (HPR, p = 0.001), and systemic immune-inflammation index (SII, p < 0.001). Correlation analysis showed NP positively correlated with platelet count (ρ = 0.23, p = 0.029), absolute neutrophil count (ρ = 0.263, p = 0.012), neutrophil-to-lymphocyte ratio (NLR, ρ = 0.248, p = 0.019), SII (ρ = 0.215, p = 0.045), and neutrophil-platelet score (NPS, ρ = 0.248, p = 0.018), while correlating negatively with haemoglobin (ρ = –0.223, p = 0.034). Logistic regression identified haemoglobin, platelet count, absolute lymphocyte count, absolute neutrophil count, NLR, and HPR as independent predictors of NP.
Conclusions:
Haematological parameters reflecting systemic inflammation are significantly associated with NP in cancer patients. These readily available indices may serve as useful adjuncts for identifying at-risk patients, particularly in resource-limited settings. Prospective studies are warranted to validate these findings.
DOI: https://doi.org/10.37349/en.2026.1006146
Hypophosphatasia (HPP) is a rare inherited metabolic disorder caused by deficient activity of tissue non-specific alkaline phosphatase (TNSALP). The resulting accumulation of its substrates, particularly inorganic pyrophosphate (PPi) and pyridoxal-5-phosphate (PLP), impairs skeletal and dental mineralization and disrupts vitamin B6 metabolism, contributing to multisystem manifestations. The clinical spectrum is highly heterogeneous, ranging from severe, life-threatening forms in the perinatal period to milder musculoskeletal and dental phenotypes presenting in adulthood. The rarity of HPP, together with the nonspecific nature of many symptoms, contributes to frequent diagnostic delay. However, recognition of characteristic biochemical abnormalities and clinical features can facilitate earlier identification and appropriate management. This review summarizes current evidence regarding the pathophysiology, clinical manifestations, diagnosis, and management of HPP, with particular emphasis on diagnostic challenges, biomarker interpretation, and recent advances in patient care.
Hypophosphatasia (HPP) is a rare inherited metabolic disorder caused by deficient activity of tissue non-specific alkaline phosphatase (TNSALP). The resulting accumulation of its substrates, particularly inorganic pyrophosphate (PPi) and pyridoxal-5-phosphate (PLP), impairs skeletal and dental mineralization and disrupts vitamin B6 metabolism, contributing to multisystem manifestations. The clinical spectrum is highly heterogeneous, ranging from severe, life-threatening forms in the perinatal period to milder musculoskeletal and dental phenotypes presenting in adulthood. The rarity of HPP, together with the nonspecific nature of many symptoms, contributes to frequent diagnostic delay. However, recognition of characteristic biochemical abnormalities and clinical features can facilitate earlier identification and appropriate management. This review summarizes current evidence regarding the pathophysiology, clinical manifestations, diagnosis, and management of HPP, with particular emphasis on diagnostic challenges, biomarker interpretation, and recent advances in patient care.
DOI: https://doi.org/10.37349/emd.2026.1007135
Plant metabolites are an invaluable source of bioactive molecules, and a high percentage of them can react covalently with their targets. Lipid-derived α,β-unsaturated systems (Michael acceptors), which are present in all plants, regulate signaling pathways in cells. In addition, they potentially represent novel molecular targets and mechanisms of action in drug development. The irreversible covalent binding of the majority of these electrophilic molecules to their corresponding molecular targets, combined with, in certain cases, unfavorable pharmacokinetic properties, i.e., absorption, distribution, metabolism, and excretion (ADME), has shifted their use predominantly to that of molecular probes for target identification. In this review, we present examples of structural modification of the original naturally occurring Michael acceptor-containing compounds, as well as examples of incorporating naturally occurring functionalities in the design of reversible covalent probes and drug candidates in order to improve ADME and increase target selectivity.
Plant metabolites are an invaluable source of bioactive molecules, and a high percentage of them can react covalently with their targets. Lipid-derived α,β-unsaturated systems (Michael acceptors), which are present in all plants, regulate signaling pathways in cells. In addition, they potentially represent novel molecular targets and mechanisms of action in drug development. The irreversible covalent binding of the majority of these electrophilic molecules to their corresponding molecular targets, combined with, in certain cases, unfavorable pharmacokinetic properties, i.e., absorption, distribution, metabolism, and excretion (ADME), has shifted their use predominantly to that of molecular probes for target identification. In this review, we present examples of structural modification of the original naturally occurring Michael acceptor-containing compounds, as well as examples of incorporating naturally occurring functionalities in the design of reversible covalent probes and drug candidates in order to improve ADME and increase target selectivity.
DOI: https://doi.org/10.37349/eds.2026.1008178
This article belongs to the special issue The Rise of Targeted Covalent Inhibitors in Drug Discovery
Biologic therapies have transformed care for people with severe asthma, yet treatment response has traditionally been assessed using clinician-derived measures, including lung function, exacerbation rates, and oral corticosteroid use. These metrics, while clinically important, frequently fail to capture what matters most to patients: their ability to participate in daily life, maintain relationships, and sustain work and social roles. The publication of the Core Outcome Measures Set for Severe Asthma (COMSA) and the subsequent CompOsite iNdexes For Response in asthMa (CONFiRM) composite score mark a shift towards patient-centred measurement of treatment response in severe asthma. Rheumatoid arthritis (RA) and inflammatory bowel disease (IBD) travelled this path decades earlier. Both conditions adopted composite scoring tools, such as the Disease Activity Score-28 (DAS28) and the Mayo Score, that incorporated Patient-Reported Outcome Measures (PROMs) alongside objective markers. Initiatives like Outcome Measures in Rheumatology (OMERACT) in RA and Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE) in IBD demonstrate that sustained, multidisciplinary collaboration between patients, clinicians, regulators, and industry can successfully embed PROMs into clinical trials and routine care. We argue that timely integration of health-related quality of life measures into clinical trials and practice requires electronic data collection, regulatory endorsement of PROMs as co-primary endpoints, and genuine patient partnership in research, beyond tokenism. By learning from parallel specialties, the asthma community can build a model of care that reflects what truly matters to those living with the disease.
Biologic therapies have transformed care for people with severe asthma, yet treatment response has traditionally been assessed using clinician-derived measures, including lung function, exacerbation rates, and oral corticosteroid use. These metrics, while clinically important, frequently fail to capture what matters most to patients: their ability to participate in daily life, maintain relationships, and sustain work and social roles. The publication of the Core Outcome Measures Set for Severe Asthma (COMSA) and the subsequent CompOsite iNdexes For Response in asthMa (CONFiRM) composite score mark a shift towards patient-centred measurement of treatment response in severe asthma. Rheumatoid arthritis (RA) and inflammatory bowel disease (IBD) travelled this path decades earlier. Both conditions adopted composite scoring tools, such as the Disease Activity Score-28 (DAS28) and the Mayo Score, that incorporated Patient-Reported Outcome Measures (PROMs) alongside objective markers. Initiatives like Outcome Measures in Rheumatology (OMERACT) in RA and Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE) in IBD demonstrate that sustained, multidisciplinary collaboration between patients, clinicians, regulators, and industry can successfully embed PROMs into clinical trials and routine care. We argue that timely integration of health-related quality of life measures into clinical trials and practice requires electronic data collection, regulatory endorsement of PROMs as co-primary endpoints, and genuine patient partnership in research, beyond tokenism. By learning from parallel specialties, the asthma community can build a model of care that reflects what truly matters to those living with the disease.
DOI: https://doi.org/10.37349/eaa.2026.1009132
This article belongs to the special issue Allergic Asthma - New Insights
