Previous
The s-triazine scaffold has emerged as a privileged heterocyclic nucleus/moiety in pharmaceutical discovery and development, owing to its presence in several natural products and clinically relevant therapeutic agents, including enasidenib, gedatolisib, bimiralisib, atrazine, indaziflam, and triaziflam. s-Triazine derivatives are not only economically accessible and synthetically versatile, but they also exhibit a broad spectrum of noteworthy biological activities, encompassing anticancer, anti-inflammatory, antiviral, antidiabetic, anticonvulsant, antitubercular, and antimicrobial properties. Their widespread utility is further supported by the ease of synthesis from inexpensive precursors such as amidines or the readily available 2,4,6-trichloro-1,3,5-triazine (cyanuric chloride), which enables sequential functionalization and the rapid generation of diverse analogues. The heightened reactivity and modularity of the s-triazine core have facilitated the development of structurally rich heterocyclic hybrids with enhanced potency and improved pharmacological profiles. These multitarget-directed systems offer exciting opportunities for addressing various forms of cancer. Considering the increasing pace of innovation in this field, a comprehensive overview of recent advancements in s-triazine-based hybrid molecules is both timely and necessary. This review highlights current progress, key design strategies, and emerging perspectives to inspire continued efforts toward the identification of promising s-triazine-based lead candidates for future drug development as anticancer agents.
The s-triazine scaffold has emerged as a privileged heterocyclic nucleus/moiety in pharmaceutical discovery and development, owing to its presence in several natural products and clinically relevant therapeutic agents, including enasidenib, gedatolisib, bimiralisib, atrazine, indaziflam, and triaziflam. s-Triazine derivatives are not only economically accessible and synthetically versatile, but they also exhibit a broad spectrum of noteworthy biological activities, encompassing anticancer, anti-inflammatory, antiviral, antidiabetic, anticonvulsant, antitubercular, and antimicrobial properties. Their widespread utility is further supported by the ease of synthesis from inexpensive precursors such as amidines or the readily available 2,4,6-trichloro-1,3,5-triazine (cyanuric chloride), which enables sequential functionalization and the rapid generation of diverse analogues. The heightened reactivity and modularity of the s-triazine core have facilitated the development of structurally rich heterocyclic hybrids with enhanced potency and improved pharmacological profiles. These multitarget-directed systems offer exciting opportunities for addressing various forms of cancer. Considering the increasing pace of innovation in this field, a comprehensive overview of recent advancements in s-triazine-based hybrid molecules is both timely and necessary. This review highlights current progress, key design strategies, and emerging perspectives to inspire continued efforts toward the identification of promising s-triazine-based lead candidates for future drug development as anticancer agents.
DOI: https://doi.org/10.37349/eds.2026.1008149
This article belongs to the special issue The Role of Triazine Scaffolds in Modern Drug Development
Multicenter imaging studies are increasingly critical in epidemiology, yet variability across scanners, acquisition protocols, and reconstruction algorithms introduces systematic biases that threaten reproducibility and comparability of quantitative biomarkers. This paper reviews the major sources of heterogeneity in MRI, CT, and PET-CT data, highlighting their impact on epidemiologic inference, including misclassification, reduced statistical power, and compromised generalizability. We outline harmonization strategies spanning pre-acquisition standardization, phantom-based calibration, post-acquisition intensity normalization, and advanced statistical and machine learning methods such as ComBat and domain adaptation. Illustrative examples from MRI flow quantification and radiomic feature extraction demonstrate how harmonization can mitigate site effects and enable robust large-scale analyses.
Multicenter imaging studies are increasingly critical in epidemiology, yet variability across scanners, acquisition protocols, and reconstruction algorithms introduces systematic biases that threaten reproducibility and comparability of quantitative biomarkers. This paper reviews the major sources of heterogeneity in MRI, CT, and PET-CT data, highlighting their impact on epidemiologic inference, including misclassification, reduced statistical power, and compromised generalizability. We outline harmonization strategies spanning pre-acquisition standardization, phantom-based calibration, post-acquisition intensity normalization, and advanced statistical and machine learning methods such as ComBat and domain adaptation. Illustrative examples from MRI flow quantification and radiomic feature extraction demonstrate how harmonization can mitigate site effects and enable robust large-scale analyses.
DOI: https://doi.org/10.37349/edht.2026.101185
Aim:
This study aimed to assess the effectiveness of mepolizumab in enhancing asthma control, achieving clinical remission, and alleviating upper airway symptoms in patients with severe eosinophilic asthma (SEA) with comorbid nasal polyps and/or chronic rhinosinusitis (CRS). Additionally, it aimed to identify clinical and laboratory predictors of remission. The findings are based on real-world data from a single center.
Methods:
This retrospective, single-center, real-world study included 99 patients diagnosed with SEA. Patients were categorized into three groups based on the presence or absence of nasal polyps and CRS. Treatment response was evaluated using the asthma control test (ACT), spirometry, laboratory biomarkers, computed tomography (CT) scores, and nasal polyp scores. Remission was defined as the absence of asthma exacerbations and systemic corticosteroid use, along with improvements in both forced expiratory volume in 1 second (FEV1) and ACT scores.
Results:
After 12 months of mepolizumab therapy, there were significant improvements in FEV1 values, asthma exacerbation frequency, systemic corticosteroid requirements, and nasal symptom scores. The overall remission rate was 30.6%. Patients with higher baseline FEV1 and no prior exposure to omalizumab were more likely to achieve remission.
Conclusions:
This real-world evidence suggests that mepolizumab provides meaningful clinical, functional, and radiological improvements in patients with SEA, regardless of comorbid nasal polyps or CRS. Furthermore, the study highlights independent predictors associated with treatment-induced remission in this population.
Aim:
This study aimed to assess the effectiveness of mepolizumab in enhancing asthma control, achieving clinical remission, and alleviating upper airway symptoms in patients with severe eosinophilic asthma (SEA) with comorbid nasal polyps and/or chronic rhinosinusitis (CRS). Additionally, it aimed to identify clinical and laboratory predictors of remission. The findings are based on real-world data from a single center.
Methods:
This retrospective, single-center, real-world study included 99 patients diagnosed with SEA. Patients were categorized into three groups based on the presence or absence of nasal polyps and CRS. Treatment response was evaluated using the asthma control test (ACT), spirometry, laboratory biomarkers, computed tomography (CT) scores, and nasal polyp scores. Remission was defined as the absence of asthma exacerbations and systemic corticosteroid use, along with improvements in both forced expiratory volume in 1 second (FEV1) and ACT scores.
Results:
After 12 months of mepolizumab therapy, there were significant improvements in FEV1 values, asthma exacerbation frequency, systemic corticosteroid requirements, and nasal symptom scores. The overall remission rate was 30.6%. Patients with higher baseline FEV1 and no prior exposure to omalizumab were more likely to achieve remission.
Conclusions:
This real-world evidence suggests that mepolizumab provides meaningful clinical, functional, and radiological improvements in patients with SEA, regardless of comorbid nasal polyps or CRS. Furthermore, the study highlights independent predictors associated with treatment-induced remission in this population.
DOI: https://doi.org/10.37349/eaa.2026.1009109
This article belongs to the special issue Update on Chronic Rhinosinusitis
Background:
Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the central nervous system, the cause of which remains unknown. Environmental, genetic, and immunological factors are considered risk factors. MS has no cure; therefore, therapy focuses on reducing the number of outbreaks, controlling symptoms, and therapies aimed at modifying the course of the disease. Innovative strategies that promote remyelination and repair of damaged brain tissue are under investigation. This review aims to compile and systematize the available knowledge on the multifactorial nature of MS, highlighting the main risk factors. It also discusses the mechanisms underlying the pathogenesis of the disease, current therapies, and prospects, presenting a comprehensive overview of the effect of various drugs on remyelination and repair of central nervous system damage.
Methods:
A comprehensive literature search, guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards, was conducted across PubMed, Cochrane Library, Web of Science, and ClinicalTrials.gov to identify relevant clinical trials. Of the studies retrieved, 13 were selected for this review. These trials specifically explored integrated therapeutic approaches, combining pharmacological and non-pharmacological interventions, for managing MS.
Results:
The results reflect the multifactorial nature of MS and the existence of several promising therapies to combat inflammation and demyelination, as well as to promote remyelination. Reducing inflammation remains the main target, but new approaches such as clemastine, liothyronine, interleukin (IL)-2, N-acetylglucosamine, and intracranial transplantation of fetal human neural precursor cells have shown promising results.
Discussion:
Currently, the therapies available for MS target the peripheral immune system. Therefore, more studies are needed on treatment therapies that combine immunomodulation of the peripheral and central nervous systems to reduce the neurological disability of patients. It is also concluded that the therapies were safe and were well tolerated, given the occurrence of a small number of adverse events.
Background:
Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease affecting the central nervous system, the cause of which remains unknown. Environmental, genetic, and immunological factors are considered risk factors. MS has no cure; therefore, therapy focuses on reducing the number of outbreaks, controlling symptoms, and therapies aimed at modifying the course of the disease. Innovative strategies that promote remyelination and repair of damaged brain tissue are under investigation. This review aims to compile and systematize the available knowledge on the multifactorial nature of MS, highlighting the main risk factors. It also discusses the mechanisms underlying the pathogenesis of the disease, current therapies, and prospects, presenting a comprehensive overview of the effect of various drugs on remyelination and repair of central nervous system damage.
Methods:
A comprehensive literature search, guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards, was conducted across PubMed, Cochrane Library, Web of Science, and ClinicalTrials.gov to identify relevant clinical trials. Of the studies retrieved, 13 were selected for this review. These trials specifically explored integrated therapeutic approaches, combining pharmacological and non-pharmacological interventions, for managing MS.
Results:
The results reflect the multifactorial nature of MS and the existence of several promising therapies to combat inflammation and demyelination, as well as to promote remyelination. Reducing inflammation remains the main target, but new approaches such as clemastine, liothyronine, interleukin (IL)-2, N-acetylglucosamine, and intracranial transplantation of fetal human neural precursor cells have shown promising results.
Discussion:
Currently, the therapies available for MS target the peripheral immune system. Therefore, more studies are needed on treatment therapies that combine immunomodulation of the peripheral and central nervous systems to reduce the neurological disability of patients. It is also concluded that the therapies were safe and were well tolerated, given the occurrence of a small number of adverse events.
DOI: https://doi.org/10.37349/ent.2026.1004138
Aim:
Mango kernel has potential as an alternative flour source to enhance the nutritional value of flatbreads, providing a cost-effective means of promoting healthier foods. This study aimed to determine the effects of mango kernel flour (MKF) incorporation on the physicochemical and sensory properties of balady flatbread.
Methods:
Balady flatbreads were prepared with different substitution levels of MKF (0%, 25%, 50%, 75%, and 100%). The samples were analyzed for proximate composition, mineral content, color attributes, texture profile, specific volume, microstructure (via scanning electron microscopy), and sensory characteristics.
Results:
Chemical analysis revealed that MKF substitution significantly increased fat (3.74–13.35%), ash (1.51–2.13%), crude fiber (0.32–2.93%), and energy (266.65–328.78 kcal/g) contents, while protein content remained unaffected. In contrast, moisture (36.34–29.37%) and carbohydrate (54.75–47.98%) contents decreased significantly. Increasing MKF levels also elevated potassium, iron, and magnesium contents. The specific volume decreased (3.48–0.70 mL/g), and texture hardness increased markedly (184.67–9,373.42 g). Scanning electron microscopy showed a more compact structure (pore size reduced from 69.07 to 42.30 μm) with darker and less yellow coloration as MKF substitution increased. Sensory evaluation by 50 panelists indicated that the control sample (100% wheat flour) received significantly higher scores for all evaluated attributes.
Conclusions:
Increasing levels of MKF incorporation enhanced fat, fiber, ash, and mineral contents but reduced loaf volume, increased hardness, decreased pore size, and lowered sensory acceptability. Among the formulations tested, flatbread containing 25% MKF (FB2) was identified as the optimal formulation, offering improved nutritional properties with acceptable sensory quality. These findings highlight the potential application of MKF as a sustainable, value-added ingredient for developing nutrient-enriched flatbreads and other bakery products, contributing to food waste reduction and functional food innovation.
Aim:
Mango kernel has potential as an alternative flour source to enhance the nutritional value of flatbreads, providing a cost-effective means of promoting healthier foods. This study aimed to determine the effects of mango kernel flour (MKF) incorporation on the physicochemical and sensory properties of balady flatbread.
Methods:
Balady flatbreads were prepared with different substitution levels of MKF (0%, 25%, 50%, 75%, and 100%). The samples were analyzed for proximate composition, mineral content, color attributes, texture profile, specific volume, microstructure (via scanning electron microscopy), and sensory characteristics.
Results:
Chemical analysis revealed that MKF substitution significantly increased fat (3.74–13.35%), ash (1.51–2.13%), crude fiber (0.32–2.93%), and energy (266.65–328.78 kcal/g) contents, while protein content remained unaffected. In contrast, moisture (36.34–29.37%) and carbohydrate (54.75–47.98%) contents decreased significantly. Increasing MKF levels also elevated potassium, iron, and magnesium contents. The specific volume decreased (3.48–0.70 mL/g), and texture hardness increased markedly (184.67–9,373.42 g). Scanning electron microscopy showed a more compact structure (pore size reduced from 69.07 to 42.30 μm) with darker and less yellow coloration as MKF substitution increased. Sensory evaluation by 50 panelists indicated that the control sample (100% wheat flour) received significantly higher scores for all evaluated attributes.
Conclusions:
Increasing levels of MKF incorporation enhanced fat, fiber, ash, and mineral contents but reduced loaf volume, increased hardness, decreased pore size, and lowered sensory acceptability. Among the formulations tested, flatbread containing 25% MKF (FB2) was identified as the optimal formulation, offering improved nutritional properties with acceptable sensory quality. These findings highlight the potential application of MKF as a sustainable, value-added ingredient for developing nutrient-enriched flatbreads and other bakery products, contributing to food waste reduction and functional food innovation.
DOI: https://doi.org/10.37349/eff.2026.1010113
Aim:
Probiotic microorganisms, primarily lactic acid bacteria (LAB) and bifidobacteria, are able to solve most of the problems of animal by-products that hinder their use in the food industry. The most important property of LAB is their antagonistic activity against pathogenic and opportunistic microorganisms. The aim of the study is to compare the antimicrobial activity of microorganisms from commercial starters, medicinal preparations, and newly isolated strains. It is important to evaluate two alternative methods for determining antimicrobial activity in terms of their interchangeability.
Methods:
A total of 11 microorganisms and consortia from various sources were studied, including five newly isolated strains. Their antagonistic activity against 8 strains of pathogenic and opportunistic microorganisms was evaluated by two in vitro methods: agar diffusion and co-cultivation. Their interchangeability was assessed using the linear Pearson correlation coefficient.
Results:
The 12th hour of cultivation, corresponding to the maximum specific growth rate of the studied newly isolated strains and consortia were determined and used to take a supernatant sample for co-cultivation with test pathogens. Of the studied cultures, lactobacilli and pediococci showed the greatest antagonistic activity against the tested pathogens, while Staphylococcus spp. showed minimal activity.
Conclusions:
The highest inhibition index was observed in consortia containing Lactobacillus and Pediococcus. The antagonistic activity of the newly isolated strains is lower than that of meat starter cultures and medicinal products. The evaluation of the comparability of analytical methods for determining antimicrobial activity demonstrates a high positive correlation of the results, but requires further research to resolve the issue of their interchangeability.
Aim:
Probiotic microorganisms, primarily lactic acid bacteria (LAB) and bifidobacteria, are able to solve most of the problems of animal by-products that hinder their use in the food industry. The most important property of LAB is their antagonistic activity against pathogenic and opportunistic microorganisms. The aim of the study is to compare the antimicrobial activity of microorganisms from commercial starters, medicinal preparations, and newly isolated strains. It is important to evaluate two alternative methods for determining antimicrobial activity in terms of their interchangeability.
Methods:
A total of 11 microorganisms and consortia from various sources were studied, including five newly isolated strains. Their antagonistic activity against 8 strains of pathogenic and opportunistic microorganisms was evaluated by two in vitro methods: agar diffusion and co-cultivation. Their interchangeability was assessed using the linear Pearson correlation coefficient.
Results:
The 12th hour of cultivation, corresponding to the maximum specific growth rate of the studied newly isolated strains and consortia were determined and used to take a supernatant sample for co-cultivation with test pathogens. Of the studied cultures, lactobacilli and pediococci showed the greatest antagonistic activity against the tested pathogens, while Staphylococcus spp. showed minimal activity.
Conclusions:
The highest inhibition index was observed in consortia containing Lactobacillus and Pediococcus. The antagonistic activity of the newly isolated strains is lower than that of meat starter cultures and medicinal products. The evaluation of the comparability of analytical methods for determining antimicrobial activity demonstrates a high positive correlation of the results, but requires further research to resolve the issue of their interchangeability.
DOI: https://doi.org/10.37349/eff.2026.1010112
Digestive diseases comprise a diverse range of illnesses, which are prevalent worldwide and represent an important health issue. This is particularly relevant for the impact of metabolic dysfunction-associated steatotic liver disease (MASLD) due to its close association with the obesity pandemic, contributing to the escalation of MASLD as the most common form of chronic liver disease, and the main cause of liver cancer. Not only does MASLD reflect the deterioration of liver health, but it also has far-reaching consequences for the development of extrahepatic digestive diseases. Along with the progression of liver and digestive diseases to liver, colorectal and pancreatic cancer, the onset of inflammation in diseases of the digestive tract, drug-induced liver injury, and cholestasis, drives and contributes to the rise of these diseases in the future, which merit the attention of clinical and translational research to increase our understanding of the pathogenic mechanisms underlying these disorders in order to improve the diagnosis, management, and treatment. With this goal in mind, the current collaborative review gathers experts in a wide range of liver and digestive diseases to provide an up-to-date overview of the mechanisms of disease and identify novel strategies for the improvement of these important health issues.
Digestive diseases comprise a diverse range of illnesses, which are prevalent worldwide and represent an important health issue. This is particularly relevant for the impact of metabolic dysfunction-associated steatotic liver disease (MASLD) due to its close association with the obesity pandemic, contributing to the escalation of MASLD as the most common form of chronic liver disease, and the main cause of liver cancer. Not only does MASLD reflect the deterioration of liver health, but it also has far-reaching consequences for the development of extrahepatic digestive diseases. Along with the progression of liver and digestive diseases to liver, colorectal and pancreatic cancer, the onset of inflammation in diseases of the digestive tract, drug-induced liver injury, and cholestasis, drives and contributes to the rise of these diseases in the future, which merit the attention of clinical and translational research to increase our understanding of the pathogenic mechanisms underlying these disorders in order to improve the diagnosis, management, and treatment. With this goal in mind, the current collaborative review gathers experts in a wide range of liver and digestive diseases to provide an up-to-date overview of the mechanisms of disease and identify novel strategies for the improvement of these important health issues.
DOI: https://doi.org/10.37349/edd.2026.1005110
Aim:
Neonatal jaundice or neonatal hyperbilirubinemia is a common medical condition impacting newborns and pathological jaundice if left untreated, leads to neurological encephalopathy and/or death. The majority of pathological jaundice cases occur in low and middle- income countries (LMIC). Phototherapy has been determined to be the safest and most effective treatment for jaundice. Although inexpensive light-emitting diodes are available on the market, commercial phototherapy devices are expensive (~US$2,000), which creates a barrier to access for these devices in LMIC. Efforts to construct cost-effective phototherapy units have been implemented in the past, but need a method to validate the intensity and wavelength of light received by the infant at a distance away from the source.
Methods:
To enable low-cost phototherapy units to be used clinically, this study provides an open-source, low-cost, distributed manufacturing approach to create a light sensor to calibrate phototherapy units. This instrument is a necessary component of any open-source phototherapy treatment used in a clinical setting. This novel instrument was validated by comparing its irradiance and wavelength reading to the commercially calibrated Ocean Insight UV-VIS spectrometer under varying lighting conditions, including that of the existing Datex-Ohmeda Giraffe Spot PT Lite phototherapy equipment accessible through Victoria Children’s Hospital Neonatal Care Ward in London, Ontario, and Kiambu County Hospital in Kenya.
Results:
The results of this study have demonstrated that for under US$150, a phototherapy calibration device can be constructed capable of measuring up to 200 uW/cm2/nm with an accuracy of 98.6% and detect the peak wavelength within ±12.5 nm.
Conclusions:
It can be concluded that 3D printed open-source irradiance meters are a viable option for calibrating phototherapy units in LMIC to treat hyperbilirubinemia.
Aim:
Neonatal jaundice or neonatal hyperbilirubinemia is a common medical condition impacting newborns and pathological jaundice if left untreated, leads to neurological encephalopathy and/or death. The majority of pathological jaundice cases occur in low and middle- income countries (LMIC). Phototherapy has been determined to be the safest and most effective treatment for jaundice. Although inexpensive light-emitting diodes are available on the market, commercial phototherapy devices are expensive (~US$2,000), which creates a barrier to access for these devices in LMIC. Efforts to construct cost-effective phototherapy units have been implemented in the past, but need a method to validate the intensity and wavelength of light received by the infant at a distance away from the source.
Methods:
To enable low-cost phototherapy units to be used clinically, this study provides an open-source, low-cost, distributed manufacturing approach to create a light sensor to calibrate phototherapy units. This instrument is a necessary component of any open-source phototherapy treatment used in a clinical setting. This novel instrument was validated by comparing its irradiance and wavelength reading to the commercially calibrated Ocean Insight UV-VIS spectrometer under varying lighting conditions, including that of the existing Datex-Ohmeda Giraffe Spot PT Lite phototherapy equipment accessible through Victoria Children’s Hospital Neonatal Care Ward in London, Ontario, and Kiambu County Hospital in Kenya.
Results:
The results of this study have demonstrated that for under US$150, a phototherapy calibration device can be constructed capable of measuring up to 200 uW/cm2/nm with an accuracy of 98.6% and detect the peak wavelength within ±12.5 nm.
Conclusions:
It can be concluded that 3D printed open-source irradiance meters are a viable option for calibrating phototherapy units in LMIC to treat hyperbilirubinemia.
DOI: https://doi.org/10.37349/edht.2026.101184
DOI: https://doi.org/10.37349/en.2025.1006125
Ultra-high molecular weight polyethylene (UHMWPE) is widely used as a key material in biomedical implants such as artificial joints due to its exceptional wear resistance, high impact strength, and good biocompatibility. However, its inherent bio-inertness, hydrophobicity, risk of osteolysis induced by wear debris, and insufficient mechanical and processing properties severely limit its long-term clinical performance. This review systematically summarizes recent advances in the functional enhancement of UHMWPE via hybrid strategies, including surface modifications (e.g., coatings, chemical grafting, laser processing, plasma treatment) and bulk blending modifications (involving both organic and inorganic composites). These approaches have been shown to significantly improve wear resistance, bioactivity, hydrophilicity, and mechanical properties, while effectively suppressing oxidative degradation and inflammatory responses. The current challenges in modification technologies, such as balancing multiple properties, ensuring long-term biosafety, and achieving clinical translation, are also discussed. Finally, future directions toward multifunctional integration, intelligent responsiveness, and personalized customization of implants are outlined, providing critical insights for the development of next-generation high-performance and long-lasting biomedical materials.
Ultra-high molecular weight polyethylene (UHMWPE) is widely used as a key material in biomedical implants such as artificial joints due to its exceptional wear resistance, high impact strength, and good biocompatibility. However, its inherent bio-inertness, hydrophobicity, risk of osteolysis induced by wear debris, and insufficient mechanical and processing properties severely limit its long-term clinical performance. This review systematically summarizes recent advances in the functional enhancement of UHMWPE via hybrid strategies, including surface modifications (e.g., coatings, chemical grafting, laser processing, plasma treatment) and bulk blending modifications (involving both organic and inorganic composites). These approaches have been shown to significantly improve wear resistance, bioactivity, hydrophilicity, and mechanical properties, while effectively suppressing oxidative degradation and inflammatory responses. The current challenges in modification technologies, such as balancing multiple properties, ensuring long-term biosafety, and achieving clinical translation, are also discussed. Finally, future directions toward multifunctional integration, intelligent responsiveness, and personalized customization of implants are outlined, providing critical insights for the development of next-generation high-performance and long-lasting biomedical materials.
DOI: https://doi.org/10.37349/ebmx.2026.101358
Background:
Heart failure (HF) remains a growing global health problem, with nearly half of all cases attributed to HF with preserved ejection fraction (HFpEF) and its precursor, left ventricular diastolic dysfunction (LVDD). Although echocardiography is the diagnostic gold standard, its high cost and limited availability restrict its use for large-scale screening. In contrast, the electrocardiogram (ECG) is inexpensive and widely accessible. Recent advances in artificial intelligence (AI) have created opportunities to leverage ECG data for the early detection of cardiac dysfunction. The objective of this study was to systematically review and meta-analyze the diagnostic performance of AI-based ECG models for detecting cardiac dysfunction.
Methods:
The QUADAS-2 tool was used to assess the risk of bias. Pooled sensitivity and specificity were estimated using a bivariate random-effects model, with heterogeneity quantified using the I2 statistic. Pre-specified subgroup analyses were conducted according to clinical endpoint and AI model type.
Results:
Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, nine eligible studies evaluating AI algorithms applied to ECG data for the detection of HFpEF were identified. Considerable methodological and population heterogeneity was observed across studies. Risk of bias was generally low for reference standards, although concerns were noted in patient selection. The pooled specificity of AI-ECG models was high at 0.83 [95% confidence interval (CI): 0.74–0.89], while pooled sensitivity was 0.82 (95% CI: 0.70–0.90). Both estimates demonstrated extremely high heterogeneity (I2 > 96%). Subgroup analyses by endpoint and model type did not explain this variability.
Discussion:
AI-enhanced ECG models show good diagnostic accuracy, specifically in ruling out cardiac dysfunction due to their high specificity. However, the high and unexplained heterogeneity across these studies limits the immediate generalizability of the results. Large, prospective validation studies across diverse populations are essential before these models can be confidently adopted into routine clinical practice.
Background:
Heart failure (HF) remains a growing global health problem, with nearly half of all cases attributed to HF with preserved ejection fraction (HFpEF) and its precursor, left ventricular diastolic dysfunction (LVDD). Although echocardiography is the diagnostic gold standard, its high cost and limited availability restrict its use for large-scale screening. In contrast, the electrocardiogram (ECG) is inexpensive and widely accessible. Recent advances in artificial intelligence (AI) have created opportunities to leverage ECG data for the early detection of cardiac dysfunction. The objective of this study was to systematically review and meta-analyze the diagnostic performance of AI-based ECG models for detecting cardiac dysfunction.
Methods:
The QUADAS-2 tool was used to assess the risk of bias. Pooled sensitivity and specificity were estimated using a bivariate random-effects model, with heterogeneity quantified using the I2 statistic. Pre-specified subgroup analyses were conducted according to clinical endpoint and AI model type.
Results:
Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, nine eligible studies evaluating AI algorithms applied to ECG data for the detection of HFpEF were identified. Considerable methodological and population heterogeneity was observed across studies. Risk of bias was generally low for reference standards, although concerns were noted in patient selection. The pooled specificity of AI-ECG models was high at 0.83 [95% confidence interval (CI): 0.74–0.89], while pooled sensitivity was 0.82 (95% CI: 0.70–0.90). Both estimates demonstrated extremely high heterogeneity (I2 > 96%). Subgroup analyses by endpoint and model type did not explain this variability.
Discussion:
AI-enhanced ECG models show good diagnostic accuracy, specifically in ruling out cardiac dysfunction due to their high specificity. However, the high and unexplained heterogeneity across these studies limits the immediate generalizability of the results. Large, prospective validation studies across diverse populations are essential before these models can be confidently adopted into routine clinical practice.
DOI: https://doi.org/10.37349/ec.2026.101293
Aim:
Tissue transglutaminase [transglutaminase 2 (TG2)] is implicated in central neuronal apoptosis and is expressed in the peripheral nervous system; however, its role in sensory neuron survival and neuropathic pain after nerve injury remains poorly defined. This study examined whether TG2 knockout (KO) affects dorsal root ganglion (DRG) neuron survival and pain-related behaviors following sciatic nerve injury.
Methods:
TG2 KO mice and wild-type (WT) controls underwent complete sciatic nerve transection (axotomy). Pain-related behavior was evaluated using detailed autotomy scoring over 14 days. DRG neuron survival was assessed using unbiased stereological counts.
Results:
TG2 KO resulted in a distinct, previously unreported “atypical autotomy” pattern, with lesions localized mainly to the midplantar paw region. In contrast, WT mice exhibited typical autotomy directed primarily at the toes. Despite this clear difference in pain phenotype, stereological analysis revealed that TG2 KO did not alter neuronal counts in intact or axotomized DRGs, with both groups showing comparable, significant neuronal loss after injury.
Conclusions:
These findings indicate that TG2 functions as an important modulator of neuropathic pain but is not required for neuronal survival in the adult DRG following nerve injury.
Aim:
Tissue transglutaminase [transglutaminase 2 (TG2)] is implicated in central neuronal apoptosis and is expressed in the peripheral nervous system; however, its role in sensory neuron survival and neuropathic pain after nerve injury remains poorly defined. This study examined whether TG2 knockout (KO) affects dorsal root ganglion (DRG) neuron survival and pain-related behaviors following sciatic nerve injury.
Methods:
TG2 KO mice and wild-type (WT) controls underwent complete sciatic nerve transection (axotomy). Pain-related behavior was evaluated using detailed autotomy scoring over 14 days. DRG neuron survival was assessed using unbiased stereological counts.
Results:
TG2 KO resulted in a distinct, previously unreported “atypical autotomy” pattern, with lesions localized mainly to the midplantar paw region. In contrast, WT mice exhibited typical autotomy directed primarily at the toes. Despite this clear difference in pain phenotype, stereological analysis revealed that TG2 KO did not alter neuronal counts in intact or axotomized DRGs, with both groups showing comparable, significant neuronal loss after injury.
Conclusions:
These findings indicate that TG2 functions as an important modulator of neuropathic pain but is not required for neuronal survival in the adult DRG following nerve injury.
DOI: https://doi.org/10.37349/en.2026.1006124
Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a rare but potentially life-threatening inherited arrhythmia disorder, often presenting in childhood or adolescence. Early and accurate diagnosis is critical, as untreated CPVT carries a high risk of sudden cardiac death, particularly in young individuals. This case underscores the importance of maintaining a high index of clinical suspicion and employing a systematic diagnostic approach. We highlight the value of integrating clinical history, family background, and targeted investigations in evaluating young adults presenting with sudden cardiac arrest. Prompt recognition and diagnosis of CPVT may be lifesaving and have significant implications for both patients and their families.
Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a rare but potentially life-threatening inherited arrhythmia disorder, often presenting in childhood or adolescence. Early and accurate diagnosis is critical, as untreated CPVT carries a high risk of sudden cardiac death, particularly in young individuals. This case underscores the importance of maintaining a high index of clinical suspicion and employing a systematic diagnostic approach. We highlight the value of integrating clinical history, family background, and targeted investigations in evaluating young adults presenting with sudden cardiac arrest. Prompt recognition and diagnosis of CPVT may be lifesaving and have significant implications for both patients and their families.
DOI: https://doi.org/10.37349/ec.2026.101292
Machine learning (ML) and deep learning (DL) models applied to electronic health records (EHRs) have substantial potential to improve oncology care across diagnosis, prognosis, treatment selection, and trial recruitment. However, opacity of many high-performing models limits clinician trust, regulatory acceptance, and safe deployment. Explainable artificial intelligence (XAI) methods aim to make model behavior understandable and actionable in clinical contexts. The present perspective summarizes current XAI approaches applied to EHR-based oncology tasks, identifies key challenges in evaluation, reproducibility, clinical utility, and equity, and proposes pragmatic recommendations and research directions to accelerate safe adoption in oncology. Common XAI categories used with EHR data include feature importance/interaction methods, intrinsically interpretable models, attention mechanisms, dimensionality reduction, and knowledge distillation or rule extraction. Tree-based models with SHapley Additive exPlanations (SHAP) explanations dominate recent EHR studies. Other interpretable strategies, such as generalized additive models and rule sets, appear in settings where transparency is prioritized. Gaps include inconsistent reporting, scarce formal evaluation of explanations for clinical utility, limited reproducibility for data and code availability, inadequate external validation, and insufficient consideration of fairness and equity that these issues are particularly important in oncology, where heterogeneity and stakes are high. Overall, integrating XAI with EHR-driven oncology models is promising but underdeveloped, which requires further progress by multi-stakeholder evaluation frameworks, reproducible pipelines, prospective and multicenter validations, and equity-aware design. The field should prioritize clinically meaningful explanations beyond ranking features and study how explanations affect clinician decision-making and patient outcomes.
Machine learning (ML) and deep learning (DL) models applied to electronic health records (EHRs) have substantial potential to improve oncology care across diagnosis, prognosis, treatment selection, and trial recruitment. However, opacity of many high-performing models limits clinician trust, regulatory acceptance, and safe deployment. Explainable artificial intelligence (XAI) methods aim to make model behavior understandable and actionable in clinical contexts. The present perspective summarizes current XAI approaches applied to EHR-based oncology tasks, identifies key challenges in evaluation, reproducibility, clinical utility, and equity, and proposes pragmatic recommendations and research directions to accelerate safe adoption in oncology. Common XAI categories used with EHR data include feature importance/interaction methods, intrinsically interpretable models, attention mechanisms, dimensionality reduction, and knowledge distillation or rule extraction. Tree-based models with SHapley Additive exPlanations (SHAP) explanations dominate recent EHR studies. Other interpretable strategies, such as generalized additive models and rule sets, appear in settings where transparency is prioritized. Gaps include inconsistent reporting, scarce formal evaluation of explanations for clinical utility, limited reproducibility for data and code availability, inadequate external validation, and insufficient consideration of fairness and equity that these issues are particularly important in oncology, where heterogeneity and stakes are high. Overall, integrating XAI with EHR-driven oncology models is promising but underdeveloped, which requires further progress by multi-stakeholder evaluation frameworks, reproducible pipelines, prospective and multicenter validations, and equity-aware design. The field should prioritize clinically meaningful explanations beyond ranking features and study how explanations affect clinician decision-making and patient outcomes.
DOI: https://doi.org/10.37349/etat.2026.1002357
Background:
Irreversible pulpitis is commonly associated with reduced success of inferior alveolar nerve block (IANB) during root canal treatment, often leading to inadequate intraoperative pain control. Inflammatory mediators can decrease local anesthetic effectiveness and alter nerve response. Preoperative administration of anti-inflammatory drugs has been proposed as a strategy to improve anesthetic success. This review evaluates whether preoperative anti-inflammatory medication enhances the efficacy of IANB in patients with irreversible pulpitis.
Methods:
Thirteen articles published between 2014 and 2024 were included in the qualitative analysis following a screening of titles, abstracts, and full texts. The quality of the studies was assessed using the ROBINS tool.
Results:
Premedication with non-steroidal anti-inflammatory drugs or corticosteroids significantly improves the success of IANB in patients with symptomatic irreversible pulpitis. Success rates in treated groups generally range between 55% and 73%, compared to less than 40% in control groups. Ibuprofen, ketorolac, and dexamethasone were among the most effective agents.
Discussion:
Premedication with non-steroidal anti-inflammatory drugs or corticosteroids, especially ibuprofen and dexamethasone, improves the efficacy of IANB in symptomatic irreversible pulpitis, enhancing anesthetic success and reducing intraoperative pain.
Background:
Irreversible pulpitis is commonly associated with reduced success of inferior alveolar nerve block (IANB) during root canal treatment, often leading to inadequate intraoperative pain control. Inflammatory mediators can decrease local anesthetic effectiveness and alter nerve response. Preoperative administration of anti-inflammatory drugs has been proposed as a strategy to improve anesthetic success. This review evaluates whether preoperative anti-inflammatory medication enhances the efficacy of IANB in patients with irreversible pulpitis.
Methods:
Thirteen articles published between 2014 and 2024 were included in the qualitative analysis following a screening of titles, abstracts, and full texts. The quality of the studies was assessed using the ROBINS tool.
Results:
Premedication with non-steroidal anti-inflammatory drugs or corticosteroids significantly improves the success of IANB in patients with symptomatic irreversible pulpitis. Success rates in treated groups generally range between 55% and 73%, compared to less than 40% in control groups. Ibuprofen, ketorolac, and dexamethasone were among the most effective agents.
Discussion:
Premedication with non-steroidal anti-inflammatory drugs or corticosteroids, especially ibuprofen and dexamethasone, improves the efficacy of IANB in symptomatic irreversible pulpitis, enhancing anesthetic success and reducing intraoperative pain.
DOI: https://doi.org/10.37349/emed.2026.1001381
DOI: https://doi.org/10.37349/emd.2026.1007115
This article belongs to the special issue Biosimilars: State of the Art in the Treatment of Rheumatic Diseases
Aim:
Although polytetrafluoroethylene (PTFE) is more hydrophobic than polyvinylidene fluoride (PVDF) in fluorocarbon polymer (FCP) membrane filters, it has been reported that the rate of amyloid fibril formation is faster on PVDF than on PTFE. To clarify whether the effect is due to the membrane’s chemical structure or its hydrophobicity at the membrane interface, studies on amyloid fibril formation were conducted using both hydrophobic and hydrophilic PVDF and PTFE membranes.
Methods:
Heat-treated insulin (INS) was adsorbed onto the FCP membrane filters. Gaussian integrals were employed to determine the amounts of β-sheet and their abundance ratios by curve fitting of attenuated total reflection Fourier transform infrared spectra.
Results:
Adsorbed heat-treated INS onto the FCP membrane filters showed a β-sheet form, with a similar or higher affinity in comparison with that of the β-rich concanavalin A. The adsorption followed a sigmoidal curve with a 2-hour lag time, reaching a plateau after 4–5 hours. The spectral patterns of the adsorbed INS indicated the β-sheet form, demonstrating that INS transformed into β-sheet and then, or simultaneously, adsorbed onto the FCP membrane filters.
Conclusions:
The results regarding the rate and strength of amyloid fibril formation for each FCP membrane filter suggest that, beyond the membrane’s surface hydrophobicity or hydrophilicity, other factors, such as the electron affinity of hydrogen in the PVDF membrane, also influence nucleation. This study provides insight into the role of INS in amyloid fibril formation within FCP membrane filters.
Aim:
Although polytetrafluoroethylene (PTFE) is more hydrophobic than polyvinylidene fluoride (PVDF) in fluorocarbon polymer (FCP) membrane filters, it has been reported that the rate of amyloid fibril formation is faster on PVDF than on PTFE. To clarify whether the effect is due to the membrane’s chemical structure or its hydrophobicity at the membrane interface, studies on amyloid fibril formation were conducted using both hydrophobic and hydrophilic PVDF and PTFE membranes.
Methods:
Heat-treated insulin (INS) was adsorbed onto the FCP membrane filters. Gaussian integrals were employed to determine the amounts of β-sheet and their abundance ratios by curve fitting of attenuated total reflection Fourier transform infrared spectra.
Results:
Adsorbed heat-treated INS onto the FCP membrane filters showed a β-sheet form, with a similar or higher affinity in comparison with that of the β-rich concanavalin A. The adsorption followed a sigmoidal curve with a 2-hour lag time, reaching a plateau after 4–5 hours. The spectral patterns of the adsorbed INS indicated the β-sheet form, demonstrating that INS transformed into β-sheet and then, or simultaneously, adsorbed onto the FCP membrane filters.
Conclusions:
The results regarding the rate and strength of amyloid fibril formation for each FCP membrane filter suggest that, beyond the membrane’s surface hydrophobicity or hydrophilicity, other factors, such as the electron affinity of hydrogen in the PVDF membrane, also influence nucleation. This study provides insight into the role of INS in amyloid fibril formation within FCP membrane filters.
DOI: https://doi.org/10.37349/ebmx.2026.101357
Left ventricular pseudoaneurysm is a rare acquired cardiac abnormality that frequently occurs after myocardial infarction or a previous cardiac procedure. Blunt chest trauma accounts for this uncommon entity in sporadic cases. However, this disease does not have any specific clinical findings, so it is necessary to monitor the suspected patient closely. The standard noninvasive techniques for diagnosing left ventricular pseudoaneurysms are transthoracic echocardiography and thoracic computed tomography. Untreated ventricular pseudoaneurysms carry a considerable risk of rupture, ranging from 30% to 45%. So, an urgent surgical treatment is often required. Herein, we aimed to present a 34-year-old male who underwent emergency surgery as a result of cardiac perforation three hours after a traffic accident and developed a giant left ventricular pseudoaneurysm 19 months after discharge. The giant pseudoaneurysm was successfully repaired. This case highlights the need for long‑term surveillance after blunt cardiac trauma to detect late pseudoaneurysm formation.
Left ventricular pseudoaneurysm is a rare acquired cardiac abnormality that frequently occurs after myocardial infarction or a previous cardiac procedure. Blunt chest trauma accounts for this uncommon entity in sporadic cases. However, this disease does not have any specific clinical findings, so it is necessary to monitor the suspected patient closely. The standard noninvasive techniques for diagnosing left ventricular pseudoaneurysms are transthoracic echocardiography and thoracic computed tomography. Untreated ventricular pseudoaneurysms carry a considerable risk of rupture, ranging from 30% to 45%. So, an urgent surgical treatment is often required. Herein, we aimed to present a 34-year-old male who underwent emergency surgery as a result of cardiac perforation three hours after a traffic accident and developed a giant left ventricular pseudoaneurysm 19 months after discharge. The giant pseudoaneurysm was successfully repaired. This case highlights the need for long‑term surveillance after blunt cardiac trauma to detect late pseudoaneurysm formation.
DOI: https://doi.org/10.37349/ec.2026.101291
Redesigning cardiovascular services at the local level is a pressing task for decentralized health systems facing the rising burden of chronic cardiovascular disease. In northern Modena (Emilia-Romagna, Italy), a post-restructuring reorganization exposed the limits of hospital-centric models and the need for integrated, patient-centered care. In 2021, Santa Maria Bianca Hospital, Mirandola—a first-level, non-interventional facility serving a largely rural population—launched a program to build a digitally integrated, prevention-oriented cardiology network. This review distills that field experience into a scalable framework for organizing peripheral cardiovascular services. The Mirandola Cardiology Network evolved along six operational domains: (1) reactivation of the cardiology unit with community outreach; (2) expansion of outpatient services and telecardiology; (3) a day hospital platform for chronic heart failure management; (4) digital transformation of the echocardiography service; (5) development of an advanced imaging center integrating coronary computed tomography (CT) angiography and planned cardiac magnetic resonance imaging (MRI); and (6) consolidation of professional education, research, and network-wide governance. By combining digital tools, non-invasive imaging, and multidisciplinary collaboration, the model established continuity of care across inpatient, outpatient, and community settings while improving access to diagnostics and appropriateness of care. Although prospective or comparative outcomes are not presented, process indicators and implementation milestones suggest scalability and sustainability, with potential to reduce avoidable admissions and streamline clinical pathways. The Mirandola experience shows that innovation in cardiology is feasible in peripheral settings when investment in technology, governance, and training is aligned with a coherent, value-based vision. It offers actionable guidance for decentralized systems seeking to implement digitally enabled, community-focused cardiology consistent with contemporary recommendations on territorial care and chronic disease management.
Redesigning cardiovascular services at the local level is a pressing task for decentralized health systems facing the rising burden of chronic cardiovascular disease. In northern Modena (Emilia-Romagna, Italy), a post-restructuring reorganization exposed the limits of hospital-centric models and the need for integrated, patient-centered care. In 2021, Santa Maria Bianca Hospital, Mirandola—a first-level, non-interventional facility serving a largely rural population—launched a program to build a digitally integrated, prevention-oriented cardiology network. This review distills that field experience into a scalable framework for organizing peripheral cardiovascular services. The Mirandola Cardiology Network evolved along six operational domains: (1) reactivation of the cardiology unit with community outreach; (2) expansion of outpatient services and telecardiology; (3) a day hospital platform for chronic heart failure management; (4) digital transformation of the echocardiography service; (5) development of an advanced imaging center integrating coronary computed tomography (CT) angiography and planned cardiac magnetic resonance imaging (MRI); and (6) consolidation of professional education, research, and network-wide governance. By combining digital tools, non-invasive imaging, and multidisciplinary collaboration, the model established continuity of care across inpatient, outpatient, and community settings while improving access to diagnostics and appropriateness of care. Although prospective or comparative outcomes are not presented, process indicators and implementation milestones suggest scalability and sustainability, with potential to reduce avoidable admissions and streamline clinical pathways. The Mirandola experience shows that innovation in cardiology is feasible in peripheral settings when investment in technology, governance, and training is aligned with a coherent, value-based vision. It offers actionable guidance for decentralized systems seeking to implement digitally enabled, community-focused cardiology consistent with contemporary recommendations on territorial care and chronic disease management.
DOI: https://doi.org/10.37349/ec.2026.101290
DOI: https://doi.org/10.37349/emd.2026.1007114
This article belongs to the special issue Magnetic Resonance Neurography: Advances, Techniques, and Clinical Applications
