Variability In Treatment Response Research Articles

Detailed Pathophysiology of Minimal Change Disease: Insights into Podocyte Dysfunction, Immune Dysregulation, and Genetic Susceptibility

Minimal Change Disease (MCD) is a predominant cause of idiopathic nephrotic syndrome in the pediatric population, yet presents significant clinical challenges due to its frequent relapses and steroid resistance. Despite its relatively benign histological appearance, MCD is characterized by severe proteinuria, hypoalbuminemia, and edema, which may affect patient outcomes. Current treatment strategies primarily rely on corticosteroids, which are effective in inducing remission but are associated with high relapse rates, steroid resistance, and numerous long-term side effects, underscoring the need for more targeted and effective therapeutic approaches. This narrative review synthesizes current knowledge on the pathophysiological mechanisms underlying MCD, focusing on the following three critical areas: podocyte dysfunction, immune dysregulation, and genetic susceptibility. Podocyte dysfunction, particularly involving alterations in nephrin, plays a central role in the breakdown of the glomerular filtration barrier, leading to the characteristic proteinuria observed in MCD. Immune dysregulation, including the presence of autoantibodies against nephrin and other podocyte components, exacerbates podocyte injury and contributes to disease progression, suggesting an autoimmune component to the disease. Genetic factors, particularly mutations in the NPHS1 and NPHS2 genes, have been identified as significant contributors to disease susceptibility, influencing the variability in treatment response and overall disease severity. Understanding these mechanisms is crucial for developing targeted therapies that address the underlying causes of MCD rather than merely managing its symptoms. This review highlights the need for further research into these pathophysiological processes to pave the way for more personalized and effective treatment strategies, ultimately improving patient outcomes and reducing reliance on corticosteroids.

Stimulant medication and symptom interrelations in children, adolescents and adults with attention-deficit/hyperactivity disorder

AbstractStimulant medication is effective in alleviating overall symptom severity of attention-deficit/hyperactivity disorder (ADHD), yet interindividual variability in treatment response and tolerability still exists. While network analysis has identified differences in ADHD symptom relations, the impact of stimulant medication remains unexplored. Increased understanding of this association could provide valuable insights for optimizing treatment approaches for individuals with ADHD. In this study, we compared and characterized ADHD symptom networks (including 18 ADHD symptoms) between stimulant-treated (n = 348) and untreated (n = 70) individuals with ADHD and non-ADHD controls (NACs; n = 444). Moreover, we compared symptom networks between subgroups defined by their stimulant treatment trajectory (early-and-intense use, late-and-moderate use). Stimulant-treated individuals with ADHD showed stronger associations between symptoms, compared with untreated individuals with ADHD and NACs. We found no differences in symptom networks between the stimulant treatment trajectory subgroups. Prospective longitudinal studies are needed to disentangle whether the identified differences stem from treatment or pre-existing factors.

RADT-41. RADIOSURGERY FOR GLOMUS TUMORS: IMPACT OF MRI-PET FUSION ON TREATMENT PLANNING AND OUTCOMES

Abstract Paragangliomas present a challenge for stereotactic radiosurgery (SRS) treatment planning, particularly regarding the delineation of tumor boundaries. We propose that integrating 68Ga-DOTATATE PET scans alongside MRI in SRS planning will facilitate superior target identification and tumor coverage compared to reliance on MRI alone. A retrospective analysis of 9 patients diagnosed with paraganglioma who underwent MRI and 68Ga-DOTATATE PET imaging over a 20-month period was conducted. Images were imported into GammaPlan treatment planning software, partitioned into separate sessions: one with MRI and another with MRI-PET fusion. A single evaluator contoured paragangliomas as gross tumor volume (GTV) initially using MRI alone and subsequently with PET/MRI fusion. The pre- and post-PET fusion GTV volumes were compared. The standard deviation of the percentage increases in volume was calculated to assess variability across the sample. Of included 9 patients, 7 were females and median age was 58.3 years. Four patients had prior surgery. Seven patients were treated with Gamma Knife, while 2 with LINAC. Two patients were treated with single fraction SRS while 7 with hypofractionated SRS. Across all treated patients (n=9), GTV volumes significantly increased with PET fusion, with an average volume increase of 26.02% (n=8). One patient reported dryness of throat after SRS. Significant PET avidity over structures like temporal bone, internal jugular vein, petrous internal carotid artery and sigmoid sinus-IJV junction were included in PET/MRI fusion GTVs, which were missed on isolated MRI contours. At median 6-month follow up, all patients had a stable radiological response. Integration of 68Ga-DOTATATE PET scans with MRI enhances the visualization of paragangliomas in patients undergoing SRS. Further extensive studies are warranted to validate this observation and to better understand the variability in treatment response observed across the patient population. Our practice has initiated routine utilization of DOTATATE-PET imaging in paraganglioma patients undergoing SRS planning.

NIMG-01. RADIOMIC DATA ANALYSIS WITH ENSEMBLE MACHINE LEARNING TECHNIQUES PREDICT GRADE, HISTOPATHOLOGIC SUBTYPE, AND 1P/19Q CO-DELETION STATUS IN PATIENTS WITH LOW-GRADE GLIOMAS

Abstract Low-grade gliomas (LGGs) are a diverse group of primary brain tumors characterized by their variable prognosis and treatment response. Traditionally, the management of LGGs has relied on histopathological analysis, which sometimes offers limited insight into tumor behavior and treatment outcomes. Recent advances in radiomics have enabled the extraction of detailed quantitative features from routine imaging, providing a non-invasive method to assess tumor characteristics. These radiomic features can capture underlying tumor heterogeneity more comprehensively than conventional methods. Integrating radiomic data with ensemble machine learning techniques offers a promising approach to enhance the prediction of tumor grade, histopathologic subtype, and genetic alterations such as 1p/19q co-deletion status in LGGs, potentially leading to more tailored therapeutic strategies. We combined radiomic-genomic data from 159 magnetic resonance imaging (MRI) scans from the updated LGG-1p19qDeletion dataset (Erickson 2020) and 114 MRI scans from the ReMIND dataset (Juvekar 2024). Expert radiologists performed segmentations. A total of 2446 extracted radiomic features were initially extracted. Feature selection was performed using wrapper- and filter-based techniques with cross-validation. Prediction models were built using machine learning techniques, including random forest and extreme gradient boosting. Using Random Forest, we achieved high accuracy in predicting histopathologic subtype (88.14%, AUC 96.68%) with precision of 87.86% and Dice score of 87.88%. For grade prediction (accuracy 76.19%, AUC 91.84%), precision was 73.91%, and the Dice score was 77.27%. For 1p/19q co-deletion status (accuracy 75.61%, AUC 82.74%), precision was 77.78%, and the Dice score was 73.68%. Our study establishes a robust radiomic workflow to predict tumor grade, histopathologic subtype, and 1p/19q co-deletion status in low-grade gliomas, enhancing diagnostic accuracy and treatment personalization. This methodology can be applied clinically to improve the stratification of treatment plans for low-grade gliomas, potentially leading to effective, personalized therapy options. Using multicentric data potentially improved external validity, something which past research lacked. Future research should focus on validating and deploying this model using observational multicentric study designs.

High RRM2 Correlates with Mitochondrial and Immune Responses in the Eosinophilic Subtype of Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC), the predominant subtype of RCC, is distinguished by unique biological characteristics and heterogeneity, including eosinophilic and clear subtypes. Notwithstanding progress in therapy, immune checkpoint inhibitors (ICIs), and tyrosine kinase inhibitors (TKIs), the prognosis for individuals with metastatic ccRCC remains poor, presumably owing to metabolic alterations leading to mitochondrial dysfunction, which affects treatment response variability. We analyzed histological and immunohistochemical data from a cohort at Dalian Medical University's First Affiliated Hospital alongside RNA-sequencing transcriptome data from the TCGA database. Histologically, eosinophilic and clear ccRCC subtypes were evaluated using Kaplan-Meier and Cox proportional hazards models for survival analysis and prognosis. Differential gene expression (DEG) analysis and Gene Set Enrichment Analysis were performed to explore transcriptomic differences and relevant pathways. The study discovered substantial histological and molecular differences between the eosinophilic and clear cell subtypes of ccRCC. The eosinophilic subtype linked with frequent high-grade tumors (69.05% eosinophil vs 35.35% clear) and a poorer prognosis (HR=2.659, 95% CI:1.437-4.919, P=0.002). DEG analysis revealed distinct expression patterns among subtypes and identified a risk score signature that remained significant even after adjusting for clinical variables (HR=3.967, 95% CI: 1.665-9.449, P=0.002), showing less favorable survival in the high-risk group (P < 0.0001). RRM2 emerged as the most prognostic gene from this risk score, particularly in the eosinophilic subtype, alongside other clinical variables. By IHC, RRM2 shows high IHC score in eosinophilic compared to clear subtype (P=0.019). In addition, highly expressed RRM2 correlates with poor outcomes and is linked to mitochondrial genes, immunological pathways, and ICIs treatment. These findings show significant differences in prognosis between subtypes. RRM2 was the most prognostic gene from the discovered novel risk score signature associated with subtypes. Future research is essential to validate these insights and their therapeutic implications for ccRCC management.

Treatment ineffectiveness towards Haemonchus contortus is highly prevalent in sheep and goat farms of North-Eastern Italy

BackgroundAnthelmintic resistance (AR) is a global threat to grazing livestock farming. In Italy, anthelmintic efficacy remains high compared to other European countries, but many parts of the country haven’t been investigated yet. Local veterinary practitioners from Trentino and Veneto regions reported suspected inefficacy towards anthelmintic drugs in some of their farms, prompting a study on AR in sheep and goat farms of northern Italy. The study aimed to assess anthelmintic effectiveness using genus-specific faecal egg count reduction tests (FECRT), to detect differences in treatment response among nematode genera involved in the infection.ResultsTwelve farms (6 sheep and 6 goat farms) were included based on clinical suspicion of AR. Treatments were carried out with either benzimidazoles (BZ) or macrocyclic lactones (ML) Treatment was effective in 3/6 goat trials, with reduced effectiveness to BZ in two farms and to ML the last one. In sheep farms (6/6), effectiveness was consistently and more severely insufficient. Ineffectiveness was particularly high towards Haemonchus contortus, while Oesophagostomum/Chabertia maintained susceptibility in nearly all trials. Trichostrongylus/Teladorsagia exhibited intermediate results.ConclusionsThis study reveals diminished efficacy of both BZ and ML in small ruminant farms in north-eastern Italy, an area previously lacking data on the topic, except for goats in South Tyrol. Variability in treatment responses among nematode genera support suspicions of AR, and further concerns are raised by the prevalence of treatment ineffectiveness against the highly pathogenic Haemonchus contortus. This finding underscores the urgent need for comprehensive AR monitoring in the area and improved management practices to prevent further resistance development and protect livestock health.

Socio-Demographic Factors of Children with Nephrotic Syndrome and Their Clinical Correlation

Background: Nephrotic syndrome (NS) is a chronic kidney disease in children marked by variability in treatment response, potentially influenced by socio-demographic and clinical factors. In resource-limited settings such as Bangladesh, understanding these potential influences is crucial for tailored healthcare strategies. This study investigates the socio-demographic profile of children with nephrotic syndrome and its clinical correlation to treatment outcomes. Methods: This cross-sectional study was conducted at Dhaka Shishu (Children) Hospital over six months, involving 168 children with nephrotic syndrome selected through convenient purposive sampling. Data were collected via structured interviews, focusing on socio-demographic factors and clinical outcomes. Statistical analysis was conducted using SPSS, with chi-square tests used to examine associations between socio-demographic factors and treatment response. A p-value &lt;0.05 was considered significant. Results: Of the 168 participants, 61.31% were male, and half were aged 4 to 7 years. Most participants (70.24%) resided in rural areas, with 64.88% belonging to the lower socio-economic class. In terms of treatment response, 48.81% achieved remission, 38.10% experienced a relapse, and 13.10% were resistant to treatment. Although trends were observed, such as higher relapse rates among male children and resistance in females, no statistically significant associations were found between socio-demographic factors and treatment outcomes. Conclusion: The study highlights observed trends in socio-demographic characteristics and treatment outcomes in children with nephrotic syndrome in Bangladesh; however, no significant associations were identified. These findings underscore the importance of larger, more comprehensive studies to further investigate these variables and support the development of tailored management approaches in resource-limited settings.

CHRONIC HEPATITIS B VIRUS INFECTION: SYSTEMATIC REVIEW OF EPIDEMIOLOGY, MECHANISMS OF VIRAL PERSISTENCE AND TREATMENT OF THE CONDITION

Objective: The general objective of this study is to analyze the scientific production on chronic infection by the Hepatitis B virus, seeking to identify the main methods used in the treatment of this pathology. Methodology: This is a systematic review focused on understanding the main aspects that permeate chronic infection by the Hepatitis B virus. The research was guided by the question: “What are the main aspects that permeate chronic infection by the Hepatitis B virus, as well as what are the diagnostic and therapeutic resources used in clinical practice?”. To find answers, searches were performed in the PubMed database using five descriptors combined with the Boolean term “AND”. This resulted in 408 articles. Twenty-four articles were selected for analysis and 15 articles were used to compose the collection. Results: The eradication of hepatitis B depends on the combination of preventive and therapeutic efforts. The persistence of cccDNA in the liver, even after viral suppression, makes complete functional cure difficult. Antivirals such as entecavir and tenofovir are effective in reducing viral load, but they fail to eradicate the virus in most patients, requiring prolonged treatments. Furthermore, the variability in treatment responses, influenced by factors such as viral genotype and disease stage, highlights the need for personalized approaches to improve clinical management. In summary, despite advances, there are still important challenges to be addressed in the search for a cure for chronic hepatitis B. Conclusion: The systematic review highlighted the main aspects of chronic hepatitis B (CHB), emphasizing its challenges and advances in clinical management. Chronic hepatitis B virus (HBV) infection remains a serious public health problem, with complications such as liver cirrhosis and hepatocellular carcinoma. Prevention strategies, such as universal vaccination and immunoprophylaxis, are effective in reducing vertical transmission, especially in newborns, but global adherence still needs to improve, especially in areas of high prevalence.

Single-cell transcriptomics reveal diverging pathobiology and opportunities for precision targeting in scleroderma-associated versus idiopathic pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) involves progressive cellular and molecular change within the pulmonary vasculature, leading to increased vascular resistance. Current therapies targeting nitric oxide (NO), endothelin, and prostacyclin pathways yield variable treatment responses. Patients with systemic sclerosis-associated PAH (SSc-PAH) often experience worse outcomes than those with idiopathic PAH (IPAH). Lung tissue samples from four SSc-PAH, four IPAH, and four failed donor specimens were obtained from the Pulmonary Hypertension Breakthrough Initiative (PHBI) lung tissue bank. Single-cell RNA sequencing (scRNAseq) was performed using the 10X Genomics Chromium Flex platform. Data normalization, clustering, and differential expression analysis were conducted using Seurat. Additional analyses included gene set enrichment analysis (GSEA), transcription factor activity analysis, and ligand-receptor signaling. Pharmacotranscriptomic screening was performed using the Connectivity Map. SSc-PAH samples showed a higher proportion of fibroblasts and dendritic cells/macrophages compared to IPAH and donor samples. GSEA revealed enriched pathways related to epithelial-to-mesenchymal transition (EMT), apoptosis, and vascular remodeling in SSc-PAH samples. There was pronounced differential gene expression across diverse pulmonary vascular cell types and in various epithelial cell types in both IPAH and SSc-PAH, with epithelial to endothelial cell signaling observed. Macrophage to endothelial cell signaling was particularly pronounced in SSc-PAH. Pharmacotranscriptomic screening identified TIE2, GSK-3, and PKC inhibitors, among other compounds, as potential drug candidates for reversing SSc-PAH gene expression signatures. Overlapping and distinct gene expression patterns exist in SSc-PAH versus IPAH, with significant molecular differences suggesting unique pathogenic mechanisms in SSc-PAH. These findings highlight the potential for precision-targeted therapies to improve SSc-PAH patient outcomes. Future studies should validate these targets clinically and explore their therapeutic efficacy.

Training rapid automatized naming in children with developmental Dyslexia

ABSTRACT The recommended rehabilitation procedures for Developmental Dyslexia (DD) are not well defined, and there is currently a large debate on which therapeutic approaches are shown to be more useful and effective. Among the trainings focused on general dysfunctional cognitive processes associated with a reading disorder, recent studies suggested the efficacy of trainings on Rapid Automatized Naming (RAN) compared to others. The present study was aimed at confirming the effectiveness of RAN training (RANt) to improve the reading performances of children with DD (n = 32) compared to children on a waiting list (WL, n = 25) and to children in different treatment groups, one following a text reading training (RT, n = 26) and the other combining RAN and text reading exercises (RANt+RT, n = 20), through an online platform that allows intensive and self-adaptive activities. Results confirmed the efficacy of RANt in improving reading speed and accuracy compared to the WL group (r2 ranging from small (.16) to medium (.48)) and found the absence of differences with the other active control groups. The single-subject level analysis confirmed the results, a high inter-subject variability in treatment response and pre-post differences were found. Further studies could consider such variability in the functional profile of the DD subjects, but RANt was confirmed to be a valid tool for improving decoding skills.

Distinct trajectories of treatment response to mepolizumab toward remission in patients with severe eosinophilic asthma.

Patients with severe eosinophilic asthma, characterised by a high disease burden, benefit from mepolizumab, which improves symptoms and reduces exacerbations, potentially leading to clinical remission in a subgroup. This study aimed to identify treatment response trajectories to mepolizumab for severe eosinophilic asthma and to assess the achievement of clinical remission.Data from the Australian Mepolizumab Registry were used to assess treatment responses at 3, 6, and 12 months. The treatment response trajectories were identified using a group-based trajectory model. The proportions achieving clinical remission at 12 months, which was defined as well-controlled symptoms, no exacerbations, and no oral corticosteroid (OCS) use for asthma management, were compared between trajectories, and baseline predictors of the trajectories were identified using logistic regression analysis.We identified three trajectory groups: group 1, responsive asthma with less OCS use (n=170); group 2, responsive late-onset asthma (n=58); and group 3, obstructed and less responsive asthma (n=70). Groups 1 and 2 demonstrated higher proportions achieving clinical remission at 36.5% and 25.9%, respectively, compared to group 3 with 5.7% (p <0.001). Baseline predictors for assigned groups included lower OCS dose in group 1; greater FEV1% predicted, higher Asthma Quality of Life Questionnaire score, higher OCS dose, and nasal polyps in group 2; with group 3 as the reference.Treatment response to mepolizumab in severe eosinophilic asthma follows 3 trajectories with varying proportions achieving clinical remission and differing baseline characteristics. Treatment response variability may influence the achievement of clinical remission with mepolizumab therapy.

Patients carrying pathogenic SCN8A variants with loss‐ and gain‐of‐function effects can be classified into five subgroups exhibiting varying developmental and epileptic components of encephalopathy

AbstractObjectivePhenotypic heterogeneity presents challenges in providing clinical care to patients with pathogenic SCN8A variants, which underly a wide disease spectrum ranging from neurodevelopmental delays without seizures to a continuum of mild to severe developmental and epileptic encephalopathies (DEEs). An important unanswered question is whether there are clinically important subgroups within this wide spectrum. Using both supervised and unsupervised machine learning (ML) approaches, we previously found statistical support for two and three subgroups associated with loss‐ and gain‐ of‐ function vari‐ants, respectively. Here, we test the hypothesis that the unsupervised subgroups (U1–U3) are distinguished by differential contributions of developmental and epileptic components.MethodsWe predicted that patients in the U1 and U2 subgroups would differ in timing of developmental delay and seizure onset, with earlier and concurrent onset of both features for the U3 subgroup. Standard statistical procedures were used to test these predictions, as well as to investigate clinically relevant associations among all five subgroups.ResultsTwo‐population proportion and Kruskal–Wallis tests supported the hypothesis of a reversed order of developmental delay and seizure onset for patients in U1 and U2, and nearly synchronous developmental delay/seizure onset for the U3 (termed DEE) subgroup. Association testing identified subgroup variation in treatment response, frequency of initial seizure type, and comorbidities, as well as different median ages of developmental delay onset for all five subgroups.SignificanceUnsupervised ML approaches discern differential developmental and epileptic components among patients with SCN8A‐related epilepsy. Patients in U1 (termed developmental encephalopathy) typically gain seizure control yet rarely experience improvements in development, whereas those in U2 (termed epileptic encephalopathy) have fewer if any developmental impairments despite difficulty in achieving seizure control. This understanding improves prognosis and clinical management and provides a framework to discover mechanisms underlying variability in clinical outcome of patients with SCN8A‐related disorders.

Current Patient Management for Bacterial Meningitis Simultaneously Affected by Stroke.

Bacterial meningitis (BM) is a critical central nervous system infection characterized by increased risks of complications and potentially fatal outcomes. The chances of full recovery are significantly reduced in the presence of concomitant neurovascular complications such as ischemic and hemorrhagic strokes, intracerebral hemorrhage, and cerebral sinus thrombosis. Effective treatment of BM requires a targeted approach that simultaneously addresses the causative pathogen and manages the neurologically related complications. However, clinicians continue to face challenges in determining optimal pharmacotherapy for these patients.The presence of neurological complications is pivotal in determining patient outcomes, contributing to high disability and mortality rates. Early medical management is crucial and begins with essential stabilization followed by rapid diagnostic testing and the administration of empirical broad-spectrum antimicrobial therapy. The use of targeted antibiotics based on culture results is standard, with adjunct therapies such as dexamethasone and, in some cases, anticoagulants playing supportive roles. Despite the deployment of such comprehensive therapeutic strategies, the variability in treatment response and the high incidence of adverse outcomes necessitate ongoing research. This includes exploring novel therapeutic approaches and enhancing current clinical practices through retrospective studies and clinical trials to mitigate the high morbidity and mortality rates associated with BM and its complications. Strategic management is crucial for patient recovery, considering the substantial risk, a broad spectrum of complications, and fatal outcomes from this meningeal infection and stroke. The use of antimicrobial therapy with intravenous adjunct dexamethasone isthe current standard of care for patients with cerebrovascular complications and acute BM. In addition, other options that can provide benefits in complicated cases include anticoagulants and neurosurgery. Further investigation into treatment algorithms for patients with meningeal infection complicated by stroke and/or increased intracranial pressure is still needed.

Advancements in the use of nanopharmaceuticals for cancer treatment.

Advances in nanotechnology make it possible to specifically target therapies to cancer cells and neoplasms, guide the surgical resection of tumors, and optimize the effectiveness of radiological treatments. This research article provides a concise synthesis of current knowledge in the field of galenic pharmacy focused on targeted drug delivery in oncology. This research article synthesizes current knowledge in galenic pharmacy, focusing on targeted drug delivery in oncology and reviewing recent advancements in nanopharmaceuticals for cancer treatment. The data for this review are derived from a comprehensive analysis of the most cited scientific literature (Pubmed). Recent studies, clinical trials, and technological breakthroughs related to nanopharmaceuticals have been rigorously examined. This diverse source ensures a comprehensive representation of the latest developments in the field. The results highlight the emergence of nanopharmaceuticals as a promising approach to cancer treatment. The most common in oncology remain liposomes, nanopolymers, and nanocrystals. From a galenic point of view, these three forms offer a wide range of improvements compared to conventional forms such as improvement in solubility as well as stability. The same observation is in the clinic where treatment response rates are significantly improved. The most advantageous form will depend on the specific characteristics of each patient and each type of cancer. The precise design of nanocarriers allows for targeted drug delivery, enhancing therapeutic efficacy while reducing side effects. Concrete examples of clinical applications are presented, illustrating the practical potential of these advancements. In conclusion, this review provides a holistic overview of recent developments in galenic pharmacy for targeted drug delivery in oncology. The stability of nanocarriers is a crucial challenge because it conditions the effectiveness and safety of the drugs transported. Environmental and biological variations encountered in the body can compromise this stability, jeopardizing the therapeutic effectiveness and safety of treatments. Likewise, personalized approaches are essential to address interindividual variations in treatment response, as well as patients' pharmacogenomic profiles, in order to optimize therapeutic effectiveness and minimize adverse effects.

Obesity-Related Ciliopathies: Focus on Advances of Biomarkers.

Obesity-related ciliopathies, as a group of ciliopathies including Alström Syndrome and Bardet-Biedl Syndrome, exhibit distinct genetic and phenotypic variability. The understanding of these diseases is highly significant for understanding the functions of primary cilia in the human body, particularly regarding the relationship between obesity and primary cilia. The diagnosis of these diseases primarily relies on clinical presentation and genetic testing. However, there is a significant lack of research on biomarkers to elucidate the variability in clinical manifestations, disease progression, prognosis, and treatment responses. Through an extensive literature review, the paper focuses on obesity-related ciliopathies, reviewing the advancements in the field and highlighting the potential roles of biomarkers in the clinical presentation, diagnosis, and prognosis of these diseases.

Stratifying heart failure patients with graph neural network and transformer using Electronic Health Records to optimize drug response prediction.

Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal is to improve drug response predictions by identifying specific HF patient subgroups that are likely to benefit from existing HF medications. A novel, graph-based model capable of predicting treatment responses, combining Graph Neural Network and Transformer was developed. This method differs from conventional approaches by transforming a patient's EHR data into a graph structure. By defining patient subgroups based on this representation via K-Means Clustering, we were able to enhance the performance of drug response predictions. Leveraging EHR data from 11627 Mayo Clinic HF patients, our model significantly outperformed traditional models in predicting drug response using NT-proBNP as a HF biomarker across five medication categories (best RMSE of 0.0043). Four distinct patient subgroups were identified with differential characteristics and outcomes, demonstrating superior predictive capabilities over existing HF subtypes (best mean RMSE of 0.0032). These results highlight the power of graph-based modeling of EHR in improving HF treatment strategies. The stratification of patients sheds light on particular patient segments that could benefit more significantly from tailored response predictions. Longitudinal EHR data have the potential to enhance personalized prognostic predictions through the application of graph-based AI techniques.

SingleNucleotide Polymorphisms as Biomarkers of Mepolizumab and Benralizumab Treatment Response in Severe Eosinophilic Asthma.

The most promising treatment options for severe uncontrolled asthma (SUA) have emerged in recent years with the development of monoclonal antibodies for blocking selective targets responsible for the underlying inflammation, such as mepolizumab and benralizumab. However, there is variability in treatment response that is not fully controlled. The variability of the response to mepolizumab and benralizumab could be influenced by single-nucleotide polymorphisms (SNPs), and it would be useful to detect these and use them as predictive biomarkers of response. We conducted a retrospective observational cohort study of 72 Caucasian patients recruited from a tertiary hospital with severe uncontrolled eosinophilic asthma treated with mepolizumab and benralizumab. Polymorphisms in the IL5 (rs4143832, rs17690122), RAD50 (rs11739623, rs4705959), IL1RL1 (rs1420101, rs17026974, rs1921622), GATA2 (rs4857855), IKZF2 (rs12619285), FCGR2A (rs1801274), FCGR2B (rs3219018, rs1050501), FCGR3A (rs10127939, rs396991), FCER1A (rs2251746, rs2427837), FCER1B (rs1441586, rs573790, rs569108), and ZNF415 (rs1054485) genes were analyzed by real-time polymerase chain reaction (PCR) using Taqman probes. The response was analyzed after 12 months of treatment. In patients under mepolizumab treatment, a treatment response defined as a reduction in exacerbations was associated with ZNF415 rs1054485-T (p = 0.042; OR = 5.33; 95% CI = 1.06-30.02), treatment response defined as a reduction in oral corticosteroids use was associated with the number of exacerbations in the previous year (p = 0.029; OR = 3.89; 95% CI = 1.24-14.92), and treatment response defined as improvement in lung function was associated with the age at the beginning of biological therapy (p = 0.002; OR = 1.10; 95% CI = 1.04-1.18), FCER1B rs569108-AA (p < 0.001; OR = 171.06; 95% CI = 12.94-6264.11), and FCER1A rs2427837-A (p = 0.021; OR = 8.61; 95% CI = 1.71-76.62). On the other hand, in patients under benralizumab treatment, treatment response, defined as a reduction in exacerbations, was associated with ZNF415 rs1054485-T (p = 0.073; OR = 1.3 × 108; 95% CI = 1.8 × 10-19-NA), FCER1B rs569108-AA (p = 0.050; OR = 11.51; 95% CI = 1.19-269.78), allergies (p = 0.045; OR = 4.02; 95% CI = 1.05-16.74), and sex (p = 0.028; OR = 4.78; 95% CI = 1.22-20.63); and treatment response defined as improvement in lung function was associated with polyposis (p = 0.027; OR = 9.16; 95% CI = 1.58-91.4), IKZF2 rs12619285-AA (p = 0.019; OR = 9.1; 95% CI = 1.7-75.78), IL5 rs4143832-T (p = 0.017; OR = 11.1; 95% CI = 1.9-112.17), and FCER1B rs1441586-C (p = 0.045; OR = 7.81; 95% CI = 1.16-73.45). The results of this study show the potential influence of the studied polymorphisms on the response to mepolizumab and benralizumab and the clinical benefit that could be obtained by defining predictive biomarkers of treatment response.

Radiomics in Oesogastric Cancer: Staging and Prediction of Preoperative Treatment Response: A Narrative Review and the Results of Personal Experience.

Oesophageal, gastroesophageal, and gastric malignancies are often diagnosed at locally advanced stage and multimodal therapy is recommended to increase the chances of survival. However, given the significant variation in treatment response, there is a clear imperative to refine patient stratification. The aim of this narrative review was to explore the existing evidence and the potential of radiomics to improve staging and prediction of treatment response of oesogastric cancers. The references for this review article were identified via MEDLINE (PubMed) and Scopus searches with the terms "radiomics", "texture analysis", "oesophageal cancer", "gastroesophageal junction cancer", "oesophagogastric junction cancer", "gastric cancer", "stomach cancer", "staging", and "treatment response" until May 2024. Radiomics proved to be effective in improving disease staging and prediction of treatment response for both oesophageal and gastric cancer with all imaging modalities (TC, MRI, and 18F-FDG PET/CT). The literature data on the application of radiomics to gastroesophageal junction cancer are very scarce. Radiomics models perform better when integrating different imaging modalities compared to a single radiology method and when combining clinical to radiomics features compared to only a radiomics signature. Radiomics shows potential in noninvasive staging and predicting response to preoperative therapy among patients with locally advanced oesogastric cancer. As a future perspective, the incorporation of molecular subgroup analysis to clinical and radiomic features may even increase the effectiveness of these predictive and prognostic models.

Immunotherapies: A Treasure Trove of Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disease that falls under the umbrella of dementia and is characterized by the presence of enormously neurotoxic amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs) of tau protein inside the brain. AD remains an intractable global health challenge with limited therapeutic options. Early diagnosis, enabled by biomarkers and neuroimaging, is pivotal for optimizing treatment outcomes. Immunotherapeutic strategies, including monoclonal antibodies, active vaccination, and passive immunization, have been developed to target hallmark AD pathology, such as amyloid-beta aggregation. Here we summarized the emerging role of immunotherapies in the early stages of AD, shedding light on recent breakthroughs and clinical progress. Challenges, including treatment response variability and safety concerns, are discussed alongside evolving approaches, such as personalized immunotherapy and combinatorial treatments. This concise review underscores the promise of immunotherapies as a transformative approach to AD intervention, offering hope for a brighter future in the quest to combat this devastating neurodegenerative disease.

Familial Arteriovenous Malformation in Extremity: A Case Report

Arteriovenous malformation (AVM) is a genetic vascular anomaly that can significantly affect daily activities. Its occurrence varies by race and gender, being more common in women. This report examines AVM in two siblings, aged 12 and 14. Clinical, radiological, and pathological evaluations revealed differing tumor sizes, expansions, and causes of vascular enlargement. Consequently, the siblings received different treatments: one underwent embolization, while the other had a wide excision. Both approaches resulted in favorable outcomes. AVM is a vascular neoplasm that may present at birth or be discovered later, often during routine check-ups or after trauma. The familial nature of AVM in this case emphasizes the variability in presentation and treatment response. Established diagnostic and therapeutic guidelines may not always be applicable, necessitating individualized treatment plans. This case highlights the importance of tailored treatment approaches for familial AVM, demonstrating successful outcomes with both embolization and wide excision