Treatment Challenges Research Articles

7117 Cushings Conundrum: Taming The Hormone Hurricane

Abstract Disclosure: S. Syed: None. A. Poloju: None. A. Krueger: None. C. O'connor: None. Ectopic ACTH syndrome is a rare disease that presents with severe hypercortisolism that can be challenging to treat. This case reviews a patient with high- grade metastatic neuroendocrine tumor causing ectopic ACTH-related Cushing's syndrome and describes navigating these treatment challenges with an evidence-based and patient centered strategy to try to optimize care.Clinical case: This 32-year-old male, with a history of metastatic pancreatic neuroendocrine tumor and liver metastases, initially presented with dyspnea, hyperglycemia, and metabolic derangements. Agitated, with a systolic blood pressure of 190mm Hg, he exhibited notable hypokalemia (2.5mmol/L), hyperglycemia (508mg/dL), and elevated beta-hydroxybutyrate (3.60mmol/L). Random cortisol was 85.9ug/dL and ACTH 472pg/ml. Urgent cortisol control prompted etomidate infusion, lowering cortisol to 27ug/dL in 24 hours. Ketoconazole was initiated but discontinued later due to rising liver enzymes, Metyrapone and spironolactone were initiated and etomidate infusion titrated off. Hemorrhagic shock, DKA, and mental status changes complicated his course.Interventional radiology-guided hepatic artery embolization was performed. Post-procedure cortisol levels improved, metyrapone and spironolactone were stopped. Dexamethasone was initiated given concern for relative adrenal insufficiency during this time and was later switched to hydrocortisone, and eventually discontinued with normalizing cortisol levels. Octreotide and later lanreotide maintained stability for a year. He was readmitted with uncontrolled diabetes, hypertension, and vertebral compression fractures, requiring rapid control with etomidate infusion again. Metyrapone was reintroduced, facilitating etomidate tapering. Spironolactone was re-initiated. Bilateral adrenalectomy was discussed as definitive treatment for the ectopic ACTH syndrome (neuroendocrine cancer was deemed incurable, however he was considered elevated risk for surgery given other co-morbidities. Even with normalization of cortisol, he intermittently refused cares/medications. Conclusion: Managing ACTH-producing neuroendocrine tumors necessitates a multidisciplinary approach. In severe Cushing’s syndrome, etomidate infusion quickly normalizes cortisol but requires intensive care due to sedation risks. Ketoconazole and levoketoconazole carry a hepatotoxicity risk. Metyrapone and mitotane are alternatives but supply challenges exist. Osilodrostat, studied for short-term use, has limited data in ectopic ACTH syndromes. Bilateral adrenalectomy is an option if surgical risks are acceptable. Patient history influences therapeutic decisions, highlighting the need for a patient-centered approach. Presentation: 6/3/2024

Construction and validation of cell cycle-related prognostic genetic model for glioblastoma.

Glioblastoma (GBM) is a common primary malignant brain tumor and the prognosis of these patients remains poor. Therefore, further understanding of cell cycle-related molecular mechanisms of GBM and identification of appropriate prognostic markers and therapeutic targets are key research imperatives. Based on RNA-seq expression datasets from The Cancer Genome Atlas database, prognosis-related biological processes in GBM were screened out. Gene Set Variation Analysis (GSVA), LASSO-COX, univariate and multivariate Cox regression analyses, Kaplan-Meier survival analysis, and Pearson correlation analysis were performed for constructing a predictive prognostic model. A total of 58 cell cycle-related genes were identified by GSVA and analysis of differential expression between GBM and control samples. By univariate Cox and LASSO regression analyses, 8 genes were identified as prognostic biomarkers in GBM. A nomogram with superior performance to predict the survival of GBM patients was established regarding risk score, cancer status, recurrence type, and mRNAsi. This study revealed the prognostic value of cell cycle-related genes in GBM. In addition, we constructed a reliable model for predicting the prognosis of GBM patients. Our findings reinforce the relationship between cell cycle and GBM and may help improve the prognostic assessment of patients with GBM. Our predictive prognostic model, based on independent prognostic factors, enables tailored treatment strategies for GBM patients. It is particularly useful for subgroups with uncertain prognosis or treatment challenges.

Small Molecule Compound DHPA Screened by Computer-Aided Drug Design and Molecular Dynamics Simulation Inhibits Neuroblastoma Cell Proliferation by Targeting TrkB.

Neuroblastoma (NB) is a rare and malignant pediatric solid tumor. Due to its heterogeneity, it poses significant challenges for treatment, resulting in a high mortality rate. This study aimed to identify new therapeutic drugs by modeling the TrkB receptor from PDB 4AT5 and conducting virtual screening of compounds from the YaTCM database (containing 47,696 compounds derived from 6220 Traditional Chinese Medicines). The screening utilized the E-pharmacophore approach to select compounds with potential binding affinity to TrkB. The binding abilities of these compounds were tested through molecular dynamics simulations, stretch dynamics simulations, and US simulations. Among the top 11 optimized hit compounds, DHPA and 3″-demethylhexahydrocurcumin are prominent. Further simulations reveal that they form stable receptor-ligand binary complexes with TrkB. In subsequent in vitro cell experiments, 3″-demethylhexahydrocurcumin is eliminated due to its high IC50 for killing NB cells. Low concentrations of DHPA can significantly kill NB cells. Additionally, DHPA can inhibit the expression of TrkB, the activation of TrkB's downstream signaling pathways, and affect the thermal stability of TrkB protein and its response to streptase protease degradation. DHPA may be a potential TrkB inhibitor.

The Necessary Rapprochement of Negative Affectivity, Personality Disorder, and Depression.

The relationship between depression and personality has long been a topic of interest in the fields of psychiatry and psychology, but consensus remains elusive. This lack of consensus poses a significant challenge in both diagnosis and treatment, especially in situations when otherwise effective therapies for depression fail. Our article aims to address this issue by reviewing the historical and recent conceptualizations of the relationship between depression and personality pathology. Specifically, we focus on the trait domain of negative affectivity found in the International Classification of Diseases, 11th Edition (ICD-11) and the Alternative Model for Personality Disorders (AMPD) as a connecting link between the two phenomena. We review recent empirical studies evaluating the association of negative affectivity, personality, and depression, along with investigations of the relationship between depressive disorders and personality disorders. Additionally, we describe the Hierarchical Taxonomy of Psychopathology (HiTOP) and the AMPD as organizing frameworks for understanding depression within a broader personality framework. Based on the available evidence, we propose that depressive disorders must be assessed within the context of the patient's personality in order to maximize treatment outcomes. Ultimately, this integrated approach can guide clinicians in developing unified treatment protocols and facilitate early detection and intervention for factors contributing to depression in order to minimize treatment resistance.

A hierarchical random effects state-space model for modeling brain activities from electroencephalogram data.

Mental disorders present challenges in diagnosis and treatment due to their complex and heterogeneous nature. Electroencephalogram (EEG) has shown promise as a source of potential biomarkers for these disorders. However, existing methods for analyzing EEG signals have limitations in addressing heterogeneity and capturing complex brain activity patterns between regions. This paper proposes a novel random effects state-space model (RESSM) for analyzing large-scale multi-channel resting-state EEG signals, accounting for the heterogeneity of brain connectivities between groups and individual subjects. We incorporate multi-level random effects for temporal dynamical and spatial mapping matrices and address non-stationarity so that the brain connectivity patterns can vary over time. The model is fitted under a Bayesian hierarchical model framework coupled with a Gibbs sampler. Compared to previous mixed-effects state-space models, we directly model high-dimensional random effects matrices of interest without structural constraints and tackle the challenge of identifiability. Through extensive simulation studies, we demonstrate that our approach yields valid estimation and inference. We apply RESSM to a multi-site clinical trial of major depressive disorder (MDD). Our analysis uncovers significant differences in resting-state brain temporal dynamics among MDD patients compared to healthy individuals. In addition, we show the subject-level EEG features derived from RESSM exhibit a superior predictive value for the heterogeneous treatment effect compared to the EEG frequency band power, suggesting the potential of EEG as a valuable biomarker for MDD.

Whole-genome sequencing resolves biochemical misidentification of Neisseria species from urogenital specimens.

Neisseria meningitidis (Nm) and Neisseria gonorrhoeae (Ng) are human pathogens that sometimes occupy the same anatomical niche. Ng, the causative agent of gonorrhea, infects 87 million individuals annually worldwide and is an urgent threat due to increasing drug resistance. Ng is a pathogen of the urogenital tract and may infect the oropharyngeal or rectal site, often asymptomatically. Conversely, Nm is an opportunistic pathogen. While often a commensal in the oropharyngeal tract, it is also the leading cause of bacterial meningitis with 1.2 million cases globally, causing significant morbidity and mortality. Horizontal gene transfer (HGT) is likely to occur between Ng and Nm due to their shared anatomical niches and genetic similarity, which poses challenges for accurate detection and treatment. Routine surveillance through the Gonococcal Isolate Surveillance Project and Strengthening the U.S. Response to Resistant Gonorrhea detected six concerning urogenital Neisseria isolates with contradicting species identification in Milwaukee (MIL). While all six isolates were positive for Ng using nucleic acid amplification testing (NAAT) and matrix-assisted laser desorption/ionization time of flight identified the isolates as Ng, two biochemical tests, Gonochek-II and API NH, classified them as Nm. To address this discrepancy, we performed whole-genome sequencing (WGS) using Illumina MiSeq on all isolates and employed various bioinformatics tools. Species detection analysis using BMScan, which uses WGS data, identified all isolates as Ng. Furthermore, Kraken revealed over 98% of WGS reads mapped to the Ng genome and <1% to Nm. Recombination analysis identified putative HGT in all MIL isolates within the γ-glutamyl transpeptidase (ggt) gene, a key component in the biochemical tests used to differentiate between Nm and Ng. Further analysis identified Nm as the source of HGT event. Specifically, the active Nm ggt gene replaced the Ng pseudogenes, ggt1 and ggt2. Together, this study demonstrates that closely related Neisseria species sharing a niche underwent HGT, which led to the misidentification of species following biochemical testing. Importantly, NAAT accurately detected Ng. The misidentification highlights the importance of using WGS to continually evaluate diagnostic or bacterial identification tests.

Unlocking the potential of lactic acid bacteria mature biofilm extracts as antibiofilm agents

The continuous growth of biofilm infections and their resilience to conventional cleaning methods and antimicrobial agents pose a worldwide challenge across diverse sectors. This persistent medical, industrial, and environmental issue contributes to treatment challenges and chronic diseases. Lactic acid bacteria have garnered global attention for their substantial antimicrobial effects against pathogens and established beneficial roles. Notably, their biofilms are also predicted to show a promising control strategy against pathogenic biofilm formation. The prevalence of biofilm-related problems underscores the need for extensive research and innovative solutions to tackle this global challenge. This novel study investigates the effect of different extracts (external, internal, and mixed extracts) obtained from Lactobacillus rhamnosus GG biofilm on pathogenic-formed biofilms. Subsequently, external extracts presented an important eradication effectiveness. Furthermore, a 6-fold concentration of these extracts led to eradication percentages of 57%, 67%, and 76% for Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa biofilms, respectively, and around 99.9% bactericidal effect of biofilm cells was observed for the three strains. The results of this research could mark a significant breakthrough in the field of anti-biofilm and antimicrobial strategies. Further studies and molecular research will be necessary to detect the molecules secreted by the biofilm, and their mechanisms of action engaged in new anti-biofilm strategies.

Development and Novel Therapeutics in Diabetic Retinopathy.

Diabetic retinopathy (DR) is a complication of diabetes mellitus which causes retinal damage which when left untreated will cause visual problems. As the prevalence of DR increases over the years, there is a need to optimise the currently available treatments as well as developing novel drugs to improve the therapy provided for the patients in the clinical practice. Several pharmacological therapies like, anti-vascular endothelial growth factor and anti-inflammatory therapies which include intravitreal, and implant of corticosteroids are significant in the management to decrease the risk of DR-related vision impairment. Clinical trials for novel drug therapies are still ongoing till this day to enhance the efficacy of DR treatment. Even though there are also modern treatments such as laser therapy for the patients, prevention should be done to lower the number of individuals affected by DR. Due to the complexity of DR, there are numerous obstacles to develop new medications for DR which include the increasing healthcare cost of DR treatment. New insights such as utilisation of artificial intelligence will be implemented into the management of DR as it has proved its potential in aiding the screening process. In parallel with the increase in DR prevalence and the number of treatments developed, extensive understanding of the mechanism of action of DR should be further improved to prevent more complications in the future. This review summarises the epidemiological trend, prevention strategies, challenges in treatment, current novel therapeutics (including drugs under clinical trials), future therapeutic trends and possibilities for implementing AI in the early diagnosis and management of DR.

The Adult Orthodontic– Restorative Interface. Part 1: Concepts of Treatment and Presenting Challenges

This is the first article in a three-part series that discusses joint orthodontic–restorative care for the adult patient. Part 1 presents an overview of the clinical presentations, challenges and strategies that may be employed to treat this complex patient group. CPD/Clinical Relevance: The reader should be able to describe a care pathway, with potential associated complications, for the provision of adult orthodontic–restorative treatment.

Therapeutic ultrasound: an innovative approach for targeting neurological disorders affecting the basal ganglia.

The basal ganglia are involved in motor control and action selection, and their impairment manifests in movement disorders such as Parkinson's disease (PD) and dystonia, among others. The complex neuronal circuitry of the basal ganglia is located deep inside the brain and presents significant treatment challenges. Conventional treatment strategies, such as invasive surgeries and medications, may have limited effectiveness and may result in considerable side effects. Non-invasive ultrasound (US) treatment approaches are becoming increasingly recognized for their therapeutic potential for reversibly permeabilizing the blood-brain barrier (BBB), targeting therapeutic delivery deep into the brain, and neuromodulation. Studies conducted on animals and early clinical trials using ultrasound as a therapeutic modality have demonstrated promising outcomes for controlling symptom severity while preserving neural tissue. These results could improve the quality of life for patients living with basal ganglia impairments. This review article explores the therapeutic frontiers of ultrasound technology, describing the brain mechanisms that are triggered and engaged by ultrasound. We demonstrate that this cutting-edge method could transform the way neurological disorders associated with the basal ganglia are managed, opening the door to less invasive and more effective treatments.

Patient feasibility as a novel approach for integrating IRT and LCA statistical models into patient-centric qualitative data-a pilot study.

Clinical research increasingly recognizes the role and value of patient-centric data incorporation in trial design, aiming for more relevant, feasible, and engaging studies for participating patients. Despite recognition, research on analytical models regarding qualitative patient data analysis has been insufficient. This pilot study aims to explore and demonstrate the analytical framework of the "patient feasibility" concept-a novel approach for integrating patient-centric data into clinical trial design using psychometric latent class analysis (LCA) and interval response theory (IRT) models. A qualitative survey was designed to capture the diverse experiences and attitudes of patients in an oncological indication. Results were subjected to content analysis and categorization as a preparatory phase of the study. The analytical phase further employed LCA and hybrid IRT models to discern distinct patient subgroups and characteristics related to patient feasibility. LCA identified three latent classes each with distinct characteristics pertaining to a latent trait defined as patient feasibility. Covariate analyses further highlighted subgroup behaviors. In addition, IRT analyses using the two-parameter logistic model, generalized partial credit model, and nominal response model highlighted further distinct characteristics of the studied group. The results provided insights into perceived treatment challenges, logistic challenges, and limiting factors regarding the standard of care therapy and clinical trial attitudes.

Closure of a secondary tracheoesophageal fistula in severe pneumonia using an Amplatzer Duct Occluder II during invasive mechanical ventilation: A case report.

Early and timely closure of secondary tracheoesophageal fistula (TEF) is crucial for critically ill patients. For those requiring invasive mechanical ventilation, the Amplatzer Duct Occluder II (ADO II) can be used as an emergency therapeutic option to rapidly close secondary TEF, providing opportunities for subsequent treatments. Secondary tracheoesophageal fistula (TEF) is a life-threatening condition characterized by high mortality, high recurrence rates, and multiple complications. Reports on the management of secondary TEF in critically ill patients are limited due to the challenges in treatment and the lack of suitable therapeutic options. We report a case of secondary TEF in a 69-year-old male diagnosed with severe pneumonia, whose condition deteriorated rapidly following the onset of TEF. Despite invasive mechanical ventilation, maintaining blood oxygen saturation above 80% was unachievable due to the TEF. Bedside bronchoscopy revealed expansion TEF expansion caused by gastrointestinal fluid reflux and respiratory machine pressure. The TEF was urgently closed using an ADO II device during invasive mechanical ventilation to prevent further deterioration. After the patient's condition stabilized, the ADO II was replaced with a Y-shaped tracheal membrane-covered stent for further TEF management. The patient's condition improved, meeting the criteria for liberation from invasive mechanical ventilation, and bedside chest X-rays revealed a gradual resolution of pulmonary inflammation. Selecting appropriate treatment modalities for early and timely closure of secondary TEF is crucial for critically ill patients. ADO II can serve as a rescue therapy to achieve rapid closure of secondary TEF in critically ill patients requiring invasive mechanical ventilation support, providing opportunities and time for subsequent treatment.

Acoustic black hole immersed sonoreactor for high-efficiency cavitation treatment

Developing innovative sonoreactors to enhance acoustic processing efficiency holds immense importance in the field of sonochemistry. Traditional immersed sonoreactors (TISs) mainly produce cavitation at the probe tip, with a relatively weak cavitation around the probe, resulting in posing challenges for high-efficiency cavitation treatment. Here we propose an acoustic black hole immersed sonoreactor (ABHIS) in longitudinal-flexural coupled vibration, enabling high-efficiency cavitation treatment by unleashing the cavitation potential of the probe. The symmetrical structure of the probe is altered to introduce a coupling of flexural vibration mode, and an acoustic black hole (ABH) profile is integrated to further enhance both flexural wave number and amplitude. In this paper, we present a systematic theoretical design method for ABHIS and compare its performance with TIS using finite element method (FEM). An ABHIS prototype is fabricated and subjected to experimental tests and cavitation observation. The results demonstrate that our theoretical analysis model accurately predicts the frequency characteristics of ABHIS. The proposed ABHIS exhibits satisfactory dynamic characteristics, with significantly increased vibration displacement and acoustic radiation ability compared to TIS. Importantly, the ABH design significantly expands ultrasonic cavitation regions and enhances acoustic radiation intensity of ABHIS resulting in a substantial improvement in acoustic processing efficiency.

Effectiveness of peritoneal lavage fluid circulating tumour cells and circulating tumour DNA in the prediction of metachronous peritoneal metastasis of gastric cancer (pT4NxM0/pT1-3N+M0) after radical resection: protocol of a prospective single-centre clinical study

BackgroundGastric cancer (GC) is the fourth leading cause of cancer mortality worldwide. Peritoneal metastasis (PM) is a significant cause of death in patients with GC, and presents a major challenge...

The Advances in the Development of Epigenetic Modifications Therapeutic Drugs Delivery Systems.

Epigenetic dysregulation can significantly trigger the onset and progression of various diseases, epigenetic therapy is a new treatment strategy by changing DNA methylation, histone modification, N6-methyladenosine, chromatin modification and other epigenetic modifications to regulate gene expression levels for therapeutic purposes. However, small-molecule epigenetic drugs face challenges in disease treatment, such as lack of selectivity, limited therapeutic efficacy, and insufficient safety. Nanomedicine delivery systems offer significant advantages in addressing these issues by enhancing drug targeting, improving bioavailability, and reducing nonspecific distribution. This help minimize side effects while increasing both therapeutic effectiveness and safety of epigenetic drugs. In this review, we focus on the mechanism and role of epigenetic regulatory factors in diseases, as well as the challenges faced by small molecule inhibitors in treatment strategies, especially the research advancements in epigenetic drug delivery systems, review and discuss the therapeutic potential and challenges of using nanotechnology to develop epigenetic drug delivery systems.

Removal of sulfamethoxazole using Fe-Mn biochar filtration columns: Influence of co-existing polystyrene microplastics

Emerging contaminants, particularly antibiotics and microplastics (MPs), present significant challenges in wastewater treatment and pose large ecological risks. This study investigates the removal efficiency of sulfamethoxazole (SMX) using Fe-Mn modified biochar (BFM) in fixed bed filtration columns, emphasizing the effect of the presence of polystyrene microplastics (PS-MPs) on SMX behavior in both water (pH ≈ 5.6) and selected wastewater (pH ≈ 8) systems. Batch sorption results show that 10 mg/L SMX in 50 mL water can be completely removed by 100 mg BFM sorbent. The Bed Depth Service Time model indicated the BFM column is feasible for SMX removal in scaled-up continuous wastewater flow operations, while the Yan model best elucidates SMX filtration behavior and suggests the dominant adsorption mechanisms include external mass transfer and intraparticle diffusion. The present of both 20 mg/L and 100 mg/L PS-MPs (pH ≈ 5.6) significantly reduced SMX retention due to competitive sorption. However, at pH 3.2, competitive sorption became negligible due to electrostatic interactions driving the PS-MPs sorption, while neutral charged SMX bound through hydrogen-bonds or π-π EDA interactions. Elevated pH shifted both PS-MPs and SMX sorption to non-electrostatic thus intensifying sorption competition, highlighting the influence of pH on their interaction dynamics. In wastewater, SMX filtration was slightly inhibited by 100 mg/L PS-MPs in BFM columns, whereas PS-MPs removal remained unaffected due to the high ionic strength and alkaline pH. These findings highlight the impact of MPs on pollution removal efficiency in filtration system, essential for enhancing biochar-based wastewater treatment strategies.

Serum metabolite biomarkers for the early diagnosis and monitoring of age-related macular degeneration

IntroductionAge-related macular degeneration (AMD) is a leading cause of irreversible blindness worldwide, with significant challenges for early diagnosis and treatment. ObjectivesTo identify new biomarkers that are important for the early diagnosis and monitoring of the severity/progression of AMD. MethodsWe investigated the diagnostic and monitoring potential of blood metabolites in a cohort of 547 individuals (167 healthy controls, 240 individuals with other eye diseases as eye disease controls, and 140 individuals with AMD) from 2 centers over three phases: discovery phase 1, discovery phase 2, and an external validation phase. The samples were analyzed via a mass spectrometry-based, widely targeted metabolomic workflow. In discovery phases 1 and 2, we built a machine learning algorithm to predict the probability of AMD. In the external validation phase, we further confirmed the performance of the biomarker panel identified by the algorithm. We subsequently evaluated the performance of the identified biomarker panel in monitoring the progression and severity of AMD. ResultsWe developed a clinically specific three-metabolite panel (hypoxanthine, 2-furoylglycine, and 1-hexadecyl-2-azelaoyl-sn-glycero-3-phosphocholine) via five machine learning models. The random forest model effectively discriminated patients with AMD from patents in the other two groups and showed acceptable calibration (area under the curve (AUC) = 1.0; accuracy = 1.0) in both discovery phases 1 and 2. An independent validation phase confirmed the diagnostic model’s efficacy (AUC = 0.962; accuracy = 0.88). The three-biomarker panel model demonstrated an AUC of 1.0 in differentiating the severity of AMD via RF machine learning, which was consistent across both the discovery and external validation phases. Additionally, the biomarker concentrations remained stable under repeated freeze–thaw cycles (P > 0.05). ConclusionsThis study reveals distinct metabolite variations in the serum of AMD patients, paving the way for the development of the first routine laboratory test for AMD.

Caffeic acid-mediated photodynamic multifunctional hyaluronic acid-gallic acid hydrogels with instant and enduring bactericidal potency accelerate bacterial infected wound healing

The emergence of drug-resistant bacteria poses significant challenges in wound treatment. Antimicrobial photodynamic therapy has emerged as an effective approach to eliminating bacteria by inducing oxidative stress without causing drug resistance. Here, we developed a natural hyaluronic acid (HA)-gallic acid (GA) conjugation-based hydrogel combined with herbal photosensitizer-caffeic acid (CA), which exhibits self-healing ability, shape adaptability, biodegradability, and robust tissue adhesion. Under exposure to 400 nm light, caffeic acid acts as a photosensitizer, generating reactive oxygen species and oxidative damage to bacterial cell membranes. Furthermore, the presence of GA and CA displayed a continuous inhibitory effect on bacterial growth, along with antioxidant properties that promote wound healing even after the cessation of light exposure. The antibacterial mechanism of the HA-GA/CA hydrogel against MRSA, S. aureus, and E. coli was investigated through various assays measuring ATP levels, Zeta potential, hydroxyl radicals (·OH) generated by light irradiation, and biofilm clearance rate. Additionally, hydrogel's application in treating MRSA-infected wounds in mice under light irradiation demonstrated rapid wound-healing effects and biocompatibility. Overall, HA-GA/CA hydrogel provides a sustainable, antibiotic-free alternative for treating MRSA-infected wounds.

The Other Site of Rhabdomyosarcoma.

Rhabdomyosarcoma (RMS) is a rare malignant soft tissue sarcoma (STS), accounting for almost 50% of pediatric STSs. Due to its heterogeneity, RMS presents challenges in diagnosis and treatment, with prognosis varying depending on multiple factors. Tumors localized in the other site (OTH)-including the paraspinal, perianal, thoracic, abdominal, pelvic, and perineal regions-are generally classified as unfavorable. This study assesses the clinical features and prognoses of RMS in OTH locations depending on its site of origin. An explorative analysis of RMS cases from the SEER 17 database 2000-2020 was conducted. Patients of all ages with histologically confirmed RMS as primary malignant disease classified under OTH, were included. OTH was categorized in four granular site classifications. Overall survival (OS) and disease-specific survival (DSS) were analyzed using Kaplan-Meier estimators. Factors independently influencing survival, including a site classification model presented in this study, were identified through Cox regression analysis. Out of 4168 patients with RMS, 990 cases of RMS with the OTH site met the inclusion criteria. The median age was 16 years. The predominant histological subtypes were embryonal (33.0%) and alveolar (25.5%). Most tumors were ≥ 5 cm (median 9 cm) and located primarily in the pelvic region (41.5%). The 3-, 5-, and 10-year OS rates were 45.4% ± 3.332 (95% CI), 40.7 ± 3.332, and 38.6% ± 3.332, respectively, while DSS rates were 43.3% ± 3.136 (95% CI), 38.3% ± 3.136, and 35.1% ± 3.332. In the multivariate analysis age, histological type, site in a granular categorization, stage, regional lymph node examination, and regional lymph node involvement (pathologically proven) were independently associated with survival. Through both univariate and multivariate analyses, an OTH favorable group could be established. The OTH favorable group consists of the anal region, gallbladder and biliary tract, and breast. RMS in OTH shows significant differences in prognosis, putting the current categorization as unfavorable into question and making a more detailed classification necessary. Furthermore, pathological regional lymph node assessment is specifically in the OTH localization recommended.

Brain tumor detection and classification in MRI using hybrid ViT and GRU model with explainable AI in Southern Bangladesh

Brain tumor, a leading cause of uncontrolled cell growth in the central nervous system, presents substantial challenges in medical diagnosis and treatment. Early and accurate detection is essential for effective intervention. This study aims to enhance the detection and classification of brain tumors in Magnetic Resonance Imaging (MRI) scans using an innovative framework combining Vision Transformer (ViT) and Gated Recurrent Unit (GRU) models. We utilized primary MRI data from Bangabandhu Sheikh Mujib Medical College Hospital (BSMMCH) in Faridpur, Bangladesh. Our hybrid ViT-GRU model extracts essential features via ViT and identifies relationships between these features using GRU, addressing class imbalance and outperforming existing diagnostic methods. We extensively processed the dataset, and then trained the model using various optimizers (SGD, Adam, AdamW) and evaluated through rigorous 10-fold cross-validation. Additionally, we incorporated Explainable Artificial Intelligence (XAI) techniques-Attention Map, SHAP, and LIME-to enhance the interpretability of the model’s predictions. For the primary dataset BrTMHD-2023, the ViT-GRU model achieved precision, recall, and F1-score metrics of 97%. The highest accuracies obtained with SGD, Adam, and AdamW optimizers were 81.66%, 96.56%, and 98.97%, respectively. Our model outperformed existing Transfer Learning models by 1.26%, as validated through comparative analysis and cross-validation. The proposed model also shows excellent performances with another Brain Tumor Kaggle Dataset outperforming the existing research done on the same dataset with 96.08% accuracy. The proposed ViT-GRU framework significantly improves the detection and classification of brain tumors in MRI scans. The integration of XAI techniques enhances the model’s transparency and reliability, fostering trust among clinicians and facilitating clinical application. Future work will expand the dataset and apply findings to real-time diagnostic devices, advancing the field.