Biological characteristics of molecular subtypes of ulcerative colitis characterized by ferroptosis and neutrophil infiltration.

Clinical ulcerative colitis (UC) is a heterogeneous condition. Moreover, medical interventions are nonspecific, and thus, treatment responses are inconsistent. The aim of this study was to explore the molecular subtypes and biological characteristics of UC based on ferroptosis and neutrophil gene sets. Multiple intestinal mucosa gene expression profiles of UC patients in the Gene Expression Omnibus (GEO) database were downloaded. Unsupervised clustering methods were used to identify potential molecular subtypes based on ferroptosis and neutrophil gene sets. Multiple immune infiltration algorithms were used to evaluate the biological characteristics of the molecular subtypes. Machine learning identifies hub genes for molecular subtypes and analyses their diagnostic efficacy for UC and predictive performance for drug therapy. The relevant conclusions were verified by clinical samples and animal experiments. Four molecular subtypes were identified according to the ferroptosis and neutrophil gene sets: neutrophil, ferroptosis, mixed and quiescent. The subtypes have different biological characteristics and immune infiltration levels. Multiple machine learning methods jointly identified four hub genes (FTH1, AQP9, STEAP3 and STEAP4). Receiver operating characteristic (ROC) curve analysis revealed that the four hub genes could be used as diagnostic markers for UC. The clinical response profile data of infliximab treatment patients showed that AQP9 and STEPA4 were reliable predictors of infliximab treatment response. In human samples the AQP9 and STEAP4 protein were shown to be increased in UC intestinal samples. In animal experiments, the ferroptosis and neutrophil phenotype were confirmed. Dual analysis of ferroptosis and neutrophil gene expression revealed four subgroups of UC patients. The molecular subtype-associated hub genes can be used as diagnostic markers for UC and predict infliximab treatment response.

Trends in Non-Tuberculous Mycobacterial Lung Disease and Treatment Outcomes in a Low-Tuberculosis Prevalence Setting: A Retrospective Analysis.

BACKGROUND: Information on the management of non-tuberculous mycobacterial (NTM) lung infection and disease is scarce. The aim of this study was to investigate the trends in NTM lung infections, and the factors associated with the initiation of treatment and treatment outcomes. METHODS: A retrospective analysis was carried out on patient medical records from Haukeland University Hospital, Bergen, Norway, from 2000 to 2021. RESULTS: Among 154 patients with NTM lung infection, the majority (70%) were older than 65 years, and 49% had an underlying pulmonary comorbidity. The most frequently observed mycobacterial species was M. avium complex (MAC), followed by M. malmoense and M. abscessus. In total, 72 (47%) patients received antibiotic treatment. Patients with high symptom scores, aged below 65, and with MAC infection had more than three times the odds of receiving antibiotic treatment. A favourable response and culture conversion was observed in 53 of 72 (74%) patients. However, 17 (32%) of them had a relapse. Out of 82 patients who did not receive treatment, 45 (55%) had spontaneous culture conversion, and 8 (18%) of them had a relapse. No factor was identified to be significantly associated with a favourable treatment response. CONCLUSION: A favourable response to treatment was seen in 74% of patients with a high relapse rate.

Using total adenosine triphosphate (tATP) measurements for cyanobacterial bloom monitoring and response assessment during algaecide treatments.

Total adenosine triphosphate (tATP) was investigated for its potential as a rapid indicator of cyanobacterial growth and algaecide effectiveness. tATP and other common bloom monitoring parameters were measured over the growth cycles of cyanobacteria and green algae in laboratory cultures and examined at a drinking water source during an active bloom. Strong correlations (R2>0.78) were observed between tATP and chlorophyll-a in cyanobacteria cultures. tATP offered greater sensitivity by increasing two orders of magnitude approximately 7 d before changes in chlorophyll-a or optical density were observed in Lyngbya sp. and Dolichospermum sp. cultures. Increases in tATP per cell coincided with the onset of exponential growth phases in lab cultures and increase in cell abundance in field samples, suggesting that ATP/cell is a sensitive indicator that may be used to identify the development of blooms. Bench-scale trials using samples harvested during a bloom showed that tATP exhibited a clear dose-response during copper sulfate (CuSO4) and hydrogen peroxide (H2O2) treatment compared to chlorophyll-a and cell counts, indicating that cellular production and storage of ATP decreases even when live and dead cells cannot be distinguished. During Copper (Cu) algaecide application at a reservoir used as a drinking water source, tATP and cell counts decreased following initial algaecide application; however, the bloom rebounded within 10 d showing that the Cu algaecide only has limited effectiveness. In this case, tATP was a sensitive indicator to bloom rebounding after algaecide treatments and correlated positively with cell counts (R2=0.7). These results support the use of tATP as a valuable complementary bloom monitoring tool for drinking water utilities to implement during the monitoring and treatment of cyanobacterial blooms.

Effect of CYP2C19 polymorphism on response to bortezomib-based therapy in multiple myeloma patients.

BACKGROUND: Bortezomib, a commonly used anti-myeloma drug, is metabolized by liver microsomal enzymes which may be polymorphic and responsible for lack of response in 30% patients. Hence, the association of CYP2C19 polymorphism with treatment response was explored in this study. METHODS: Treatment naive multiple myeloma (MM) patients, eligible for bortezomib-based induction treatment, were recruited as per the inclusion - exclusion criteria. The genotyping of CYP2C19 was done using polymerase chain reaction-restriction fragment length polymorphism for *2, *3 and *17 alleles. The incidence and severity of peripheral neuropathy were noted at follow-up visits and graded as per CTCAE criteria ver 5.0. RESULTS: Total 220 patients were recruited from August 2016 till May 2021; with a mean age of 55.6 (9.5) years and 65.9% males. Bortezomib+cyclophosphamide+dexamethasone (41.8%) and bortezomib+lenalidomide+dexamethasone (38.2%) were the most prescribed regimens. The CYP2C19 was polymorphic in 38.6%, 2.3% and 23.7% patients for *2, *3 and *17 allele respectively. There were 195 treatment responders and 25 non-responders, and CYP2C19*2 allele was different between responders and non-responders (p = 0.02). All extensive metabolisers (n = 54) were noted to be treatment responders. Peripheral neuropathy was reported by 23.2% patients. The frequency of peripheral neuropathy was somewhat lower in patients having either *2/*2 or *3/*3 allele pattern for CYP2C19 (p = 0.44). CONCLUSIONS: Polymorphism in CYP2C19 enzyme is likely to have an impact on bortezomib treatment response and peripheral neuropathy. The study suggests the role of pharmacogenetics in personalised treatment of MM.

Effectiveness of online group cognitive-behavior therapy for adolescents with obsessive-compulsive disorder: a pilot study.

OBJECTIVE: This study aims to evaluate the effectiveness of online group cognitive-behavioral therapy (GCBT) guided by the CAMALEO TOC manual in treating of adolescents with obsessive compulsive disorder (OCD). METHOD: A quasi-experimental study with a single group pre-posttest intervention. Over 12 weeks 11 adolescents aged 11 to 17 years with OCD received weekly online sessions of GCBT based on CAMALEO TOC manual. The Children's Yale-Brown Obsessive-Compulsive Scale was used to assess OCD symptoms severity, the Family accommodation scale for obsessive-compulsive disorder interviewer-rated for family accommodation, the Children's Depression Inventory to assess depression symptoms, the Revised Children's Manifest Anxiety Scale for anxiety, and the Multidimensional Student Life Satisfaction Scale to assess life satisfaction. RESULTS: OCD symptoms decreased significantly (d = -1.55). A strong effect size (d = -1.03) was also found for family accommodation. No significant difference in OCD symptoms and family accommodation scores were found when controlling for differences between being in psychotherapeutic treatment, medication use, or psychiatric comorbidities. There was also no evidence that the intervention was effective in reducing symptoms of depression, anxiety or improving quality of life. CONCLUSION: We demonstrate the feasibility of a short-term online GCBT as an effective treatment for adolescents with OCD.

Cholangiocarcinoma imaging: from diagnosis to response assessment.

Cholangiocarcinoma (CCA), a highly aggressive primary liver cancer arising from the bile duct epithelium, represents a substantial proportion of hepatobiliary malignancies, posing formidable challenges in diagnosis and treatment. Notably, the global incidence of intrahepatic CCA has seen a rise, necessitating a critical examination of diagnostic and management strategies, especially due to presence of close imaging mimics such as hepatocellular carcinoma (HCC) and combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA). Hence, it is imperative to understand the role of various imaging modalities such as ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), elucidating their strengths, and limitations in diagnostic precision and staging accuracy. Beyond conventional approaches, there is emerging significance of functional imaging tools including positron emission tomography (PET)-CT and diffusion-weighted (DW)-MRI, providing pivotal insights into diagnosis, therapeutic assessment, and prognostic evaluation. This comprehensive review explores the risk factors, classification, clinical features, and role of imaging in the holistic spectrum of diagnosis, staging, management, and restaging for CCA, hence serving as a valuable resource for radiologists evaluating CCA.

Predicting responses to omalizumab in antihistamine-refractory chronic urticaria: A real-world longitudinal study.

Background: Treating chronic urticaria (CU) that is unresponsive to H1-antihistamines (H1AHs) is challenging, and the real-world effectiveness of omalizumab remains unclear. Objective: Our aim was to evaluate the real-world effectiveness of omalizumab, optimal response assessment timing, and predictive factors. Methods: Initially, 5535 patients with CU who were receiving at least 20 mg of loratadine daily for at least 6 months (January 2007-August 2021) were screened. Ultimately, 386 patients who had been receiving omalizumab add-on treatment for >6 months were followed-up for more than 2 years. Predictors of treatment response to omalizumab add-on therapy for patients with antihistamine-refractory CU were identified by using a generalized linear model. Results: In our retrospective cohort, omalizumab treatment showed cumulative response rates of 55.2% at 3 months, 71.0% at 6 months, and 81.4% at 9 months for patients with H1AH-refractory CU. Analysis of longitudinal responses to omalizumab treatment revealed 3 distinct clusters: favorable (cluster 1 [n = 158]), intermediate (cluster 2 [n =1 43]), and poor responses (cluster 3 [n = 85]). Subjects were categorized on the basis of whether they had achieved a complete response within 3 months; 213 early responders, 117 late responders, and 56 nonresponders were identified. The initial dose of omalizumab differed significantly among the 3 clusters. Low total IgE level (<40 kU/L) predicted nonresponse (odds ratio [OR] = 3.10 [P = .018]). Early responders were associated with a higher initial omalizumab dose (≥300 mg) (OR = 2.07 [P = .016]), higher basophil counts (OR = 2.0 [P = .014]), total IgE levels exceeding 798 kU/L (OR = 0.37 [P = .047]), and lower platelet-to-lymphocyte ratio (OR = 0.50 [P = .050]). Conclusion: Real-world data reveal 3 distinct clusters for response to omalizumab treatment; confirm low serum total IgE level (<40 kU/L) as a predictor of nonresponse; and identify potential biomarkers, including IgE level, basophil count, and PLR, for early responders.

Circumventing drug resistance in gastric cancer: A spatial multi-omics exploration of chemo and immuno-therapeutic response dynamics.

BACKGROUND: Gastric Cancer (GC) characteristically exhibits heterogeneous responses to treatment, particularly in relation to immuno plus chemo therapy, necessitating a precision medicine approach. This study is centered around delineating the cellular and molecular underpinnings of drug resistance in this context. METHODS: We undertook a comprehensive multi-omics exploration of postoperative tissues from GC patients undergoing the chemo and immuno-treatment regimen. Concurrently, an image deep learning model was developed to predict treatment responsiveness. RESULTS: Our initial findings associate apical membrane cells with resistance to fluorouracil and oxaliplatin, critical constituents of the therapy. Further investigation into this cell population shed light on substantial interactions with resident macrophages, underscoring the role of intercellular communication in shaping treatment resistance. Subsequent ligand-receptor analysis unveiled specific molecular dialogues, most notably TGFB1-HSPB1 and LTF-S100A14, offering insights into potential signaling pathways implicated in resistance. Our SVM model, incorporating these multi-omics and spatial data, demonstrated significant predictive power, with AUC values of 0.93 and 0.84 in the exploration and validation cohorts respectively. Hence, our results underscore the utility of multi-omics and spatial data in modeling treatment response. CONCLUSION: Our integrative approach, amalgamating mIHC assays, feature extraction, and machine learning, successfully unraveled the complex cellular interplay underlying drug resistance. This robust predictive model may serve as a valuable tool for personalizing therapeutic strategies and enhancing treatment outcomes in gastric cancer.

Inflammatory and subtype-dependent serum protein signatures predict survival beyond the ctDNA in aggressive B cell lymphomas.

BACKGROUND: Biological heterogeneity of large B cell lymphomas (LBCLs) is poorly captured by current prognostic tools, hampering optimal treatment decisions. METHODS: We dissected the levels of 1,463 serum proteins in a uniformly treated trial cohort of 109 patients with high-risk primary LBCL (ClinicalTrials.gov: NCT01325194) and correlated the profiles with molecular data from tumor tissue and circulating tumor DNA (ctDNA) together with clinical data. FINDINGS: We discovered clinically and biologically relevant associations beyond established clinical estimates and ctDNA. We identified an inflamed serum protein profile, which reflected host response to lymphoma, associated with inflamed and exhausted tumor microenvironment features and high ctDNA burden, and translated to poor outcome. We composed an inflammation score based on the identified inflammatory proteins and used the score to predict survival in an independent LBCL trial cohort (ClinicalTrials.gov: NCT03293173). Furthermore, joint analyses with ctDNA uncovered multiple serum proteins that correlate with tumor burden. We found that SERPINA9, TACI, and TARC complement minimally invasive subtype profiling and that TACI and TARC can be used to evaluate treatment response in a subtype-dependent manner in the liquid biopsy. CONCLUSIONS: Altogether, we discovered distinct serum protein landscapes that dissect the heterogeneity of LBCLs and provide agile, minimally invasive tools for precision oncology. FUNDING: This research was funded by grants from the Research Council of Finland, Finnish Cancer Organizations, Sigrid Juselius Foundation, University of Helsinki, iCAN Digital Precision Cancer Medicine Flagship, Orion Research Foundation sr, and Helsinki University Hospital.

Stratified Patient Profiling for Vedolizumab Effectiveness in Crohn's Disease: Identifying Optimal Subgroups for Enhanced Treatment Response in the EVOLVE Study.

INTRODUCTION: This analysis evaluated the relative performance of vedolizumab and anti-tumor necrosis factor alpha (anti-TNFα) agents in subpopulations of biologic therapy-naive patients with Crohn's disease (CD) and assessed whether patients in whom vedolizumab would have a larger treatment effect vs anti-TNFα agents could be identified. METHODS: Data were from EVOLVE, a real-world, multicountry, retrospective cohort study of patients with inflammatory bowel disease who initiated first-line biologic treatment with vedolizumab (n = 195) or anti-TNFα agents (n = 245). Prediction models for time to clinical remission were developed in vedolizumab- and anti-TNFα-treated patients and used to estimate effect scores, a metric of predicted comparative efficacy, for each patient. Patients were ranked by effect scores and potential subpopulations were investigated. Simplified rules to identify these subpopulations were also developed using classification tree analysis. RESULTS: Among all patients, median time to clinical remission was 7.8 months (vedolizumab) and 11.1 months (anti-TNFα) (P < 0.05). Among patients in the top 40% of the effect score distribution, the median time to clinical remission was 4.8 months (vedolizumab) vs 18.1 months (anti-TNFα) (adjusted hazard ratio 2.0, 95% confidence interval 1.3-2.9). A simplified rule for identifying a subpopulation more likely to benefit from vedolizumab was based on having an ongoing CD exacerbation, no prior emergency visits, and non-stricturing disease. CONCLUSIONS: Subpopulations of biologic-naive patients with CD in whom vedolizumab appeared to have a larger effect relative to anti-TNFα agents for the outcome of clinical remission were identified. Validation of the identified subpopulations and simplified rules are warranted to confirm these findings. GOV IDENTIFIER: NCT03710486. Graphical Abstract available for this article.

Leveraging DNA methylation to predict treatment response in major depressive disorder: A critical review.

Major depressive disorder (MDD) is a debilitating and prevalent mental disorder with a high disease burden. Despite a wide array of different treatment options, many patients do not respond to initial treatment attempts. Selection of the most appropriate treatment remains a significant clinical challenge in psychiatry, highlighting the need for the development of biomarkers with predictive utility. Recently, the epigenetic modification DNA methylation (DNAm) has emerged to be of great interest as a potential predictor of MDD treatment outcomes. Here, we review efforts to date that seek to identify DNAm signatures associated with treatment response in individuals with MDD. Searches were conducted in the databases PubMed, Scopus, and Web of Science with the concepts and keywords MDD, DNAm, antidepressants, psychotherapy, cognitive behavior therapy, electroconvulsive therapy, transcranial magnetic stimulation, and brain stimulation therapies. We identified 32 studies implicating DNAm patterns associated with MDD treatment outcomes. The majority of studies (N = 25) are focused on selected target genes exploring treatment outcomes in pharmacological treatments (N = 22) with a few studies assessing treatment response to electroconvulsive therapy (N = 3). Additionally, there are few genome-scale efforts (N = 7) to characterize DNAm patterns associated with treatment outcomes. There is a relative dearth of studies investigating DNAm patterns in relation to psychotherapy, electroconvulsive therapy, or transcranial magnetic stimulation; importantly, most existing studies have limited sample sizes. Given the heterogeneity in both methods and results of studies to date, there is a need for additional studies before existing findings can inform clinical decisions.

Predictors of treatment response in lymphogenic metastasized papillary thyroid cancer: a histopathological study.

BACKGROUND: Lymph node metastases in papillary thyroid cancer (PTC) increase the risk for persistent and recurrent disease. Data on the predictive value of histopathological features of lymph node metastases, however, are inconsistent. The aim of this study was to evaluate the prognostic significance of known and new histopathological features of lymph node metastases in a well-defined cohort of PTC patients with clinically evident lymph node metastases. METHODS: A total of 1042 lymph node metastases, derived from 129 PTC patients, were re-examined according to a predefined protocol and evaluated for diameter, extranodal extension, cystic changes, necrosis, calcifications and the proportion of the lymph node taken up by tumor cells. Predictors for a failure to achieve a complete biochemical and structural response to treatment were determined. RESULTS: The presence of more than 5 lymph node metastases was the only independent predictor for a failure to achieve a complete response to treatment (OR 3.39 [95% CI 1.57-7.33], p < 0.05). Diameter nor any of the other evaluated lymph node features were significantly associated with the response to treatment. CONCLUSIONS: Detailed re-examination of lymph nodes revealed that only the presence of more than 5 lymph node metastases was an independent predictor of failure to achieve a complete response to treatment. No predictive value was found for other histopathological features, including the diameter of the lymph node metastases. These findings have the potential to improve risk stratification in patients with PTC and clinically evident lymph node metastases.

Utility of clinical and MR imaging parameters for prediction and monitoring of response to capecitabine and temozolomide (CAPTEM) therapy in patients with liver metastases of neuroendocrine tumors.

BACKGROUND: This study explores the predictive and monitoring capabilities of clinical and multiparametric MR parameters in assessing capecitabine and temozolomide (CAPTEM) therapy response in patients with neuroendocrine tumors (NET). PATIENTS AND METHODS: This retrospective study (n = 44) assessed CAPTEM therapy response in neuroendocrine liver metastases (NELM) patients. Among 33 monitored patients, as a subgroup of the overall study cohort, pretherapeutic and follow-up MRI data (size, apparent diffusion coefficient [ADC] values, and signal intensities), along with clinical parameters (chromogranin A [CgA] and Ki-67%), were analyzed. Progression-free survival (PFS) served as the reference. Responders were defined as those with PFS ≥ 6 months. RESULTS: Most patients were male (75%) and had G2 tumors (76%) with a pancreatic origin (84%). Median PFS was 5.7 months; Overall Survival (OS) was 25 months. Non-responders (NR) had higher Ki-67 in primary tumors (16.5 vs. 10%, p = 0.01) and increased hepatic burden (20% vs. 5%, p = 0.007). NR showed elevated CgA post-treatment, while responders (R) exhibited a mild decrease. ADC changes differed significantly between groups, with NR having decreased ADCmin (-23%) and liver-adjusted ADCmean/ADCmean liver (-16%), compared to R's increases of ADCmin (50%) and ADCmean/ADCmean liver (30%). Receiver operating characteristic (ROC) analysis identified the highest area under the curve (AUC) (0.76) for a single parameter for ∆ ADC mean/liver ADCmean, with a cut-off of < 6.9 (76% sensitivity, 75% specificity). Combining ∆ Size NELM and ∆ ADCmin achieved the best balance (88% sensitivity, 60% specificity) outperforming ∆ Size NELM alone (69% sensitivity, 65% specificity). Kaplan-Meier analysis indicated significantly longer PFS for ∆ ADCmean/ADCmean liver < 6.9 (p = 0.024) and ∆ Size NELM > 0% + ∆ ADCmin < -2.9% (p = 0.021). CONCLUSIONS: Survival analysis emphasizes the need for adapted response criteria, involving combined evaluation of CgA, ADC values, and tumor size for monitoring CAPTEM response in hepatic metastasized NETs.

Same-day post-therapy imaging with a new generation whole-body digital SPECT/CT in assessing treatment response to [177Lu]Lu-PSMA-617 in metastatic castration-resistant prostate cancer.

PURPOSE: Lutetium-177 [177Lu]Lu-PSMA-617 radioligand therapy (RLT) represents a significant advancement for metastatic castration-resistant prostate cancer (mCRPC), demonstrating improvements in radiographic progression free survival (rPFS) and overall survival (OS) with a low rate of associated side effects. Currently, most post-therapy SPECT/CT is conducted at 24 h after infusion. This study examines the clinical utility of a next-generation multi-detector Cadmium-Zinc-Telluride (CZT) SPECT/CT system (StarGuide) in same-day post-infusion assessment and early treatment response to [177Lu]Lu-PSMA-617. METHODS: In this retrospective study, 68 men with progressive mCRPC treated with [177Lu]Lu-PSMA-617 at our center from June 2022 to June 2023 were evaluated. Digital whole-body SPECT/CT imaging was performed after [177Lu]Lu-PSMA-617infusion (mean ± SD: 1.8 ± 0.6 h, range 1.1-4.9 h). Quantitative analysis of [177Lu]Lu-PSMA-617 positive lesions was performed in patients who underwent at least 2 post-therapy SPECT/CT, using liver parenchyma uptake as reference. Metrics including [177Lu]Lu-PSMA-617 positive total tumor volume (Lu-TTV), SUVmax and SUVmean were calculated. These quantitative metrics on post-infusion SPECT/CT images after cycles 1, 2 and 3 were correlated with overall survival (OS), prostate specific antigen-progression free survival (PSA-PFS) as defined by prostate cancer working group 3 (PCWG3), and PSA decrease over 50% (PSA50) response rates. RESULTS: 56 patients (means age 76.2 ± 8.1 years, range: 60-93) who underwent at least 2 post-therapy SPECT/CT were included in the image analysis. The whole-body SPECT/CT scans (~ 12 min per scan) were well tolerated, with 221 same-day scans performed (89%). At a median of 10-months follow-up, 33 (58.9%) patients achieved PSA50 after [177Lu]Lu-PSMA-617 treatment and median PSA-PFS was 5.0 months (range: 1.0-15 months) while median OS was not reached. Quantitative analysis of SPECT/CT images showed that 37 patients (66%) had > 30% reduction in Lu-TTV, associated with significantly improved overall survival (median not reached vs. 6 months, P = 0.008) and PSA-PFS (median 6 months vs. 1 months, P < 0.001). However, changes in SUVmax or SUVmean did not correlate with PSA-PFS or OS. CONCLUSION: We successfully implemented same-day post-therapy SPECT/CT after [177Lu]Lu-PSMA-617 infusions. Quantitation of 1-2 h post-therapy SPECT/CT images is a promising method for assessing treatment response. However, the approach is currently limited by its suboptimal detection of small tumor lesions and the necessity of incorporating a third-cycle SPECT/CT to mitigate the effects of any potential treatment-related flare-up. Further investigation in a larger patient cohort and prospective validation is essential to confirm these findings and to explore the role of SPECT/CT as a potential adjunct to PSMA PET/CT in managing mCRPC.

Machine learning and optical coherence tomography-derived radiomics analysis to predict persistent diabetic macular edema in patients undergoing anti-VEGF intravitreal therapy.

BACKGROUND: Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. This study aimed to develop and evaluate an OCT-omics prediction model for assessing anti-vascular endothelial growth factor (VEGF) treatment response in patients with DME. METHODS: A retrospective analysis of 113 eyes from 82 patients with DME was conducted. Comprehensive feature engineering was applied to clinical and optical coherence tomography (OCT) data. Logistic regression, support vector machine (SVM), and backpropagation neural network (BPNN) classifiers were trained using a training set of 79 eyes, and evaluated on a test set of 34 eyes. Clinical implications of the OCT-omics prediction model were assessed by decision curve analysis. Performance metrics (sensitivity, specificity, F1 score, and AUC) were calculated. RESULTS: The logistic, SVM, and BPNN classifiers demonstrated robust discriminative abilities in both the training and test sets. In the training set, the logistic classifier achieved a sensitivity of 0.904, specificity of 0.741, F1 score of 0.887, and AUC of 0.910. The SVM classifier showed a sensitivity of 0.923, specificity of 0.667, F1 score of 0.881, and AUC of 0.897. The BPNN classifier exhibited a sensitivity of 0.962, specificity of 0.926, F1 score of 0.962, and AUC of 0.982. Similar discriminative capabilities were maintained in the test set. The OCT-omics scores were significantly higher in the non-persistent DME group than in the persistent DME group (p < 0.001). OCT-omics scores were also positively correlated with the rate of decline in central subfield thickness after treatment (Pearson's R = 0.44, p < 0.001). CONCLUSION: The developed OCT-omics model accurately assesses anti-VEGF treatment response in DME patients. The model's robust performance and clinical implications highlight its utility as a non-invasive tool for personalized treatment prediction and retinal pathology assessment.

One size does not fit all: notable individual variation in brain activity correlates of antidepressant treatment response.

Introduction: To date, no robust electroencephalography (EEG) markers of antidepressant treatment response have been identified. Variable findings may arise from the use of group analyses, which neglect individual variation. Using a combination of group and single-participant analyses, we explored individual variability in EEG characteristics of treatment response. Methods: Resting-state EEG data and Montgomery-Åsberg Depression Rating Scale (MADRS) symptom scores were collected from 43 patients with depression before, at 1 and 12 weeks of pharmacotherapy. Partial least squares (PLS) was used to: 1) identify group differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between eventual medication responders and non-responders, and 2) determine whether group patterns could be identified in individual patients. Results: Responders showed decreased alpha and increased beta connectivity, and early, widespread decreases in complexity over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in complexity. Thus, as in previous studies, our group analyses identified significant differences between groups of patients with different treatment outcomes. These group-level EEG characteristics were only identified in ~40-60% of individual patients, as assessed quantitatively by correlating the spatiotemporal brain patterns between groups and individual results, and by independent raters through visualization. Discussion: Our single-participant analyses suggest that substantial individual variation exists, and needs to be considered when investigating characteristics of antidepressant treatment response for potential clinical applicability. Clinical trial registration: https://clinicaltrials.gov, identifier NCT00519428.

Relating pre-treatment non-Gaussian intravoxel incoherent motion diffusion-weighted imaging to human papillomavirus status and response in oropharyngeal carcinoma.

Background and purpose: Diffusion-weighted imaging (DWI) is a promising technique for response assessment in head-and-neck cancer. Recently, we optimized Non-Gaussian Intravoxel Incoherent Motion Imaging (NG-IVIM), an extension of the conventional apparent diffusion coefficient (ADC) model, for the head and neck. In the current study, we describe the first application in a group of patients with human papillomavirus (HPV)-positive and HPV-negative oropharyngeal squamous cell carcinoma. The aim of this study was to relate ADC and NG-IVIM DWI parameters to HPV status and clinical treatment response. Materials and methods: Thirty-six patients (18 HPV-positive, 18 HPV-negative) were prospectively included. Presence of progressive disease was scored within one year. The mean pre-treatment ADC and NG-IVIM parameters in the gross tumor volume were compared between HPV-positive and HPV-negative patients. In HPV-negative patients, ADC and NG-IVIM parameters were compared between patients with and without progressive disease. Results: ADC, the NG-IVIM diffusion coefficient D, and perfusion fraction f were significantly higher, while pseudo-diffusion coefficient D* and kurtosis K were significantly lower in the HPV-negative compared to HPV-positive patients. In the HPV-negative group, a significantly lower D was found for patients with progressive disease compared to complete responders. No relation with ADC was observed. Conclusion: The results of our single-center study suggest that ADC is related to HPV status, but not an independent response predictor. The NG-IVIM parameter D, however, was independently associated to response in the HPV-negative group. Noteworthy in the opposite direction as previously thought based on ADC.

An update on the use of antihistamines in managing chronic urticaria.

INTRODUCTION: Urticaria, a mast cell-mediated skin disease, manifests as acute or chronic, with the latter divided into spontaneous and inducible types and requires individualized management, including identifying triggers and comorbidities. Antihistamines, particularly the second generation group, form the mainstay of primary treatment plans consisting of dosage adjustments and/or in combination with other treatment modalities depending on underlying disease control. AREAS COVERED: A literature search was conducted using 'antihistamines,' 'urticaria,' 'pharmacogenomics,' 'genomics,' 'biomarkers' and 'treatment response' as key words. In this review, we focus on the comprehensive understanding and application of antihistamines in managing adult and adolescent patients with chronic urticaria. EXPERT OPINION: Using antihistamines to treat urticaria is set to change significantly, focusing more on personalized medicine and identifying key biomarkers to enhance treatment response prediction. These changes aim to make treatments more specific and cost-effective by avoiding unnecessary tests. Applying new approaches in everyday clinical care faces challenges like proving the biomarkers' reliability, updating current guidelines, and incorporating individualized treatments into standard procedures. Efforts should now concentrate on finding easy-to-use biomarkers, improving access to pharmacogenomics, understanding why some patients are resistant to treatment, and creating more specific treatment options based on patient needs.

Measurement of metabolite levels and treatment-induced changes in hepatic metastases of gastro-esophageal cancer using 7-T phosphorus magnetic resonance spectroscopic imaging.

Methods for early treatment response evaluation to systemic therapy of liver metastases are lacking. Tumor tissue often exhibits an increased ratio of phosphomonoesters to phosphodiesters (PME/PDE), which can be noninvasively measured by phosphorus magnetic resonance spectroscopy (31P MRS), and may be a marker for early therapy response assessment in liver metastases. However, with commonly used 31P surface coils for liver 31P MRS, the liver is not fully covered, and metastases may be missed. The objective of this study was to demonstrate the feasibility of 31P MRS imaging (31P MRSI) with full liver coverage to assess 31P metabolite levels and chemotherapy-induced changes in liver metastases of gastro-esophageal cancer, using a 31P whole-body birdcage transmit coil in combination with a 31P body receive array at 7 T. 3D 31P MRSI data were acquired in two patients with hepatic metastases of esophageal cancer, before the start of chemotherapy and after 2 (and 9 in patient 2) weeks of chemotherapy. 3D 31P MRSI acquisitions were performed using an integrated 31P whole-body transmit coil in combination with a 16-channel body receive array at 7 T, with a field of view covering the full abdomen and a nominal voxel size of 20-mm isotropic. From the 31P MRSI data, 12 31P metabolite signals were quantified. Prior to chemotherapy initiation, both PMEs, that is, phosphocholine (PC) and phosphoethanolamine (PE), were significantly higher in all metastases compared with the levels previously determined in the liver of healthy volunteers. After 2 weeks of chemotherapy, PC and PE levels remained high or even increased further, resulting in increased PME/PDE ratios compared with healthy liver tissue, in correspondence with the clinical assessment of progressive disease after 2 months of chemotherapy. The suggested approach may present a viable tool for early therapy (non)response assessment of tumor metabolism in patients with liver metastases.