Citations

Background This study investigated the efficacy of ChatGPT-3.5 and ChatGPT-4 in assessing drug safety for patients with kidney diseases, comparing their performance to Micromedex, a well-established drug information source. Despite the perception of non-prescription medications and supplements as safe, risks exist, especially for those with kidney issues. The study's goal was to evaluate ChatGPT's versions for their potential in clinical decision-making regarding kidney disease patients. Method The research involved analyzing 124 common non-prescription medications and supplements using ChatGPT-3.5 and ChatGPT-4 with queries about their safety for people with kidney disease. The AI responses were categorized as “generally safe,” “potentially harmful,” or “unknown toxicity.” Simultaneously, these medications and supplements were assessed in Micromedex using similar categories, allowing for a comparison of the concordance between the two resources. Results Micromedex identified 85 (68.5%) medications as generally safe, 35 (28.2%) as potentially harmful, and 4 (3.2%) of unknown toxicity. ChatGPT-3.5 identified 89 (71.8%) as generally safe, 11 (8.9%) as potentially harmful, and 24 (19.3%) of unknown toxicity. GPT-4 identified 82 (66.1%) as generally safe, 29 (23.4%) as potentially harmful, and 13 (10.5%) of unknown toxicity. The overall agreement between Micromedex and ChatGPT-3.5 was 64.5% and ChatGPT-4 demonstrated a higher agreement at 81.4%. Notably, ChatGPT-3.5's suboptimal performance was primarily influenced by a lower concordance rate among supplements, standing at 60.3%. This discrepancy could be attributed to the limited data on supplements within ChatGPT-3.5, with supplements constituting 80% of medications identified as unknown. Conclusion ChatGPT's capabilities in evaluating the safety of non-prescription drugs and supplements for kidney disease patients are modest compared to established drug information resources. Neither ChatGPT-3.5 nor ChatGPT-4 can be currently recommended as reliable drug information sources for this demographic. The results highlight the need for further improvements in the model's accuracy and reliability in the medical domain.

Abstract Objectives ChatGPT (OpenAI, San Francisco, CA) has shown impressive results across various medical examinations, but its performance in kidney pathology is not yet established. This study evaluated proficiencies of GPT-4 Vision (GPT-4V), an updated version of the platform with the ability to analyze images, on kidney pathology questions and compared its responses with those of nephrology trainees. Methods Thirty-nine questions (19 text-based questions and 20 with various kidney biopsy images) designed specifically for the training of nephrology fellows were employed. Results GPT-4V displayed comparable accuracy rates in the first and second runs (67% and 72%, respectively, P = .50). The aggregated accuracy, however—particularly, the consistent accuracy—of GPT-4V was lower than that of trainees (72% and 67% vs 79%). Both GPT-4V and trainees displayed comparable accuracy in responding to image-based and text-only questions (55% vs 79% and 81% vs 78%, P = .11 and P = .67, respectively). The consistent accuracy in image-based, directly asked questions for GPT-4V was 29%, much lower than its 88% consistency on text-only, directly asked questions (P = .02). In contrast, trainees maintained similar accuracy in directly asked image-based and text-based questions (80% vs 77%, P = .65). Although the aggregated accuracy for correctly interpreting images was 69%, the consistent accuracy across both runs was only 39%. The accuracy of GPT-4V in answering questions with correct image interpretation was significantly higher than for questions with incorrect image interpretation (100% vs 0% and 100% vs 33% for the first and second runs, P = .001 and P = .02, respectively). Conclusions The performance of GPT-4V in handling kidney pathology questions, especially those including images, is limited. There is a notable need for enhancement in GPT-4V proficiency in interpreting images.

Abstract Background The purpose of this study was to interrogate brain iron accumulation in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI), and to determine if functional connectivity is affected in areas with iron accumulation. We aimed to examine the correlations between iron accumulation and headache frequency, post-concussion symptom severity, number of mTBIs and time since most recent TBI. Methods Sixty participants with acute PTH and 60 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging including quantitative T2* maps and resting-state functional connectivity imaging. Between group T2* differences were determined using T-tests (p < 0.005, cluster size threshold of 10 voxels). For regions with T2* differences, two analyses were conducted. First, the correlations with clinical variables including headache frequency, number of lifetime mTBIs, time since most recent mTBI, and Sport Concussion Assessment Tool (SCAT) symptom severity scale scores were investigated using linear regression. Second, the functional connectivity of these regions with the rest of the brain was examined (significance of p < 0.05 with family wise error correction for multiple comparisons). Results The acute PTH group consisted of 60 participants (22 male, 38 female) with average age of 42 ± 14 years. The HC group consisted of 60 age-matched controls (17 male, 43 female, average age of 42 ± 13). PTH participants had lower T2* values compared to HC in the left posterior cingulate and the bilateral cuneus. Stronger functional connectivity was observed between bilateral cuneus and right cerebellar areas in PTH compared to HC. Within the PTH group, linear regression showed negative associations of T2* and SCAT symptom severity score in the left posterior cingulate (p = 0.05) and with headache frequency in the left cuneus (p = 0.04). Conclusions Iron accumulation in posterior cingulate and cuneus was observed in those with acute PTH relative to HC; stronger functional connectivity was detected between the bilateral cuneus and the right cerebellum. The correlations of decreased T2* (suggesting higher iron content) with headache frequency and post mTBI symptom severity suggest that the iron accumulation that results from mTBI might reflect the severity of underlying mTBI pathophysiology and associate with post-mTBI symptom severity including PTH.

Abstract Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient. We propose to predictively fuse Magnetic Resonance Imaging (MRI) with the underlying intratumoral heterogeneity in recurrent GBM using machine learning (ML) by leveraging image-localized biopsies with their associated locoregional MRI features. To this end, we develop BioNet, a biologically-informed neural network model, to predict regional distributions of three tissue-specific gene modules: proliferating tumor, reactive/inflammatory cells, and infiltrated brain tissue. BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to describe in mathematical formulations. BioNet performs significantly better than a range of existing methods on cross-validation and blind test datasets. Voxel-level prediction maps of the gene modules by BioNet help reveal intratumoral heterogeneity, which can improve surgical targeting of confirmatory biopsies and evaluation of neuro-oncological treatment effectiveness. The non-invasive nature of the approach can potentially facilitate regular monitoring of the gene modules over time, and making timely therapeutic adjustment. These results also highlight the emerging role of ML in precision medicine.

Abstract Recycling of parental histones is an important step in epigenetic inheritance. During DNA replication, DNA polymerase epsilon subunit DPB3/DPB4 and DNA replication helicase subunit MCM2 are involved in the transfer of parental histones to the leading and lagging strands, respectively. Single Dpb3 deletion (dpb3Δ) or Mcm2 mutation (mcm2-3A), which each disrupts one parental histone transfer pathway, leads to the other's predominance. However, the biological impact of the two histone transfer pathways on chromatin structure and DNA repair remains elusive. In this study, we used budding yeast Saccharomyces cerevisiae to determine the genetic and epigenetic outcomes from disruption of parental histone H3–H4 tetramer transfer. We found that a dpb3Δ mcm2-3A double mutant did not exhibit the asymmetric parental histone patterns caused by a single dpb3Δ or mcm2-3A mutation, suggesting that the processes by which parental histones are transferred to the leading and lagging strands are independent. Surprisingly, the frequency of homologous recombination was significantly lower in dpb3Δ, mcm2-3A and dpb3Δ mcm2-3A mutants, likely due to the elevated levels of free histones detected in the mutant cells. Together, these findings indicate that proper transfer of parental histones during DNA replication is essential for maintaining chromatin structure and that lower homologous recombination activity due to parental histone transfer defects is detrimental to cells.

Abstract Background This study aimed to determine whether proton craniospinal irradiation (CSI) decreased the dose to normal tissue and resulted in less toxicity than photon CSI for adult patients. Methods This single-institution retrospective analyzed differences in radiation doses, acute toxicity, and cost between proton and CSI for adult medulloblastoma patients. Results Of 39 total patients, 20 were treated with photon CSI prior to 2015, and 19 were treated with proton CSI thereafter. Median age was 28 years (range 18–66). The molecular subtype was most commonly sonic hedgehog (68%). Patients most commonly received 36 Gy CSI in 20 fractions with a boost to 54–55.8 Gy (92%). Proton CSI delivered significantly lower mean doses to cochleae, lacrimal glands, lens, parotid glands, pharyngeal constrictors, esophagus, lungs, liver, and skin (all P &lt; .001). Patients receiving proton CSI had significantly lower rates of acute dysphagia of any grade (5% versus 35%, P = .044) and decreased median weight loss during radiation (+1.0 versus –2.8 kg, P = .011). Weight loss was associated with acute hospitalization (P = .009). Median follow-up was 2.9 and 12.9 years for proton and photon patients, respectively, limiting late toxicity and outcome comparisons. At the last follow-up, 5 photon patients had died (2 of progressive disease, 3 without recurrence ages 41–63) and 21% had experienced major cardiovascular events. At 10 years, 89% were alive and 82% were recurrence free. Conclusions This study demonstrates dosimetric improvements with proton CSI, potentially leading to decreased acute toxicity including dysphagia and weight loss during treatment.