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Eyal Klang,1– 3,&ast; Shelly Soffer,3– 5,&ast; Yiftach Barash,1– 3 Eyal Shachar,2,6 Adi Lahat2,6 1Department of Diagnostic Imaging, Sheba Medical Center, Ramat Gan, Israel; 2Sackler Medical School, Tel Aviv University, Tel Aviv, Israel; 3DeepVision Lab, Sheba Medical Center, Ramat Gan, Israel; 4Internal Medicine B, Samson Assuta Ashdod University Hospital, Ashdod, Israel; 5Ben-Gurion University of the Negev, Be’er Sheva, Israel; 6Department of Gastroenterology, Sheba Medical Center, Ramat Gan, Israel&ast;These authors contributed equally to this workCorrespondence: Shelly Soffer, Internal Medicine B, Samson Assuta Ashdod University Hospital, Ha-Refu’a St 7, Ashdod, 7747629, Israel, Tel +973-8-300-4100, Fax +972-3-5357315, Email soffer.shelly@gmail.comBackground: Since the discovery of Helicobacter pylori (H. pylori) 40 years ago, treatment options have changed dramatically adjacent to new drugs development and the emergence of multi-drug resistance. In this study, we aimed to assess published literature on treatment regimens for H. pylori in the past four decades, with regards to specific drug resistance and geographic distribution.Methods: We have queried PubMed for all available H. pylori-related entries published during 1987– 2020. For each entry, we retrieved the title, abstract, and keywords. Two gastrointestinal specialists decided in consensus on a list of terms to classify entries. The terms specify types of treatment and different types of regimens. Annual trends of publications were plotted for different treatment types and sub-analyses.Results: Overall, 47,170 H. pylori-related entries were published between 1987 and 2020. Medication treatment showed the highest number of total publications 6183/47,170 (13.1%), followed by antibiotics 5493/47,170 (11.6%), and probiotic which was substantially lower (0.7%). For treatment regimens type, triple therapy had the highest number of publications 2400/47,170 (5.1%) followed by sequential therapy 342/47,170 (0.7%), and bismuth quadruple therapy 115/47,170 (0.2%). Analysis by antibiotic resistance showed that clarithromycin treatment had the highest number of publications 3537/47,170 (7.5%). Since 2013, there is a steep upward slope (5.1± 0.7 publications/year, p < 0.001) for publications originating from China.Conclusion: Our findings reflect the changes of the commonly prescribed regimens along the years, following the occurrence and the rise of H. pylori antibiotic resistance. In recent years, there is a steep rise in publications in countries with policies of screening and eradication for gastric cancer prevention, which is currently not applied in Western countries. A text-mining analysis of H. pylori publications contributes to the understanding of treatment options and development trends worldwide.Keywords: Helicobacter pylori, antibiotics, treatment regimens, antibiotic resistance

Background: Empathy, a fundamental aspect of human interaction, is characterized as the ability to experience another being's emotions within oneself. In health care, empathy is a fundamental for health care professionals and patients' interaction. It is a unique quality to humans that large language models (LLMs) are believed to lack., Objective: We aimed to review the literature on the capacity of LLMs in demonstrating empathy., Methods: We conducted a literature search on MEDLINE, Google Scholar, PsyArXiv, medRxiv, and arXiv between December 2022 and February 2024. We included English-language full-length publications that evaluated empathy in LLMs' outputs. We excluded papers evaluating other topics related to emotional intelligence that were not specifically empathy. The included studies' results, including the LLMs used, performance in empathy tasks, and limitations of the models, along with studies' metadata were summarized., Results: A total of 12 studies published in 2023 met the inclusion criteria. ChatGPT-3.5 (OpenAI) was evaluated in all studies, with 6 studies comparing it with other LLMs such GPT-4, LLaMA (Meta), and fine-tuned chatbots. Seven studies focused on empathy within a medical context. The studies reported LLMs to exhibit elements of empathy, including emotions recognition and emotional support in diverse contexts. Evaluation metric included automatic metrics such as Recall-Oriented Understudy for Gisting Evaluation and Bilingual Evaluation Understudy, and human subjective evaluation. Some studies compared performance on empathy with humans, while others compared between different models. In some cases, LLMs were observed to outperform humans in empathy-related tasks. For example, ChatGPT-3.5 was evaluated for its responses to patients' questions from social media, where ChatGPT's responses were preferred over those of humans in 78.6% of cases. Other studies used subjective readers' assigned scores. One study reported a mean empathy score of 1.84-1.9 (scale 0-2) for their fine-tuned LLM, while a different study evaluating ChatGPT-based chatbots reported a mean human rating of 3.43 out of 4 for empathetic responses. Other evaluations were based on the level of the emotional awareness scale, which was reported to be higher for ChatGPT-3.5 than for humans. Another study evaluated ChatGPT and GPT-4 on soft-skills questions in the United States Medical Licensing Examination, where GPT-4 answered 90% of questions correctly. Limitations were noted, including repetitive use of empathic phrases, difficulty following initial instructions, overly lengthy responses, sensitivity to prompts, and overall subjective evaluation metrics influenced by the evaluator's background., Conclusions: LLMs exhibit elements of cognitive empathy, recognizing emotions and providing emotionally supportive responses in various contexts. Since social skills are an integral part of intelligence, these advancements bring LLMs closer to human-like interactions and expand their potential use in applications requiring emotional intelligence. However, there remains room for improvement in both the performance of these models and the evaluation strategies used for assessing soft skills., (©Vera Sorin, Dana Brin, Yiftach Barash, Eli Konen, Alexander Charney, Girish Nadkarni, Eyal Klang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.12.2024.)

Purpose: While mammography is considered the gold standard for screening women for breast cancer, its accuracy declines in women with dense breasts. The purpose of the study is to evaluate the diagnostic accuracy of contrast enhanced mammography (CEM) for detecting breast cancer in intermediate and high-risk women, including those with genetic predispositions, over a decade-long cohort at a tertiary center., Methods: We retrospectively analyzed all CEM examinations performed for screening purposes at a tertiary center between 2012 and 2023. Data were extracted from imaging reports and from medical records. All biopsies performed up to one year following CEM examinations, and all breast cancer cases were extracted. BI-RADS scores from CEM reports were compared to biopsy results and to imaging follow-up. Sensitivity, specificity, positive and negative predictive values, area under the ROC curve (AUC), and cumulative cancer detection rate were calculated., Results: Overall 5,424 screening CEM examinations were analyzed. The mean age was 54.8 ± 8.9 years. Family history of breast cancer was recorded in 1,134/5,424 (20.9 %) women. Most women (4,606/5,424, 84.9 %) had dense breasts (BI-RADS C-D). Overall, 628 biopsies were performed within one year of screening, and 74 cancers were detected. CEM had sensitivity 95.9 % (71/74), specificity 81.8 % (4378/5350), positive predictive value 6.8 % (71/1043), negative predictive value 99.9 % (4378/4381). The cancer detection rate for CEM was 13.1 per 1,000 cases, and the AUC was 0.923., Conclusions: CEM is a viable breast cancer screening method for women with dense breasts. Future prospective studies are needed to evaluate the long-term prognostic impact of CEM screening., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: In BRCA germline pathogenic sequence variants (PSV) carriers aged 30-39 years imaging is recommended at six-month intervals. The European society for medical oncology recommendation of the use of 6-monthly MRI six-monthly MRI screening is being considered at our institution, particularly for younger carriers under the age of 35, although it is not mandatory. If 6-monthly MRI is unavailable, annual MRI may be supplemented by ultrasound (with or without mammography). The aim of this study was to evaluate the utility of ultrasound screening added to mammography, as a 6-month supplement to annual MRI in BRCA PSV carriers aged 30-39 years., Materials and Methods: This IRB approved retrospective study included BRCA PSV carriers aged 30-39 years, who underwent breast cancer screening at our institution between January 2015 and March 2023. Participants were divided into two groups, those who had supplemental whole-breast US and mammography at six months and underwent screening before March 2019, and those who had only mammography without supplemental US and enrolled in screening after March 2019. Patient characteristics, cancer detection rates and cancer characteristics were compared between the two groups., Results: Overall, 200 asymptomatic BRCA1/2 PSV carriers undergoing screening in our institution were included in the study. Mean age was 35.7 ± 3.5 years, and mean follow-up time was 37.4 ± 38.0 months. There were 118 (59 %) women screened with supplemental US, and 82 (41 %) women without. Eight cancers were diagnosed during the study period, four in women with supplemental US and four in women without. The sensitivity of whole-breast screening US was 25 % (1/4), specificity 85.7 % (222/259), PPV 2.6 % (1/38), and NPV 98.7 % (222/225). Of the four cancers detected in women screened with supplemental US, one was diagnosed by whole-breast US, two by MRI, and one by mammography. Of eight cancers included in this study, two were not detectable by targeted second-look US. All eight cancers were detectable by MRI., Conclusion: The addition of whole-breast ultrasound to mammography and MRI screening in BRCA PSV carriers aged 30-39 years offered limited incremental benefit. MRI with 6 months supplemental mammography without US detected all cancer cases., Competing Interests: Declaration of competing interest All authors declare none., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: To evaluate tibial single access in treatment of chronic total occlusions (CTO) in patients with ipsilateral chronic-limb ischemia (CLTI)., Materials and Methods: In this retrospective study, data was collected on patients treated for ipsilateral CTO via a tibial artery access between March 2017 and March 2021. Fifty-nine limbs in 57 patients, (42 men, average age 73 years; range 47-96) were treated. Patient's symptoms were classified in accordance with the Rutherford category. The end points were freedom from major amputation and the need for reintervention up to 1 year of follow up., Results: Out of the 59 treated limbs, technical success was achieved in 57 (97%). The treated multilevel segments involved 5 common and 12 external iliac arteries, 23 common and 37 superficial femoral arteries, 23 femoropopliteal segments, 14 popliteal arteries, and 4 bypasses. Mean length of occlusion was 186 mm (range 7-670). Rutherford classification of the treated limbs was category 5 and 6 in 45 patients and category 4 in 14 patients. Three procedural complications occurred and were successfully treated during the same procedure. No immediate post-procedural complication was encountered. Median follow-up was 13 months (range 1-45.3). Reintervention was required in 9 limbs, after an average of 6 months. One year free from amputation rate was 91.2%., Conclusions: Single access via the ipsilateral tibial artery can be a useful, effective, and safe approach for treating CTO in CLTI patients., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Aim: To evaluate the accuracy of the Emergency Severity Index (ESI) assignments by GPT-4, a large language model (LLM), compared to senior emergency department (ED) nurses and physicians., Method: An observational study of 100 consecutive adult ED patients was conducted. ESI scores assigned by GPT-4, triage nurses, and by a senior clinician. Both model and human experts were provided the same patient data., Results: GPT-4 assigned a lower median ESI score (2.0) compared to human evaluators (median 3.0; p < 0.001), suggesting a potential overestimation of patient severity by the LLM. The results showed differences in the triage assessment approaches between GPT-4 and the human evaluators, including variations in how patient age and vital signs were considered in the ESI assignments., Conclusion: While GPT-4 offers a novel methodology for patient triage, its propensity to overestimate patient severity highlights the necessity for further development and calibration of LLM tools in clinical environments. The findings underscore the potential and limitations of LLM in clinical decision-making, advocating for cautious integration of LLMs in healthcare settings., Reporting Method: This study adhered to relevant EQUATOR guidelines for reporting observational studies., (© 2024 The Author(s). Journal of Clinical Nursing published by John Wiley & Sons Ltd.)

Mapping transcriptomic variations using either short- or long-read RNA sequencing is a staple of genomic research. Long reads are able to capture entire isoforms and overcome repetitive regions, whereas short reads still provide improved coverage and error rates. Yet, open questions remain, such as how to quantitatively compare the technologies, can we combine them, and what is the benefit of such a combined view? We tackle these questions by first creating a pipeline to assess matched long- and short-read data using a variety of transcriptome statistics. We find that across data sets, algorithms, and technologies, matched short-read data detects ∼30% more splice junctions, such that ∼10%-30% of the splice junctions included at ≥20% by short reads are missed by long reads. In contrast, long reads detect many more intron-retention events and can detect full isoforms, pointing to the benefit of combining the technologies. We introduce MAJIQ-L, an extension of the MAJIQ software, to enable a unified view of transcriptome variations from both technologies and demonstrate its benefits. Our software can be used to assess any future long-read technology or algorithm and can be combined with short-read data for improved transcriptome analysis., (© 2024 Han et al.; Published by Cold Spring Harbor Laboratory Press.)

Relapsed or refractory B-cell acute lymphoblastic leukemia (B-ALL) is a major cause of pediatric cancer-related deaths. Relapse-specific mutations do not account for all chemotherapy failures in B-ALL patients, suggesting additional mechanisms of resistance. By mining RNA sequencing datasets of paired diagnostic/relapse pediatric B-ALL samples, we discovered pervasive alternative splicing (AS) patterns linked to relapse and affecting drivers of resistance to glucocorticoids, antifolates, and thiopurines. Most splicing variations represented cassette exon skipping, "poison" exon inclusion, and intron retention, phenocopying well-documented loss-of-function mutations. In contrast, relapse-associated AS of NT5C2 mRNA yielded an isoform with the functionally uncharacterized in-frame exon 6a. Incorporation of the 8-amino acid sequence SQVAVQKR into this enzyme created a putative phosphorylation site and resulted in elevated nucleosidase activity, which is a known consequence of gain-of-function mutations in NT5C2 and a common determinant of 6-mercaptopurine resistance. Consistent with this finding, NT5C2ex6a and the R238W hotspot variant conferred comparable levels of resistance to 6-mercaptopurine in B-ALL cells both in vitro and in vivo. Furthermore, both NT5C2ex6a and the R238W variant induced collateral sensitivity to the inosine monophosphate dehydrogenase inhibitor mizoribine. These results ascribe to splicing perturbations an important role in chemotherapy resistance in relapsed B-ALL and suggest that inosine monophosphate dehydrogenase inhibitors, including the commonly used immunosuppressive agent mycophenolate mofetil, could be a valuable therapeutic option for treating thiopurine-resistant leukemias. Significance: Alternative splicing is a potent mechanism of acquired drug resistance in relapsed/refractory acute lymphoblastic leukemias that has diagnostic and therapeutic implications for patients who lack mutations in known chemoresistance genes., (©2024 The Authors; Published by the American Association for Cancer Research.)

Previously, we showed that the germ cell-specific nuclear protein RBMXL2 represses cryptic splicing patterns during meiosis and is required for male fertility (Ehrmann et al., 2019). Here, we show that in somatic cells the similar yet ubiquitously expressed RBMX protein has similar functions. RBMX regulates a distinct class of exons that exceed the median human exon size. RBMX protein-RNA interactions are enriched within ultra-long exons, particularly within genes involved in genome stability, and repress the selection of cryptic splice sites that would compromise gene function. The RBMX gene is silenced during male meiosis due to sex chromosome inactivation. To test whether RBMXL2 might replace the function of RBMX during meiosis we induced expression of RBMXL2 and the more distantly related RBMY protein in somatic cells, finding each could rescue aberrant patterns of RNA processing caused by RBMX depletion. The C-terminal disordered domain of RBMXL2 is sufficient to rescue proper splicing control after RBMX depletion. Our data indicate that RBMX and RBMXL2 have parallel roles in somatic tissues and the germline that must have been conserved for at least 200 million years of mammalian evolution. We propose RBMX family proteins are particularly important for the splicing inclusion of some ultra-long exons with increased intrinsic susceptibility to cryptic splice site selection., Competing Interests: CS, SL, SA, GH, CD, KC, MG, IY, KJ, MK, IE, GS, SC, JM, SW, YB, DE No competing interests declared, (© 2023, Siachisumo, Luzzi, Aldalaqan et al.)

Background: Differential diagnosis in radiology relies on the accurate identification of imaging patterns. The use of large language models (LLMs) in radiology holds promise, with many potential applications that may enhance the efficiency of radiologists' workflow. The study aimed to evaluate the efficacy of generative pre-trained transformer (GPT)-4, a LLM, in providing differential diagnoses in neuroradiology, comparing its performance with board-certified neuroradiologists., Methods: Sixty neuroradiology reports with variable diagnoses were inserted into GPT-4, which was tasked with generating a top-3 differential diagnosis for each case. The results were compared to the true diagnoses and to the differential diagnoses provided by three blinded neuroradiologists. Diagnostic accuracy and agreement between readers were assessed., Results: Of the 60 patients (mean age 47.8 years, 65% female), GPT-4 correctly included the diagnoses in its differentials in 61.7% (37/60) of cases, while the neuroradiologists' accuracy ranged from 63.3% (38/60) to 73.3% (44/60). Agreement between GPT-4 and the neuroradiologists, and among the neuroradiologists was fair to moderate [Cohen's kappa (kw) 0.34-0.44 and kw 0.39-0.54, respectively]., Conclusions: GPT-4 shows potential as a support tool for differential diagnosis in neuroradiology, though it was outperformed by human experts. Radiologists should remain mindful to the limitations of LLMs, while harboring their potential to enhance educational and clinical work., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-200/coif). The authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

RNA-sequencing (RNA-seq) is widely adopted for transcriptome analysis but has inherent biases which hinder the comprehensive detection and quantification of alternative splicing. To address this, we present an efficient targeted RNA-seq method that greatly enriches for splicing-informative junction-spanning reads. Local Splicing Variation sequencing (LSV-seq) utilizes multiplexed reverse transcription from highly scalable pools of primers anchored near splicing events of interest. Primers are designed using Optimal Prime, a novel machine learning algorithm trained on the performance of thousands of primer sequences. In experimental benchmarks, LSV-seq achieves high on-target capture rates and concordance with RNA-seq, while requiring significantly lower sequencing depth. Leveraging deep learning splicing code predictions, we used LSV-seq to target events with low coverage in GTEx RNA-seq data and newly discover hundreds of tissue-specific splicing events. Our results demonstrate the ability of LSV-seq to quantify splicing of events of interest at high-throughput and with exceptional sensitivity.

Genome-wide association studies (GWAS) have identified thousands of putative disease causing variants with unknown regulatory effects. Efforts to connect these variants with splicing quantitative trait loci (sQTLs) have provided functional insights, yet sQTLs reported by existing methods cannot explain many GWAS signals. We show current sQTL modeling approaches can be improved by considering alternative splicing representation, model calibration, and covariate integration. We then introduce MAJIQTL, a new pipeline for sQTL discovery. MAJIQTL includes two new statistical methods: a weighted multiple testing approach for sGene discovery and a model for sQTL effect size inference to improve variant prioritization. By applying MAJIQTL to GTEx, we find significantly more sGenes harboring sQTLs with functional significance. Notably, our analysis implicates the novel variant rs582283 in Alzheimer's disease. Using antisense oligonucleotides, we validate this variant's effect by blocking the implicated YBX3 binding site, leading to exon skipping in the gene MS4A3., Competing Interests: Competing Interests: The authors declare that they have no competing interests.

Background and Objective: Acute myelogenous leukemia (AML) is a common blood cancer marked by heterogeneity in disease and diverse genetic abnormalities. Additional therapies are needed as the 5-year survival remains below 30%. Trametinib is a mitogen-activated extracellular signal-regulated kinase (MEK) inhibitor that is widely used in solid tumors and also in tumors with activating RAS mutations. A subset of patients with AML carry activating RAS mutations; however, a small-scale clinical trial with trametinib showed little efficacy. Here, we sought to identify transcriptomic determinants of trametinib sensitivity in AML., Methods: We tested the activity of trametinib against a panel of tumor cells from patients with AML ex vivo and compared this with RNA sequencing (RNA-Seq) data from untreated blasts from the same patient samples. We then used a correlation analysis between gene expression and trametinib sensitivity to identify potential biomarkers predictive of drug response., Results: We found that a subset of AML tumor cells were sensitive to trametinib ex vivo, only a fraction of which (3/10) carried RAS mutations. On the basis of our RNA-Seq analysis we found that markers of trametinib sensitivity are associated with a myeloid differentiation profile that includes high expression of CD14 and CLEC7A (Dectin-1), similar to the gene expression profile of monocytes. Further characterization confirmed that trametinib-sensitive samples display features of monocytic differentiation with high CD14 surface expression and were enriched for the M4 subtypes of the FAB classification., Conclusions: Our study identifies additional molecular markers that can be used with molecular features including RAS status to identify patients with AML that may benefit from trametinib treatment., (© 2024. The Author(s).)

Objectives: This study aims to assess the performance of a multimodal artificial intelligence (AI) model capable of analyzing both images and textual data (GPT-4V), in interpreting radiological images. It focuses on a range of modalities, anatomical regions, and pathologies to explore the potential of zero-shot generative AI in enhancing diagnostic processes in radiology., Methods: We analyzed 230 anonymized emergency room diagnostic images, consecutively collected over 1 week, using GPT-4V. Modalities included ultrasound (US), computerized tomography (CT), and X-ray images. The interpretations provided by GPT-4V were then compared with those of senior radiologists. This comparison aimed to evaluate the accuracy of GPT-4V in recognizing the imaging modality, anatomical region, and pathology present in the images., Results: GPT-4V identified the imaging modality correctly in 100% of cases (221/221), the anatomical region in 87.1% (189/217), and the pathology in 35.2% (76/216). However, the model's performance varied significantly across different modalities, with anatomical region identification accuracy ranging from 60.9% (39/64) in US images to 97% (98/101) and 100% (52/52) in CT and X-ray images (p < 0.001). Similarly, pathology identification ranged from 9.1% (6/66) in US images to 36.4% (36/99) in CT and 66.7% (34/51) in X-ray images (p < 0.001). These variations indicate inconsistencies in GPT-4V's ability to interpret radiological images accurately., Conclusion: While the integration of AI in radiology, exemplified by multimodal GPT-4, offers promising avenues for diagnostic enhancement, the current capabilities of GPT-4V are not yet reliable for interpreting radiological images. This study underscores the necessity for ongoing development to achieve dependable performance in radiology diagnostics., Clinical Relevance Statement: Although GPT-4V shows promise in radiological image interpretation, its high diagnostic hallucination rate (> 40%) indicates it cannot be trusted for clinical use as a standalone tool. Improvements are necessary to enhance its reliability and ensure patient safety., Key Points: GPT-4V's capability in analyzing images offers new clinical possibilities in radiology. GPT-4V excels in identifying imaging modalities but demonstrates inconsistent anatomy and pathology detection. Ongoing AI advancements are necessary to enhance diagnostic reliability in radiological applications., (© 2024. The Author(s).)

Large language models (LLMs) are transforming the field of natural language processing (NLP). These models offer opportunities for radiologists to make a meaningful impact in their field. NLP is a part of artificial intelligence (AI) that uses computer algorithms to study and understand text data. Recent advances in NLP include the Attention mechanism and the Transformer architecture. Transformer-based LLMs, such as GPT-4 and Gemini, are trained on massive amounts of data and generate human-like text. They are ideal for analysing large text data in academic research and clinical practice in radiology. Despite their promise, LLMs have limitations, including their dependency on the diversity and quality of their training data and the potential for false outputs. Albeit these limitations, the use of LLMs in radiology holds promise and is gaining momentum. By embracing the potential of LLMs, radiologists can gain valuable insights and improve the efficiency of their work. This can ultimately lead to improved patient care., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology.)

Background: Traumatic knee injuries are challenging to diagnose accurately through radiography and to a lesser extent, through CT, with fractures sometimes overlooked. Ancillary signs like joint effusion or lipo-hemarthrosis are indicative of fractures, suggesting the need for further imaging. Artificial Intelligence (AI) can automate image analysis, improving diagnostic accuracy and help prioritizing clinically important X-ray or CT studies., Objective: To develop and evaluate an AI algorithm for detecting effusion of any kind in knee X-rays and selected CT images and distinguishing between simple effusion and lipo-hemarthrosis indicative of intra-articular fractures., Methods: This retrospective study analyzed post traumatic knee imaging from January 2016 to February 2023, categorizing images into lipo-hemarthrosis, simple effusion, or normal. It utilized the FishNet-150 algorithm for image classification, with class activation maps highlighting decision-influential regions. The AI's diagnostic accuracy was validated against a gold standard, based on the evaluations made by a radiologist with at least four years of experience., Results: Analysis included CT images from 515 patients and X-rays from 637 post traumatic patients, identifying lipo-hemarthrosis, simple effusion, and normal findings. The AI showed an AUC of 0.81 for detecting any effusion, 0.78 for simple effusion, and 0.83 for lipo-hemarthrosis in X-rays; and 0.89, 0.89, and 0.91, respectively, in CTs., Conclusion: The AI algorithm effectively detects knee effusion and differentiates between simple effusion and lipo-hemarthrosis in post-traumatic patients for both X-rays and selected CT images further studies are needed to validate these results., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding., Methods: Angiographic images were retrospectively collected from mesenteric and celiac artery embolization procedures performed between 2018 and 2022. This dataset included images showing both active bleeding and non-bleeding phases from the same patients. The images were labeled as normal versus images that contain active bleeding. A convolutional neural network was trained and validated to automatically classify the images. Algorithm performance was tested in terms of area under the curve, accuracy, sensitivity, specificity, F1 score, positive and negative predictive value., Results: The dataset included 587 pre-labeled images from 142 patients. Of these, 302 were labeled as normal angiogram and 285 as containing active bleeding. The model's performance on the validation cohort was area under the curve 85.0 ± 10.9% (standard deviation) and average classification accuracy 77.43 ± 4.9%. For Youden's index cutoff, sensitivity and specificity were 85.4 ± 9.4% and 81.2 ± 8.6%, respectively., Conclusion: In this study, we explored the application of AI in mesenteric and celiac artery angiography for detecting active bleeding. The results of this study show the potential of an AI-based algorithm to accurately classify images with active bleeding. Further studies using a larger dataset are needed to improve accuracy and allow segmentation of the bleeding., (© 2024. The Author(s).)

Background and Aims: Artificial Intelligence (AI) models like GPT-3.5 and GPT-4 have shown promise across various domains but remain underexplored in healthcare. Emergency Departments (ED) rely on established scoring systems, such as NIHSS and HEART score, to guide clinical decision-making. This study aims to evaluate the proficiency of GPT-3.5 and GPT-4 against experienced ED physicians in calculating five commonly used medical scores., Methods: This retrospective study analyzed data from 150 patients who visited the ED over one week. Both AI models and two human physicians were tasked with calculating scores for NIH Stroke Scale, Canadian Syncope Risk Score, Alvarado Score for Acute Appendicitis, Canadian CT Head Rule, and HEART Score. Cohen's Kappa statistic and AUC values were used to assess inter-rater agreement and predictive performance, respectively., Results: The highest level of agreement was observed between the human physicians (Kappa = 0.681), while GPT-4 also showed moderate to substantial agreement with them (Kappa values of 0.473 and 0.576). GPT-3.5 had the lowest agreement with human scorers. These results highlight the superior predictive performance of human expertise over the currently available automated systems for this specific medical outcome. Human physicians achieved a higher ROC-AUC on 3 of the 5 scores, but none of the differences were statistically significant., Conclusions: While AI models demonstrated some level of concordance with human expertise, they fell short in emulating the complex clinical judgments that physicians make. The study suggests that current AI models may serve as supplementary tools but are not ready to replace human expertise in high-stakes settings like the ED. Further research is needed to explore the capabilities and limitations of AI in emergency medicine., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: Despite advanced technologies in breast cancer management, challenges remain in efficiently interpreting vast clinical data for patient-specific insights. We reviewed the literature on how large language models (LLMs) such as ChatGPT might offer solutions in this field., Methods: We searched MEDLINE for relevant studies published before December 22, 2023. Keywords included: "large language models", "LLM", "GPT", "ChatGPT", "OpenAI", and "breast". The risk bias was evaluated using the QUADAS-2 tool., Results: Six studies evaluating either ChatGPT-3.5 or GPT-4, met our inclusion criteria. They explored clinical notes analysis, guideline-based question-answering, and patient management recommendations. Accuracy varied between studies, ranging from 50 to 98%. Higher accuracy was seen in structured tasks like information retrieval. Half of the studies used real patient data, adding practical clinical value. Challenges included inconsistent accuracy, dependency on the way questions are posed (prompt-dependency), and in some cases, missing critical clinical information., Conclusion: LLMs hold potential in breast cancer care, especially in textual information extraction and guideline-driven clinical question-answering. Yet, their inconsistent accuracy underscores the need for careful validation of these models, and the importance of ongoing supervision., (© 2024. The Author(s).)

Introduction: The field of vestibular science, encompassing the study of the vestibular system and associated disorders, has experienced notable growth and evolving trends over the past five decades. Here, we explore the changing landscape in vestibular science, focusing on epidemiology, peripheral pathologies, diagnosis methods, treatment, and technological advancements., Methods: Publication data was obtained from the US National Center for Biotechnology Information (NCBI) PubMed database. The analysis included epidemiological, etiological, diagnostic, and treatment-focused studies on peripheral vestibular disorders, with a particular emphasis on changes in topics and trends of publications over time., Results: Our dataset of 39,238 publications revealed a rising trend in research across all age groups. Etiologically, benign paroxysmal positional vertigo (BPPV) and Meniere's disease were the most researched conditions, but the prevalence of studies on vestibular migraine showed a marked increase in recent years. Electronystagmography (ENG)/ Videonystagmography (VNG) and Vestibular Evoked Myogenic Potential (VEMP) were the most commonly discussed diagnostic tools, while physiotherapy stood out as the primary treatment modality., Conclusion: Our study presents a unique opportunity and point of view, exploring the evolving landscape of vestibular science publications over the past five decades. The analysis underscored the dynamic nature of the field, highlighting shifts in focus and emerging publication trends in diagnosis and treatment over time., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wolfovitz, Gecel, Gimmon, Shivatzki, Sorin, Barash, Klang and Tessler.)

This study's aim is to describe the imaging findings in pregnant patients undergoing emergent MRI for suspected acute appendicitis, and the various alternative diagnoses seen on those MRI scans. This is a single center retrospective analysis in which we assessed the imaging, clinical and pathological data for all consecutive pregnant patients who underwent emergent MRI for suspected acute appendicitis between April 2013 and June 2021. Out of 167 patients, 35 patients (20.9%) were diagnosed with acute appendicitis on MRI. Thirty patients (18%) were diagnosed with an alternative diagnosis on MRI: 17/30 (56.7%) patients had a gynecological source of abdominal pain (e.g. ectopic pregnancy, red degeneration of a leiomyoma); 8 patients (26.7%) had urological findings such as pyelonephritis; and 6 patients (20%) had gastrointestinal diagnoses (e.g. abdominal wall hernia or inflammatory bowel disease). Our conclusions are that MRI is a good diagnostic tool in the pregnant patient, not only in diagnosing acute appendicitis, but also in providing information on alternative diagnoses to acute abdominal pain. Our findings show the various differential diagnoses on emergent MRI in pregnant patients with suspected acute appendicitis, which may assist clinicians and radiologists is patient assessment and imaging utilization., Competing Interests: The authors have declared no competing interest exist., (Copyright: © 2024 Bufman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Advancements in artificial intelligence (AI) and natural language processing (NLP) have led to the development of language models such as ChatGPT. These models have the potential to transform healthcare and medical research. However, understanding their applications and limitations is essential., Objectives: To present a view of ChatGPT research and to critically assess ChatGPT's role in medical writing and clinical environments., Methods: We performed a literature review via the PubMed search engine from 20 November 2022, to 23 April 2023. The search terms included ChatGPT, OpenAI, and large language models. We included studies that focused on ChatGPT, explored its use or implications in medicine, and were original research articles. The selected studies were analyzed considering study design, NLP tasks, main findings, and limitations., Results: Our study included 27 articles that examined ChatGPT's performance in various tasks and medical fields. These studies covered knowledge assessment, writing, and analysis tasks. While ChatGPT was found to be useful in tasks such as generating research ideas, aiding clinical reasoning, and streamlining workflows, limitations were also identified. These limitations included inaccuracies, inconsistencies, fictitious information, and limited knowledge, highlighting the need for further improvements., Conclusions: The review underscores ChatGPT's potential in various medical applications. Yet, it also points to limitations that require careful human oversight and responsible use to improve patient care, education, and decision-making.

Quantification of RNA splicing variations based on RNA-Sequencing can reveal tissue- and disease-specific splicing patterns. To study such splicing variations, we introduce MAJIQlopedia, an encyclopedia of splicing variations that encompasses 86 human tissues and 41 cancer datasets. MAJIQlopedia reports annotated and unannotated splicing events for a total of 486 175 alternative splice junctions in normal tissues and 338 317 alternative splice junctions in cancer. This database, available at https://majiq.biociphers.org/majiqlopedia/, includes a user-friendly interface that provides graphical representations of junction usage quantification for each junction across all tissue or cancer types. To demonstrate case usage of MAJIQlopedia, we review splicing variations in genes WT1, MAPT and BIN1, which all have known tissue or cancer-specific splicing variations. We also use MAJIQlopedia to highlight novel splicing variations in FDX1 and MEGF9 in normal tissues, and we uncover a novel exon inclusion event in RPS6KA6 that only occurs in two cancer types. Users can download the database, request the addition of data to the webtool, or install a MAJIQlopedia server to integrate proprietary data. MAJIQlopedia can serve as a reference database for researchers seeking to understand what splicing variations exist in genes of interest, and those looking to understand tissue- or cancer-specific splice isoform usage., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: The impaired drainage of cerebrospinal fluid through the glymphatic system is thought to play a role in the idiopathic intracranial hypertension (IIH) pathophysiology. Limited data exist regarding the glymphatic system's involvement in pediatric patients with IIH. Therefore, the study's objective was to quantitatively evaluate alterations in parenchymal diffusivity and magnetic resonance imaging (MRI)-visible dilated perivascular spaces (PVS) as imaging indicators of glymphatic dysfunction in pediatric patients with IIH., Methods: Patients diagnosed with IIH in 2017-2022 in a single tertiary center (Sheba Medical Center, Israel) were retrospectively reviewed. Twenty-four pediatric patients were enrolled. All patients underwent clinical 3-T brain MRI. The control group included 24 age- and gender-matched healthy subjects with a normal-appearing brain on imaging. We used automatic atlas-based diffusion-weighted imaging analysis to determine regional diffusivity of the thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, and brain stem. PVS were evaluated using a semi-quantitative rating scale on T2-weighted images. Variables were compared using the Mann-Whitney test. Multivariate analysis of covariance was used to test for differences between controls and IIH patients., Results: No significant differences in regional brain diffusivity were observed between individuals with IIH and healthy controls (P=0.14-0.91 for various brain regions). The number of visible PVS was comparable between patients with IIH and the control group across all evaluated sites (P=0.12-0.74 for various brain regions)., Conclusions: Pediatric IIH patients exhibited similar patterns of parenchymal diffusivity and PVS compared to age-matched controls. These findings do not support the hypothesis that the glymphatic system may play a role in the pathophysiology of pediatric IIH, although previously postulated. However, employing more sophisticated magnetic resonance (MR) techniques could enhance the sensitivity in uncovering underlying glymphatic dysfunction. Further research is warranted to validate and explore this association in larger cohorts and investigate the underlying mechanisms involved in IIH., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-1043/coif). The authors have no conflicts of interest to declare., (2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

This study explores the potential of OpenAI's ChatGPT as a decision support tool for acute ulcerative colitis presentations in the setting of an emergency department. We assessed ChatGPT's performance in determining disease severity using TrueLove and Witts criteria and the necessity of hospitalization for patients with ulcerative colitis, comparing results with those of expert gastroenterologists. Of 20 cases, ChatGPT's assessments were found to be 80% consistent with gastroenterologist evaluations and indicated a high degree of reliability. This suggests that ChatGPT could provide as a clinical decision support tool in assessing acute ulcerative colitis, serving as an adjunct to clinical judgment., (Copyright © 2023 by The American College of Gastroenterology.)

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, limitations, and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for continuous extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies, while the containers and reproducible workflows could easily be deployed and extended to evaluate new methods or data sets., (© 2023 Bryce-Smith et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.)

Aberrant skipping of coding exons in CD19 and CD22 compromises the response to immunotherapy in B-cell malignancies. Here, we showed that the MS4A1 gene encoding human CD20 also produces several messenger RNA (mRNA) isoforms with distinct 5' untranslated regions. Four variants (V1-4) were detected using RNA sequencing (RNA-seq) at distinct stages of normal B-cell differentiation and B-lymphoid malignancies, with V1 and V3 being the most abundant. During B-cell activation and Epstein-Barr virus infection, redirection of splicing from V1 to V3 coincided with increased CD20 positivity. Similarly, in diffuse large B-cell lymphoma, only V3, but not V1, correlated with CD20 protein levels, suggesting that V1 might be translation-deficient. Indeed, the longer V1 isoform contained upstream open reading frames and a stem-loop structure, which cooperatively inhibited polysome recruitment. By modulating CD20 isoforms with splice-switching morpholino oligomers, we enhanced CD20 expression and anti-CD20 antibody rituximab-mediated cytotoxicity in a panel of B-cell lines. Furthermore, reconstitution of CD20-knockout cells with V3 mRNA led to the recovery of CD20 positivity, whereas V1-reconstituted cells had undetectable levels of CD20 protein. Surprisingly, in vitro CD20-directed chimeric antigen receptor T cells were able to kill both V3- and V1-expressing cells, but the bispecific T-cell engager mosunetuzumab was only effective against V3-expressing cells. To determine whether CD20 splicing is involved in immunotherapy resistance, we performed RNA-seq on 4 postmosunetuzumab follicular lymphoma relapses and discovered that in 2 of them, the downregulation of CD20 was accompanied by a V3-to-V1 shift. Thus, splicing-mediated mechanisms of epitope loss extend to CD20-directed immunotherapies., (© 2023 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Parkin is an E3 ubiquitin ligase, which plays a key role in the development of Parkinson disease. Parkin defects also occur in numerous cancers, and a growing body of evidence indicates that Parkin functions as a tumor suppressor that impedes a number of cellular processes involved in tumorigenesis. Here, we generated murine and human models that closely mimic the advanced-stage tumors where Parkin deficiencies are found to provide deeper insights into the tumor suppressive functions of Parkin. Loss of Parkin expression led to aggressive tumor growth, which was associated with poor tumor antigen presentation and limited antitumor CD8+ T-cell infiltration and activation. The effect of Parkin deficiency on tumor growth was lost following depletion of CD8+ T cells. In line with previous findings, Parkin deficiency was linked with mitochondria-associated metabolic stress, PTEN degradation, and enhanced Akt activation. Increased Akt signaling led to dysregulation of antigen presentation, and treatment with the Akt inhibitor MK2206-2HCl restored antigen presentation in Parkin-deficient tumors. Analysis of data from patients with clear cell renal cell carcinoma indicated that Parkin expression was downregulated in tumors and that low expression correlated with reduced overall survival. Furthermore, low Parkin expression correlated with reduced patient response to immunotherapy. Overall, these results identify a role for Parkin deficiency in promoting tumor immune evasion that may explain the poor prognosis associated with loss of Parkin across multiple types of cancer., Significance: Parkin prevents immune evasion by regulating tumor antigen processing and presentation through the PTEN/Akt network, which has important implications for immunotherapy treatments in patients with Parkin-deficient tumors., (©2023 The Authors; Published by the American Association for Cancer Research.)

Purpose: To describe a single-center experience in the treatment of chronic limb-threatening ischemia (CLTI) with the application of BeBack catheter (Bentley InnoMed, Germany) in patients with arterial chronic total occlusion (CTO)., Materials and Methods: A retrospective review of patients who underwent limb revascularizations using the BeBack catheter between 2015 and 2022. All patients had an initial failed attempt using a traditional guidewire and catheter technique. Technical success was considered whenever a successful re-entry or lesion crossing using the study device was achieved. Procedural success was defined as recanalization of the occluded artery with residual stenosis of less than 30%, and improvement in ankle-brachial index (ABI) after 24 hours. A Rutherford score was assigned to each limb and affected anatomical segments and lesion length were documented. Procedural access sites and complications were noted., Results: The study included 72 patients who underwent 78 procedures using the BeBack crossing catheter. Procedural success was achieved in 91% of cases, with a technical success rate of 92.3%. The most frequently involved occluded segments were the femoral and popliteal arteries. The average ABI improved from 0.59 to 0.95 after the procedure. The most used access site was the contralateral femoral, and the BeBack catheter was employed on 85 occasions. Only 1 patient suffered a severe immediate adverse effect, and during the 30-day follow-up period, 2 patients needed reintervention. Unfortunately, 3 patients died during the follow-up period., Conclusion: The BeBack catheter offers a viable option for the treatment of patients with chronic total occlusion, with high procedural success and a low complication rate., Clinical Impact: The BeBack catheter presents a notable advancement for clinicians managing chronic limb-threatening ischemia (CLTI) and arterial chronic total occlusion (CTO), showcasing over 90% procedural and technical success rates in this study. Its adept ability to navigate and recanalize occluded segments provides a robust alternative, especially when traditional techniques falter. This innovation may chane clinical strategies in vascular interventions, offering an efficient and reliable option, thereby potentially enhancing patient outcomes in limb revascularizations., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Purpose: The quality of radiology referrals influences patient management and imaging interpretation by radiologists. The aim of this study was to evaluate ChatGPT-4 as a decision support tool for selecting imaging examinations and generating radiology referrals in the emergency department (ED)., Methods: Five consecutive clinical notes from the ED were retrospectively extracted, for each of the following pathologies: pulmonary embolism, obstructing kidney stones, acute appendicitis, diverticulitis, small bowel obstruction, acute cholecystitis, acute hip fracture, and testicular torsion. A total of 40 cases were included. These notes were entered into ChatGPT-4, requesting recommendations on the most appropriate imaging examinations and protocols. The chatbot was also asked to generate radiology referrals. Two independent radiologists graded the referral on a scale ranging from 1 to 5 for clarity, clinical relevance, and differential diagnosis. The chatbot's imaging recommendations were compared with the ACR Appropriateness Criteria (AC) and with the examinations performed in the ED. Agreement between readers was assessed using linear weighted Cohen's κ coefficient., Results: ChatGPT-4's imaging recommendations aligned with the ACR AC and ED examinations in all cases. Protocol discrepancies between ChatGPT and the ACR AC were observed in two cases (5%). ChatGPT-4-generated referrals received mean scores of 4.6 and 4.8 for clarity, 4.5 and 4.4 for clinical relevance, and 4.9 from both reviewers for differential diagnosis. Agreement between readers was moderate for clinical relevance and clarity and substantial for differential diagnosis grading., Conclusions: ChatGPT-4 has shown potential in aiding imaging study selection for select clinical cases. As a complementary tool, large language models may improve radiology referral quality. Radiologists should stay informed about this technology and be mindful of potential challenges and risks., (Copyright © 2023 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Purpose: Abnormal fetal brain measurements might affect clinical management and parental counseling. The effect of between-field-strength differences was not evaluated in quantitative fetal brain imaging until now. Our study aimed to compare fetal brain biometry measurements in 3.0 T with 1.5 T scanners., Methods: A retrospective cohort of 1150 low-risk fetuses scanned between 2012 and 2021, with apparently normal brain anatomy, were retrospectively evaluated for biometric measurements. The cohort included 1.5 T (442 fetuses) and 3.0 T scans (708 fetuses) of populations with comparable characteristics in the same tertiary medical center. Manually measured biometry included bi-parietal, fronto-occipital and trans-cerebellar diameters, length of the corpus-callosum, vermis height, and width. Measurements were then converted to centiles based on previously reported biometric reference charts. The 1.5 T centiles were compared with the 3.0 T centiles., Results: No significant differences between centiles of bi-parietal diameter, trans-cerebellar diameter, or length of the corpus callosum between 1.5 T and 3.0 T scanners were found. Small absolute differences were found in the vermis height, with higher centiles in the 3.0 T, compared to the 1.5 T scanner (54.6th-centile, vs. 39.0th-centile, p < 0.001); less significant differences were found in vermis width centiles (46.9th-centile vs. 37.5th-centile, p = 0.03). Fronto-occipital diameter was higher in 1.5 T than in the 3.0 T scanner (66.0th-centile vs. 61.8th-centile, p = 0.02)., Conclusions: The increasing use of 3.0 T MRI for fetal imaging poses a potential bias when using 1.5 T-based charts. We elucidate those biometric measurements are comparable, with relatively small between-field-strength differences, when using manual biometric measurements. Small inter-magnet differences can be related to higher spatial resolution with 3 T scanners and may be substantial when evaluating small brain structures, such as the vermis., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: The growing application of deep learning in radiology has raised concerns about cybersecurity, particularly in relation to adversarial attacks. This study aims to systematically review the literature on adversarial attacks in radiology., Methods: We searched for studies on adversarial attacks in radiology published up to April 2023, using MEDLINE and Google Scholar databases., Results: A total of 22 studies published between March 2018 and April 2023 were included, primarily focused on image classification algorithms. Fourteen studies evaluated white-box attacks, three assessed black-box attacks and five investigated both. Eleven of the 22 studies targeted chest X-ray classification algorithms, while others involved chest CT (6/22), brain MRI (4/22), mammography (2/22), abdominal CT (1/22), hepatic US (1/22), and thyroid US (1/22). Some attacks proved highly effective, reducing the AUC of algorithm performance to 0 and achieving success rates up to 100 %., Conclusions: Adversarial attacks are a growing concern. Although currently the threats are more theoretical than practical, they still represent a potential risk. It is important to be alert to such attacks, reinforce cybersecurity measures, and influence the formulation of ethical and legal guidelines. This will ensure the safe use of deep learning technology in medicine., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Computerized tomography (CT) is an integral part of the follow-up and decision-making process in complicated acute appendicitis (AA) treated non-operatively. However, repeated CT scans are costly and cause radiation exposure. Ultrasound-tomographic image fusion is a novel tool that integrates CT images to an Ultrasound (US) machine, thus allowing accurate assessment of the healing process compared to CT on presentation. In this study, we aimed to assess the feasibility of US-CT fusion as part of the management of appendicitis., Materials and Methods: We retrospectively collected data of consecutive patients with complicated AA managed non-operatively and followed up with US Fusion for clinical decision-making. Patients demographics, clinical data, and follow-up outcomes were extracted and analyzed., Results: Overall, 19 patients were included. An index Fusion US was conducted in 13 patients (68.4%) during admission, while the rest were performed as part of an ambulatory follow-up. Nine patients (47.3%) had more than 1 US Fusion performed as part of their follow-up, and 3 patients underwent a third US Fusion. Eventually, 5 patients (26.3%) underwent elective interval appendectomy based on the outcomes of the US Fusion, due to a non-resolution of imaging findings and ongoing symptoms. In 10 patients (52.6%), there was no evidence of an abscess in the repeated US Fusion, while in 3 patients (15.8%), it significantly diminished to less than 1 cm in diameter., Conclusion: Ultrasound-tomographic image fusion is feasible and can play a significant role in the decision-making process for the management of complicated AA.

Neural crest (NC) is a unique vertebrate cell type arising from the border of the neural plate and epidermis that gives rise to diverse tissues along the entire body axis. Roberto Mayor and colleagues have made major contributions to our understanding of NC induction, delamination, and migration. We report that a truncating mutation of the classical tumor suppressor Adenomatous Polyposis Coli ( apc) disrupts craniofacial development in zebrafish larvae, with a marked reduction in the cranial neural crest (CNC) cells that contribute to mandibular and hyoid pharyngeal arches. While the mechanism is not yet clear, the altered expression of signaling molecules that guide CNC migration could underlie this phenotype. For example, apc mcr/mcr larvae express substantially higher levels of complement c3 , which Mayor and colleagues showed impairs CNC cell migration when overexpressed. However, we also observe reduction in stroma-derived factor 1 ( sdf1/cxcl12 ), which is required for CNC migration into the head. Consistent with our previous work showing that APC directly enhances the activity of glycogen synthase kinase 3 (GSK-3) and, independently, that GSK-3 phosphorylates multiple core mRNA splicing factors, we identify 340 mRNA splicing variations in apc mutant zebrafish, including a splice variant that deletes a conserved domain in semaphorin 3f ( sema3f ), an axonal guidance molecule and a known regulator of CNC migration. Here, we discuss potential roles for apc in CNC development in the context of some of the seminal findings of Mayor and colleagues.

Autonomous finite element analyses (AFE) based on CT scans predict the biomechanical response of femurs during stance and sidewise fall positions. We combine AFE with patient data via a machine learning (ML) algorithm to predict the risk of hip fracture. An opportunistic retrospective clinical study of CT scans is presented, aimed at developing a ML algorithm with AFE for hip fracture risk assessment in type 2 diabetic mellitus (T2DM) and non-T2DM patients. Abdominal/pelvis CT scans of patients who experienced a hip fracture within 2 years after an index CT scan were retrieved from a tertiary medical center database. A control group of patients without a known hip fracture for at least 5 years after an index CT scan was retrieved. Scans belonging to patients with/without T2DM were identified from coded diagnoses. All femurs underwent an AFE under three physiological loads. AFE results, patient's age, weight, and height were input to the ML algorithm (support vector machine [SVM]), trained by 80% of the known fracture outcomes, with cross-validation, and verified by the other 20%. In total, 45% of available abdominal/pelvic CT scans were appropriate for AFE (at least 1/4 of the proximal femur was visible in the scan). The AFE success rate in automatically analyzing CT scans was 91%: 836 femurs we successfully analyzed, and the results were processed by the SVM algorithm. A total of 282 T2DM femurs (118 intact and 164 fractured) and 554 non-T2DM (314 intact and 240 fractured) were identified. Among T2DM patients, the outcome was: Sensitivity 92%, Specificity 88% (cross-validation area under the curve [AUC] 0.92) and for the non-T2DM patients: Sensitivity 83%, Specificity 84% (cross-validation AUC 0.84). Combining AFE data with a ML algorithm provides an unprecedented prediction accuracy for the risk of hip fracture in T2DM and non-T2DM populations. The fully autonomous algorithm can be applied as an opportunistic process for hip fracture risk assessment. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR)., (© 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).)

Large language models (LLM) such as ChatGPT have gained public and scientific attention. The aim of this study is to evaluate ChatGPT as a support tool for breast tumor board decisions making. We inserted into ChatGPT-3.5 clinical information of ten consecutive patients presented in a breast tumor board in our institution. We asked the chatbot to recommend management. The results generated by ChatGPT were compared to the final recommendations of the tumor board. They were also graded independently by two senior radiologists. Grading scores were between 1-5 (1 = completely disagree, 5 = completely agree), and in three different categories: summarization, recommendation, and explanation. The mean age was 49.4, 8/10 (80%) of patients had invasive ductal carcinoma, one patient (1/10, 10%) had a ductal carcinoma in-situ and one patient (1/10, 10%) had a phyllodes tumor with atypia. In seven out of ten cases (70%), ChatGPT's recommendations were similar to the tumor board's decisions. Mean scores while grading the chatbot's summarization, recommendation and explanation by the first reviewer were 3.7, 4.3, and 4.6 respectively. Mean values for the second reviewer were 4.3, 4.0, and 4.3, respectively. In this proof-of-concept study, we present initial results on the use of an LLM as a decision support tool in a breast tumor board. Given the significant advancements, it is warranted for clinicians to be familiar with the potential benefits and harms of the technology., (© 2023. The Author(s).)

Pulmonary embolism (PE) is a common, life threatening cardiovascular emergency. Risk stratification is one of the core principles of acute PE management and determines the choice of diagnostic and therapeutic strategies. In routine clinical practice, clinicians rely on the patient's electronic health record (EHR) to provide a context for their medical imaging interpretation. Most deep learning models for radiology applications only consider pixel-value information without the clinical context. Only a few integrate both clinical and imaging data. In this work, we develop and compare multimodal fusion models that can utilize multimodal data by combining both volumetric pixel data and clinical patient data for automatic risk stratification of PE. Our best performing model is an intermediate fusion model that incorporates both bilinear attention and TabNet, and can be trained in an end-to-end manner. The results show that multimodality boosts performance by up to 14% with an area under the curve (AUC) of 0.96 for assessing PE severity, with a sensitivity of 90% and specificity of 94%, thus pointing to the value of using multimodal data to automatically assess PE severity., (© 2023. The Author(s).)

Noncanonical exon usage plays many important roles in cellular phenotypes, but its contribution to human B-cell development remains sketchily understood. To fill this gap, we collected various B-cell fractions from bone marrow (BM) and tonsil donors, performed RNA sequencing, and examined transcript variants. We identified 150 genes that harbor local splicing variations in all pairwise comparisons. One of them encodes FBXW7, an E3 ubiquitin ligase implicated as a driver in several blood cancers. Surprisingly, we discovered that in normal human pro-B cells, the predominant transcript used an alternative first exon to produce the poorly characterized FBXW7β isoform, previously thought to be restricted to neural tissues. The FBXW7β transcript was also abundant in cell lines and primary samples of pediatric B-cell acute lymphoblastic leukemia (B-ALL), which originates in the BM. When overexpressed in a heterologous cell system, this transcript yielded the expected protein product, as judged by anti-FLAG immunoblotting and mass spectrometry. Furthermore, in REH B-ALL cells, FBXW7β mRNA was the only FBXW7 isoform enriched in the polyribosome fraction. To shed light on possible functions of FBXW7β, we used gain- and loss-of-function approaches and identified an FBXW7-dependent inflammatory gene signature, apparent in a subset of B-ALL with high FBXW7β expression. This signature contained several members of the tumor necrosis factor superfamily, including those comprising the HLA Class III cluster (LTB, LST1, NCR3, LTA, and NFKBIL1). Our findings suggest that FBXW7β expression drives proinflammatory responses, which could contribute to normal B-cell development, leukemogenesis, and responses to anticancer therapies., (© 2023 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity. We describe here a suite of algorithms and tools implemented in the MAJIQ v2 package to address challenges in detection, quantification, and visualization of splicing variations from such datasets. Using both large scale synthetic data and GTEx v8 as benchmark datasets, we assess the advantages of MAJIQ v2 compared to existing methods. We then apply MAJIQ v2 package to analyze differential splicing across 2,335 samples from 13 brain subregions, demonstrating its ability to offer insights into brain subregion-specific splicing regulation., (© 2023. The Author(s).)

Background: The association between diverticular disease and atherosclerotic cardiovascular disease (ASCVD) has been demonstrated previously, mainly in symptomatic subjects., Aims: To evaluate 10 years cardiovascular risk, exercise performance and association to ASCVD among subjects with asymptomatic diverticulosis., Methods: A retrospective cross-sectional cohort of self-referred participants in a medical screening program, who underwent a screening colonoscopy. Demographics, clinical and laboratory variables, ASCVD score, and metabolic equivalents (METs) during treadmill stress test were compared between subjects with and without diverticulosis as diagnosed on screening colonoscopy., Results: 4586 participants underwent screening colonoscopy; 799 (17.4%) had diverticulosis. Among 50-69 yo participants, diverticulosis subjects had a higher ASCVD score compared to non-diverticulosis subjects. Exercise performance was comparable between the groups, across all age groups. Using logistic regression analysis, advanced age group (50-59 yo Adjusted odds ratio (AOR) [95% confidence interval (CI)] 2.57 (1.52-4.34), p < 0.001; 60-69 yo, AOR 2.87 (2.09-3.95), p < 0.001; ≥ 70 yo AOR 4.81 (3.23-7.15), p < 0.001; compared to < 50 yo age group), smoking [AOR 1.27 (1.05-1.55), p = 0.016], HTN [AOR 1.27 (1.03-1.56), p = 0.022], obesity [AOR 1.36 (1.06-1.74), p = 0.014] and male sex [AOR 1.29 (1.02-1.64), p = 0.036] were associated with diverticular detection during screening colonoscopy. Among males, achieving METs score ≥ 10 was inversely associated with diverticular detection during screening colonoscopy [AOR 0.64 (0.43-0.95), p = 0.027]., Conclusions: Ten years probability for ASCVD estimated by the ASCVD score is higher among subjects with asymptomatic diverticulosis compared to subjects without diverticulosis. Improved exercise performance is demonstrated for the first time to correlate with decreased probability for diverticular disease in screening colonoscopy., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Identification of cancer sub-types is a pivotal step for developing personalized treatment. Specifically, sub-typing based on changes in RNA splicing has been motivated by several recent studies. We thus develop CHESSBOARD, an unsupervised algorithm tailored for RNA splicing data that captures "tiles" in the data, defined by a subset of unique splicing changes in a subset of patients. CHESSBOARD allows for a flexible number of tiles, accounts for uncertainty of splicing quantification, and is able to model missing values as additional signals. We first apply CHESSBOARD to synthetic data to assess its domain specific modeling advantages, followed by analysis of several leukemia datasets. We show detected tiles are reproducible in independent studies, investigate their possible regulatory drivers and probe their relation to known AML mutations. Finally, we demonstrate the potential clinical utility of CHESSBOARD by supplementing mutation based diagnostic assays with discovered splicing profiles to improve drug response correlation., (© 2023. The Author(s).)

The fetal-to-adult hemoglobin transition is clinically relevant because reactivation of fetal hemoglobin (HbF) significantly reduces morbidity and mortality associated with sickle cell disease (SCD) and β-thalassemia. Most studies on the developmental regulation of the globin genes, including genome-wide genetics screens, have focused on DNA binding proteins, including BCL11A and ZBTB7A/LRF and their cofactors. Our understanding of RNA binding proteins (RBPs) in this process is much more limited. Two RBPs, LIN28B and IGF2BP1, are known posttranscriptional regulators of HbF production, but a global view of RBPs is still lacking. Here, we carried out a CRISPR/Cas9-based screen targeting RBPs harboring RNA methyltransferase and/or RNA recognition motif (RRM) domains and identified RNA binding motif 12 (RBM12) as a novel HbF suppressor. Depletion of RBM12 induced HbF expression and attenuated cell sickling in erythroid cells derived from patients with SCD with minimal detrimental effects on cell maturation. Transcriptome and proteome profiling revealed that RBM12 functions independently of major known HbF regulators. Enhanced cross-linking and immunoprecipitation followed by high-throughput sequencing revealed strong preferential binding of RBM12 to 5' untranslated regions of transcripts, narrowing down the mechanism of RBM12 action. Notably, we pinpointed the first of 5 RRM domains as essential, and, in conjunction with a linker domain, sufficient for RBM12-mediated HbF regulation. Our characterization of RBM12 as a negative regulator of HbF points to an additional regulatory layer of the fetal-to-adult hemoglobin switch and broadens the pool of potential therapeutic targets for SCD and β-thalassemia., (© 2022 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Purpose: Intraoperative ultrasonography (IOUS) of the liver is a crucial adjunct in every liver resection and may significantly impact intraoperative surgical decisions. However, IOUS is highly operator dependent and has a steep learning curve. We describe the design and assessment of an artificial intelligence (AI) system to identify focal liver lesions in IOUS., Methods: IOUS images were collected during liver resections performed between November 2020 and November 2021. The images were labeled by radiologists and surgeons as normal liver tissue versus images that contain liver lesions. A convolutional neural network (CNN) was trained and tested to classify images based on the labeling. Algorithm performance was tested in terms of area under the curves (AUCs), accuracy, sensitivity, specificity, F1 score, positive predictive value, and negative predictive value., Results: Overall, the dataset included 5043 IOUS images from 16 patients. Of these, 2576 were labeled as normal liver tissue and 2467 as containing focal liver lesions. Training and testing image sets were taken from different patients. Network performance area under the curve (AUC) was 80.2 ± 2.9%, and the overall classification accuracy was 74.6% ± 3.1%. For maximal sensitivity of 99%, the classification specificity is 36.4 ± 9.4%., Conclusions: This study provides for the first time a proof of concept for the use of AI in IOUS and show that high accuracy can be achieved. Further studies using high volume data are warranted to increase accuracy and differentiate between lesion types., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Hepatits C virus (HCV) rates have lowered due to direct-acting antiviral treatment. Nonalcoholic steatohepatitis (NASH)/nonalcoholic fatty liver disease (NAFLD) is rising with no available therapy. We employed text-mining to analyze trends in HCV and NAFLD research from the past two decades., Materials and Methods: We queried PubMed for all HCV and NASH/NAFLD entries published between 2000 and 2020. We compared the total number of publications on both etiologies. We performed subanalyses for different terms of interest and for geographic origin., Results: Overall, 75,934 HCV-related entries and 24,987 NASH/NAFLD-related entries were published during the study period. Up to 2015, there was a linear upward slope in the number of annual HCV publications (154.9 publications/year, p  < 0.001). In 2015, the yearly number of HCV publications started showing a downward slope (-242.2 publications/year, p  < 0.001). The number of NASH/NAFLD publications showed a continuous upward slope during the study period. The NASH/NAFLD field lacks publications on screening and treatment methods., Conclusion: Trends in publications varied between both etiologies. They reflect the success of antiviral treatment for HCV. The growing rates of NAFLD/NASH and the lack of a targeted cure explain the rise in related publications., Competing Interests: The authors declare no conflict of interest., (© The Authors. Health Science Reports published by Wiley Periodicals LLC.)

The epithelial splicing regulatory proteins, ESRP1 and ESRP2, are essential for mammalian development through the regulation of a global program of alternative splicing of genes involved in the maintenance of epithelial cell function. To further inform our understanding of the molecular functions of ESRP1, we performed enhanced crosslinking immunoprecipitation coupled with high-throughput sequencing (eCLIP) in epithelial cells of mouse epidermis. The genome-wide binding sites of ESRP1 were integrated with RNA-Seq analysis of alterations in splicing and total gene expression that result from epidermal ablation of Esrp1 and Esrp2 . These studies demonstrated that ESRP1 functions in splicing regulation occur primarily through direct binding in a position-dependent manner to promote either exon inclusion or skipping. In addition, we also identified widespread binding of ESRP1 in 3' and 5' untranslated regions (UTRs) of genes involved in epithelial cell function, suggesting that its post-transcriptional functions extend beyond splicing regulation., Competing Interests: R.P.C is currently employed at Merck. The authors otherwise declare no competing interests., (© 2022 The Authors.)