A Multicenter Retrospective Cohort Study to Characterize Patients Hospitalized With Multisystem Inflammatory Syndrome in Adults and Coronavirus Disease 2019 in the United States, 2020-2021.

BACKGROUND: The diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated multisystem inflammatory syndrome in adults (MIS-A) requires distinguishing it from acute coronavirus disease 2019 (COVID-19) and may affect clinical management. METHODS: In this retrospective cohort study, we applied the US Centers for Disease Control and Prevention case definition to identify adults hospitalized with MIS-A at 6 academic medical centers from 1 March 2020 to 31 December 2021. Patients MIS-A were matched by age group, sex, site, and admission date at a 1:2 ratio to patients hospitalized with acute symptomatic COVID-19. Conditional logistic regression was used to compare demographic characteristics, presenting symptoms, laboratory and imaging results, treatments administered, and outcomes between cohorts. RESULTS: Through medical record review of 10 223 patients hospitalized with SARS-CoV-2-associated illness, we identified 53 MIS-A cases. Compared with 106 matched patients with COVID-19, those with MIS-A were more likely to be non-Hispanic black and less likely to be non-Hispanic white. They more likely had laboratory-confirmed COVID-19 ≥14 days before hospitalization, more likely had positive in-hospital SARS-CoV-2 serologic testing, and more often presented with gastrointestinal symptoms and chest pain. They were less likely to have underlying medical conditions and to present with cough and dyspnea. On admission, patients with MIS-A had higher neutrophil-to-lymphocyte ratio and higher levels of C-reactive protein, ferritin, procalcitonin, and D-dimer than patients with COVID-19. They also had longer hospitalization and more likely required intensive care admission, invasive mechanical ventilation, and vasopressors. The mortality rate was 6% in both cohorts. CONCLUSIONS: Compared with patients with acute symptomatic COVID-19, adults with MIS-A more often manifest certain symptoms and laboratory findings early during hospitalization. These features may facilitate diagnosis and management.

Fumarate hydratase FH c.1431_1433dupAAA (p.Lys477dup) variant is not associated with cancer including renal cell carcinoma.

Fumarate hydratase (FH) mutations underpin the autosomal recessive syndrome. FH deficiency and the autosomal dominant syndrome hereditary leiomyomatosis and renal cell carcinoma (HLRCC). The FH c.1431_1433dupAAA (p.Lys477dup) genomic alteration has been conclusively shown to contribute to FH deficiency when occurring with another FH germline alteration. However, a sufficiently large dataset has been lacking to conclusively determine its clinical significance to cancer predisposition in the heterozygous state. We reviewed a series of 7,571 patients with cancer who received germline results through MSK-IMPACT testing at the Memorial Sloan Kettering Cancer Center. The FH c.1431_1433dupAAA (p.Lys477dup) variant was detected in 24 individuals, none of whom was affected with renal cancer. Eleven of the 372 patients with renal cancer were identified to carried pathogenic FH variants associated with HLRCC. None of these 372 patients with renal cancer carried the FH c.1431_1433dupAAA variant. Our data indicate the FH c.1431_1433dupAAA is not associated with cancer including renal cell carcinoma.

How Well Do Artificial Intelligence Chatbots Respond to the Top Search Queries About Urological Malignancies?

Artificial intelligence (AI) chatbots are becoming a popular source of information but there are limited data on the quality of information on urological malignancies that they provide. Our objective was to characterize the quality of information and detect misinformation about prostate, bladder, kidney, and testicular cancers from four AI chatbots: ChatGPT, Perplexity, Chat Sonic, and Microsoft Bing AI. We used the top five search queries related to prostate, bladder, kidney, and testicular cancers according to Google Trends from January 2021 to January 2023 and input them into the AI chatbots. Responses were evaluated for quality, understandability, actionability, misinformation, and readability using published instruments. AI chatbot responses had moderate to high information quality (median DISCERN score 4 out of 5, range 2-5) and lacked misinformation. Understandability was moderate (median Patient Education Material Assessment Tool for Printable Materials [PEMAT-P] understandability 66.7%, range 44.4-90.9%) and actionability was moderate to poor (median PEMAT-P actionability 40%, range 0-40%The responses were written at a fairly difficult reading level. AI chatbots produce information that is generally accurate and of moderate to high quality in response to the top urological malignancy-related search queries, but the responses lack clear, actionable instructions and exceed the reading level recommended for consumer health information. PATIENT SUMMARY: Artificial intelligence chatbots produce information that is generally accurate and of moderately high quality in response to popular Google searches about urological cancers. However, their responses are fairly difficult to read, are moderately hard to understand, and lack clear instructions for users to act on.

Quality of Information About Kidney Stones from Artificial Intelligence Chatbots.

Introduction: Kidney stones are common and morbid conditions in the general population with a rising incidence globally. Previous studies show substantial limitations of online sources of information regarding prevention and treatment. The objective of this study was to examine the quality of information on kidney stones from artificial intelligence (AI) chatbots. Methods: The most common online searches about kidney stones from Google Trends and headers from the National Institute of Diabetes and Digestive and Kidney Diseases website were used as inputs to four AI chatbots (ChatGPT version 3.5, Perplexity, Chat Sonic, and Bing AI). Validated instruments were used to assess the quality (DISCERN instrument from 1 low to 5 high), understandability, and actionability (PEMAT, from 0% to 100%) of the chatbot outputs. In addition, we examined the reading level of the information and whether there was misinformation compared with guidelines (5 point Likert scale). Results: AI chatbots generally provided high-quality consumer health information (median DISCERN 4 out of 5) and did not include misinformation (median 1 out of 5). The median understandability was moderate (median 69.6%), and actionability was moderate to poor (median 40%). Responses were presented at an advanced reading level (11th grade; median Flesch-Kincaid score 11.3). Conclusions: AI chatbots provide generally accurate information on kidney stones and lack misinformation; however, it is not easily actionable and is presented above the recommended reading level for consumer health information.

Readability and Information Quality in Cancer Information From a Free vs Paid Chatbot.

Importance: The mainstream use of chatbots requires a thorough investigation of their readability and quality of information. Objective: To identify readability and quality differences in information between a free and paywalled chatbot cancer-related responses, and to explore if more precise prompting can mitigate any observed differences. Design, Setting, and Participants: This cross-sectional study compared readability and information quality of a chatbot's free vs paywalled responses with Google Trends' top 5 search queries associated with breast, lung, prostate, colorectal, and skin cancers from January 1, 2021, to January 1, 2023. Data were extracted from the search tracker, and responses were produced by free and paywalled ChatGPT. Data were analyzed from December 20, 2023, to January 15, 2024. Exposures: Free vs paywalled chatbot outputs with and without prompt: "Explain the following at a sixth grade reading level: [nonprompted input]." Main Outcomes and Measures: The primary outcome measured the readability of a chatbot's responses using Flesch Reading Ease scores (0 [graduate reading level] to 100 [easy fifth grade reading level]). Secondary outcomes included assessing consumer health information quality with the validated DISCERN instrument (overall score from 1 [low quality] to 5 [high quality]) for each response. Scores were compared between the 2 chatbot models with and without prompting. Results: This study evaluated 100 chatbot responses. Nonprompted free chatbot responses had lower readability (median [IQR] Flesh Reading ease scores, 52.60 [44.54-61.46]) than nonprompted paywalled chatbot responses (62.48 [54.83-68.40]) (P < .05). However, prompting the free chatbot to reword responses at a sixth grade reading level was associated with increased reading ease scores than the paywalled chatbot nonprompted responses (median [IQR], 71.55 [68.20-78.99]) (P < .001). Prompting was associated with increases in reading ease in both free (median [IQR], 71.55 [68.20-78.99]; P < .001)and paywalled versions (median [IQR], 75.64 [70.53-81.12]; P < .001). There was no significant difference in overall DISCERN scores between the chatbot models, with and without prompting. Conclusions and Relevance: In this cross-sectional study, paying for the chatbot was found to provide easier-to-read responses, but prompting the free version of the chatbot was associated with increased response readability without changing information quality. Educating the public on how to prompt chatbots may help promote equitable access to health information.

Assessment of Artificial Intelligence Chatbot Responses to Top Searched Queries About Cancer.

Importance: Consumers are increasingly using artificial intelligence (AI) chatbots as a source of information. However, the quality of the cancer information generated by these chatbots has not yet been evaluated using validated instruments. Objective: To characterize the quality of information and presence of misinformation about skin, lung, breast, colorectal, and prostate cancers generated by 4 AI chatbots. Design, Setting, and Participants: This cross-sectional study assessed AI chatbots' text responses to the 5 most commonly searched queries related to the 5 most common cancers using validated instruments. Search data were extracted from the publicly available Google Trends platform and identical prompts were used to generate responses from 4 AI chatbots: ChatGPT version 3.5 (OpenAI), Perplexity (Perplexity.AI), Chatsonic (Writesonic), and Bing AI (Microsoft). Exposures: Google Trends' top 5 search queries related to skin, lung, breast, colorectal, and prostate cancer from January 1, 2021, to January 1, 2023, were input into 4 AI chatbots. Main Outcomes and Measures: The primary outcomes were the quality of consumer health information based on the validated DISCERN instrument (scores from 1 [low] to 5 [high] for quality of information) and the understandability and actionability of this information based on the understandability and actionability domains of the Patient Education Materials Assessment Tool (PEMAT) (scores of 0%-100%, with higher scores indicating a higher level of understandability and actionability). Secondary outcomes included misinformation scored using a 5-item Likert scale (scores from 1 [no misinformation] to 5 [high misinformation]) and readability assessed using the Flesch-Kincaid Grade Level readability score. Results: The analysis included 100 responses from 4 chatbots about the 5 most common search queries for skin, lung, breast, colorectal, and prostate cancer. The quality of text responses generated by the 4 AI chatbots was good (median [range] DISCERN score, 5 [2-5]) and no misinformation was identified. Understandability was moderate (median [range] PEMAT Understandability score, 66.7% [33.3%-90.1%]), and actionability was poor (median [range] PEMAT Actionability score, 20.0% [0%-40.0%]). The responses were written at the college level based on the Flesch-Kincaid Grade Level score. Conclusions and Relevance: Findings of this cross-sectional study suggest that AI chatbots generally produce accurate information for the top cancer-related search queries, but the responses are not readily actionable and are written at a college reading level. These limitations suggest that AI chatbots should be used supplementarily and not as a primary source for medical information.

Inhibition of ERK signaling for treatment of ERRα positive TNBC.

Breast cancer is the second leading cause of cancer-related deaths in women and triple-negative breast cancer (TNBC), in particular, is an aggressive and highly metastatic type of breast cancer that does not respond to established targeted therapies and is associated with poor prognosis and worse survival. Previous studies identified a subgroup of triple-negative breast cancer patients with high expression of estrogen related receptor alpha (ERRα) that has better prognosis when treated with tamoxifen. We therefore set out to identify common targets of tamoxifen and ERRα in the context of TNBC using phosphoproteomic analysis. In this study, we discovered that phosphorylation of mitogen-activated protein kinase 1 (MAPK1) is regulated by tamoxifen as well as ERRα. Additionally, we showed that inhibition of MAPK signaling together with the use of a selective ERRα inverse agonist, XCT-790, leads to a significant upregulation of apoptosis and paves way for the therapeutic use of MAPK inhibitors for treatment of ERRα expressing TNBC.

Single-Cell Approach Reveals Intercellular Heterogeneity in Phage-Producing Capacities.

Bacteriophage burst size is the average number of phage virions released from infected bacterial cells, and its magnitude depends on the duration of an intracellular progeny accumulation phase. Burst size is often measured at the population level, not the single-cell level, and consequently, statistical moments are not commonly available. In this study, we estimated the bacteriophage lambda (λ) single-cell burst size mean and variance following different intracellular accumulation period durations by employing Escherichia coli lysogens bearing lysis-deficient λ prophages. Single lysogens can be isolated and chemically lysed at desired times following prophage induction to quantify progeny intracellular accumulation within individual cells. Our data showed that λ phage burst size initially increased exponentially with increased lysis time (i.e., period between induction and chemical lysis) and then saturated at longer lysis times. We also demonstrated that cell-to-cell variation, or "noise," in lysis timing did not contribute significantly to burst size noise. The burst size noise remained constant with increasing mean burst size. The most likely explanation for the experimentally observed constant burst size noise was that cell-to-cell differences in burst size originated from intercellular heterogeneity in cellular capacities to produce phages. The mean burst size measured at different lysis times was positively correlated to cell volume, which may determine the cellular phage production capacity. However, experiments controlling for cell size indicated that there are other factors in addition to cell size that determine this cellular capacity. IMPORTANCE Phages produce offspring by hijacking a cell's replicative machinery. Previously, it was noted that the variation in the number of phages produced by single infected cells far exceeded cell size variation. It was hypothesized that this variation is a consequence of variation in the timing of host cell lysis. Here, we show that cell-to-cell variation in lysis timing does not significantly contribute to the burst size variation. We suggest that the constant burst size variation across different host lysis times results from cell-to-cell differences in capacity to produce phages. We found that the mean burst size measured at different lysis times was positively correlated to cell volume, which may determine the cellular phage production capacity. However, experiments controlling for cell size indicated that there are other factors in addition to cell size that determine this cellular capacity.

Endocrine therapy resistance: what we know and future directions.

Endocrine resistance is a major hurdle in the treatment of estrogen receptor (ER)-positive breast cancer. When abnormally regulated, molecular signals responsible for cellular proliferation, as well as ER itself, allow for cellular evasion of ER-dependent treatments. Therefore, pharmacological treatments that target these evasion mechanisms are beneficial for the treatment of endocrine-resistant breast cancers. This review summarizes currently understood molecular signals that contribute to endocrine resistance and their crosstalk that stem from mitogen-activated protein kinase (MAPK), phosphoinositol-3 kinase/protein kinase B (PI3K/AKT), mechanistic target of rapamycin (mTOR), cyclin-dependent kinases 4 and 6 (CDK4/6) and aberrant ER function. Recent clinical trials that target these molecular signals as a treatment strategy for endocrine-resistant breast cancer are also highlighted.

Social defeat stress induces depression-like behavior and alters spine morphology in the hippocampus of adolescent male C57BL/6 mice.

Social stress, including bullying during adolescence, is a risk factor for common psychopathologies such as depression. To investigate the neural mechanisms associated with juvenile social stress-induced mood-related endophenotypes, we examined the behavioral, morphological, and biochemical effects of the social defeat stress model of depression on hippocampal dendritic spines within the CA1 stratum radiatum. Adolescent (postnatal day 35) male C57BL/6 mice were subjected to defeat episodes for 10 consecutive days. Twenty-four h later, separate groups of mice were tested on the social interaction and tail suspension tests. Hippocampi were then dissected and Western blots were conducted to quantify protein levels for various markers important for synaptic plasticity including protein kinase M zeta (PKMζ), protein kinase C zeta (PKCζ), the dopamine-1 (D1) receptor, tyrosine hydroxylase (TH), and the dopamine transporter (DAT). Furthermore, we examined the presence of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-receptor subunit GluA2 as well as colocalization with the post-synaptic density 95 (PSD95) protein, within different spine subtypes (filopodia, stubby, long-thin, mushroom) using an immunohistochemistry and Golgi-Cox staining technique. The results revealed that social defeat induced a depression-like behavioral profile, as inferred from decreased social interaction levels, increased immobility on the tail suspension test, and decreases in body weight. Whole hippocampal immunoblots revealed decreases in GluA2, with a concomitant increase in DAT and TH levels in the stressed group. Spine morphology analyses further showed that defeated mice displayed a significant decrease in stubby spines, and an increase in long-thin spines within the CA1 stratum radiatum. Further evaluation of GluA2/PSD95 containing-spines demonstrated a decrease of these markers within long-thin and mushroom spine types. Together, these results indicate that juvenile social stress induces GluA2- and dopamine-associated dysregulation in the hippocampus - a neurobiological mechanism potentially underlying the development of mood-related syndromes as a consequence of adolescent bullying.