Percent Predicted Peak Exercise Oxygen Pulse Provides Insights Into Ventricular-Vascular Response and Prognosticates HFpEF.

Background: Peak oxygen consumption and oxygen pulse along with their respective percent predicted measures are gold standards of exercise capacity. To date, no studies have investigated the relationship between percent predicted peak oxygen pulse (%PredO2P) and ventricular-vascular response (VVR) and the association of %PredO2P with all-cause mortality in heart failure with preserved ejection fraction (HFpEF) patients. Objectives: The authors investigated the association between: 1) CPET measures of %PredO2P and VVR; and 2) %PredO2P and all-cause mortality in HFpEF patients. Methods: Our cohort of 154 HFpEF patients underwent invasive CPET and were grouped into %PredO2P tertiles. The association between percent predicted Fick components and markers of VVR (ie, proportionate pulse pressure, effective arterial elastance) was determined with correlation analysis. The Cox proportional hazards model was used to identify predictors of mortality. Results: The participants' mean age was 57 ± 15 years. Higher %PredO2P correlated with higher exercise capacity. In terms of VVR, higher %PredO2P correlated with a lower pressure for a given preload (effective arterial elastance r = -0.45, P < 0.001 and proportionate pulse pressure r = -0.22, P = 0.008). %PredO2P distinguished normal and abnormal percent predicted peak stroke volume and correlated positively with %PredVO2 (r = 0.61, P < 0.001). Participants had a median follow-up time of 5.6 years and 15% death. Adjusted for age and body mass index, there was a 5% relative reduction in mortality (HR: 0.95, 95% CI: 0.92-0.98, P = 0.003) for every percent increase in %PredO2P. Conclusions: In HFpEF, %PredO2P is a VVR marker that can stratify invasive parameters such as percent predicted peak stroke volume. %PredO2P is an independent prognostic marker for all-cause mortality and those with higher %PredO2P exhibited longer survival.

Open suture repair versus PermacolTM mesh repair of small ventral hernias in patients with end-stage kidney disease.

BACKGROUND: Ventral hernia is a common surgical problem among patients with end-stage kidney disease (ESKD), while the optimal repair technique for small ventral hernias is controversial. This study aimed to compare the outcomes of open suture repair versus biological mesh repair of small ventral hernias with defect size ≤2 cm in ESKD patients. METHOD: Data from consecutive ESKD patients who underwent elective ventral hernia repair with defect size ≤2 cm at a single institution from January 2012 to January 2022 were retrospectively reviewed. Outcomes of open suture repair were compared to PermacolTM mesh repair. The primary outcome was recurrence rate. Secondary outcomes included post-operative complications, peri-operative and post-operative dialysis regimen. RESULTS: Forty-seven ventral hernia repairs were included, with 20 being suture repairs and 27 being PermacolTM mesh repairs. Median age at hernia repair was 60 (range 32-81) years old. Pre-operatively, 42 patients (89.4%) were on peritoneal dialysis (PD). Paraumbilical hernia (59.6%) was most common. Median hernia defect size was 15 mm (range 2-20 mm). Upon median follow-up of 56 (range 9-119) months, more patients in the suture repair group developed recurrence (30% vs. 0%, p = 0.004). Median time to recurrence was 10 (range 5-16) months. There was no wound or mesh infection. The majority of patients underwent intermittent PD peri-operatively and were able to resume on PD in the long run. CONCLUSION: Ventral hernia repair is indicated in ESKD patients even for small defects; repair with PermacolTM mesh was associated with a lower recurrence rate when compared to suture repair and post-operative morbidity was low.

Malignant Pericardial Effusion: A Systematic Review.

Background: Malignant pericardial effusion (Eff) is often asymptomatic and has an unknown prevalence, due to its occult presentation. The condition often is identified postmortem on autopsy, and it is associated with a poor prognosis. Given the late presentation of malignant pericardial Effs, a minimal volume of literature has examined the epidemiology, clinical characteristics, and outcomes of these complex patients. We conducted a systematic review to advance present understanding of this condition. Methods: A search of 4 databases resulted in 41 case reports meeting criteria. Inclusion criteria were being a patient aged > 18 years who presented with pericardial Eff in the setting of malignancy. Intervention was medical and/or surgical therapy, and the outcome was mortality. Results: For the 41 patients included, the median age was 54 years, and the majority were male patients (58%). Dyspnea was the leading symptom (90%), and cardiac tamponade was present in 78% of cases. Common cancers included lung, gastrointestinal, and renal neoplasms (59%). Pericardiocentesis occurred in 98% of cases, with a median fluid extraction volume of 1000 mL. Death occurred in 44%, primarily due to disease progression and/or metastasis. Conclusions: This study presents the largest systematic review on malignancy-induced pericardial Effs to date. Notably, solid tumours, and specifically lung adenocarcinomas, are common culprits. Malignant pericardial Effs are often severe, with a majority of patients presenting with cardiac tamponade. Overall, treatment options are limited, and the associated mortality rate is high.

Contexte: L'épanchement péricardique malin (EPM) est un état généralement asymptomatique, de prévalence inconnue en raison de son tableau clinique occulte. Il est souvent reconnu post-mortem, à l'autopsie, et est associé à un pronostic médiocre. En raison de la consultation tardive pour un EPM, les données publiées relatives à l'épidémiologie, aux caractéristiques cliniques et à l'issue de ces cas complexes sont limitées. Nous avons réalisé une analyse systématique dans le but d'élargir les connaissances sur cette affection. Méthodologie: Une recherche réalisée dans quatre bases de données a permis de repérer 41 rapports de cas qui répondaient aux critères de recherche. Les critères d'inclusion étaient les suivants : être âgé de plus de 18 ans; présenter un épanchement péricardique en présence d'un cancer; intervention pharmacologique et/ou chirurgicale; issue mortelle. Résultats: L'âge médian des 41 patients inclus était de 54 ans; la majorité d'entre eux étaient des hommes (58 %). Le symptôme principal était la dyspnée (90 %), et une tamponnade cardiaque était présente dans 78 % des cas. Les cancers les plus fréquents étaient le cancer du poumon, le cancer gastro-intestinal et les néoplasmes rénaux (59 %). Une péricardiocentèse a été réalisée dans 98 % des cas. Le volume de drainage médian était de 1 000 mL. Quarante-quatre pour cent des sujets sont décédés, principalement en raison de la progression de la maladie et/ou de métastases. Conclusions: Cette étude est la plus vaste analyse systématique réalisée à ce jour sur l'EPM. Les tumeurs solides, et plus particulièrement les adénocarcinomes pulmonaires, sont des causes fréquentes. L'EPM est souvent grave, la majorité des patients présentant une tamponnade cardiaque. Les traitements disponibles sont généralement limités, et le taux de mortalité associé est élevé.

A new method for network bioinformatics identifies novel drug targets for mucinous ovarian carcinoma.

Mucinous ovarian carcinoma (MOC) is a subtype of ovarian cancer that is distinct from all other ovarian cancer subtypes and currently has no targeted therapies. To identify novel therapeutic targets, we developed and applied a new method of differential network analysis comparing MOC to benign mucinous tumours (in the absence of a known normal tissue of origin). This method mapped the protein-protein network in MOC and then utilised structural bioinformatics to prioritise the proteins identified as upregulated in the MOC network for their likelihood of being successfully drugged. Using this protein-protein interaction modelling, we identified the strongest 5 candidates, CDK1, CDC20, PRC1, CCNA2 and TRIP13, as structurally tractable to therapeutic targeting by small molecules. siRNA knockdown of these candidates performed in MOC and control normal fibroblast cell lines identified CDK1, CCNA2, PRC1 and CDC20, as potential drug targets in MOC. Three targets (TRIP13, CDC20, CDK1) were validated using known small molecule inhibitors. Our findings demonstrate the utility of our pipeline for identifying new targets and highlight potential new therapeutic options for MOC patients.

FLUEnT: Transformer for detecting lung consolidations in videos using fused lung ultrasound encodings.

Pneumonia is the leading cause of death among children around the world. According to WHO, a total of 740,180 lives under the age of five were lost due to pneumonia in 2019. Lung ultrasound (LUS) has been shown to be particularly useful for supporting the diagnosis of pneumonia in children and reducing mortality in resource-limited settings. The wide application of point-of-care ultrasound at the bedside is limited mainly due to a lack of training for data acquisition and interpretation. Artificial Intelligence can serve as a potential tool to automate and improve the LUS data interpretation process, which mainly involves analysis of hyper-echoic horizontal and vertical artifacts, and hypo-echoic small to large consolidations. This paper presents, Fused Lung Ultrasound Encoding-based Transformer (FLUEnT), a novel pediatric LUS video scoring framework for detecting lung consolidations using fused LUS encodings. Frame-level embeddings from a variational autoencoder, features from a spatially attentive ResNet-18, and encoded patient information as metadata combiningly form the fused encodings. These encodings are then passed on to the transformer for binary classification of the presence or absence of consolidations in the video. The video-level analysis using fused encodings resulted in a mean balanced accuracy of 89.3 %, giving an average improvement of 4.7 % points in comparison to when using these encodings individually. In conclusion, outperforming the state-of-the-art models by an average margin of 8 % points, our proposed FLUEnT framework serves as a benchmark for detecting lung consolidations in LUS videos from pediatric pneumonia patients.

Interaction of NF-κB and FOSL1 drives glioma stemness.

Glioblastoma multiforme (GBM) is the most common and malignant primary brain tumor; GBM's inevitable recurrence suggests that glioblastoma stem cells (GSC) allow these tumors to persist. Our previous work showed that FOSL1, transactivated by the STAT3 gene, functions as a tumorigenic gene in glioma pathogenesis and acts as a diagnostic marker and potential drug target in glioma patients. Accumulating evidence shows that STAT3 and NF-κB cooperate to promote the development and progression of various cancers. The link between STAT3 and NF-κB suggests that NF-κB can also transcriptionally regulate FOSL1 and contribute to gliomagenesis. To investigate downstream molecules of FOSL1, we analyzed the transcriptome after overexpressing FOSL1 in a PDX-L14 line characterized by deficient FOSL1 expression. We then conducted immunohistochemical staining for FOSL1 and NF-κB p65 using rabbit polyclonal anti-FOSL1 and NF-κB p65 in glioma tissue microarrays (TMA) derived from 141 glioma patients and 15 healthy individuals. Next, mutants of the human FOSL1 promoter, featuring mutations in essential binding sites for NF-κB were generated using a Q5 site-directed mutagenesis kit. Subsequently, we examined luciferase activity in glioma cells and compared it to the wild-type FOSL1 promoter. Then, we explored the mutual regulation between NF-κB signaling and FOSL1 by modulating the expression of NF-κB or FOSL1. Subsequently, we assessed the activity of FOSL1 and NF-κB. To understand the role of FOSL1 in cell growth and stemness, we conducted a CCK-8 assay and cell cycle analysis, assessing apoptosis and GSC markers, ALDH1, and CD133 under varying FOSL1 expression conditions. Transcriptome analyses of downstream molecules of FOSL1 show that NF-κB signaling pathway is regulated by FOSL1. NF-κB p65 protein expression correlates to the expression of FOSL1 in glioma patients, and both are associated with glioma grades. NF-κB is a crucial transcription factor activating the FOSL1 promoter in glioma cells. Mutual regulation between NF-κB and FOSL1 contributes to glioma tumorigenesis and stemness through promoting G1/S transition and inhibiting apoptosis. Therefore, the FOSL1 molecular pathway is functionally connected to NF-κB activation, enhances stemness, and is indicative that FOSL1 may potentially be a novel GBM drug target.

Immune checkpoint inhibitors and pericardial disease: a systematic review.

INTRODUCTION: Despite the growing use of immune checkpoint inhibitors (ICI) in cancer treatment, data regarding ICI-associated pericardial disease are primarily derived from case reports and case series. ICI related pericardial disease can be difficult to diagnose and is associated with significant morbidity. We conducted a systematic review to further characterize the epidemiology, clinical presentation, and outcomes of this patient population. METHODS: A search of four databases resulted in 31 studies meeting inclusion criteria. Patients > 18 years old who presented with ICI mediated pericardial disease were included. Intervention was medical + surgical therapy and outcomes were development of cardiac tamponade, morbidity, and mortality. RESULTS: Thirty- eight patients across 31 cases were included. Patients were majority male (72%) with a median age of 63. Common symptoms included dyspnea (59%) and chest pain (32%), with 41% presenting with cardiac tamponade. Lung cancer (81%) was the most prevalent, and nivolumab (61%) and pembrolizumab (34%) were the most used ICIs. Pericardiocentesis was performed in 68% of patients, and 92% experienced symptom improvement upon ICI cessation. Overall mortality was 16%. DISCUSSION: This study provides the most comprehensive analysis of ICI-mediated pericardial disease to date. Patients affected were most commonly male with lung cancer treated with either Nivolumab or Pembrolizumab. Diagnosis may be challenging in the setting of occult presentation with normal EKG and physical exam as well as delayed onset from therapy initiation. ICI-associated pericardial disease demonstrates high morbidity and mortality, as evidenced by a majority of patients requiring pericardiocentesis.

Coronary microvascular dysfunction and inflammation: Insights from the Coronary Microvascular Disease Registry.

BACKGROUND: Coronary microvascular dysfunction (CMD) is associated with various inflammatory conditions that worsen endothelial dysfunction. This study aimed to investigate the relationship between CMD and inflammation using common inflammatory markers derived from complete blood count (CBC) analysis. METHODS: Information was gathered from the Coronary Microvascular Disease Registry to examine the neutrophil-to-lymphocyte ratio (NLR), eosinophil-to-monocyte ratio (EMR), and monocyte-to-high-density lipoprotein ratio (MHR) in a cohort of patients with angina who showed non-obstructive coronary arteries and underwent invasive physiological assessments for CMD. RESULTS: Of the 171 patients studied, 126 were CMD-negative and 45 were CMD-positive, constituting two groups of interest. The average age of all patients was 61.7 ± 11.1 years, and 63.7 % were female. No significant differences were observed between the two groups in terms of baseline characteristics, cardiovascular risk factors, or potential anti-inflammatory medications. Furthermore, there were no statistically significant differences in NLR (2.54 ± 3.71 vs. 2.52 ± 2.28, p = 0.97), EMR (0.3 ± 0.21 vs. 0.34 ± 0.29, p = 0.31), or MHR (0.02 ± 0.01 vs. 0.01 ± 0.01, p = 0.54) between CMD-positive and CMD-negative patients. CONCLUSION: Our findings did not show a noteworthy connection between CMD and inflammation, as suggested by various simple CBC-based biomarkers.

Combination Immunotherapy with Vaccine and Oncolytic HSV Virotherapy Is Time Dependent.

Oncolytic virotherapy or immunovirotherapy is a strategy that utilizes viruses to selectively infect and kill tumor cells while also stimulating an immune response against the tumor. Early clinical trials in both pediatric and adult patients using oncolytic herpes simplex viruses (oHSV) have demonstrated safety and promising efficacy; however, combinatorial strategies designed to enhance oncolysis while also promoting durable T-cell responses for sustaining disease remission are likely required. We hypothesized that combining the direct tumor cell killing and innate immune stimulation by oHSV with a vaccine that promotes T cell-mediated immunity may lead to more durable tumor regression. To this end, we investigated the preclinical efficacy and potential synergy of combining oHSV with a self-assembling nanoparticle vaccine codelivering peptide antigens and Toll-like receptor 7 and 8 agonists (referred to as SNAPvax),which induces robust tumor-specific T-cell immunity. We then assessed how timing of the treatments (i.e., vaccine before or after oHSV) impacts T-cell responses, viral replication, and preclinical efficacy. The sequence of treatments was critical, as survival was significantly enhanced when the SNAPvax vaccine was given prior to oHSV. Increased clinical efficacy was associated with reduced tumor volume and increases in virus replication and tumor antigen-specific CD8+ T cells. These findings substantiate the criticality of combination immunotherapy timing and provide preclinical support for combining SNAPvax with oHSV as a promising treatment approach for both pediatric and adult tumors.

A genome-wide spectrum of tandem repeat expansions in 338,963 humans.

The Genome Aggregation Database (gnomAD), widely recognized as the gold-standard reference map of human genetic variation, has largely overlooked tandem repeat (TR) expansions, despite the fact that TRs constitute ∼6% of our genome and are linked to over 50 human diseases. Here, we introduce the TR-gnomAD (https://wlcb.oit.uci.edu/TRgnomAD), a biobank-scale reference of 0.86 million TRs derived from 338,963 whole-genome sequencing (WGS) samples of diverse ancestries (39.5% non-European samples). TR-gnomAD offers critical insights into ancestry-specific disease prevalence using disparities in TR unit number frequencies among ancestries. Moreover, TR-gnomAD is able to differentiate between common, presumably benign TR expansions, which are prevalent in TR-gnomAD, from those potentially pathogenic TR expansions, which are found more frequently in disease groups than within TR-gnomAD. Together, TR-gnomAD is an invaluable resource for researchers and physicians to interpret TR expansions in individuals with genetic diseases.

Multimodal epigenetic sequencing analysis (MESA) of cell-free DNA for non-invasive colorectal cancer detection.

BACKGROUND: Detecting human cancers through cell-free DNA (cfDNA) in blood is a sensitive and non-invasive option. However, capturing multiple forms of epigenetic information remains a technical and financial challenge. METHODS: To address this, we developed multimodal epigenetic sequencing analysis (MESA), a flexible and sensitive approach to capturing and integrating a diverse range of epigenetic features in cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq. MESA enables simultaneous inference of four epigenetic modalities: cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and windowed protection score for regions surrounding gene promoters and polyadenylation sites. RESULTS: When applied to 690 cfDNA samples from 3 colorectal cancer clinical cohorts, MESA's novel modalities, which include nucleosome fuzziness, and genomic features, including polyadenylation sites, improve cancer detection beyond the traditional epigenetic markers of promoter DNA methylation. CONCLUSIONS: Together, MESA stands as a major advancement in the field by utilizing comprehensive and complementary epigenetic profiles of cfDNA for effective non-invasive cancer detection.

Lite It Fly: An All-Deformable-Butterfly Network.

Most deep neural networks (DNNs) consist fundamentally of convolutional and/or fully connected layers, wherein the linear transform can be cast as the product between a filter matrix and a data matrix obtained by arranging feature tensors into columns. Recently proposed deformable butterfly (DeBut) decomposes the filter matrix into generalized, butterfly-like factors, thus achieving network compression orthogonal to the traditional ways of pruning or low-rank decomposition. This work reveals an intimate link between DeBut and a systematic hierarchy of depthwise and pointwise convolutions, which explains the empirically good performance of DeBut layers. By developing an automated DeBut chain generator, we show for the first time the viability of homogenizing a DNN into all DeBut layers, thus achieving extreme sparsity and compression. Various examples and hardware benchmarks verify the advantages of All-DeBut networks. In particular, we show it is possible to compress a PointNet to 5% parameters with 5% accuracy drop, a record not achievable by other compression schemes.

Emerging Landscape of Preclinical Models for Studying COVID-19 Neurologic Diseases.

COVID-19 (Coronavirus Disease 2019) is an infectious disease caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and has globally infected 768 million people and caused over 6 million deaths. COVID-19 primarily affects the respiratory system but increasing reports of neurologic symptoms associated with COVID-19 have been reported in the literature. The exact mechanism behind COVID-19 neurologic pathophysiology remains poorly understood due to difficulty quantifying clinical neurologic symptoms in humans and correlating them to findings in human post-mortem samples and animal models. Thus, robust preclinical experimental models for COVID-19 neurologic manifestations are urgently needed. Here, we review recent advances in in vitro, in vivo, and other models and technologies for studying COVID-19 including primary cell cultures, pluripotent stem cell-derived neurons and organoids, rodents, nonhuman primates, 3D bioprinting, artificial intelligence, and multiomics. We specifically focus our discussion on the contribution, recent advancements, and limitations these preclinical models have on furthering our understanding of COVID-19's neuropathic physiology. We also discuss these models' roles in the screening and development of therapeutics, vaccines, antiviral drugs, and herbal medicine, and on future opportunities for COVID-19 neurologic research and clinical management.

TRPM7 transactivates the FOSL1 gene through STAT3 and enhances glioma stemness.

INTRODUCTION: We previously reported that TRPM7 regulates glioma cells' stemness through STAT3. In addition, we demonstrated that FOSL1 is a response gene for TRPM7, and the FOSL1 gene serves as an oncogene to promote glioma proliferation and invasion. METHODS: In the present study, we determined the effects of FOSL1 on glioma stem cell (GSC) markers CD133 and ALDH1 by flow cytometry, and the maintenance of stem cell activity by extreme limiting dilution assays (ELDA). To further gain insight into the mechanism by which TRPM7 activates transcription of the FOSL1 gene to contribute to glioma stemness, we constructed a FOSL1 promoter and its GAS mutants followed by luciferase reporter assays and ChIP-qPCR in a glioma cell line and glioma patient-derived xenoline. We further examined GSC markers ALDH1 and TRPM7 as well as FOSL1 by immunohistochemistry staining (IHC) in brain tissue microarray (TMA) of glioma patients. RESULTS: We revealed that FOSL1 knockdown reduces the expression of GSC markers CD133 and ALDH1, and FOSL1 is required to maintain stem cell activity in glioma cells. The experiments also showed that mutations of - 328 to - 336 and - 378 to - 386 GAS elements markedly reduced FOSL1 promoter activity. Constitutively active STAT3 increased while dominant-negative STAT3 decreased FOSL1 promoter activity. Furthermore, overexpression of TRPM7 enhanced while silencing of TRPM7 reduced FOSL1 promoter activity. ChIP-qPCR assays revealed that STAT3, present in nuclear lysates of glioma cells stimulated by constitutively activated STAT3, can bind to two GAS elements, respectively. We demonstrated that deacetylation of FOSL1 at the Lys-116 residue located within its DNA binding domain led to an increase in FOSL1 transcriptional activity. We found that the expression of TRPM7, ALDH1, and FOSL1 protein is associated with grades of malignant glioma, and TRPM7 protein expression correlates to the expression of ALDH1 and FOSL1 in glioma patients. CONCLUSIONS: These combined results demonstrated that TRPM7 induced FOSL1 transcriptional activation, which is mediated by the action of STAT3, a mechanism shown to be important in glioma stemness. These results indicated that FOSL1, similar to GSC markers ALDH1 and TRPM7, is a diagnostic marker and potential drug target for glioma patients.

Post-Myocardial Infarction Free-Wall Rupture: Rapid Diagnosis and Management.

We present a case of post-myocardial infarction free-wall rupture in a critically ill patient presenting to the emergency department. Through our case we highlight the prompt evaluation, diagnosis, and management necessary to improve survival in a patient with this life-threatening condition. (Level of Difficulty: Beginner.).

Cardiovascular Protection by Metformin: Latest Advances in Basic and Clinical Research.

BACKGROUND: Metformin is among the most frequently prescribed antidiabetic drugs worldwide and remains the first-line therapy for type 2 diabetes due to its well-established glucose-lowering efficacy and favorable safety profile. SUMMARY: Studies over the past decades show that metformin also exerts many other beneficial effects independent of its glucose-lowering effect both in experimental models and human subjects. Among them, the most notable is its cardiovascular protective effect. In this review, we discuss the latest cutting-edge research findings on metformin's cardiovascular protection from both preclinical studies and randomized clinical trials. We focus on describing novel basic research discoveries reported in influential journals and discussing their implications in the context of latest clinical trial findings related to common cardiovascular and metabolic disorders, including atherosclerosis and dyslipidemia, myocardial injury, and heart failure. KEY MESSAGES: While substantial preclinical and clinical evidence suggests metformin as a potential cardiovascular protectant, large-scale randomized controlled trials are warranted to establish its clinical efficacy in treating patients with atherosclerotic cardiovascular disease and heart failure.

An allosteric pan-TEAD inhibitor blocks oncogenic YAP/TAZ signaling and overcomes KRAS G12C inhibitor resistance.

The Hippo pathway is a key growth control pathway that is conserved across species. The downstream effectors of the Hippo pathway, YAP (Yes-associated protein) and TAZ (transcriptional coactivator with PDZ-binding motif), are frequently activated in cancers to drive proliferation and survival. Based on the premise that sustained interactions between YAP/TAZ and TEADs (transcriptional enhanced associate domain) are central to their transcriptional activities, we discovered a potent small-molecule inhibitor (SMI), GNE-7883, that allosterically blocks the interactions between YAP/TAZ and all human TEAD paralogs through binding to the TEAD lipid pocket. GNE-7883 effectively reduces chromatin accessibility specifically at TEAD motifs, suppresses cell proliferation in a variety of cell line models and achieves strong antitumor efficacy in vivo. Furthermore, we uncovered that GNE-7883 effectively overcomes both intrinsic and acquired resistance to KRAS (Kirsten rat sarcoma viral oncogene homolog) G12C inhibitors in diverse preclinical models through the inhibition of YAP/TAZ activation. Taken together, this work demonstrates the activities of TEAD SMIs in YAP/TAZ-dependent cancers and highlights their potential broad applications in precision oncology and therapy resistance.

Artificial intelligence for clinical decision support for monitoring patients in cardiovascular ICUs: A systematic review.

Background: Artificial intelligence (AI) and machine learning (ML) models continue to evolve the clinical decision support systems (CDSS). However, challenges arise when it comes to the integration of AI/ML into clinical scenarios. In this systematic review, we followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), the population, intervention, comparator, outcome, and study design (PICOS), and the medical AI life cycle guidelines to investigate studies and tools which address AI/ML-based approaches towards clinical decision support (CDS) for monitoring cardiovascular patients in intensive care units (ICUs). We further discuss recent advances, pitfalls, and future perspectives towards effective integration of AI into routine practices as were identified and elaborated over an extensive selection process for state-of-the-art manuscripts. Methods: Studies with available English full text from PubMed and Google Scholar in the period from January 2018 to August 2022 were considered. The manuscripts were fetched through a combination of the search keywords including AI, ML, reinforcement learning (RL), deep learning, clinical decision support, and cardiovascular critical care and patients monitoring. The manuscripts were analyzed and filtered based on qualitative and quantitative criteria such as target population, proper study design, cross-validation, and risk of bias. Results: More than 100 queries over two medical search engines and subjective literature research were developed which identified 89 studies. After extensive assessments of the studies both technically and medically, 21 studies were selected for the final qualitative assessment. Discussion: Clinical time series and electronic health records (EHR) data were the most common input modalities, while methods such as gradient boosting, recurrent neural networks (RNNs) and RL were mostly used for the analysis. Seventy-five percent of the selected papers lacked validation against external datasets highlighting the generalizability issue. Also, interpretability of the AI decisions was identified as a central issue towards effective integration of AI in healthcare.