Clinical and video-polysomnographic characterization of restless sleep disorder in adult patients.

Adults with restless sleep disorder (RSD) have never been studied clinically and polysomnographically. This study aimed to describe the clinical manifestation, duration, and distribution of sleep-related movements in adult patients with restless sleep disorder. Patients who had performed VPSG from Jan 2021 to Jan 2022 and met the diagnosis criteria of RSD were enrolled in the study. Patients' bed partners were also interviewed or telephoned in identifying this disorder. Scoring of movements during sleep was according to the diagnosis criteria of RSD and scoring of large muscle group movements during sleep proposed by the International RLS Study Group in 2020 and 2021, respectively. The clinical manifestation, the distribution of sleep stage as well as the types and duration of the movements were carefully recorded and analyzed. We included ten patients in the study with a mean age of 27.6 years (range 22-38). There was a male prevalence in adults with RSD. The study highlighted the findings from video-polysomnography, which indicated frequent sleep-related movements occurring throughout the Night. These movements were most prominent during N1 and N2 sleep stage, followed by REM sleep, while fewer movements were observed during N3 sleep. Adults with RSD experienced significant daytime functioning impairments, including non-refreshing sleep, daytime fatigue/sleepiness, and mood disturbance. Two of the patients in the study were diagnosed with anxiety and depression, further underscoring the impact of RSD on mental health. Adult patients also suffer from severe RSD, and the RSD that originates in childhood tends to persist into adulthood. In these cases, longer duration of the disease and poor sleep quality may be associated with an increased risk of developing psychiatric comorbidities. Our cases represent an objectively documented type of RSD in younger adult patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s41105-024-00524-1.

Machine learning-Based model for prediction of Narcolepsy Type 1 in Patients with Obstructive Sleep Apnea with Excessive Daytime Sleepiness.

Background: Excessive daytime sleepiness (EDS) forms a prevalent symptom of obstructive sleep apnea (OSA) and narcolepsy type 1 (NT1), while the latter might always be overlooked. Machine learning (ML) models can enable the early detection of these conditions, which has never been applied for diagnosis of NT1. Objective: The study aimed to develop ML prediction models to help non-sleep specialist clinicians identify high probability of comorbid NT1 in patients with OSA early. Methods: Totally, clinical features of 246 patients with OSA in three sleep centers were collected and analyzed for the development of nine ML models. LASSO regression was used for feature selection. Various metrics such as the area under the receiver operating curve (AUC), calibration curve, and decision curve analysis (DCA) were employed to evaluate and compare the performance of these ML models. Model interpretability was demonstrated by Shapley Additive explanations (SHAP). Results: Based on the analysis of AUC, DCA, and calibration curves, the Gradient Boosting Machine (GBM) model demonstrated superior performance compared to other machine learning (ML) models. The top five features used in the GBM model, ranked by feature importance, were age of onset, total limb movements index, sleep latency, non-REM (Rapid Eye Movement) sleep stage 2 and severity of OSA. Conclusion: The study yielded a simple and feasible screening ML-based model for the early identification of NT1 in patients with OSA, which warrants further verification in more extensive clinical practices.

A new mechanism of antibody diversity: formation of the natural antibodies containing LAIR1 and LILRB1 extracellular domains.

The recent discovery of public antibodies targeting Plasmodium falciparum-encoded repetitive interspersed families of polypeptides (RIFINs), which contain extracellular immunoglobulin-like domains from LAIR1 or LILRB1, constitutes a significant step forward in comprehending the reactivity of the Plasmodium parasite. These antibodies arise from unique B cell clones and demonstrate extensive cross-reactivity through their interaction with P. falciparum RIFINs. LAIR1 and LILRBs are specialized type I transmembrane glycoproteins, classified as immune inhibitory receptors, restricted to primates and mainly found on hematopoietic cells. They are instrumental in modulating interactions within the tumor microenvironment and across the immune system, and are increasingly recognized as important in anti-cancer immunotherapy and pathogen defense. The presence of LAIR1/LILRB1-containing antibodies offers new insights into malaria parasite evasion strategies and the immune system's response. Additionally, the innovative method of integrating extra exons into the antibody switch region is a noteworthy advancement, enriching the strategies for the generation of a varied array of bispecific and multispecific antibodies.

Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1.

BACKGROUND: Major depression disorder (MDD) forms a common psychiatric comorbidity among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often overlooked by neurologists. Currently, there is a lack of effective methods for accurately predicting MDD in patients with NT1. OBJECTIVE: This study utilized machine learning (ML) algorithms to identify critical variables and developed the prediction model for predicting MDD in patients with NT1. METHODS: The study included 267 NT1 patients from four sleep centers. The diagnosis of comorbid MDD was based on Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5). ML models, including six full models and six compact models, were developed using a training set. The performance of these models was compared in the testing set, and the optimal model was evaluated in the testing set. Various evaluation metrics, such as Area under the receiver operating curve (AUC), precision-recall (PR) curve and calibration curve were employed to assess and compare the performance of the ML models. Model interpretability was demonstrated using SHAP. RESULT: In the testing set, the logistic regression (LG) model demonstrated superior performance compared to other ML models based on evaluation metrics such as AUC, PR curve, and calibration curve. The top eight features used in the LG model, ranked by feature importance, included social impact scale (SIS) score, narcolepsy severity scale (NSS) score, total sleep time, body mass index (BMI), education years, age of onset, sleep efficiency, sleep latency. CONCLUSION: The study yielded a straightforward and practical ML model for the early identification of MDD in patients with NT1. A web-based tool for clinical applications was developed, which deserves further verification in diverse clinical settings.

Exosomes derived from M2 macrophages prevent steroid-induced osteonecrosis of the femoral head by modulating inflammation, promoting bone formation and inhibiting bone resorption.

Inflammatory reactions are involved in the development of steroid-induced osteonecrosis of the femoral head(ONFH). Studies have explored the therapeutic efficacy of inhibiting inflammatory reactions in steroid-induced ONFH and revealed that inhibiting inflammation may be a new strategy for preventing the development of steroid-induced ONFH. Exosomes derived from M2 macrophages(M2-Exos) display anti-inflammatory properties. This study aimed to examine the preventive effect of M2-Exos on early-stage steroid-induced ONFH and explore the underlying mechanisms involved. In vitro, we explored the effect of M2-Exos on the proliferation and osteogenic differentiation of bone marrow-derived mesenchymal stem cells(BMMSCs). In vivo, we investigated the role of M2-Exos on inflammation, osteoclastogenesis, osteogenesis and angiogenesis in an early-stage rat model of steroid-induced ONFH. We found that M2-Exos promoted the proliferation and osteogenic differentiation of BMMSCs. Additionally, M2-Exos effectively attenuated the osteonecrotic changes, inhibited the expression of proinflammatory mediators, promoted osteogenesis and angiogenesis, reduced osteoclastogenesis, and regulated the polarization of M1/M2 macrophages in steroid-induced ONFH. Taken together, our data suggest that M2-Exos are effective at preventing steroid-induced ONFH. These findings may be helpful for providing a potential strategy to prevent the development of steroid-induced ONFH.

A pancreatic cancer organoid-in-matrix platform shows distinct sensitivities to T cell killing.

Poor treatment responses of pancreatic ductal adenocarcinoma (PDAC) are in large part due to tumor heterogeneity and an immunosuppressive desmoplastic tumor stroma that impacts interactions with cells in the tumor microenvironment (TME). Thus, there is a pressing need for models to probe the contributions of cellular and noncellular crosstalk. Organoids are promising model systems with the potential to generate a plethora of data including phenotypic, transcriptomic and genomic characterization but still require improvements in culture conditions mimicking the TME. Here, we describe an INTERaction with Organoid-in-MatriX ("InterOMaX") model system, that presents a 3D co-culture-based platform for investigating matrix-dependent cellular crosstalk. We describe its potential to uncover new molecular mechanisms of T cell responses to murine KPC (LSL-KrasG12D/+27/Trp53tm1Tyj/J/p48Cre/+) PDAC cells as well as PDAC patient-derived organoids (PDOs). For this, a customizable matrix and homogenously sized organoid-in-matrix positioning of cancer cells were designed based on a standardized agarose microwell chip array system and established for co-culture with T cells and inclusion of stromal cells. We describe the detection and orthogonal analysis of murine and human PDAC cell populations with distinct sensitivity to T cell killing that is corroborated in vivo. By enabling both identification and validation of gene candidates for T cell resistance, this platform sets the stage for better mechanistic understanding of cancer cell-intrinsic resistance phenotypes in PDAC.

Fever-induced acute sleep terrors in children and adolescents following SARS-CoV-2 infection.

OBJECTIVE: This study aims to provide physicians with insights into the clinical manifestations and outcomes of children and young adolescents experiencing sleep terrors following SARS-CoV-2 infection. METHODS: We enrolled patients who developed new onset sleep terrors after SARS-CoV-2infection fromDecember2022to April 2023 in the Xijing hospital, Xi'an, China. RESULTS: We enrolled six patients who experienced sleep terrors following SARS-CoV-2 infection. Out of these patients, five were children and only one was an adolescent, with a mean age of 9 years. Neuroimaging results were negative for all cases. Sleep terrors occurred during both the active course of COVID-19 illness and the recovery period in all patients. Symptoms included crying or screaming in terror, hyperactivity, inappropriate behavior and periods of mental confusion during sleep. These episodes typically occurred 40 min to 1 h after falling asleep. EEG monitoring confirmed two patients' episodes occurred during non-rapid eye movement (NREM) stage 3 sleep. The duration of sleep terrors ranged from 3mines to30 mines, with each patient experiencing 3-4 to 30-40 instances. Initially, the frequency of episodes was highest at 3-4 times per night, gradually decreasing to once a night, then once a week, until complete disappearance. No medical intervention was required. Clinical follow-up ranged from 6 to 12 months, with spontaneous remission occurring within 1 week to 2 months for different patients. CONCLUSION: SARS-CoV-2 infection may precipitate acute sleep terrors in children and adolescents. The course of these sleep terrors is generally benign, with all patients achieving spontaneous complete remission over time.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

ResDAC-Net: a novel pancreas segmentation model utilizing residual double asymmetric spatial kernels.

The pancreas not only is situated in a complex abdominal background but is also surrounded by other abdominal organs and adipose tissue, resulting in blurred organ boundaries. Accurate segmentation of pancreatic tissue is crucial for computer-aided diagnosis systems, as it can be used for surgical planning, navigation, and assessment of organs. In the light of this, the current paper proposes a novel Residual Double Asymmetric Convolution Network (ResDAC-Net) model. Firstly, newly designed ResDAC blocks are used to highlight pancreatic features. Secondly, the feature fusion between adjacent encoding layers fully utilizes the low-level and deep-level features extracted by the ResDAC blocks. Finally, parallel dilated convolutions are employed to increase the receptive field to capture multiscale spatial information. ResDAC-Net is highly compatible to the existing state-of-the-art models, according to three (out of four) evaluation metrics, including the two main ones used for segmentation performance evaluation (i.e., DSC and Jaccard index).

Tongue Biting Event in Patients with Sleep-Related Facial Mandibular Myoclonus: A Case Series Study.

Background: Sleep-related facial mandibular myoclonus (SRFMM) remains rare in clinical practice. The aim of this study was to provide a comprehensive understanding of the electroclinical manner, therapeutic regimen, and prognosis of SRFMM. Methods: Twenty-three patients who were diagnosed with SRFMM by clinical manifestation, video-electroencephalography (EEG) and electromyography over bilateral masseter and temporalis muscles were enrolled. Clinical and electrophysiological evaluation as well as follow-up information were recorded and analyzed. Results: The cohort involved 4 infants and 19 adults with a mean onset age of 43.5 years for SRFMM, among whom 19 were male. Twenty-one patients complained of tongue injuries and disturbed night-time sleep. SRFMM in 4 patients were ascribed to oral aripiprazole, brainstem ischemia and brain trauma. In 62 SRFMM episodes, 93.5% occurred in NREM sleep and 6.5% in REM sleep, and all events were associated with EEG arousals. In 13 patients with or without clonazepam, the motor events gradually disappeared, and the rest turned to be sporadic. Conclusion: SRFMM is a characteristic parasomnia manifested by tongue biting and accompanying facial mandibular myoclonus, leading to disrupted sleep. Besides adults, infants can also experience SRFMM with spontaneous remission. Most patients respond well to clonazepam, eventually with favorable prognosis.

Adaptive metabolic response to short-term intensive fasting.

BACKGROUND & AIMS: Short-term intensive fasting (STIF), known as beego in Chinese phonetic articulation, has been practiced for more than two thousand years. However, the potential risk of STIF and the body's response to the risk have not been adequately evaluated. This study aims to address this issue, focusing on the STIF-triggered metabolic response of the liver and kidney. METHODS: The STIF procedure in the clinical trial includes a 7-day water-only intensive fasting phase and a 7-day gradual refeeding phase followed by a regular diet. The intensive fasting in humans was assisted with psychological induction. To gain insights not available in the clinical trial, we designed a STIF program for mice that resulted in similar phenotypes seen in humans. Plasma metabolic profiling and examination of gene expression as well as liver and kidney function were performed by omics, molecular, biochemical and flow cytometric analyses. A human cell line model was also used for mechanistic study. RESULTS: Clinically significant metabolites of fat and protein were found to accumulate during the fasting phase, but they were relieved after gradual refeeding. Metabolomics profiling revealed a universal pattern in the consumption of metabolic intermediates, in which pyruvate and succinate are the two key metabolites during STIF. In the STIF mouse model, the accumulation of metabolites was mostly counteracted by the upregulation of catabolic enzymes in the liver, which was validated in a human cell model. Kidney filtration function was partially affected by STIF but could be recovered by refeeding. STIF also reduced oxidative and inflammatory levels in the liver and kidney. Moreover, STIF improved lipid metabolism in mice with fatty liver without causing accumulation of metabolites after STIF. CONCLUSIONS: The accumulation of metabolites induced by STIF can be relieved by spontaneous upregulation of catabolic enzymes, suggesting an adaptive and protective metabolic response to STIF stress in the mammalian body.

The Role of High Mobility Group Box B-1 in the Prognosis of Colorectal Cancer Based on the Changes in the Intestinal Mucosal Barrier.

Background: To investigate the expression of high mobility group box B-1 (HMGB-1) in patients with colorectal cancer (CRC) and its association with clinicopathological features and prognosis in colorectal carcinoma by combining bioinformatics and clinical data analysis, and to clarify the role of HMGB-1. To examine whether HMGB-1 expression is related to the damage of the intestinal mucosal barrier, and then explore the potential HMGB-1-dependent mechanisms affecting the progression of CRC. Methods: CRC datasets of GSE12945, GSE17536, and GSE17537 from the public gene chip database were screened and downloaded. Clinical information and CRC tissue samples from patients with stage I-III CRC from the hospital were collected. Serum samples of patients were applied by enzyme-linked immunosorbent assay on HMGB-1, and were divided into high and low HMGB-1 expression, which was examined by 16S rDNA sequencing. Immunohistochemistry was performed to examine the relationship between the expression of HMGB-1 and tight junction protein, occludin, tumor necrosis factor-α, and interferon-γ. Results: Based on the Cutoff value of 10.24 ng/mL, the CRC patients were divided into high and low expression groups. In the HMGB-1H patient group, the TNM staging, overall survival, disease-free survival, recurrence, and metastasis were inferior to the HMGB-1L group. The results of 16S rDNA sequencing demonstrated that the Providencia genus was found to be enriched in the HMGB-1L group. Immunohistochemical results showed that HMGB-1 expression was negatively correlated with the expression of ZO-1 and occludin (R = 0.035, R = 0.003, P < .05), but was positively correlated with the expression of TNF-α and IFN-γ (R = 0.016, R = 0.001, P < .05). Conclusion: The survival of CRC patients with positive HMGB-1 expression was significantly shortened, which may be related to the decrease of Rovitensis content, the decreased expression of ZO-1 and occludin, and the increased levels of TNF-α and IFN-γ, which in turn damage the intestinal mucosal barrier, leading to the development of CRC.

COLOCdb: a comprehensive resource for multi-model colocalization of complex traits.

Large-scale genome-wide association studies (GWAS) have provided profound insights into complex traits and diseases. Yet, deciphering the fine-scale molecular mechanisms of how genetic variants manifest to cause the phenotypes remains a daunting task. Here, we present COLOCdb (https://ngdc.cncb.ac.cn/colocdb), a comprehensive genetic colocalization database by integrating more than 3000 GWAS summary statistics and 13 types of xQTL to date. By employing two representative approaches for the colocalization analysis, COLOCdb deposits results from three key components: (i) GWAS-xQTL, pair-wise colocalization between GWAS loci and different types of xQTL, (ii) GWAS-GWAS, pair-wise colocalization between the trait-associated genetic loci from GWASs and (iii) xQTL-xQTL, pair-wise colocalization between the genetic loci associated with molecular phenotypes in xQTLs. These results together represent the most comprehensive colocalization analysis, which also greatly expands the list of shared variants with genetic pleiotropy. We expect that COLOCdb can serve as a unique and useful resource in advancing the discovery of new biological mechanisms and benefit future functional studies.

PharmGWAS: a GWAS-based knowledgebase for drug repurposing.

Leveraging genetics insights to promote drug repurposing has become a promising and active strategy in pharmacology. Indeed, among the 50 drugs approved by FDA in 2021, two-thirds have genetically supported evidence. In this regard, the increasing amount of widely available genome-wide association studies (GWAS) datasets have provided substantial opportunities for drug repurposing based on genetics discoveries. Here, we developed PharmGWAS, a comprehensive knowledgebase designed to identify candidate drugs through the integration of GWAS data. PharmGWAS focuses on novel connections between diseases and small-molecule compounds derived using a reverse relationship between the genetically-regulated expression signature and the drug-induced signature. Specifically, we collected and processed 1929 GWAS datasets across a diverse spectrum of diseases and 724 485 perturbation signatures pertaining to a substantial 33609 molecular compounds. To obtain reliable and robust predictions for the reverse connections, we implemented six distinct connectivity methods. In the current version, PharmGWAS deposits a total of 740 227 genetically-informed disease-drug pairs derived from drug-perturbation signatures, presenting a valuable and comprehensive catalog. Further equipped with its user-friendly web design, PharmGWAS is expected to greatly aid the discovery of novel drugs, the exploration of drug combination therapies and the identification of drug resistance or side effects. PharmGWAS is available at https://ngdc.cncb.ac.cn/pharmgwas.

Seed Germination and Growth Improvement for Early Maturing Pear Breeding.

Breeding early maturing cultivars is one of the most important objectives in pear breeding. Very early maturing pears provide an excellent parental material for crossing, but the immature embryo and low seed germination of their hybrid progenies often limit the selection and breeding of new early maturing pear cultivars. In this study, we choose a very early maturing pear cultivar 'Pearl Pear' as the study object and investigate the effects of cold stratification, the culture medium, and the seed coat on the germination and growth of early maturing pear seeds. Our results show that cold stratification (4 °C) treatment could significantly improve the germination rates of early maturing pear seeds. A total of 100 days of cold-temperature treatment in 4 °C and in vitro germination on White medium increased the germination rate to 84.54%. We also observed that seed coat removal improved the germination of early maturing pear seeds, with middle seed coat removal representing the optimal method, with a high germination rate and low contamination. The results of our study led to the establishment of an improved protocol for the germination of early maturing pear, which will greatly facilitate the breeding of new very early maturing pear cultivars.

CircUsp9x/miR-599/stim1 axis regulates proliferation and migration in vascular smooth muscle cells induced by oxidized-low density lipoprotein.

Circular RNAs (circRNAs) regulate the function of vascular smooth muscle cells (VSMCs) in atherosclerosis (AS) progression. We aimed to explore the role of circUSP9X in oxidized low-density lipoprotein (ox-LDL)-induced VSMCs. Cell proliferation was assessed using cell counting kit-8 and EDU assays. Cell migration was evaluated using Transwell and wound healing assays. The interaction between circUSP9X or STIM1 and miR-599 was analyzed using dual-luciferase reporter and RNA pull-down assays. Their levels were examined using quantitative real-time PCR. CircUSP9X and STIM1 expression was increased, whereas miR-599 expression was reduced in the serum of patients with AS and ox-LDL-stimulated VSMCs. Overexpression of circUSP9X facilitated the proliferation and migration of VSMCs induced by ox-LDL. CircUSP9X sponged miR-599, which targeted STIM1. MiR-599 reversed the effects induced by circUSP9X, and STIM1 reversed the effects induced by miR-599. Taken together, CircUSP9X promoted proliferation and migration in ox-LDL-treated VSMCs via the miR-599/STIM1 axis, providing a theoretical basis for the role of circUSP9X/miR-599/STIM1 axis in AS.

Expanded Salinity Window of Middle-Phase Microemulsions and Reduced Surfactant Adsorption by Hydrotrope.

Using surfactant blends to mobilize residual oil offers a promising technique for enhanced oil recovery (EOR) and surfactant-enhanced aquifer remediation (SEAR). A major financial setback for broader application of this method is the loss of surfactants, as they get absorbed onto reservoir mineral surfaces. This loss becomes even more costly in oil fields with high-salinity formation water. Our research delved into the use of hydrotropes to minimize the surfactant absorption. The impacts of surfactant adsorption with hydrotrope additives were quantified and compared to three representative porous media. Initial tests studied the ideal salinity range influenced by hydrotropes with the observations of Winsor Type III microemulsions with selected surfactants, and four specific hydrocarbons were confirmed through interfacial tension measurements. When tested on three types of porous media, the presence of hydrotropes reduced the adsorption rates: up to 65% on Indiana limestone, 21% on Ottawa sand, and 53% on activated carbon. Notably, our study revealed urea's role in reducing surfactant retention in porous media. This discovery can help modify the salinity range of middle-phase microemulsions, which is crucial for EOR by easing salinity constraints of target reservoirs. The large middle-phase microemulsion window is also very advantageous for other potential applications. Moreover, urea proves to be more effective than typical sacrificial agents for reservoirs, as it binds the surfactant to the liquid rather than acting as a mere sacrificial component. Our research underscores the potential of improving surfactant flooding results by integrating hydrotropes, offering substantial cost savings in surfactant consumption and enhancing the overall efficiency of EOR and SEAR projects.

Sudden unexpected death in epilepsy disclosure causes anxiety in patients with epilepsy: a Chinese questionnaire survey.

Background and objective: Sudden unexpected death in epilepsy (SUDEP) has been regarded as a leading cause of premature death in patients with epilepsy (PWE). Although patients, relatives and caregivers have the right to be informed of SUDEP, neurologists prefer not to release the facts for fear of associated anxiety. In the study, a Chinese questionnaire survey was carried out to elucidate effect of SUDEP disclosure on anxiety in PWE and variables determining the anxiety of patients and provided suggestions for SUDEP disclosure. Methods: A survey study in China was conducted. We recruited 305 PWE from 3 tertiary epilepsy centers who attended outpatient clinic from December 2021 to February 2022. Two hundred and thirty-two PWE completed the screening evaluation, survey and Hamilton anxiety rating scale (HAMA) twice with 171 PWE completing third HAMA at follow-up. HAMA scores at baseline, T1, T2 were compared using analysis of variance and dependent samples t-test. The variables related to anxiety were screened out by univariate analysis and used for multivariate logistic regression. Result: We found 127 (54.7%) among the 232 participants experienced anxiety after SUDEP disclosure. HAMA scores at T1 were significantly higher than at baseline and T2, while there was no statistical difference between baseline and T2. Medical insurance, seizure severity, and whether the PWE supported SUDEP being disclosed to their relatives and caregivers only were associated with the occurrence of anxiety. Conclusion: SUDEP disclosures may cause short-term acute anxiety, but have no long-term effects in PWE. Acute anxiety caused by SUDEP disclosure may be more common in PWE with NCMI and severe seizures. Meanwhile, compared with indirect SUDEP disclosure to their relatives and caregivers, direct SUDEP disclosure to PWE reduces the risk of anxiety. Recommendations are provided to avoid anxiety caused by SUDEP disclosure.

Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management.

Patients diagnosed with cancer face an increased risk of cardiovascular events in the short term, while those experiencing acute myocardial infarction (AMI) have a higher incidence of cancer. Given limitations in clinical resources, identifying shared biomarkers offers a cost-effective approach to risk assessment by minimizing the need for multiple tests and screenings. Hence, it is crucial to identify common biomarkers for both cancer survival and AMI prediction. Our study suggests that monocyte-derived biomarkers, specifically WEE1, PYHIN1, SEC61A2, and HAL, hold potential as predictors for cancer prognosis and AMI. We employed a novel formula to analyze mRNA levels in clinical samples from patients with AMI and cancer, resulting in the development of a new risk score based on expression profiles. By categorizing patients into high-risk and low-risk groups based on the median risk score, we observed significantly poorer overall survival among high-risk patients in cancer cohorts using Kaplan-Meier analysis. Furthermore, calibration curves, decision curve analysis (DCA), and clinical impact curve analyses provided additional evidence supporting the robust diagnostic capacity of the risk score for AMI. Noteworthy is the shared activation of the Notch Signaling pathway, which may shed light on common high-risk factors underlying both AMI and cancer. Additionally, we validated the differential expression of these genes in cell lines and clinical samples, respectively, reinforcing their potential as meaningful biomarkers. In conclusion, our study demonstrates the promise of mRNA levels as biomarkers and emphasizes the significance of further research for validation and refinement.