Optimizing hydropower scheduling through accurate power load prediction: A practical case study.

Hydropower stations that are part of the grid system frequently encounter challenges related to the uneven distribution of power generation and associated benefits, primarily stemming from delays in obtaining timely load data. This research addresses this issue by developing a scheduling model that combines power load prediction and dual-objective optimization. The practical application of this model is demonstrated in a real-case scenario, focusing on the Shatuo Hydropower Station in China. In contrast to current models, the suggested model can achieve optimal dispatch for grid-connected hydropower stations even when power load data is unavailable. Initially, the model assesses various prediction models for estimating power load and subsequently incorporates the predictions into the GA-NSGA-II algorithm, specifically an enhanced elite non-dominated sorting genetic algorithm. This integration is performed while considering the proposed objective functions to optimize the discharge flow of the hydropower station. The outcomes reveal that the CNN-GRU model, denoting Convolutional Neural Network-Gated Recursive Unit, exhibits the highest prediction accuracy, achieving R-squared and RMSE (i.e., Root Mean Square Error) values of 0.991 and 0.026, respectively. The variance between scheduling based on predicted load values and actual load values is minimal, staying within 5 (m3/s), showcasing practical effectiveness. The optimized scheduling outcomes in the real case study yield dual advantages, meeting both the demands of ship navigation and hydropower generation, thus achieving a harmonious balance between the two requirements. This approach addresses the real-world challenges associated with delayed load data collection and insufficient scheduling, offering an efficient solution for managing hydropower station scheduling to meet both power generation and navigation needs.

The Burgeoning Significance of Liquid-Liquid Phase Separation in the Pathogenesis and Therapeutics of Cancers.

Liquid-liquid phase separation (LLPS) is a physiological phenomenon that parallels the mixing of oil and water, giving rise to compartments with diverse physical properties. Biomolecular condensates, arising from LLPS, serve as critical regulators of gene expression and control, with a particular significance in the context of malignant tumors. Recent investigations have unveiled the intimate connection between LLPS and cancer, a nexus that profoundly impacts various facets of cancer progression, including DNA repair, transcriptional regulation, oncogene expression, and the formation of critical membraneless organelles within the cancer microenvironment. This review provides a comprehensive account of the evolution of LLPS from the molecular to the pathological level. We explore the mechanisms by through which biomolecular condensates govern diverse cellular physiological processes, encompassing gene expression, transcriptional control, signal transduction, and responses to environmental stressors. Furthermore, we concentrate on potential therapeutic targets and the development of small-molecule inhibitors associated with LLPS in prevalent clinical malignancies. Understanding the role of LLPS and its interplay within the tumor milieu holds promise for enhancing cancer treatment strategies, particularly in overcoming drug resistance challenges. These insights offer innovative perspectives and support for advancing cancer therapy.

NeRF-NQA: No-Reference Quality Assessment for Scenes Generated by NeRF and Neural View Synthesis Methods.

Neural View Synthesis (NVS) has demonstrated efficacy in generating high-fidelity dense viewpoint videos using a image set with sparse views. However, existing quality assessment methods like PSNR, SSIM, and LPIPS are not tailored for the scenes with dense viewpoints synthesized by NVS and NeRF variants, thus, they often fall short in capturing the perceptual quality, including spatial and angular aspects of NVS-synthesized scenes. Furthermore, the lack of dense ground truth views makes the full reference quality assessment on NVS-synthesized scenes challenging. For instance, datasets such as LLFF provide only sparse images, insufficient for complete full-reference assessments. To address the issues above, we propose NeRF-NQA, the first no-reference quality assessment method for densely-observed scenes synthesized from the NVS and NeRF variants. NeRF-NQA employs a joint quality assessment strategy, integrating both viewwise and pointwise approaches, to evaluate the quality of NVS-generated scenes. The viewwise approach assesses the spatial quality of each individual synthesized view and the overall inter-views consistency, while the pointwise approach focuses on the angular qualities of scene surface points and their compound inter-point quality. Extensive evaluations are conducted to compare NeRF-NQA with 23 mainstream visual quality assessment methods (from fields of image, video, and light-field assessment). The results demonstrate NeRF-NQA outperforms the existing assessment methods significantly and it shows substantial superiority on assessing NVS-synthesized scenes without references. An implementation of this paper are available at https://github.com/VincentQQu/NeRF-NQA.

Few-Shot Relation Extraction With Automatically Generated Prompts.

Relation extraction (RE) tends to struggle when the supervised training data is few and difficult to be collected. In this article, we elicit relational and factual knowledge from large pretrained language models (PLMs) for few-shot RE (FSRE) with prompting techniques. Concretely, we automatically generate a diverse set of natural language templates and modulate PLM's behavior through these prompts for FSRE. To mitigate the template bias which leads to unstableness of few-shot learning, we propose a simple yet effective template regularization network (TRN) to prevent deep networks from over-fitting uncertain templates and thus stabilize the FSRE models. TRN alleviates the template bias with three mechanisms: 1) an attention mechanism over mini-batch to weight each template; 2) a ranking regularization mechanism to regularize the attention weights and constrain the importance of uncertain templates; and 3) a template calibration module with two calibrating techniques to modify the uncertain templates in the lowest-ranked group. Experimental results on two benchmark datasets (i.e., FewRel and NYT) show that our model has robust superiority over strong competitors. For reproducibility, we will release our code and data upon the publication of this article.

Effects of Fe-N co-modified biochar on methanogenesis performance, microbial community, and metabolic pathway during anaerobic co-digestion of alternanthera philoxeroides and cow manure.

The performance of anaerobic digestion (AD) is susceptible to disturbances in feedstock degradation, intermediates accumulation, and methanogenic archaea activity. To improve the methanogenesis performance of the AD system, Fe-N co-modified biochar was prepared under different pyrolysis temperatures (300,500, and 700 °C). Meanwhile, pristine and Fe-modified biochar were also derived from alternanthera philoxeroides (AP). The aim was to compare the effects of Fe-N co-modification, Fe modification, and pristine biochar on the methanogenic performance and explicit the responding mechanism of the microbial community in anaerobic co-digestion (coAD) of AP and cow manure (CM). The highest cumulative methane production was obtained with the addition of Fe-N-BC500 (260.38 mL/gVS), which was 42.37 % higher than the control, while the acetic acid, propionic acid, and butyric acid concentration of Fe-N-BC were increased by 147.58 %, 44.25 %, and 194.06 % compared with the control, respectively. The co-modified biochar enhanced the abundance of Chloroflexi and Methanosarcina in the AD system. Metabolic pathway analysis revealed that the increased methane production was related to the formation and metabolism of volatile fatty acids and that Fe-N-BC500 enhanced the biosynthesis of coenzyme A and the cell activity of microorganisms, accelerating the degradation of propionic acid and enhancing the hydrogenotrophic methanogenesis pathway. Overall, Fe-N co-modified biochar was proved to be an effective promoter for accelerated methane production during AD.

Personalized application of antimicrobial drugs in pediatric patients with augmented renal clearance: a review of literature.

The effect of renal functional status on drug metabolism is a crucial consideration for clinicians when determining the appropriate dosage of medications to administer. In critically ill patients, there is often a significant increase in renal function, which leads to enhanced drug metabolism and potentially inadequate drug exposure. This phenomenon, known as augmented renal clearance (ARC), is commonly observed in pediatric critical care settings. The findings of the current study underscore the significant impact of ARC on the pharmacokinetics and pharmacodynamics of antimicrobial drugs in critically ill pediatric patients. Moreover, the study reveals a negative correlation between increased creatinine clearance and blood concentrations of antimicrobial drugs. The article provides a comprehensive review of ARC screening in pediatric patients, including its definition, risk factors, and clinical outcomes. Furthermore, it summarizes the dosages and dosing regimens of commonly used antibacterial and antiviral drugs for pediatric patients with ARC, and recommendations are made for dose and infusion considerations and the role of therapeutic drug monitoring. CONCLUSION:  ARC impacts antimicrobial drugs in pediatric patients. WHAT IS KNOWN: • ARC is inextricably linked to the failure of antimicrobial therapy, recurrence of infection, and subtherapeutic concentrations of drugs. WHAT IS NEW: • This study provides an updated overview of the influence of ARC on medication use and clinical outcomes in pediatric patients. • In this context, there are several recommendations for using antibiotics in pediatric patients with ARC: 1) increase the dose administered; 2) prolonged or continuous infusion administration; 3) use of TDM; and 4) use alternative drugs that do not undergo renal elimination.

Association of flavonoid intake with coronary artery disease risk in the older population based on the National Health and Nutrition Examination Survey.

We investigated the association between flavonoid intake and coronary artery disease (CAD) risk in older adults. Data were extracted from the National Health and Nutrition Examination Survey (age ≥ 70 years; 2007-2010 and 2017-2018; n = 2 417). The total flavonoid and flavonoid subclass intake was calculated using validated food frequency questionnaires. The association between flavonoid intake and CAD risk was examined using generalized linear models with restricted cubic spline models. After multivariate adjustment, anthocyanin intake was positively associated with CAD risk; no significant associations were observed between other flavonoid subcategories and endpoint outcomes. Anthocyanins exhibited a non-linear association with CAD risk, and threshold effect analysis showed an inflection point of 15.8 mg/day for anthocyanins. Per unit increase in anthocyanins, the odds of CAD on the left of the inflection point decreased by 2%, while the odds on the right increased by 35.8%. Excessive flavonoid intake may increase CAD risk in the older population.

Equilibrative nucleotide transporter ENT3 (SLC29A3): A unique transporter for inherited disorders and cancers.

As a crucial gene associated with diseases, the SLC29A3 gene encodes the equilibrative nucleoside transporter 3 (ENT3). ENT3 plays an essential regulatory role in transporting intracellular hydrophilic nucleosides, nucleotides, hydrophilic anticancer and antiviral nucleoside drugs, energy metabolism, subcellular localization, protein stability, and signal transduction. The mutation and inactivation of SLC29A3 are intimately linked to the occurrence, development, and prognosis of various human tumors. Moreover, many hereditary human diseases, such as H syndrome, pigmentary hypertrichosis and non-autoimmune insulin-dependent diabetes mellitus (PHID) syndrome, Faisalabad histiocytosis (FHC), are related to SLC29A3 mutations. This review explores the mechanisms of SLC29A3 mutations and expression alterations in inherited disorders and cancers. Additionally, we compile studies on the inhibition of ENT3, which may serve as an effective strategy to potentiate the anticancer activity of chemotherapy. Thus, the synopsis of genetics, permeant function and drug therapy of ENT3 provides a new theoretical and empirical foundation for the diagnosis, prognosis of evaluation and treatment of various related diseases.

Room-Temperature Synthesis of Carbon-Nanotube-Interconnected Amorphous NiFe-Layered Double Hydroxides for Boosting Oxygen Evolution Reaction.

The oxygen evolution reaction (OER) is a key half-reaction in electrocatalytic water splitting. Large-scale water electrolysis is hampered by commercial noble-metal-based OER electrocatalysts owing to their high cost. To address these issues, we present a facile, one-pot, room-temperature co-precipitation approach to quickly synthesize carbon-nanotube-interconnected amorphous NiFe-layered double hydroxides (NiFe-LDH@CNT) as cost-effective, efficient, and stable OER electrocatalysts. The hybrid catalyst NiFe-LDH@CNT delivered outstanding OER activity with a low onset overpotential of 255 mV and a small Tafel slope of 51.36 mV dec-1, as well as outstanding long-term stability. The high catalytic capability of NiFe-LDH@CNT is associated with the synergistic effects of its room-temperature synthesized amorphous structure, bi-metallic modulation, and conductive CNT skeleton. The room-temperature synthesis can not only offer economic feasibility, but can also allow amorphous NiFe-LDH to be obtained without crystalline boundaries, facilitating long-term stability during the OER process. The bi-metallic nature of NiFe-LDH guarantees a modified electronic structure, providing additional catalytic sites. Simultaneously, the highly conductive CNT network fosters a nanoporous structure, facilitating electron transfer and O2 release and enriching catalytic sites. This study introduces an innovative approach to purposefully design nanoarchitecture and easily synthesize amorphous transition-metal-based OER catalysts, ensuring their cost effectiveness, production efficiency, and long-term stability.

Hydropower station scheduling with ship arrival prediction and energy storage.

Effectiveness improvement in power generation and navigation for grid-connected hydropower stations have emerged as a significant concern due to the challenges such as discrepancies between declared and actual ship arrival times, as well as unstable power generation. To address these issues, this paper proposes a multi-objective real-time scheduling model. The proposed model incorporates energy storage and ship arrival prediction. An energy storage mechanism is introduced to stabilize power generation by charging the power storage equipment during surplus generation and discharging it during periods of insufficient generation at the hydropower stations. To facilitate the scheduling with the eneragy storage mechanism, the arrival time of ships to the stations are predicted. We use the maximization of generation minus grid load demand and the maximization of navigability assurance rate as two objective functions in the scheduling process. The model uses the Non-Dominated Sorting Beluga Whale Optimization (NSBWO) algorithm to optimize and solve the real-time discharge flow scheduling of the hydropower stations in different time periods. The NSBWO algorithm combines the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) and the Beluga Whale Optimization (BWO). The experimental results show that the proposed method has advantages in predicting the expected arrival time of ships and scheduling the discharge flow. The prediction using XGBoost model reaches accuracy with more than 0.9, and the discharged flow obtained from scheduling meets the demand of hydropower stations grid load while also improves the navigation benefits. This study provides theoretical analysis with its practical applications in a real hyropower station as a case study for solving hydropower scheduling problems.

Association of Blood Trace Elements Levels with Cardiovascular Disease in US Adults: a Cross-Sectional Study from the National Health and Nutrition Examination Survey 2011-2016.

We aimed to explore the overall association between trace elements and cardiovascular disease (CVD) and its types in humans. A total of 5101 participants' blood samples from the 2011-2016 National Health and Nutrition Examination Survey were included. Biochemical data were collected from laboratory tests conducted at mobile screening centers. After assessing linearity, weighted logistic regression estimated the association between trace elements and various CVD types. Weighted quantile sum (WQS) regression and quantile-based g-computation (Qgcomp) evaluated the overall relationship between biological trace elements and CVD types. After fully adjusting for confounding factors, the odds ratios of overall CVD morbidity corresponding to the second, third, and fourth quartiles of higher selenium (Se) concentration were 0.711 (95% CI, 0.529-0.956, p = 0.024), 0.734 (95% CI, 0.546-0.987, p = 0.041), and 0.738 (95% CI, 0.554-0.983, p = 0.038), respectively. Moreover, an increase in the concentration of copper (Cu) was associated with an increased risk of stroke (95% CI, 1.012-1.094, p = 0.01), heart failure (95% CI, 1.001-1.095, p = 0.046), and heart attack (95% CI, 1.001-1.083, p = 0.046). As the concentration of trace elements in the body increased, there was a significant positive association between Cu and CVD prevalence. On the other hand, Se and zinc were negatively associated with CVD prevalence. A nonlinear relationship between Se and CVD was found, and an appropriate Se intake may reduce the risk of CVD. Cu levels positively correlated with CVD risk. However, prospective cohort studies are warranted to confirm the causal effects of the micronutrients on CVD and its types.

Low lean mass with obesity in older adults with hypertension: prevalence and association with mortality rate.

BACKGROUND: The influence of sarcopenic obesity (SO) on overall survival in older adults with hypertension has not been addressed. The aim of this study was to investigate the prevalence and mortality predictive value of various body composition phenotypes, focusing mainly on SO, in older adults with hypertension. METHODS: We included 1105 hypertensive patients aged ≥ 60 years from the National Health and Nutrition Examination Survey 1999-2004. Sarcopenia was broadly defined based on low lean mass (LLM; as measured by dual-energy X-ray absorptiometry), and was defined using appendicular lean mass (ALM) divided by height squared (ALM/height2), weight (ALM/weight), and body mass index (BMI; ALM/BMI), respectively. Obesity was defined as BMI ≥ 30 kg/m2, body fat percentage ≥ 30/42%, or waist circumference ≥ 102/88 cm. The prevalence of LLM with obesity was estimated according to each ALM index (ALMI). Multivariable Cox regression analysis and sensitivity analysis were used to examine the association between various body composition phenotypes and all-cause mortality. RESULTS: In older adults with hypertension, the prevalence of LLM with obesity by the ALM/height2 index (9.8%) was lower relative to the ALM/weight (11.7%) and ALM/BMI indexes (19.6%). After a median follow-up of 15.4 years, 642 deaths occurred. In the fully adjusted models, LLM with obesity was significantly associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.69, 95% confidence interval [CI] 1.14-2.49, P = 0.008; HR 1.48, 95% CI 1.04-2.10, P = 0.028; HR 1.30, 95% CI 1.02-1.66, P = 0.037; respectively) compared with the normal body phenotype, with no statistical differences found in individuals with LLM or obesity alone. Sensitivity analysis confirmed the robustness of the results. CONCLUSIONS: The prevalence of LLM with obesity markedly differed in older adults with hypertension according to the 3 different ALMIs, varying from 9.8%, 11.7%, to 19.6%. Patients with both LLM and obesity had a higher risk of all-cause mortality. Further large, prospective, cohort studies are warranted to validate these findings and uncover underlying mechanisms.

Corrigendum: Bibliometric analysis of evolutionary trends and hotspots of super-enhancers in cancer.

[This corrects the article DOI: 10.3389/fphar.2023.1192855.].

Integrated Bioinformatic Analyses Reveal Immune Molecular Markers and Regulatory Networks for Cerebral Ischemia-Reperfusion.

BACKGROUND: Cerebral ischemia-reperfusion injury (CIR) following a stroke results in secondary damage and is a leading cause of adult disability. The present study aimed to identify hub genes and networks in CIR to explore potential therapeutic agents for its treatment. METHODS: Differentially expressed genes based on the GSE23163 dataset were identified, and weighted gene co-expression network analysis was performed to explore co-expression modules associated with CIR. Hub genes were identified by intersecting immune gene profiles, differentially expressed genes, and modular genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, and transcription factor-microRNA-gene regulatory network analyses were then conducted in selected crucial modules. Subsequently, their expression levels in animal models were verified using real-time quantitative polymerase chain reaction and Western blotting. Finally, potential drug molecules were screened for, and molecular docking simulations were performed to identify potential therapeutic targets. RESULTS: Seven hub genes-namely, Ccl3, Ccl4, Ccl7, Cxcl1, Hspa1a, Cd14, and Socs3-were identified. Furthermore, we established a protein interaction network using the STRING database and found that the core genes selected through the cytohubba plugin remained consistent. Animal experiments showed that at the transcriptional level, all seven genes showed significant differences (p < 0.001, fold change vs sham, 5-200). At the translational level, however, only Ccl3, Ccl4, Ccl7, Hspa1a, and Socs3 showed significant differences, while Cxcl1 and Cd14 did not. Nifedipine, with the highest predicted score, was identified as a therapeutic agent and successfully docked with the protein encoded by the hub genes. CONCLUSIONS: The expression of Ccl3, Ccl4, Ccl7, Hspa1a, and Socs3 was significantly different in CIR tissues compared to normal tissues both at the transcriptional and translational levels. Systems biology approaches indicated that these could be possible CIR marker genes, providing a stepping stone for further experimental studies.

BO-DNA: Biologically optimized encoding model for a highly-reliable DNA data storage.

DNA data storage is a promising technology that utilizes computer simulation, and synthetic biology, offering high-density and reliable digital information storage. It is challenging to store massive data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the reliability of stored data. This study proposes a novel biologically optimized encoding model for DNA data storage (BO-DNA) to overcome the reliability problem. BO-DNA model is developed by a new rule-based mapping method to avoid data drop during the transcoding of binary data to premier nucleotides. A customized optimization algorithm based on a tent chaotic map is applied to maximize the lower bounds that help to minimize the nonspecific hybridization errors. The robustness of BO-DNA is computed by four bio-constraints to confirm the reliability of newly generated DNA sequences. Experimentally, different medical images are encoded and decoded successfully with 12%-59% improved lower bounds and optimally constrained-based DNA sequences reported with 1.77bit/nt average density. BO-DNA's results demonstrate substantial advantages in constructing reliable DNA data storage.

A complicated infection by cutaneous Nocardia wallacei and pulmonary Mycobacterium abscessus in a Chinese immunocompetent patient: a case report.

Nocardiosis is an infectious disease caused by Nocardia that primarily affects immunocompromised hosts. Mycobacterium abscessus is a common opportunistic pathogen that causes disease in humans, including pulmonary and extrapulmonary infection. Nocardia spp. infection is uncommon, and infection with Nocardia wallacei and Mycobacterium abscessus is even rarer. A 59-year-old immunocompetent woman with risk factors for environmental exposure developed nocardiosis and presented to the hospital with a cough, shortness of breath, hemoptysis, and a back abscess. An enhanced computed tomography (CT) of the chest revealed partial destruction of the right lung, as well as consolidation of the right upper lobe. Rare pathogens N. wallacei and Mycobacterium abscessus were detected by metagenomic next-generation sequencing (mNGS) from abscess on the back and lung puncture tissue, respectively. She was treated with a combination of antibiotics and was finally discharged with a good prognosis. In this case, we present a patient who was successfully diagnosed with N. wallacei and Mycobacterium abscessus infection using mNGS. This importance of using mNGS in pathogen detection and the effective use of antibiotics in treating patients with long-term rare infections is highlighted in this report.

Individualized antibiotic dosage regimens for patients with augmented renal clearance.

Objectives: Augmented renal clearance (ARC) is a state of enhanced renal function commonly observed in 30%-65% of critically ill patients despite normal serum creatinine levels. Using unadjusted standard dosing regimens of renally eliminated drugs in ARC patients often leads to subtherapeutic concentrations, poor clinical outcomes, and the emergence of multidrug-resistant bacteria. We summarized pharmaceutical, pharmacokinetic, and pharmacodynamic research on the definition, underlying mechanisms, and risk factors of ARC to guide individualized dosing of antibiotics and various strategies for optimizing outcomes. Methods: We searched for articles between 2010 and 2022 in the MEDLINE database about ARC patients and antibiotics and further provided individualized antibiotic dosage regimens for patients with ARC. Results: 25 antibiotic dosage regimens for patients with ARC and various strategies for optimization of outcomes, such as extended infusion time, continuous infusion, increased dosage, and combination regimens, were summarized according to previous research. Conclusion: ARC patients, especially critically ill patients, need to make individualized adjustments to antibiotics, including dose, frequency, and method of administration. Further comprehensive research is required to determine ARC staging, expand the range of recommended antibiotics, and establish individualized dosing guidelines for ARC patients.

Bibliometric analysis of evolutionary trends and hotspots of super-enhancers in cancer.

Introduction: In the past decade, super-enhancer (SE) has become a research hotspot with increasing attention on cancer occurrence, development, and prognosis. To illustrate the hotspots of SE in cancer research and its evolutionary tendency, bibliometric analysis was carried out for this topic. Methods: Literature published before Dec 31, 2022, in WOSCC, was systematically classified, and Citespace, bibliometric.com/app, and GraphPad Prism analyzed the data. Results: After screening out inappropriate documents and duplicate data, 911 publications were selected for further bibliometric analysis. The top five research areas were Oncology (257, 28.211%), Cell Biology (210, 23.052%), Biochemistry Molecular Biology (209, 22.942%), Science Technology Other Topics (138, 15.148%), and Genetics Heredity (132, 14.490%). The United States of America (United States) has the highest number of documents (462, 50.71%), followed by China (303, 33.26%). Among the most productive institutions, four of which are from the United States and one from Singapore, the National University of Singapore. Harvard Medical School (7.68%) has the highest percentage of articles. Young, Richard A, with 32 publications, ranks first in the number of articles. The top three authors came from Whitehead Institute for Biomedical Research as a research team. More than two-thirds of the research are supported by the National Institutes of Health of the United States (337, 37.654%) and the United States Department of Health Human Services (337, 37.654%). And "super enhancer" (525), "cell identity" (258), "expression" (223), "cancer" (205), and "transcription factor" (193) account for the top 5 occurrence keywords. Discussion: Since 2013, SE and cancer related publications have shown a rapid growth trend. The United States continues to play a leading role in this field, as the top literature numbers, affiliations, funding agencies, and authors were all from the United States, followed by China and European countries. A high degree of active cooperation is evident among a multitude of countries. The role of SEs in cell identity, gene transcription, expression, and inhibition, as well as the relationship between SEs and TFs, and the selective inhibition of SEs, have received much attention, suggesting that they are hot issues for research.

A rare case of giant hepatic angiomyolipoma with subcapsular rupture.

Hepatic angiomyolipoma (HAML) is a rare mesenchymal neoplasm that predominantly affects middle-aged women. In this study, we present a case of a 49-year-old woman with a giant HAML accompanied by spontaneous subcapsular rupture. The patient initially experienced nausea and abdominal distention, followed by an enlargement of the upper abdominal circumference. Laboratory examination revealed decreased serum hemoglobin, while tumor biomarkers were within normal ranges. Imaging studies, such as abdominal ultrasound and contrast-enhanced computed tomography (CT), demonstrated a large upper abdominal mass with heterogeneous density and hypervascularity. The tumor appeared to have invaded the left liver, raising concerns about possible malignancy. Subsequent positron-emission tomography/CT confirmed increased fluorodeoxyglucose uptake in the mass. Laparoscopic exploration revealed a protruding, well-encapsulated tumor from the left liver, exhibiting subcapsular hemorrhage. Surgical resection of the tumor and the left liver was performed, leading to a successful outcome.