A Cost-Effective Model for Predicting Recurrent Gastric Cancer Using Clinical Features.

This study used artificial intelligence techniques to identify clinical cancer biomarkers for recurrent gastric cancer survivors. From a hospital-based cancer registry database in Taiwan, the datasets of the incidence of recurrence and clinical risk features were included in 2476 gastric cancer survivors. We benchmarked Random Forest using MLP, C4.5, AdaBoost, and Bagging algorithms on metrics and leveraged the synthetic minority oversampling technique (SMOTE) for imbalanced dataset issues, cost-sensitive learning for risk assessment, and SHapley Additive exPlanations (SHAPs) for feature importance analysis in this study. Our proposed Random Forest outperformed the other models with an accuracy of 87.9%, a recall rate of 90.5%, an accuracy rate of 86%, and an F1 of 88.2% on the recurrent category by a 10-fold cross-validation in a balanced dataset. We identified clinical features of recurrent gastric cancer, which are the top five features, stage, number of regional lymph node involvement, Helicobacter pylori, BMI (body mass index), and gender; these features significantly affect the prediction model's output and are worth paying attention to in the following causal effect analysis. Using an artificial intelligence model, the risk factors for recurrent gastric cancer could be identified and cost-effectively ranked according to their feature importance. In addition, they should be crucial clinical features to provide physicians with the knowledge to screen high-risk patients in gastric cancer survivors as well.

Applying Object Detection and Large Language Model to Establish a Smart Telemedicine Diagnosis System with Chatbot: A Case Study of Pressure Injuries Diagnosis System.

Background: The scarcity of medical resources and personnel has worsened due to COVID-19. Telemedicine faces challenges in assessing wounds without physical examination. Evaluating pressure injuries is time consuming, energy intensive, and inconsistent. Most of today's telemedicine platforms utilize graphical user interfaces with complex operational procedures and limited channels for information dissemination. The study aims to establish a smart telemedicine diagnosis system based on YOLOv7 and large language model. Methods: The YOLOv7 model is trained using a clinical data set, with data augmentation techniques employed to enhance the data set to identify six types of pressure injury images. The established system features a front-end interface that includes responsive web design and a chatbot with ChatGPT, and it is integrated with a database for personal information management. Results: This research provides a practical pressure injury staging classification model with an average F1 score of 0.9238. The system remotely provides real-time accurate diagnoses and prescriptions, guiding patients to seek various medical help levels based on symptom severity. Conclusions: This study establishes a smart telemedicine auxiliary diagnosis system based on the YOLOv7 model, which possesses capabilities for classification and real-time detection. During teleconsultations, it provides immediate and accurate diagnostic information and prescription recommendations and seeks various medical assistance based on the severity of symptoms. Through the setup of a chatbot with ChatGPT, different users can quickly achieve their respective objectives.

General anesthesia is not associated with dementia in older adults with osteoarthritis for hip/knee replacements, a national population-based nested case-control study.

BACKGROUND: Dementia is a prevalent neurological condition, yet the relationship between dementia and general anesthesia remains uncertain. The study aimed to explore the association between general anesthesia and dementia using a nationwide population-based database. METHODS: The study extracted data from Taiwan's national health insurance, which encompassed the records of one million insured residents. A total of 59,817 patients aged 65 years and above, diagnosed with osteoarthritis between 2002 and 2010, were included. Among these patients, 3277 individuals with an initial diagnosis of dementia between 2004 and 2013 were matched with non-dementia patients based on age, gender, and the date of osteoarthritis diagnosis. Following a 1:2 random matching, the case group included 2171 patients with dementia, while the control group consisted of 4342 patients without dementia. The data was analyzed using conditional and unconditional logistic regressions. RESULTS: No significant differences in the odds of dementia were found between individuals exposed to general and regional anesthesia during hip/knee replacement surgeries (OR = 1.11; 95%CI: 0.73-1.70), after adjusting for age, sex, and co-morbidities. Similarly, there were no significant differences in the odds of dementia based on different durations of anesthesia exposure (General: <2 h: OR = 0.91, 95%CI = 0.43-1.92; 2-4 h: OR = 1.21, 95%CI = 0.82-1.79; >4 h: OR = 0.39, 95%CI = 0.15-1.01; compared to no exposure. Regional: <2 h: OR = 1.18, 95%CI = 0.85-1.62; 2-4 h: OR = 0.9, 95%CI = 0.64-1.27; >4 h: OR = 0.55, 95%CI = 0.15-1.96; compared to no exposure). Likewise, no significant differences were observed in the odds of dementia based on the number of replacement surgeries (twice: OR = 0.74, 95%CI = 0.44-1.23, compared to once). CONCLUSION: Neither general anesthesia nor regional anesthesia in hip/knee surgery was associated with dementia. Different numbers and durations of anesthesia exposure showed no significant differences in the odds for dementia.

Radiomic biomarkers for platinum-refractory head and neck cancer in the era of immunotherapy.

OBJECTIVE: Immune checkpoint inhibitors (ICI) are recommended as the first-line therapy for platinum-refractory head and neck squamous cell carcinoma (HNSCC), a disease with a poor prognosis. However, biomarkers in this situation are rare. The objective was to identify radiomic features-associated biomarkers to guide the prognosis and treatment opinions in the era of ICI. METHODS: A total of 31 platinum-refractory HNSCC patients were retrospectively enrolled. Of these, 65.5% (20/31) received ICI-based therapy and 35.5% (11/31) did not. Radiomic features of the primary site at the onset of recurrent metastatic (R/M) status were extracted. Prognostic and predictive radiomic biomarkers were analysed. RESULTS: The median overall survival from R/M status (R/M OS) was 9.6 months. Grey-level co-occurrence matrix-associated texture features were the most important in identifying the patients with or without 9-month R/M death. A radiomic risk-stratification model was established and equally separated the patients into high-, intermittent- and lower-risk groups (1-year R/M death rate, 100.0% vs. 70.8% vs. 27.1%, p = 0.001). Short-run high grey-level emphasis (SRHGE) was more suitable than programmed death ligand 1 (PD-L1) expression in selecting whether patients received ICI-based therapy. CONCLUSIONS: Radiomic features were effective prognostic and predictive biomarkers. Future studies are warranted.

Association of Late Radiographic Assessment of Lung Edema Score with Clinical Outcome in Patients with Influenza-Associated Acute Respiratory Distress Syndrome.

Background: Influenza virus infection leads to acute pulmonary injury and acute respiratory distress syndrome (ARDS). The Radiographic Assessment of Lung Edema (RALE) score has been proposed as a reliable tool for the evaluation of the opacity of chest X-rays (CXRs). This study aimed to examine the RALE scores and outcomes in patients with influenza-associated ARDS. Methods: Patients who were newly diagnosed with influenza-associated ARDS from December 2015 to March 2016 were enrolled. Two independent reviewers scored the CXRs obtained on the day of ICU admission and on days 2 and 7 after intensive care unit (ICU) admission. Results: During the study, 47 patients had influenza-associated ARDS. Five died within 7 days of ICU admission. Of the remaining 42, non-survivors (N = 12) had higher Sequential Organ Failure Assessment scores (SOFA) at ICU admission and higher day 7 RALE scores than survivors (N = 30). The day 7 RALE score independently related to late in-hospital mortality (aOR = 1.121, 95% CI: 1.014-1.240, p = 0.025). Conclusions: The RALE score for the evaluation of opacity on CXRs is a highly reproducible tool. Moreover, RALE score on day 7 was an independent predictor of late in-hospital mortality in patients with influenza-associated ARDS.

Implementing AI Models for Prognostic Predictions in High-Risk Burn Patients.

BACKGROUND AND OBJECTIVES: Burn injuries range from minor medical issues to severe, life-threatening conditions. The severity and location of the burn dictate its treatment; while minor burns might be treatable at home, severe burns necessitate medical intervention, sometimes in specialized burn centers with extended follow-up care. This study aims to leverage artificial intelligence (AI)/machine learning (ML) to forecast potential adverse effects in burn patients. METHODS: This retrospective analysis considered burn patients admitted to Chi Mei Medical Center from 2010 to 2019. The study employed 14 features, comprising supplementary information like prior comorbidities and laboratory results, for building models for predicting graft surgery, a prolonged hospital stay, and overall adverse effects. Overall, 70% of the data set trained the AI models, with the remaining 30% reserved for testing. Three ML algorithms of random forest, LightGBM, and logistic regression were employed with evaluation metrics of accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). RESULTS: In this research, out of 224 patients assessed, the random forest model yielded the highest AUC for predictions related to prolonged hospital stays (>14 days) at 81.1%, followed by the XGBoost (79.9%) and LightGBM (79.5%) models. Besides, the random forest model of the need for a skin graft showed the highest AUC (78.8%), while the random forest model and XGBoost model of the occurrence of adverse complications both demonstrated the highest AUC (87.2%) as well. Based on the best models with the highest AUC values, an AI prediction system is designed and integrated into hospital information systems to assist physicians in the decision-making process. CONCLUSIONS: AI techniques showcased exceptional capabilities for predicting a prolonged hospital stay, the need for a skin graft, and the occurrence of overall adverse complications for burn patients. The insights from our study fuel optimism for the inception of a novel predictive model that can seamlessly meld with hospital information systems, enhancing clinical decisions and bolstering physician-patient dialogues.

Atezolizumab-induced subacute cerebellar ataxia in a patient with extensive-stage small cell lung cancer.

Recently, immune checkpoint inhibitors (ICIs) have become the standard treatment option for patients with lung cancer, including small cell lung cancer (SCLC). ICI-induced neurological immune-related adverse events are rare and exhibit diverse clinical manifestations, often leading to missed or delayed diagnosis. Herein, we report the case of a patient with extensive-stage SCLC who received atezolizumab with etoposide/platinum and gradually developed neurological symptoms after three cycles of chemoimmunotherapy. Subsequently, the patient received a diagnosis of subacute immune-related cerebellar ataxia and was treated successfully with pulse steroid therapy. The patient exhibited almost complete remission of neurological symptoms and had progression-free survival for >24 months.

Nonreciprocal Supercurrents in a Field-Free Graphene Josephson Triode.

Superconducting diodes are proposed nonreciprocal circuit elements that should exhibit nondissipative transport in one direction while being resistive in the opposite direction. Multiple examples of such devices have emerged in the past couple of years; however, their efficiency is typically limited, and most of them require a magnetic field to function. Here we present a device that achieves efficiencies approaching 100% while operating at zero field. Our samples consist of a network of three graphene Josephson junctions linked by a common superconducting island, to which we refer as a Josephson triode. The three-terminal nature of the device inherently breaks the inversion symmetry, and the control current applied to one of the contacts breaks the time-reversal symmetry. The triode's utility is demonstrated by rectifying a small (nA scale amplitude) applied square wave. We speculate that devices of this type could be realistically employed in the modern quantum circuits.

Aspergillus oryzae Fermentation Extract Alleviates Inflammation in Mycoplasma pneumoniae Pneumonia.

The filamentous fungus Aspergillus oryzae, also known as koji mold, has been used for centuries in the production of fermented foods in East Asia. A. oryzae fermentation can produce enzymes and metabolites with various bioactivities. In this study, we investigated whether A. oryzae fermentation extract (AOFE) has any effect on Mycoplasma pneumoniae (Mp) pneumonia. We performed solid-state fermentation of A. oryzae and obtained the ethanol extract. AOFE was analyzed by HPLC, and the major component was identified to be kojic acid. In vitro, AOFE suppressed Mp growth and invasion into A549 lung epithelial cells as determined by the gentamicin protection assay. AOFE treatment also suppressed Mp-stimulated production of tumor necrosis factor (TNF)-α and interleukin (IL)-6 at mRNA and protein levels in murine MH-S alveolar macrophages. In a mouse model of Mp pneumonia, Mp infection induced a marked pulmonary infiltration of neutrophils, which was significantly reduced in mice pre-treated orally with AOFE. AOFE administration also suppressed the production of proinflammatory cytokines and chemokines in the lungs. Collectively, our results show that AOFE has the potential to be developed into a preventive/therapeutic agent for Mp pneumonia.

Continuous Bose-Einstein condensation.

Bose-Einstein condensates (BECs) are macroscopic coherent matter waves that have revolutionized quantum science and atomic physics. They are important to quantum simulation1 and sensing2,3, for example, underlying atom interferometers in space4 and ambitious tests of Einstein's equivalence principle5,6. A long-standing constraint for quantum gas devices has been the need to execute cooling stages time-sequentially, restricting these devices to pulsed operation. Here we demonstrate continuous Bose-Einstein condensation by creating a continuous-wave (CW) condensate of strontium atoms that lasts indefinitely. The coherent matter wave is sustained by amplification through Bose-stimulated gain of atoms from a thermal bath. By steadily replenishing this bath while achieving 1,000 times higher phase-space densities than previous works7,8, we maintain the conditions for condensation. Our experiment is the matter wave analogue of a CW optical laser with fully reflective cavity mirrors. This proof-of-principle demonstration provides a new, hitherto missing piece of atom optics, enabling the construction of continuous coherent-matter-wave devices.

Preoperative prediction model to evaluate salvage surgery in patients with recurrent or second primary oral cavity squamous cell carcinoma.

OBJECTIVE: In approximately 50% of patients with oral cavity squamous cell carcinoma (OCSCC), the disease progresses after curative surgery. However, the role of salvage surgery (SS) is controversial, and life expectancy after SS is unknown. METHODS: In this study, 262 patients with OCSCC with locoregional recurrence and second primary OCSCC were retrospectively enrolled and divided into a resectable (55.0%, 144/262) and unresectable (45.0%, 118/262) groups. After excluding neck recurrence only, SS had been performed 195 times in the resectable group. The corresponding preoperative clinicopathologic factors and postsurgery survival (PSS) of each SS were pooled for analysis. RESULTS: Median survival after disease progression was 64.2 and 10.4 months for the resectable and unresectable groups, respectively. In the resectable group, one-fifth (19.5%, 37/190) of the patients died within 1 year of SS (PSS < 1 year), and one-third (32.8%, 64/195) of the patients had undergone SS two or more times. The interval from the last surgery ≤ 12 months, depth of invasion of the last surgery > 1 cm, and clinical evidence of nodal disease at the preoperative evaluation were independent predictors of poor PSS. A scoring prediction model was established with 1 point for each factor. The results revealed 1-year postsurgery death rates of 10.3% in the low-risk group (score: 0-1) and 48.6% in the high-risk group (score: 2 or 3) (P < 0.001). CONCLUSIONS: In conclusion, an effective scoring model predicting life expectancy after SS for patients with OCSCC was established.

Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors.

Despite a considerable expansion in the present therapeutic repertoire for other malignancy managements, mortality from head and neck cancer (HNC) has not significantly improved in recent decades. Moreover, the second primary cancer (SPC) diagnoses increased in patients with HNC, but studies providing evidence to support SPCs prediction in HNC are lacking. Several base classifiers are integrated forming an ensemble meta-classifier using a stacked ensemble method to predict SPCs and find out relevant risk features in patients with HNC. The balanced accuracy and area under the curve (AUC) are over 0.761 and 0.847, with an approximately 2% and 3% increase, respectively, compared to the best individual base classifier. Our study found the top six ensemble risk features, such as body mass index, primary site of HNC, clinical nodal (N) status, primary site surgical margins, sex, and pathologic nodal (N) status. This will help clinicians screen HNC survivors before SPCs occur.

Risk Prediction of Second Primary Endometrial Cancer in Obese Women: A Hospital-Based Cancer Registry Study.

Due to the high effectiveness of cancer screening and therapies, the diagnosis of second primary cancers (SPCs) has increased in women with endometrial cancer (EC). However, previous studies providing adequate evidence to support screening for SPCs in endometrial cancer are lacking. This study aimed to develop effective risk prediction models of second primary endometrial cancer (SPEC) in women with obesity (body mass index (BMI) > 25) and included datasets on the incidence of SPEC and the other risks of SPEC in 4480 primary cancer survivors from a hospital-based cancer registry database. We found that obesity plays a key role in SPEC. We used 10 independent variables as predicting variables, which correlated to obesity, and so should be monitored for the early detection of SPEC in endometrial cancer. Our proposed scheme is promising for SPEC prediction and demonstrates the important influence of obesity and clinical data representation in all cases following primary treatments. Our results suggest that obesity is still a crucial risk factor for SPEC in endometrial cancer.

Prediction Model of Distant Metastasis in Oral Cavity Squamous Cell Carcinoma With or Without Regional Lymphatic Metastasis.

Patients with oral cavity squamous cell carcinoma (OCSCC) who develop distant metastasis (DM) face poor outcomes, and effective prediction models of DM are rare. A total of 595 patients with OCSCC were retrospectively enrolled in this study. Because pathological N staging significantly influences the development and mechanisms of DM, the patients were divided into nodal-negative (pN-) and -positive (pN+) groups. Clinical outcomes, prognoses, and prediction models were analyzed separately for both groups. Overall, 8.9% (53/595) of these patients developed DM. Among the DM cases, 84.9% (45/53) of them developed DM within the first 3 years. The median overall survival, locoregional recurrence-free survival, time until DM development, and postmetastatic survival were 19.8, 12.7, 14.6, and 4.1 months, respectively. Distinguishing patients who only developed locoregional recurrence from those with DM according to locoregional conditions was difficult. Age, surgical margin, and early locoregional recurrence were predictors of DM that were independent of time until DM in the pN- group; the lymphocyte-to-monocyte ratio, presence of lymphovascular invasion, and early locoregional recurrence in the pN+ group were determined. If one point was scored for each factor, then two scoring systems were used to classify the patients into low- (score = 0), intermittent- (score = 1), or high- (score = 2 or 3) risk for the pN- and pN+ groups. According to this scoring system, the 3-year DM rates for the low, intermittent, and high risk subgroups were 0.0%, 5.9%, and 17.8% for the pN- group and 7.1%, 44.9%, and 82.5% for the pN+ group, respectively. These systems also effectively predicted DM, and the areas under the curve predicted DM occurring within the first 3 years were 0.744 and 0.820 for the pN- and pN+ groups, respectively. In conclusion, effective scoring models were established for predicting DM.

The RbSr 2Σ+ ground state investigated via spectroscopy of hot and ultracold molecules.

We report on spectroscopic studies of hot and ultracold RbSr molecules, and combine the results in an analysis that allows us to fit a potential energy curve (PEC) for the X(1)2Σ+ ground state bridging the short-to-long-range domains. The ultracold RbSr molecules are created in a µK sample of Rb and Sr atoms and probed by two-colour photoassociation spectroscopy. The data yield the long-range dispersion coefficients C6 and C8, along with the total number of supported bound levels. The hot RbSr molecules are created in a 1000 K gas mixture of Rb and Sr in a heat-pipe oven and probed by thermoluminescence and laser-induced fluorescence spectroscopy. We compare the hot molecule data with spectra we simulated using previously published PECs determined by three different ab initio theoretical methods. We identify several band heads corresponding to radiative decay from the B(2)2Σ+ state to the deepest bound levels of X(1)2Σ+. We determine a mass-scaled high-precision model for X(1)2Σ+ by fitting all data using a single fit procedure. The corresponding PEC is consistent with all data, thus spanning short-to-long internuclear distances and bridging an energy gap of about 75% of the potential well depth, still uncharted by any experiment. We benchmark previous ab initio PECs against our results, and give the PEC fit parameters for both X(1)2Σ+ and B(2)2Σ+ states. As first outcomes of our analysis, we calculate the s-wave scattering properties for all stable isotopic combinations and corroborate the locations of Fano-Feshbach resonances between alkali Rb and closed-shell Sr atoms recently observed [V. Barbéet al., Nat. Phys., 2018, 14, 881]. These results and more generally our strategy should greatly contribute to the generation of ultracold alkali-alkaline-earth dimers, whose applications range from quantum simulation to state-controlled quantum chemistry.

Steady-State Magneto-Optical Trap with 100-Fold Improved Phase-Space Density.

We demonstrate a continuously loaded ^{88}Sr magneto-optical trap (MOT) with a steady-state phase-space density of 1.3(2)×10^{-3}. This is 2 orders of magnitude higher than reported in previous steady-state MOTs. Our approach is to flow atoms through a series of spatially separated laser cooling stages before capturing them in a MOT operated on the 7.4-kHz linewidth Sr intercombination line using a hybrid slower+MOT configuration. We also demonstrate producing a Bose-Einstein condensate at the MOT location, despite the presence of laser cooling light on resonance with the 30-MHz linewidth transition used to initially slow atoms in a separate chamber. Our steady-state high phase-space density MOT is an excellent starting point for a continuous atom laser and dead-time free atom interferometers or clocks.

Antiplatelet Therapy is Associated with a Better Prognosis for Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma after Liver Resection.

BACKGROUND: Recurrence of hepatocellular carcinoma (HCC) with unsatisfactory survival is common after surgical resection. Antiplatelet therapy with aspirin or clopidogrel was recently shown to prevent hepatic carcinogenesis in a murine model, but its effect in humans had not been clarified. This study aimed to investigate the association between antiplatelet therapy and the outcomes for patients with hepatitis B virus (HBV)-related HCC after liver resection. METHODS: By analyzing data from the Taiwan National Health Insurance Research Database, 9461 HBV-related HCC patients who had undergone liver resection between January 1997 and December 2011 were identified. After one-to-four matching by sex, age, and propensity score, 442 patients with antiplatelet therapy and 1768 patients without antiplatelet therapy were enrolled for the analysis. The Kaplan-Meier method and modified Cox proportional hazards models were used for survival and multivariable, stratified analyses. RESULTS: Recurrence-free survival and overall survival after resection surgery were significantly better after 5 years in the treated cohort than in the untreated cohort (52.8 vs 47.9 %; p = 0.021 and 80.3 vs 65.4 %; p < 0.001, respectively). Besides, antiplatelet therapy reduced the risk of HCC recurrence (hazard ratio [HR] 0.73; p < 0.001) and overall mortality (HR 0.57; p < 0.001) in the multivariable analysis. However, antiplatelet use significantly increased the risk of upper gastrointestinal bleeding (odds ratio [OR] 1.91; p < 0.001). CONCLUSIONS: Use of aspirin or clopidogrel was associated with better recurrence-free survival and overall survival among patients with HBV-related HCC after liver resection. However, these agents should be used with caution due to the adverse effects of upper gastrointestinal bleeding.

Differentiation and apoptosis induction by lovastatin and γ-tocotrienol in HL-60 cells via Ras/ERK/NF-κB and Ras/Akt/NF-κB signaling dependent down-regulation of glyoxalase 1 and HMG-CoA reductase.

Glyoxalase 1 (GLO1) and HMG-CoA reductase (HMGCR) are highly expressed in most tumor cells and little in normal cells. In this study, treatment of HL-60 cells with lovastatin induced characteristic apoptosis in a dose-dependent manner. We demonstrated that lovastatin treatment inhibited Ras and Raf protein translocation to cell membrane and eliminated the phosphorylation of the downstream effectors Akt and ERK, and the subsequent NF-κB translocation into nucleus. Specific inhibitors and γ-tocotrienol confirmed the Ras/Raf/ERK/NF-κB/GLO1 and Ras/Akt/NF-κB/GLO1 pathways. Data revealed that lovastatin induced HL-60 cell death was attenuated by mevalonate treatment. We demonstrated also that γ-tocotrienol showed its apoptotic effect on the HL-60 cell through the same pathway. γ-Tocotrienol enhanced the apoptotic effect of lovastatin through the down-regulation of GLO1 and HMGCR resulting in an increase of methylglyoxal and a decrease of cholesterol and led to the apoptosis of HL-60 cells. Data also revealed that both lovastatin and gamma-tocotrienol induced significant HL-60 cell differentiation. These results suggest that both lovastatin and gamma-tocotrienol could induce differentiation and followed by apoptosis.

Blockade of the Ras/Raf/ERK and Ras/PI3K/Akt Pathways by Monacolin K Reduces the Expression of GLO1 and Induces Apoptosis in U937 Cells.

Monacolin K, a hydrolytic product of icaritin, is the major active component in the traditional fermented Monascus purpureus. Monacolin K inhibits the proliferation of acute myeloid leukemia (AML), but underlying mechanisms remain to be identified. The present study demonstrates that monacolin K inhibits the proliferation of human AML cell line U937 in a dose-dependent manner. Importantly, morphological, DNA fragmentation, and image cytometry analyses indicated that monacolin K induced U937 cell apoptosis. Monacolin K could inactivate Ras translocation from cytosol to cell membrane. Monacolin K could also reduce the Ras-dependent phosphorylation of ERK and Akt, and the subsequent translocation of nuclear factor kappa B (NF-κB) from cytosol to nucleus in U937 cells. The underlying mechanisms of apoptotic activity of monacolin K were associated with inhibition of the Ras/Raf/ERK and Ras/PI3K/Akt signals and down-regulation of HMG-CoA reductase and glyoxalase 1. On the basis of results obtained using specific inhibitors U0126, LY294002, and JSH-23, the Ras/Raf/ERK/NF-κB/GLO1 and Ras/Akt/NF-κB/GLO1 pathways were proposed for the apoptotic effect of monacolin K in U937 cells.