Breast cancer malignancy is governed by regulation of the macroH2A2/TM4SF1 axis, the AKT/NF-κB pathway, and elevated MMP13 expression.

The histone variant, macroH2A (mH2A) influences gene expression through epigenetic regulation. Tumor suppressive function of mH2A isoforms has been reported in various cancer types, but few studies have investigated the functional role of mH2A2 in breast cancer pathophysiology. This study aimed to determine the significance of mH2A2 in breast cancer development and progression by exploring its downstream regulatory mechanisms. Knockdown of mH2A2 facilitated the migration and invasion of breast cancer cells, whereas its overexpression exhibited the opposite effect. In vivo experiments revealed that augmenting mH2A2 expression reduced tumor growth and lung metastasis. Microarray analysis showed that TM4SF1 emerged as a likely target linked to mH2A2 owing to its significant suppression in breast cancer cell lines where mH2A2 was overexpressed among the genes that exhibited over twofold upregulation upon mH2A2 knockdown. Suppressing TM4SF1 reduced the migration, invasion, tumor growth, and metastasis of breast cancer cells in vitro and in vivo. TM4SF1 depletion reversed the increased aggressiveness triggered by mH2A2 knockdown, suggesting a close interplay between mH2A2 and TM4SF1. Our findings also highlight the role of the mH2A2/TM4SF1 axis in activating the AKT/NF-κB pathway. Consequently, activated NF-κB signaling leads to increased expression and secretion of MMP13, a potent promoter of metastasis. In summary, we propose that the orchestrated regulation of the mH2A2/TM4SF1 axis in conjunction with the AKT/NF-κB pathway and the subsequent elevation in MMP13 expression constitute pivotal factors governing the malignancy of breast cancer.

Medication-related incidents in acute care hospitals among different age groups: An analysis of national patient safety report data.

PURPOSE: This study aimed to perform a nationwide analysis of medication errors (MEs) from hospitals using national reporting system data and to compare the ME patterns among different age groups. METHODS: We analyzed medication-related incidents in acute care hospitals reported to the Korean Patient Safety Reporting and Learning System (KOPS), which is a patient safety reporting system, from July 2016 to December 2020. The stages of the medication use process, type of errors, medication class involved in MEs, and degree of harm were analyzed. RESULTS: Among a total of 5071 medication-related incidents, 37.7% (1911 cases) were incidents that caused patient harm and 1.2% caused long-term, permanent, and fatal harm. The proportion of medication-related incidents that resulted in harm was the highest among the <1-year-old age group (67 cases, 51.5%), followed by the elderly (≥ 65 years) (828 cases, 40.9%). The cases leading to patient death were most frequently reported in patients aged ≥65 years. Medication-related incidents occurred mainly in the administration stage (2954 cases, 58.3%), and wrong dose was the most frequently reported ME type. The most prevalent medication class occurring in the 20-64-year age group (256 cases, 11.7%) was 'antibacterials for systemic use', whereas 'contrast media' (236 cases, 11.6%) and 'blood substitutes and perfusion solutions' (98 cases, 19.3%) were the most prevalent drug classes in the ≥65- and <20-year-old age groups, respectively. CONCLUSIONS: It is necessary to establish guidelines for the prevention of medication-related incidents according to the medication use process and patient age group.

Development and validation of a predictive model for persistent opioid use in new opioid analgesic users via a nationwide claims database.

BACKGROUND: Chronic opioid use is associated with problematic opioid use, such as opioid abuse. It is important to develop a prediction model for safe opioid use. In this study, we aimed to develop and validate a risk score model for chronic opioid use in opioid-naïve, noncancer patients, using data from a nationwide database. METHODS: Data from the National Health Insurance Claims Database in the Republic of Korea from 2016 to 2018 were used, and adult, noncancer patients who were started on non-injectable opioid analgesics (NIOAs) were included. The risk score model was developed using the ß coefficient of each variable in the multivariable logistic regression analysis. RESULTS: Overall, 676,676 noncancer patients were started on NIOAs, of which 65,877 (9.7%) were prescribed NIOAs chronically. Age, baseline healthcare utilization, comorbidities, co-medications, and pattern of first NIOA prescription were identified as risk factors for chronic opioid use. The c-static for the performance of our risk score model was 0.754 (95% confidence interval, 0.750-0.758). CONCLUSION: To our knowledge, this is the first tool that can predict chronic opioid use in the Korean population. The model can help physicians examine the risk of chronic opioid use by patients who are started on NIOA.

Derivation and validation of a risk prediction score for nonsteroidal anti-inflammatory drug-related serious gastrointestinal complications in the elderly.

AIMS: Few studies have quantified the impact of risk factors on GI complications in elderly nonsteroidal anti-inflammatory drug (NSAID) users. This study aimed to develop and validate a risk prediction score for severe GI complications to identify high-risk elderly patients using NSAID. METHODS: We used the following two Korean claims datasets: customized data with an enrolment period 2016-2017 for model development, and the sample data in 2019 for external validation. We conducted a nested case-control study for model development and validation. NSAID users were identified as the elderly (≥65 years) who received NSAIDs for more than 30 days. Serious GI complications were defined as hospitalizations or emergency department visits, with a main diagnosis of GI bleeding or perforation. We applied the logistic least absolute shrinkage and selection operator (LASSO) regression model for variable selection and model fitting. RESULTS: We identified 8176 cases and 81 760 controls with a 1:10 matched follow-up period in the derivation cohort. In the external validation cohort, we identified 372 cases from 254 551 patients. The risk predictors were high-dose NSAIDs, nonselective NSAID, complicated GI ulcer history, male sex, concomitant gastroprotective agents, relevant co-medications, severe renal disease and cirrhosis. Area under the receiver operating characteristic curve was 0.79 (95% confidence interval, 0.77-0.81) in the external validation dataset. CONCLUSIONS: The prediction model may be a useful tool for reducing the risk of serious GI complications by identifying high-risk elderly patients.

Development and validation of a machine learning-based fall-related injury risk prediction model using nationwide claims database in Korean community-dwelling older population.

BACKGROUND: Falls impact over 25% of older adults annually, making fall prevention a critical public health focus. We aimed to develop and validate a machine learning-based prediction model for serious fall-related injuries (FRIs) among community-dwelling older adults, incorporating various medication factors. METHODS: Utilizing annual national patient sample data, we segmented outpatient older adults without FRIs in the preceding three months into development and validation cohorts based on data from 2018 and 2019, respectively. The outcome of interest was serious FRIs, which we defined operationally as incidents necessitating an emergency department visit or hospital admission, identified by the diagnostic codes of injuries that are likely associated with falls. We developed four machine-learning models (light gradient boosting machine, Catboost, eXtreme Gradient Boosting, and Random forest), along with a logistic regression model as a reference. RESULTS: In both cohorts, FRIs leading to hospitalization/emergency department visits occurred in approximately 2% of patients. After selecting features from initial set of 187, we retained 26, with 15 of them being medication-related. Catboost emerged as the top model, with area under the receiver operating characteristic of 0.700, along with sensitivity and specificity rates around 65%. The high-risk group showed more than threefold greater risk of FRIs than the low-risk group, and model interpretations aligned with clinical intuition. CONCLUSION: We developed and validated an explainable machine-learning model for predicting serious FRIs in community-dwelling older adults. With prospective validation, this model could facilitate targeted fall prevention strategies in primary care or community-pharmacy settings.

A cleavage-based surrogate reporter for the evaluation of CRISPR-Cas9 cleavage efficiency.

CRISPR-Cas9 is a powerful tool for genome engineering, but its efficiency largely depends on guide RNA (gRNA). There are multiple methods available to evaluate the efficiency of gRNAs, including the T7E1 assay, surveyor nuclease assay, deep sequencing, and surrogate reporter systems. In the present study, we developed a cleavage-based surrogate that we have named the LacI-reporter to evaluate gRNA cleavage efficiency. The LacI repressor, under the control of the EF-1α promoter, represses luciferase or EGFP reporter expression by binding to the lac operator. Upon CRISPR-Cas9 cleavage at a target site located between the EF-1α promoter and the lacI gene, repressor expression is disrupted, thereby triggering luciferase or EGFP expression. Using this system, we can quantitate gRNA cleavage efficiency by assessing luciferase activity or EGFP expression. We found a strong positive correlation between the cleavage efficiency of gRNAs measured using this reporter and mutation frequency, measured using surveyor and deep sequencing. The genome-editing efficiency of gRNAs was validated in human liver organoids. Our LacI-reporter system provides a useful tool to select efficient gRNAs for genome editing.

Risk Factors for Emergency Department Presentations after the Initiation of Opioid Analgesics in Non-Cancer Patients in Korea: A Nationwide Study.

Background and Objectives: Opioid use in Korea is lower than in other developed countries. However, recent studies have reported an increase in opioid prescriptions and the number of chronic opioid users. The current status of adverse events (AEs) associated with opioid analgesics in Korea is unclear. This nested case-control study aimed to evaluate the influence of opioid analgesic use patterns on all emergency department (ED) visits and opioid-related ED visits after opioid analgesic initiation using the national claims database. Materials and Methods: Adult non-cancer patients who initiated non-injectable opioid analgesics (NIOA) between January 2017 and June 2018 were included. We defined the case group as patients who visited the ED within six months of opioid initiation, and the control group was selected in a 1:1 ratio using an exact matching method. Results: A total of 97,735 patients (13.58%) visited the ED within six months of NIOA initiation. Nearly 32% of cases were linked to opioid-related AEs. The most frequent AEs were falls and fractures (61.27%). After adjusting for covariates, opioid initiation at the ED was associated with all-cause or opioid-related ED visits (adjusted odds ratio (aOR) = 3.19, 95% confidence interval (CI) = 3.09-3.29; aOR = 3.82, 95% CI = 3.62-4.04, respectively). Chronic NIOA use was associated with all-cause and opioid-related ED visits (aOR = 1.32, 95% CI = 1.23-1.40; aOR = 1.56, 95% CI = 1.39-1.76, respectively). Conclusion: This study found that 13% of non-cancer patients visited the ED within six months of NIOA initiation. In addition, the NIOA use pattern was significantly associated with all-cause and opioid-related ED visits.

Analysis of Medication Errors Reported by Community Pharmacists in the Republic of Korea: A Cross-Sectional Study.

Background and objectives: We aimed to describe medication-related incidents or medication errors (MEs) reported by community pharmacists and analyze the prevalent medications involved. Materials and Methods: We extracted ME reports from databases comprising patient safety incidents reported to the Korean Pharmaceutical Association between January 2013 and June 2021. Medications were analyzed according to the second (therapeutic subgroup) and fifth (chemical substance) levels of the Anatomical Therapeutic Chemical classification. Results: A total of 9046 MEs were identified, most of which were near miss reports (88.3%). Among the errors that reached the patients (521 cases), harmful incidents accounted for 76.8%. Most MEs occurred during prescription (89.5%), while harmful MEs occurred mainly during dispensing (73.3%). In the prescription step, wrong drugs (44.8%), dosing errors (27.0%), and wrong durations (14.0%) were common. Anti-inflammatory and anti-rheumatic products (M01), drugs for acid-related disorders (A02), and antihistamines for systemic use (R06) were the most frequently reported medication classes involved. Harmful incidents were most common for dosing errors (31.0%) and wrong drugs (26.8%) and were common with warfarin, levothyroxine, and glimepiride. Conclusions: The MEs reported by community pharmacists were mainly prescribing errors, most of which were rectified before reaching patients. The prevalent medications involved in harmful errors include anti-diabetic, anti-thrombotic, and anti-inflammatory agents.

Risk factors of chronic opioid use after surgical procedures in noncancer patients: A nationwide case-control study.

BACKGROUND: Surgery is an indication for opioid prescription in noncancer patients, and chronic use of opioids is associated with overdose and abuse. OBJECTIVES: We aimed to evaluate the prevalence and risk factors associated with chronic opioid use (COU) following surgery among noncancer patients. DESIGN: A nationwide case-control study. SETTING: Retrospective analysis of the annual national patient sample data from 2012 to 2018 in South Korea. PATIENTS: Adults without cancer who had undergone surgery and received noninjectable opioids during hospital stay. MAIN OUTCOME MEASURES: COU during 3 months following surgery. RESULTS: A total of 15 543 participants were included, and the prevalence overall and in opioid-naïve users was 8.1 and 5.7%, respectively. Prior exposure patterns of opioids [intermittent user, adjusted odds ratio (aOR) 2.35; 95% CI, 2.00 to 2.77, and continuous user, aOR 8.58; 95% CI, 6.54 to 11.24] and concomitant use of benzodiazepine (in continuous user, aOR 18.60; 95% CI 11.70 to 29.55) were strongly associated with COU compared with naïve users. Morphine milligram equivalent, type of opioid strength at discharge and prescription of nonopioid analgesics at discharge were also associated with COU. Compared with minor surgery, knee (aOR 1.49; 95% CI 1.17 to 1.89), spine (aOR 1.65; 95% CI 1.33 to 2.06) and shoulder (aOR 2.54; 95% CI 1.97 to 3.27) procedures showed a significantly positive association with COU. Sensitivity analysis in opioid-naïve patients showed similar results. CONCLUSION: About 8.1% of noncancer patients who had undergone surgery and were prescribed noninjectable opioids became chronic opioid users in Korea. Identified risk factors could be used to derive strategies for safe opioid use in noncancer patients in the future.

G9a Knockdown Suppresses Cancer Aggressiveness by Facilitating Smad Protein Phosphorylation through Increasing BMP5 Expression in Luminal A Type Breast Cancer.

Epigenetic abnormalities affect tumor progression, as well as gene expression and function. Among the diverse epigenetic modulators, the histone methyltransferase G9a has been focused on due to its role in accelerating tumorigenesis and metastasis. Although epigenetic dysregulation is closely related to tumor progression, reports regarding the relationship between G9a and its possible downstream factors regulating breast tumor growth are scarce. Therefore, we aimed to verify the role of G9a and its presumable downstream regulators during malignant progression of breast cancer. G9a-depleted MCF7 and T47D breast cancer cells exhibited suppressed motility, including migration and invasion, and an improved response to ionizing radiation. To identify the possible key factors underlying these effects, microarray analysis was performed, and a TGF-ß superfamily member, BMP5, was selected as a prominent target gene. It was found that BMP5 expression was markedly increased by G9a knockdown. Moreover, reduction in the migration/invasion ability of MCF7 and T47D breast cancer cells was induced by BMP5. Interestingly, a G9a-depletion-mediated increase in BMP5 expression induced the phosphorylation of Smad proteins, which are the intracellular signaling mediators of BMP5. Accordingly, we concluded that the observed antitumor effects may be based on the G9a-depletion-mediated increase in BMP5 expression and the consequent facilitation of Smad protein phosphorylation.

VprBP has intrinsic kinase activity targeting histone H2A and represses gene transcription.

Histone modifications play important roles in the regulation of gene expression and chromatin organization. VprBP has been implicated in transcriptionally silent chromatin formation and cell-cycle regulation, but the molecular basis underlying such effects remains unclear. Here we report that VprBP possesses an intrinsic protein kinase activity and is capable of phosphorylating histone H2A on threonine 120 (H2AT120p) in a nucleosomal context. VprBP is localized to a large set of tumor suppressor genes and blocks their transcription, in a manner that is dependent on its kinase activity toward H2AT120. The functional significance of VprBP-mediated H2AT120p is further underscored by the fact that RNAi knockdown and small-molecule inhibition of VprBP reactivate growth regulatory genes and impede tumor growth. Our findings establish VprBP as a major kinase responsible for H2AT120p in cancer cells and suggest that VprBP inhibition could be a new strategy for the development of anticancer therapeutics.

Melatonin as an Oncostatic Molecule Based on Its Anti-Aromatase Role in Breast Cancer.

Breast cancer is the most common type of cancer. In the developmental stages of breast cancer, estrogens are strongly involved. As estrogen synthesis is regulated by the enzyme aromatase, targeting the activity of this enzyme represents a therapeutic option. The pineal hormone melatonin may exert a suppressive role on aromatase activity, leading to reduced estrogen biosynthesis. A melatonin-mediated decrease in the expression of aromatase promoters and associated genes would provide suitable evidence of this molecule's efficacy as an aromatase inhibitor. Furthermore, melatonin intensifies radiation-induced anti-aromatase effects and counteracts the unwanted disadvantages of chemotherapeutic agents. In this manner, this review summarizes the inhibitory role of melatonin in aromatase action, suggesting its role as a possible oncostatic molecule in breast cancer.

CCAR1, a key regulator of mediator complex recruitment to nuclear receptor transcription complexes.

DNA-bound transcription factors recruit many coactivator proteins to remodel chromatin and activate transcription. The Mediator complex is believed to recruit RNA polymerase II to most protein-encoding genes. It is generally assumed that interaction of Mediator subunits with DNA-binding transcription factors is responsible for Mediator recruitment to promoters. However, we report here that Mediator recruitment by nuclear receptors (NR) requires a coactivator protein, CCAR1 (cell-cycle and apoptosis regulator 1). CCAR1 associates with components of the Mediator and p160 coactivator complexes and is recruited to endogenous NR target genes in response to the appropriate hormone. Reduction of endogenous CCAR1 levels inhibited hormone-induced expression of endogenous NR target genes, hormone-induced recruitment of Mediator components and RNA polymerase II to target gene promoters, and estrogen-dependent growth of breast cancer cells. Thus, CCAR1 regulates expression of key proliferation-inducing genes. CCAR1 also functions as a p53 coactivator, suggesting a broader role in transcriptional regulation.

FACT-mediated exchange of histone variant H2AX regulated by phosphorylation of H2AX and ADP-ribosylation of Spt16.

The phosphorylation of histone variant H2AX at DNA double-strand breaks is believed to be critical for recognition and repair of DNA damage. However, little is known about the molecular mechanism regulating the exchange of variant H2AX with conventional H2A in the context of the nucleosome. Here, we isolate the H2AX-associated factors, which include FACT (Spt16/SSRP1), DNA-PK, and PARP1 from a human cell line. Our analyses demonstrate that the H2AX-associated factors efficiently promote both integration and dissociation of H2AX and this exchange reaction is mainly catalyzed by FACT among the purified factors. The phosphorylation of H2AX by DNA-PK facilitates the exchange of nucleosomal H2AX by inducing conformational changes of the nucleosome. In contrast, poly-ADP-ribosylation of Spt16 by PARP1 significantly inhibits FACT activities for H2AX exchange. Thus, these data establish FACT as the major regulator involved in H2AX exchange process that is modulated by H2AX phosphorylation and Spt16 ADP-ribosylation.

Identification of radiation-induced aberrant hypomethylation in colon cancer.

BACKGROUND: Exposure to ionizing radiation (IR) results in the simultaneous activation or downregulation of multiple signaling pathways that play critical roles in cell type-specific control of survival or death. IR is a well-known genotoxic agent and human carcinogen that induces cellular damage through direct and indirect mechanisms. However, its impact on epigenetic mechanisms has not been elucidated, and more specifically, little information is available regarding genome-wide DNA methylation changes in cancer cells after IR exposure. Recently, genome-wide DNA methylation profiling technology using the Illumina HumanMethylation450K platform has emerged that allows us to query >450,000 loci within the genome. This improved technology is capable of identifying genome-wide DNA methylation changes in CpG islands and other CpG island-associated regions. RESULTS: In this study, we employed this technology to test the hypothesis that exposure to IR not only induces differential DNA methylation patterns at a genome-wide level, but also results in locus- and gene-specific DNA methylation changes. We screened for differential DNA methylation changes in colorectal cancer cells after IR exposure with 2 and 5 Gy. Twenty-nine genes showed radiation-induced hypomethylation in colon cancer cells, and of those, seven genes showed a corresponding increase in gene expression by reverse transcriptase polymerase chain reaction (RT-PCR). In addition, we performed chromatin immunoprecipitation (ChIP) to confirm that the DNA-methyltransferase 1 (DNMT1) level associated with the promoter regions of these genes correlated with their methylation level and gene expression changes. Finally, we used a gene ontology (GO) database to show that a handful of hypomethylated genes induced by IR are associated with a variety of biological pathways related to cancer. CONCLUSION: We identified alterations in global DNA methylation patterns and hypomethylation at specific cancer-related genes following IR exposure, which suggests that radiation exposure plays a critical role in conferring epigenetic alterations in cancer.

Real-world incidence and risk factors of bortezomib-related cardiovascular adverse events in patients with multiple myeloma.

BACKGROUND: Although most studies on the cardiovascular toxicity of proteasome inhibitors have focused on carfilzomib, the risk of cardiotoxicity associated with bortezomib remains controversial. This study aimed to evaluate the incidence and risk factors of cardiovascular adverse events (CVAEs) associated with bortezomib in patients with multiple myeloma in a real-world setting. METHODS: This cross-sectional study included patients who were treated with bortezomib at a tertiary hospital in South Korea. CVAEs, defined as hypertension, arrhythmia, heart failure, myocardial infarction, pulmonary arterial hypertension, angina, and venous thromboembolism, were detected using cardiac markers, ECG, echocardiography, medications, or documentation by clinicians. The patients were observed for at least 6 months and up to 2 years after starting bortezomib administration. RESULTS: Among the 395 patients, 20.8% experienced CVAEs of any grade, and 14.7% experienced severe adverse events. The median onset time for any CVAE was 101.5 days (IQR, 42-182 days), and new-onset/worsened hypertension was the most prevalent CVAE. The risk of CVAEs increased in patients with a body mass index lower than 18.5 (adjusted HR (aHR) 3.50, 95% confidence interval (CI) 1.05-11.72), light chain (1.80, 1.04-3.13), and IgD (4.63, 1.06-20.20) as the multiple myeloma subtype, baseline stroke (4.52, 1.59-12.80), and hypertension (1.99, 1.23-3.23). However, CVAEs did not significantly affect the 2-year overall survival and progression-free survival. CONCLUSION: Approximately 15% of the Korean patients treated with bortezomib experienced severe CVAEs. Thus, patients, especially those with identified risk factors, should be closely monitored for CVAE symptoms during bortezomib treatment.

Development and validation of a medication-based risk prediction model for acute kidney injury in older outpatients.

BACKGROUND: Older adults are at an increased risk of acute kidney injury (AKI), particularly in community settings, often due to medications. Effective prevention hinges on identifying high-risk patients, yet existing models for predicting AKI risk in older outpatients are scarce, particularly those incorporating medication variables. We aimed to develop an AKI risk prediction model that included medication-related variables for older outpatients. METHODS: We constructed a cohort of 2,272,257 outpatients aged ≥65 years using a national claims database. This cohort was split into a development (70%) and validation (30%) groups. Our primary goal was to identify newly diagnosed AKI within one month of cohort entry in an outpatient context. We screened 170 variables and developed a risk prediction model using logistic regression. RESULTS: The final model integrated 12 variables: 2 demographic, 4 comorbid, and 6 medication-related. It showed good performance with acceptable calibration. In the validation cohort, the area under the receiver operating characteristic curve value was 0.720 (95% confidence interval, 0.692-0.748). Sensitivity and specificity were 69.9% and 61.9%, respectively. Notably, the model identified high-risk patients as having a 27-fold increased AKI risk compared with low-risk individuals. CONCLUSION: We have developed a new AKI risk prediction model for older outpatients, incorporating critical medication-related variables with good discrimination. This tool may be useful in identifying and targeting patients who may require interventions to prevent AKI in an outpatient setting.

Development of a claims-based risk-scoring model to predict emergency department visits in older patients receiving anti-neoplastic therapy.

This study developed and validated a risk-scoring model, with a particular emphasis on medication-related factors, to predict emergency department (ED) visits among older Korean adults (aged 65 and older) undergoing anti-neoplastic therapy. Utilizing national claims data, we constructed two cohorts: the development cohort (2016-2018) with 34,642 patients and validation cohort (2019) with 10,902 patients. The model included a comprehensive set of predictors: demographics, cancer type, comorbid conditions, ED visit history, and medication use variables. We employed the least absolute shrinkage and selection operator (LASSO) regression to refine and select the most relevant predictors. Out of 120 predictor variables, 12 were integral to the final model, including seven related to medication use. The model demonstrated acceptable predictive performance in the validation cohort with a C-statistic of 0.76 (95% CI 0.74-0.77), indicating reasonable calibration. This risk-scoring model, after further clinical validation, has the potential to assist healthcare providers in the effective management and care of older patients receiving anti-neoplastic therapy.

AM-18002, a derivative of natural anmindenol A, enhances radiosensitivity in mouse breast cancer cells.

Natural anmindenol A isolated from the marine-derived bacteria Streptomyces sp. caused potent inhibition of inducible nitric oxide synthase without any significant cytotoxicity. This compound consists of a structurally unique 3,10-dialkylbenzofulvene skeleton. We previously synthesized and screened the novel derivatives of anmindenol A and identified AM-18002, an anmindenol A derivative, as a promising anticancer agent. The combination of AM-18002 and ionizing radiation (IR) improved anticancer effects, which were exerted by promoting apoptosis and inhibiting the proliferation of FM3A mouse breast cancer cells. AM-18002 increased the production of reactive oxygen species (ROS) and was more effective in inducing DNA damage. AM-18002 treatment was found to inhibit the expansion of myeloid-derived suppressor cells (MDSC), cancer cell migration and invasion, and STAT3 phosphorylation. The AM-18002 and IR combination synergistically induced cancer cell death, and AM-18002 acted as a potent anticancer agent by increasing ROS generation and blocking MDSC-mediated STAT3 activation in breast cancer cells.

Development of machine learning algorithms for scaling-up antibiotic stewardship.

BACKGROUND: Antibiotic stewardship programs (ASP) aim to reduce inappropriate use of antibiotics, but their labor-intensive nature impedes their wide adoption. The present study introduces explainable machine learning (ML) models designed to prioritize inpatients who would benefit most from stewardship interventions. METHODS: A cohort of inpatients who received systemic antibiotics and were monitored by a multidisciplinary ASP team at a tertiary hospital in the Republic of Korea was assembled. Data encompassing over 130,000 patient-days and comprising more than 160 features from multiple domains, including prescription records, laboratory, microbiology results, and patient conditions was collected.Outcome labels were generated using medication administration history: discontinuation, switching from intravenous to oral medication (IV to PO), and early or late de-escalation. The models were trained using Extreme Gradient Boosting (XGB) and light Gradient Boosting Machine (LGBM), with SHapley Additive exPlanations (SHAP) analysis used to explain the model's predictions. RESULTS: The models demonstrated strong discrimination when evaluated on a hold-out test set(AUROC - IV to PO: 0.81, Early de-escalation: 0.78, Late de-escalation: 0.72, Discontinue: 0.80). The models identified 41%, 16%, 22%, and 17% more cases requiring discontinuation, IV to PO, early and late de-escalation, respectively, compared to the conventional length of therapy strategy, given that the same number of patients were reviewed by the ASP team. The SHAP results explain how each model makes their predictions, highlighting a unique set of important features that are well-aligned with the clinical intuitions of the ASP team. CONCLUSIONS: The models are expected to improve the efficiency of ASP activities by prioritizing cases that would benefit from different types of ASP interventions along with detailed explanations.