Depressive symptoms of people living in areas with high exposure to environmental noise: a multilevel analysis.

Exposure and damage caused by noise have been reported in many countries around the world. However, few nationwide studies explored the association of residential environmental noise with depressive symptoms, this study aims to examine this association. The Korean Community Health Survey at the individual-level and the Korean Environmental Noise Measurement Database at the regional-level were used. A total of 30,630 individuals were eligible for the analysis. Multilevel model framework was applied to account for the clustered structure of the regional-level data in which individual-level data containing demographic characteristics and health information were nested. As a result of the analysis, Individuals living in the highest environmental noise area had a 1.55 times higher likelihood of experiencing depressive symptoms than those living in the lowest environmental noise area (95% CI, 1.04-2.31). After stratified analysis according to depressive symptom severity, individuals residing in areas with the highest environmental noise exposure had significantly higher odds of mild (aOR, 1.46; 95% CI, 1.02-2.07) and moderate symptoms (aOR, 1.70; 95% CI, 1.00-2.91). In conclusion, the higher the residential environmental noise, the higher the possibility of mild-to-moderate depressive symptoms. Our findings suggest the need for continued attention to and management of noise pollution, which has the potential to adversely affect individual's mental health.

Comparative analysis of resting-state EEG-based multiscale entropy between schizophrenia and bipolar disorder.

BACKGROUND: Studies that use nonlinear methods to identify abnormal brain dynamics in patients with psychiatric disorders are limited. This study investigated brain dynamics based on EEG using multiscale entropy (MSE) analysis in patients with schizophrenia (SZ) and bipolar disorder (BD). METHODS: The eyes-closed resting-state EEG data were collected from 51 patients with SZ, 51 patients with BD, and 51 healthy controls (HCs). Patients with BD were further categorized into type I (n = 23) and type II (n = 16), and then compared with patients with SZ. A sample entropy-based MSE was evaluated from the bilateral frontal, central, and parieto-occipital regions using 30-s artifact-free EEG data for each individual. Correlation analyses of MSE values and psychiatric symptoms were performed. RESULTS: For patients with SZ, higher MSE values were observed at higher-scale factors (i.e., 41-70) across all regions compared with both HCs and patients with BD. Furthermore, there were positive correlations between the MSE values in the left frontal and parieto-occipital regions and PANSS scores. For patients with BD, higher MSE values were observed at middle-scale factors (i.e., 13-40) in the bilateral frontal and central regions compared with HCs. Patients with BD type I exhibited higher MSE values at higher-scale factors across all regions compared with those with BD type II. In BD type I, positive correlations were found between MSE values in all left regions and YMRS scores. CONCLUSIONS: Patients with psychiatric disorders exhibited group-dependent MSE characteristics. These results suggest that MSE features may be useful biomarkers that reflect pathophysiological characteristics.

Effect of Corticosteroid Use on the Occurrence and Progression of Osteonecrosis of the Femoral Head: A nationwide Nested Case-Control Study.

BACKGROUND: Although it is very well known that corticosteroids cause osteonecrosis of the femoral head (ONFH), it is unclear as to which patients develop ONFH. Additionally, there are no studies on the association between corticosteroid use and femoral head collapse in ONFH patients. We aimed to investigate the association between corticosteroid use and the risk of ONFH among the general population and what factors affect ONFH occurrence. Additionally, we aimed to demonstrate which factors affect femoral head collapse and total hip arthroplasty (THA) after ONFH occurrence. METHODS: A nationwide, nested case-control study was conducted with data from the National Health Insurance Service Physical Health Examination Cohort (2002 to 2019) in the Republic of Korea. We defined ONFH (N = 3,500) using diagnosis and treatment codes. Patients who had ONFH were matched 1:5 to form a control group based on the variables of birth year, sex, and follow-up duration. Additionally, in patients who have ONFH, we looked for risk factors for progression to THA. RESULTS: Compared with the control group, ONFH patients had a low household income and had more diabetes, hypertension, dyslipidemia, and heavy alcohol use (drinking more than 3 to 7 drinks per week). Systemic corticosteroid use (≥ 1,800 mg) was significantly associated with an increased risk of ONFH incidence. However, lipid profiles, corticosteroid prescription, and cumulative doses of corticosteroid did not affect the progression to THA. CONCLUSION: The ONFH risk increased rapidly when cumulative prednisolone use was ≥ 1,800 mg. However, oral or high-dose intravenous corticosteroid use and cumulative dose did not affect the prognosis of ONFH. Since the occurrence and prognosis of ONFH are complex and multifactorial processes, further study is needed.

Bacterial neuraminidase inhibitory chalcones from flowers of Coreopsis lanceolata, their kinetic characterization and antibiofilm effect.

BACKGROUND: Bacteria within biofilms are thousand times more resistant to antibiotics. Neuraminidase is a crucial enzyme for bacterial adhesion and biofilm formation, it hydrolyzes glycosidic residue of glycoproteins, glycolipids, and oligosaccharides. Coreopsis lanceolata L. flowers may have a significant potential of bacterial neuraminidase (BNA) inhibition because of high natural abundance of chalcones. PURPOSE: The investigation of bacterial biofilm inhibitors has emerged as a novel therapeutic strategy against antibiotic resistance. Therefore, individual chalcones were isolated from C. lanceolata and their capacity to inhibit BNA and formation of Escherichia coli biofilm were evaluated. METHODS: Different chromatographic techniques were used to isolate the compounds (1-12). Enzyme inhibition and detailed kinetic behavior of compounds was determined by estimation of kinetic parameters (Michaelis-Menten constants (Km), maximum velocity (Vmax), dissociation constant for binding with the free enzyme (KI) and enzyme-substate complex (KIS)). Binding affinities (KSV) and binding modes of inhibitors were elucidated by fluorescence quenching and molecular docking, respectively. The natural abundance of chalcones was established through UPLC-Q-TOF/MS. The most potent inhibitor (1) was tested for its ability to inhibit the formation of E. coli biofilm, which was examined by crystal violet assay, scanning electron microscope (SEM) and confocal laser scanning microscope (CLSM). RESULTS: A series of eight chalcones (1-8) and four chalcone glucosides (9-12), inhibited BNA in a dose-dependent manner with IC50 of 8.3 ∼ 77.0 µM. The most potent chalcones were butein (1, IC50 = 8.3 µM) and its glucoside 9 (IC50 = 13.8 µM). The aglycones (1-8) showed non-competitive inhibition, while chalcone glucosides (9-12) displayed a mixed type I (KI < KIS). Inhibitory behaviors were doubly confirmed by KSV and matched with tendency of IC50. The functional group responsible for BNA inhibition were disclosed as 4'-hydroxyl group on B-ring by structure activity relationship (SAR) and molecular docking experiments. Butein (1) suppressed E. coli biofilm formation by > 50 % at 100 µM according to crystal violet assay, which was confirmed by SEM and CLSM imaging. CONCLUSION: The results showed that chalcones (1-8) and chalcone glucosides (9-12), metabolites isolated from the flowers of C. lanceolata, had BNA inhibitory and antibiofilm formation effect on E. coli.

Diabetic Ketoacidosis as an Effect of Sodium-Glucose Cotransporter 2 Inhibitor: Real World Insights.

One of the notable adverse effects of sodium-glucose cotransporter 2 (SGLT2) inhibitor is diabetic ketoacidosis (DKA) often characterized by euglycemia. In this retrospective review of patients with DKA from 2015 to 2023, 21 cases of SGLT2 inhibitorassociated DKA were identified. Twelve (57.1%) exhibited euglycemic DKA (euDKA) while nine (42.9%) had hyperglycemic DKA (hyDKA). More than 90% of these cases were patients with type 2 diabetes mellitus. Despite similar age, sex, body mass index, and diabetes duration, individuals with hyDKA showed poorer glycemic control and lower C-peptide levels compared with euDKA. Renal impairment and acidosis were worse in the hyDKA group, requiring hemodialysis in two patients. Approximately one-half of hyDKA patients had concurrent hyperosmolar hyperglycemic state. Common symptoms included nausea, vomiting, general weakness, and dyspnea. Seizure was the initial manifestation of DKA in two cases. Infection and volume depletion were major contributors, while carbohydrate restriction and inadequate insulin treatment also contributed to SGLT2 inhibitor-associated DKA. Despite their beneficial effects, clinicians should be vigilant for SGLT2 inhibitor risk associated with DKA.

Highly efficient and specific regulation of gene expression using enhanced CRISPR-Cas12f system.

The recently developed CRISPR activator (CRISPRa) system uses a CRISPR-Cas effector-based transcriptional activator to effectively control the expression of target genes without causing DNA damage. However, existing CRISPRa systems based on Cas9/Cas12a necessitate improvement in terms of efficacy and accuracy due to limitations associated with the CRISPR-Cas module itself. To overcome these limitations and effectively and accurately regulate gene expression, we developed an efficient CRISPRa system based on the small CRISPR-Cas effector Candidatus Woesearchaeota Cas12f (CWCas12f). By engineering the CRISPR-Cas module, linking activation domains, and using various combinations of linkers and nuclear localization signal sequences, the optimized eCWCas12f-VPR system enabled effective and target-specific regulation of gene expression compared with that using the existing CRISPRa system. The eCWCas12f-VPR system developed in this study has substantial potential for controlling the transcription of endogenous genes in living organisms and serves as a foundation for future gene therapy and biological research.

Real-time analysis and prediction method of ion concentration using the effect of O-H stretching bands in aqueous solutions based on ATR-FTIR spectroscopy.

Analyzing the concentration of ions in aqueous solutions in real-time plays an important role in the fields of chemistry and biology. Traditional methods for measuring ion concentrations, such as concentration analysis by measuring electrical conductivity, inductively coupled plasma mass spectrometry, and ion chromatography, have been used in many research fields. However, these methods are limited in determining ion concentrations instantaneously. Fourier-transform infrared-attenuated total reflectance (ATR-FTIR) spectroscopy provides a new approach for determining ion concentrations in aqueous solutions. This allows for fast analysis without pretreatment and is scalable for real-time measurements. In this study, we present a method for measuring ion concentrations by examining ion-water interactions in the O-H stretching band of aqueous solutions using ATR-FTIR spectroscopy. Five aqueous solutions, namely LiCl + HCl, LiOH + HCl, LiOH, Li3PO4, and NaCl were used in the experiments and prepared at concentrations between 0.5-2 M. The ion concentrations in the prepared aqueous solutions were measured using ATR-FTIR spectroscopy. We observed that the difference in absorbance increased and decreased linearly with changes in concentration. The concentration of ions in the aqueous solution could be measured by validating the designed linear regression analysis function model. In this study, we proposed five linear regression analysis function models, all of which showed high coefficients of determination above 0.9, with the highest coefficient of determination reaching 0.9969. These results show that ATR-FTIR spectroscopy has the potential to be applied as a rapid and simple concentration analysis system.

Effects of statin use on serum creatinine phosphokinase levels in normal thyroid function.

Background/Aims: Statins are common lipid-lowering agents used in dyslipidemia. However, they increase serum creatinine phosphokinase (CPK) levels. Currently, there are no studies on the effect of thyroid-stimulating hormone (TSH) levels on CPK levels after statin administration. Therefore, this study aimed to investigate CPK level alterations after statin administration according to TSH quartiles in participants with euthyroidism. Methods: This retrospective analysis included 25,047 patients with euthyroidism. CPK levels were measured before and 6 months after statin administration. Normal TSH levels were divided into four quartiles, and the CPK levels and proportions of patients with normal CPK levels after statin administration for each TSH quartile were evaluated. Results: The baseline CPK level was significantly higher in the lowest TSH quartile (Q1) compared to the other quartiles but decreased after statin administration. Thus, the difference between the CPK levels and the other quartile groups was not significant. The proportion of patients with normal CPK levels was also significantly lowest in Q1 before statin administration; however, no significant difference was noted in the ratio among each group after statin administration. These findings were consistent with the findings of the analysis according to statin intensity. Conclusions: In patients in the lowest TSH quartile of the normal TSH range, the CPK level decreased, and the proportion of normal CPK levels increased significantly after statin administration. However, similar changes were not observed in other TSH quartiles. Therefore, further studies are required to mechanistically confirm these conclusions.

Lipid Variability Induces Endothelial Dysfunction by Increasing Inflammation and Oxidative Stress.

BACKGRUOUND: This study investigates the impact of fluctuating lipid levels on endothelial dysfunction. METHODS: Human aortic and umbilical vein endothelial cells were cultured under varying palmitic acid (PA) concentrations: 0, 50, and 100 µM, and in a variability group alternating between 0 and 100 µM PA every 8 hours for 48 hours. In the lipid variability group, cells were exposed to 100 µM PA during the final 8 hours before analysis. We assessed inflammation using real-time polymerase chain reaction, Western blot, and cytokine enzyme-linked immunosorbent assay (ELISA); reactive oxygen species (ROS) levels with dichlorofluorescin diacetate assay; mitochondrial function through oxygen consumption rates via XF24 flux analyzer; and endothelial cell functionality via wound healing and cell adhesion assays. Cell viability was evaluated using the MTT assay. RESULTS: Variable PA levels significantly upregulated inflammatory genes and adhesion molecules (Il6, Mcp1, Icam, Vcam, E-selectin, iNos) at both transcriptomic and protein levels in human endothelial cells. Oscillating lipid levels reduced basal respiration, adenosine triphosphate synthesis, and maximal respiration, indicating mitochondrial dysfunction. This lipid variability also elevated ROS levels, contributing to a chronic inflammatory state. Functionally, these changes impaired cell migration and increased monocyte adhesion, and induced endothelial apoptosis, evidenced by reduced cell viability, increased BAX, and decreased BCL2 expression. CONCLUSION: Lipid variability induce endothelial dysfunction by elevating inflammation and oxidative stress, providing mechanistic insights into how lipid variability increases cardiovascular risk.

Clinical Implication of Maumgyeol Basic Biotypes-Electroencephalography- and Photoplethysmogram-Based Bwave State Inventory.

OBJECTIVE: The development of individual subtypes based on biomarkers offers a cost-effective and timely avenue to comprehending individual differences pertaining to mental health, independent from individuals' subjective insights. Incorporating 2-channel electroencephalography (EEG) and photoplethysmogram (PPG), we sought to establish a subtype classification system with clinical relevance. METHODS: One hundred healthy participants and 99 patients with psychiatric disorders were recruited. Classification thresholds were determined using the EEG and PPG data from 2,278 individuals without mental disorders, serving to classify subtypes in our sample of 199 participants. Multivariate analysis of variance was applied to examine psychological distinctions among these subtypes. K-means clustering was employed to verify the classification system. RESULTS: The distribution of subtypes differed between healthy participants and those with psychiatric disorders. Cognitive abilities were contingent upon brain subtypes, while mind subtypes exhibited significant differences in symptom severity, overall health, and cognitive stress. K-means clustering revealed that the results of our theory-based classification and data-driven classification are comparable. The synergistic assessment of both brain and mind subtypes was also explored. CONCLUSION: Our subtype classification system offers a concise means to access individuals' mental health. The utilization of EEG and PPG signals for subtype classification offers potential for the future of digital mental healthcare.

Machine learning model based on radiomics features for AO/OTA classification of pelvic fractures on pelvic radiographs.

Depending on the degree of fracture, pelvic fracture can be accompanied by vascular damage, and in severe cases, it may progress to hemorrhagic shock. Pelvic radiography can quickly diagnose pelvic fractures, and the Association for Osteosynthesis Foundation and Orthopedic Trauma Association (AO/OTA) classification system is useful for evaluating pelvic fracture instability. This study aimed to develop a radiomics-based machine-learning algorithm to quickly diagnose fractures on pelvic X-ray and classify their instability. data used were pelvic anteroposterior radiographs of 990 adults over 18 years of age diagnosed with pelvic fractures, and 200 normal subjects. A total of 93 features were extracted based on radiomics:18 first-order, 24 GLCM, 16 GLRLM, 16 GLSZM, 5 NGTDM, and 14 GLDM features. To improve the performance of machine learning, the feature selection methods RFE, SFS, LASSO, and Ridge were used, and the machine learning models used LR, SVM, RF, XGB, MLP, KNN, and LGBM. Performance measurement was evaluated by area under the curve (AUC) by analyzing the receiver operating characteristic curve. The machine learning model was trained based on the selected features using four feature-selection methods. When the RFE feature selection method was used, the average AUC was higher than that of the other methods. Among them, the combination with the machine learning model SVM showed the best performance, with an average AUC of 0.75±0.06. By obtaining a feature-importance graph for the combination of RFE and SVM, it is possible to identify features with high importance. The AO/OTA classification of normal pelvic rings and pelvic fractures on pelvic AP radiographs using a radiomics-based machine learning model showed the highest AUC when using the SVM classification combination. Further research on the radiomic features of each part of the pelvic bone constituting the pelvic ring is needed.

Efficacy and Safety of Metformin and Atorvastatin Combination Therapy vs. Monotherapy with Either Drug in Type 2 Diabetes Mellitus and Dyslipidemia Patients (ATOMIC): Double-Blinded Randomized Controlled Trial.

Background: It is well known that a large number of patients with diabetes also have dyslipidemia, which significantly increases the risk of cardiovascular disease (CVD). This study aimed to evaluate the efficacy and safety of combination drugs consisting of metformin and atorvastatin, widely used as therapeutic agents for diabetes and dyslipidemia. Methods: This randomized, double-blind, placebo-controlled, parallel-group and phase III multicenter study included adults with glycosylated hemoglobin (HbA1c) levels >7.0% and <10.0%, low-density lipoprotein cholesterol (LDL-C) >100 and <250 mg/dL. One hundred eighty-five eligible subjects were randomized to the combination group (metformin+atorvastatin), metformin group (metformin+atorvastatin placebo), and atorvastatin group (atorvastatin+metformin placebo). The primary efficacy endpoints were the percent changes in HbA1c and LDL-C levels from baseline at the end of the treatment. Results: After 16 weeks of treatment compared to baseline, HbA1c showed a significant difference of 0.94% compared to the atorvastatin group in the combination group (0.35% vs. -0.58%, respectively; P<0.0001), whereas the proportion of patients with increased HbA1c was also 62% and 15%, respectively, showing a significant difference (P<0.001). The combination group also showed a significant decrease in LDL-C levels compared to the metformin group (-55.20% vs. -7.69%, P<0.001) without previously unknown adverse drug events. Conclusion: The addition of atorvastatin to metformin improved HbA1c and LDL-C levels to a significant extent compared to metformin or atorvastatin alone in diabetes and dyslipidemia patients. This study also suggested metformin's preventive effect on the glucose-elevating potential of atorvastatin in patients with type 2 diabetes mellitus and dyslipidemia, insufficiently controlled with exercise and diet. Metformin and atorvastatin combination might be an effective treatment in reducing the CVD risk in patients with both diabetes and dyslipidemia because of its lowering effect on LDL-C and glucose.

Evaporation-Driven Energy Generation Using an Electrospun Polyacrylonitrile Nanofiber Mat with Different Support Substrates.

Water evaporation-driven energy harvesting is an emerging mechanism for contributing to green energy production with low cost. Herein, we developed polyacrylonitrile (PAN) nanofiber-based evaporation-driven electricity generators (PEEGs) to confirm the feasibility of utilizing electrospun PAN nanofiber mats in an evaporation-driven energy harvesting system. However, PAN nanofiber mats require a support substrate to enhance its durability and stability when it is applied to an evaporation-driven energy generator, which could have additional effects on generation performance. Accordingly, various support substrates, including fiberglass, copper, stainless mesh, and fabric screen, were applied to PEEGs and examined to understand their potential impacts on electrical generation outputs. As a result, the PAN nanofiber mats were successfully converted to a hydrophilic material for an evaporation-driven generator by dip-coating them in nanocarbon black (NCB) solution. Furthermore, specific electrokinetic performance trends were investigated and the peak electricity outputs of Voc were recorded to be 150.8, 6.5, 2.4, and 215.9 mV, and Isc outputs were recorded to be 143.8, 60.5, 103.8, and 121.4 µA, from PEEGs with fiberglass, copper, stainless mesh, and fabric screen substrates, respectively. Therefore, the implications of this study would provide further perspectives on the developing evaporation-induced electricity devices based on nanofiber materials.

Intrinsically Stretchable Floating Gate Memory Transistors for Data Storage of Electronic Skin Devices.

To propel electronic skin (e-skin) to the next level by integrating artificial intelligence features with advanced sensory capabilities, it is imperative to develop stretchable memory device technology. A stretchable memory device for e-skin must offer, in particular, long-term data storage while ensuring the security of personal information under any type of deformation. However, despite the significance of these needs, technology related to stretchable memory devices remains in its infancy. Here, we report an intrinsically stretchable floating gate (FG) polymer memory transistor. The device features a dual-stimuli (optical and electrical) writing system to prevent easy erasure of recorded data. An FG comprising an intermixture of Ag nanoparticles and elastomer and with proper energy-band alignment between the semiconductor and dielectric facilitated sustainable memory performance, while achieving a high memory on/off ratio (>105) and a long retention time (106 s) with the ability to withstand 50% uniaxial or 30% biaxial strain. In addition, our memory transistor exhibited high mechanical durability over multiple stretching cycles (1000 times), along with excellent environmental stability with respect to factors such as temperature, moisture, air, and delamination. Finally, we fabricated a 7 × 7 active-matrix memory transistor array for personalized storage of e-skin data and successfully demonstrated its functionality.

A Host Receptor Nanodisc-Based Biosensor Platform for the Detection of a Specific Virus and Its Variants.

The host receptor is a key element in the initial stage of the virus entry into the host. The use of this host receptor is valuable as a sensing element for selectively and sensitively detecting specific viruses. Also, viruses tend to escape neutralizing antibodies through viral mutation but still utilize the cell entry process using the same host receptors, so it would be a powerful detection tool even for the mutant viruses. The angiotensin-converting enzyme 2 (ACE2) receptor, which is the representative host receptor, performs an essential function in facilitating viral penetration by interacting with the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. In this study, we introduce a novel approach, where we fabricated a carbon nanotube field-effect transistor (CNT-FET) sensor and combined it with ACE2 receptor-embedded nanodisc (ND). ACE2 was produced using an E. coli expression system, purified, and integrated into the ND platform. ACE2 NDs showed robust functionality through interactions with a pseudotyped virus (PV) containing the spike protein, enabling sensitive detection of both SARS-CoV-2 and its genetic variations at 102 PFU/mL. The ACE ND-based sensor exhibited excellent selectivity by accurately differentiating SARS-CoV-2 wild-type and variants (Omicron, Delta) from other viruses (ZIKA and MERS-CoV). As a result of comparative analysis, ACE2 ND showed approximately 49% superior long-term functionality up to the second week compared to that of soluble ACE2. These findings highlight the high selectivity and sensitivity of host receptor-based sensors for detecting viral variants and provide a promising tool to prevent the spread of unknown viruses.

MXene/Hydrogel-based bioelectronic nose for the direct evaluation of food spoilage in both liquid and gas-phase environments.

Various bioelectronic noses have been recently developed for mimicking human olfactory systems. However, achieving direct monitoring of gas-phase molecules remains a challenge for the development of bioelectronic noses due to the instability of receptor and the limitations of its surrounding microenvironment. Here, we report a MXene/hydrogel-based bioelectronic nose for the sensitive detection of liquid and gaseous hexanal, a signature odorant from spoiled food. In this study, a conducting MXene/hydrogel structure was formed on a sensor via physical adsorption. Then, canine olfactory receptor 5269-embedded nanodiscs (cfOR5269NDs) which could selectively recognize hexanal molecules were embedded in the three-dimensional (3D) MXene/hydrogel structures using glutaraldehyde as a linker. Our MXene/hydrogel-based bioelectronic nose exhibited a high selectivity and sensitivity for monitoring hexanal in both liquid and gas phases. The bioelectronic noses could sensitively detect liquid and gaseous hexanal down to 10-18 M and 6.9 ppm, and they had wide detection ranges of 10-18 - 10-6 M and 6.9-32.9 ppm, respectively. Moreover, our bioelectronic nose allowed us to monitor hexanal levels in fish and milk. In this respect, our MXene/hydrogel-based bioelectronic nose could be a practical strategy for versatile applications such as food spoilage assessments in both liquid and gaseous systems.

Targeting CD73 with flavonoids inhibits cancer stem cells and increases lymphocyte infiltration in a triple-negative breast cancer mouse model.

Introduction: Chemotherapy remains the mainstay treatment for triple-negative breast cancer (TNBC) due to the lack of specific targets. Given a modest response of immune checkpoint inhibitors in TNBC patients, improving immunotherapy is an urgent and crucial task in this field. CD73 has emerged as a novel immunotherapeutic target, given its elevated expression on tumor, stromal, and specific immune cells, and its established role in inhibiting anti-cancer immunity. CD73-generated adenosine suppresses immunity by attenuating tumor-infiltrating T- and NK-cell activation, while amplifying regulatory T cell activation. Chemotherapy often leads to increased CD73 expression and activity, further suppressing anti-tumor immunity. While debulking the tumor mass, chemotherapy also enriches heterogenous cancer stem cells (CSC), potentially leading to tumor relapse. Therefore, drugs targeting both CD73, and CSCs hold promise for enhancing chemotherapy efficacy, overcoming treatment resistance, and improving clinical outcomes. However, safe and effective inhibitors of CD73 have not been developed as of now. Methods: We used in silico docking to screen compounds that may be repurposed for inhibiting CD73. The efficacy of these compounds was investigated through flow cytometry, RT-qPCR, CD73 activity, cell viability, tumorsphere formation, and other in vitro functional assays. For assessment of clinical translatability, TNBC patient-derived xenograft organotypic cultures were utilized. We also employed the ovalbumin-expressing AT3 TNBC mouse model to evaluate tumor-specific lymphocyte responses. Results: We identified quercetin and luteolin, currently used as over-the-counter supplements, to have high in silico complementarity with CD73. When quercetin and luteolin were combined with the chemotherapeutic paclitaxel in a triple-drug regimen, we found an effective downregulation in paclitaxel-enhanced CD73 and CSC-promoting pathways YAP and Wnt. We found that CD73 expression was required for the maintenance of CD44highCD24low CSCs, and co-targeting CD73, YAP, and Wnt effectively suppressed the growth of human TNBC cell lines and patient-derived xenograft organotypic cultures. Furthermore, triple-drug combination inhibited paclitaxel-enriched CSCs and simultaneously improved lymphocyte infiltration in syngeneic TNBC mouse tumors. Discussion: Conclusively, our findings elucidate the significance of CSCs in impairing anti-tumor immunity. The high efficacy of our triple-drug regimen in clinically relevant platforms not only underscores the importance for further mechanistic investigations but also paves the way for potential development of new, safe, and cost-effective therapeutic strategies for TNBC.

Blood vessel organoids generated by base editing and harboring single nucleotide variation in Notch3 effectively recapitulate CADASIL-related pathogenesis.

Human blood vessel organoids (hBVOs) offer a promising platform for investigating vascular diseases and identifying therapeutic targets. In this study, we focused on in vitro modeling and therapeutic target finding of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), the most common form of hereditary stroke disorder caused by mutations in the NOTCH3 gene. Despite the identification of these mutations, the underlying pathological mechanism is elusive, and effective therapeutic approaches are lacking. CADASIL primarily affects the blood vessels in the brain, leading to ischemic strokes, migraines, and dementia. By employing CRISPR/Cas9 base-editing technology, we generated human induced pluripotent stem cells (hiPSCs) carrying Notch3 mutations. These mutant hiPSCs were differentiated into hBVOs. The NOTCH3 mutated hBVOs exhibited CADASIL-like pathology, characterized by a reduced vessel diameter and degeneration of mural cells. Furthermore, we observed an accumulation of Notch3 extracellular domain (Notch3ECD), increased apoptosis, and cytoskeletal alterations in the NOTCH3 mutant hBVOs. Notably, treatment with ROCK inhibitors partially restored the disconnection between endothelial cells and mural cells in the mutant hBVOs. These findings shed light on the pathogenesis of CADASIL and highlight the potential of hBVOs for studying and developing therapeutic interventions for this debilitating human vascular disorder.