Targeting DNA junction sites by bis-intercalators induces topological changes with potent antitumor effects.

Targeting inter-duplex junctions in catenated DNA with bidirectional bis-intercalators is a potential strategy for enhancing anticancer effects. In this study, we used d(CGTATACG)2, which forms a tetraplex base-pair junction that resembles the DNA-DNA contact structure, as a model target for two alkyl-linked diaminoacridine bis-intercalators, DA4 and DA5. Cross-linking of the junction site by the bis-intercalators induced substantial structural changes in the DNA, transforming it from a B-form helical end-to-end junction to an over-wounded side-by-side inter-duplex conformation with A-DNA characteristics and curvature. These structural perturbations facilitated the angled intercalation of DA4 and DA5 with propeller geometry into two adjacent duplexes. The addition of a single carbon to the DA5 linker caused a bend that aligned its chromophores with CpG sites, enabling continuous stacking and specific water-mediated interactions at the inter-duplex contacts. Furthermore, we have shown that the different topological changes induced by DA4 and DA5 lead to the inhibition of topoisomerase 2 activities, which may account for their antitumor effects. Thus, this study lays the foundations for bis-intercalators targeting biologically relevant DNA-DNA contact structures for anticancer drug development.

FDX1-dependent and independent mechanisms of elesclomol-mediated intracellular copper delivery.

Recent studies have uncovered the therapeutic potential of elesclomol (ES), a copper-ionophore, for copper deficiency disorders. However, we currently do not understand the mechanism by which copper brought into cells as ES-Cu(II) is released and delivered to cuproenzymes present in different subcellular compartments. Here, we have utilized a combination of genetic, biochemical, and cell-biological approaches to demonstrate that intracellular release of copper from ES occurs inside and outside of mitochondria. The mitochondrial matrix reductase, FDX1, catalyzes the reduction of ES-Cu(II) to Cu(I), releasing it into mitochondria where it is bioavailable for the metalation of mitochondrial cuproenzyme- cytochrome c oxidase. Consistently, ES fails to rescue cytochrome c oxidase abundance and activity in copper-deficient cells lacking FDX1. In the absence of FDX1, the ES-dependent increase in cellular copper is attenuated but not abolished. Thus, ES-mediated copper delivery to nonmitochondrial cuproproteins continues even in the absence of FDX1, suggesting alternate mechanism(s) of copper release. Importantly, we demonstrate that this mechanism of copper transport by ES is distinct from other clinically used copper-transporting drugs. Our study uncovers a unique mode of intracellular copper delivery by ES and may further aid in repurposing this anticancer drug for copper deficiency disorders.

Zbtb16 increases susceptibility of atrial fibrillation in type 2 diabetic mice via Txnip-Trx2 signaling.

Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, and recent epidemiological studies suggested type 2 diabetes mellitus (T2DM) is an independent risk factor for the development of AF. Zinc finger and BTB (broad-complex, tram-track and bric-a-brac) domain containing 16 (Zbtb16) serve as transcriptional factors to regulate many biological processes. However, the potential effects of Zbtb16 in AF under T2DM condition remain unclear. Here, we reported that db/db mice displayed higher AF vulnerability and Zbtb16 was identified as the most significantly enriched gene by RNA sequencing (RNA-seq) analysis in atrium. In addition, thioredoxin interacting protein (Txnip) was distinguished as the key downstream gene of Zbtb16 by Cleavage Under Targets and Tagmentation (CUT&Tag) assay. Mechanistically, increased Txnip combined with thioredoxin 2 (Trx2) in mitochondrion induced excess reactive oxygen species (ROS) release, calcium/calmodulin-dependent protein kinase II (CaMKII) overactivation, and spontaneous Ca2+ waves (SCWs) occurrence, which could be inhibited through atrial-specific knockdown (KD) of Zbtb16 or Txnip by adeno-associated virus 9 (AAV9) or Mito-TEMPO treatment. High glucose (HG)-treated HL-1 cells were used to mimic the setting of diabetic in vitro. Zbtb16-Txnip-Trx2 signaling-induced excess ROS release and CaMKII activation were also verified in HL-1 cells under HG condition. Furthermore, atrial-specific Zbtb16 or Txnip-KD reduced incidence and duration of AF in db/db mice. Altogether, we demonstrated that interrupting Zbtb16-Txnip-Trx2 signaling in atrium could decrease AF susceptibility via reducing ROS release and CaMKII activation in the setting of T2DM.

From Monomers to Hexamers: A Theoretical Probability of the Neighbor Density Approach to Dissect Protein Oligomerization in Cells.

Deciphering the oligomeric state of proteins within cells is pivotal to understanding their role in intricate cellular processes. With the recent advances in single-molecule localization microscopy, previous efforts have harnessed protein location density approaches, coupled with simulations, to extract membrane protein oligomeric states in cells, highlighting the value of such techniques. However, a comprehensive theoretical approach that can be universally applied across different proteins (e.g., membrane and cytosolic proteins) remains elusive. Here, we introduce the theoretical probability of neighbor density (PND) as a robust tool to discern protein oligomeric states in cellular environments. Utilizing our approach, the theoretical PND was validated against simulated data for both membrane and cytosolic proteins, consistently aligning with experimental baselines for membrane proteins. This congruence was maintained even when adjusting for protein concentrations or exploring proteins of various oligomeric states. The strength of our method lies not only in its precision but also in its adaptability, accommodating diverse cellular protein scenarios without compromising the accuracy. The development and validation of the theoretical PND facilitate accurate protein oligomeric state determination and bolster our understanding of protein-mediated cellular functions.

Banff-based histologic chronicity index is associated with graft failure but has poor interobserver reproducibility.

BACKGROUND: Antibody-mediated rejection (AMR) often leads to chronic kidney allograft damage and is a critical cause of allograft failure. The Banff classification, used to diagnose AMR, has become complex and challenging for clinicians. A Banff-based histologic chronicity index (CI) was recently proposed as a simplified prognostic indicator. Its reliability and reproducibility have not been externally validated. METHODS: This study investigated 71 kidney allograft biopsies diagnosed with AMR. Interobserver reproducibility of the recently proposed CI and its components (cg, cv, ct, and ci) were assessed. The association between CI and allograft failure was analyzed, and CI cut-off values were evaluated by Cox proportional hazards regression and Kaplan-Meier estimator with log-rank test. RESULTS: The study confirmed the association of CI with allograft failure, but also revealed that the assessment of CI varied between pathologists, impacting its reproducibility as a prognostic tool. Only 49 (69.0%) of the biopsies showed complete agreement on the proposed cut-off value of CI < 4 or CI ≥ 4. Furthermore, this cut-off did not reliably stratify allograft failure. Notably, the cg score, which carries significant weight in the CI calculation, had the lowest agreement between observers (kappa = .281). CONCLUSIONS: While a simplified prognostic indicator for AMR is needed, this study highlights the limitations of CI, particularly its poor interobserver reproducibility. Our findings suggest that clinicians should interpret CI cautiously and consider establishing their own cut-off values. This study underscores the need to address interobserver reproducibility before CI can be widely adopted for AMR management.

Hepatic and Extrahepatic Characteristics of Autoimmune Hepatitis: A 23-year Hospital-Based Cohort Study.

BACKGROUND: The characteristics of autoimmune hepatitis (AIH) in Asia mostly remain elusive. METHODS: A cohort study of liver biopsy-proven AIH patients was conducted in a tertiary care cancer of Taiwan. RESULTS: From 1999 to 2022, of 13,766 patients who underwent liver biopsy, 150 patients with AIH were enrolled. The female-to-male ratio was 2.26. At baseline, the mean age was 51.09 years, mean alanine aminotransferase level was 494.11 U/L, and 17 (11.3%) had cirrhosis. All except one patient had AIH type 1. The females were older and had higher baseline cirrhosis rates than did the males. The 23-year cumulative incidences of cirrhosis, hepatocellular carcinoma (HCC), mortality/liver transplantation, autoimmune diseases and extrahepatic cancer were 64.2%, 13.3%, 23.4%, 30.7% and 21.2%, respectively. The 1-year, 2-year, 3-year, 5-year, 10-year and 20-year postimmunosuppressive therapy relapse rates were 60%, 78.2%, 81.8%, 89.1%, 94.5% and 100%, respectively. Baseline associations were as follows: alkaline phosphatase (Alk-p) levels with postimmunosuppressive therapy flare [hazard ratio (HR): 1.003; 95% CI HR: 1.000-1.005]; age with HCC (1.072; 1.010-1.138) and all-cause cancer (1.041;1.005-1.079); cirrhosis with mortality/liver transplantation (11.933;1.984-71.787); and antinuclear antibody (ANA) titers with mortality/liver transplantation (1.001;1.000-1.003), cirrhosis (1.001;1.000-1.002), and autoimmune diseases (1.001; 1.000-1.002). CONCLUSION: In an Asian country endemic for viral hepatitis, the female-to-male and baseline cirrhosis rates of AIH patients were lower than expected, while over 60% of the patients eventually developed cirrhosis. The high posttherapy relapse rate warrants cautious monitoring, particularly for patients with high baseline Alk-p levels. Baseline age, cirrhosis status and ANA titers are crucial for outcomes.

Associations of Atopic Dermatitis with Attention Deficit/Hyperactivity Disorder and Autism Spectrum Disorder: A Systematic Review and Meta-Analysis.

BACKGROUND: Atopic dermatitis (AD) shares similarities with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) regarding pathogenesis involving neuroinflammation and genetics. Nevertheless, evidence on the associations of AD with ADHD and/or ASD is inconclusive. This study aimed to systematically examine the existing evidence on the associations between AD, ADHD, and ASD. METHODS: The Meta-Analysis of Observational Studies in Epidemiology guideline was followed. We searched MEDLINE, Embase, Cochrane Library, and Web of Science databases from their respective inceptions to March 4, 2022. Observational studies providing adjusted estimates and/or prevalences for ADHD and ASD in patients with AD were enrolled. A random-effects model meta-analysis was conducted to calculate pooled odds ratios (ORs) and confidence intervals (CIs). Subgroup analyses according to AD severity, age, geographic location, and study design were performed. RESULTS: Overall, a total of 24 studies with 71,373,639 subjects were enrolled. Our meta-analysis demonstrated significant associations of AD with ADHD (pooled OR: 1.28; 95% CI: 1.18-1.40) and ASD (pooled OR: 1.87; 95% CI: 1.30-2.68). Subgroup analyses revealed that the associations for ADHD were the most prominent in studies evaluating severe AD patients as well as in studies focusing on school-age children and adolescents. Among patients with AD, the pooled prevalence of ADHD was 6.6%, and the respective prevalence of ASD was 1.6%. CONCLUSION: The evidence to date suggests significant associations of AD with ADHD and ASD. Psychiatric consultation and an interdisciplinary approach would benefit patients with AD presented with behavioral symptoms suggestive of ADHD or ASD.

Exploring the key elements for the successful management of primary otolaryngologic clinics in Taiwan.

AIM: This study aims to investigate the key elements for successful operation and management of primary otolaryngologic clinics in Taiwan amidst a declining birth rate and increasing competition among clinics. It employs the Innovation Through Tradition (ITT) theory as a theoretical framework to develop an operational model for effective management strategies. METHODS: This research utilized the triangulation method to identify key elements crucial for the operation and management of primary otolaryngologic clinics. Five key elements were identified, namely service attitude, medication efficacy, diagnostic and treatment procedures, treatment costs, and operating hours. Outpatient satisfaction was analyzed using Donabedian's structure-process-outcomes model to assess the impact of these elements on patient experience. RESULTS: Analysis revealed that service attitude significantly influences outpatient visits, indicating its paramount importance in clinic management. Patient satisfaction was highest in the service outcome dimension, emphasizing the significance of effective treatment outcomes. However, satisfaction was lowest in the service structure dimension, indicating potential areas for improvement in clinic infrastructure and organization. CONCLUSION: Understanding these key elements and enhancing outpatient satisfaction can drive improvements in the quality of medical services, contributing to the overall success of primary otolaryngologic clinics.

Radiomics analysis for the prediction of locoregional recurrence of locally advanced oropharyngeal cancer and hypopharyngeal cancer.

PURPOSE: By radiomic analysis of the postcontrast CT images, this study aimed to predict locoregional recurrence (LR) of locally advanced oropharyngeal cancer (OPC) and hypopharyngeal cancer (HPC). METHODS: A total of 192 patients with stage III-IV OPC or HPC from two independent cohort were randomly split into a training cohort with 153 cases and a testing cohort with 39 cases. Only primary tumor mass was manually segmented. Radiomic features were extracted using PyRadiomics, and then the support vector machine was used to build the radiomic model with fivefold cross-validation process in the training data set. For each case, a radiomics score was generated to indicate the probability of LR. RESULTS: There were 94 patients with LR assigned in the progression group and 98 patients without LR assigned in the stable group. There was no significant difference of TNM staging, treatment strategies and common risk factors between these two groups. For the training data set, the radiomics model to predict LR showed 83.7% accuracy and 0.832 (95% CI 0.72, 0.87) area under the ROC curve (AUC). For the test data set, the accuracy and AUC slightly declined to 79.5% and 0.770 (95% CI 0.64, 0.80), respectively. The sensitivity/specificity of training and test data set for LR prediction were 77.6%/89.6%, and 66.7%/90.5%, respectively. CONCLUSIONS: The image-based radiomic approach could provide a reliable LR prediction model in locally advanced OPC and HPC. Early identification of those prone to post-treatment recurrence would be helpful for appropriate adjustments to treatment strategies and post-treatment surveillance.

Influencing factors of examiner: Examples from certificated orthodontists board examination.

BACKGROUND: The rating result reflects not only the performance of the candidate but some extent of the examiner's preference. Examiner bias could be objective, which means it can't be changed by the examiner like gender, age, race, educational level, or professional experience. No study about examiner bias was performed in the dental education realm, especially in the orthodontic field. Therefore, this study aimed to figure out possible influencing factors in examiners from examples of the Taiwan Board of Orthodontist examination. METHODS: The examiner groups comprised 29 males and 21 females selected from the certificated Taiwan Board of Orthodontists. Every examiner would receive a series of lectures about rating standards before the exam. The score data were collected from 2009 to 2019. RESULTS: As for the univariate regression model of the Taiwan Board of Orthodontist examination, the experienced examiner with a certification of more than 15 years tends to rate more leniently, but female examiners tend to rate harsher. The scores would increase with the examiner's age in both the univariate regression model of self-prepared and assigned cases. CONCLUSION: As for the multivariate model of self-prepared exams, the elder and the examiner who work in private practice clinics tend to rate more leniently. As for the multivariate model of the assigned case exam, the score would be only affected by age. However, further studies are necessary to determine the direct relation among these factors.

From Molecules to Classrooms: A Comprehensive Guide to Single-Molecule Localization Microscopy.

Single-molecule localization microscopy (SMLM) has revolutionized our ability to visualize cellular structures, offering unprecedented detail. However, the intricate biophysical principles that underlie SMLM can be daunting for newcomers, particularly undergraduate and graduate students. To address this challenge, we introduce the fundamental concepts of SMLM, providing a solid theoretical foundation. In addition, we have developed an intuitive graphical interface APP that simplifies these core concepts, making them more accessible for students. This APP clarifies how super-resolved images are fitted and highlights the crucial factors determining image quality. Our approach deepens students' understanding of SMLM by combining theoretical instruction with practical learning. This development equips them with the skills to carry out single-molecule super-resolved experiments and explore the microscopic world beyond the diffraction limit.

Active control of terahertz surface plasmonic wave excitation using electromagnetically induced transparency based graphene metasurfaces.

Surface plasmonic waves (SPWs) that propagate at meta-dielectric interface are a good source of information carrier waves for on-chip photonic devices, where SPW excitation is one key procedure. Recently, controlling SPW excitation using metasurface methods has drawn considerable attention owing to their design flexibility, wherein achieving dynamic control is of great importance. However, most studies in the terahertz regime so far are working in a passive way or only dynamically controllable at the propagation process. In this work, an active design for controlling terahertz SPWs at the excitation process is proposed using graphene metasurfaces based on the manipulation of the electromagnetically induced transparency (EIT) effect. Large modulation depth with controllable SPW excitations is demonstrated. Our method is flexible and promising in achieving more controlling degree of freedom, which can find broadband applications in future integrated devices and systems.

SARS-CoV-2 Cases Reported on International Arriving and Domestic Flights: United States, January 2020-December 2021.

Objectives. To describe trends in the number of air travelers categorized as infectious with SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2; the virus that causes COVID-19) in the context of total US COVID-19 vaccinations administered, and overall case counts of SARS-CoV-2 in the United States. Methods. We searched the Quarantine Activity Reporting System (QARS) database for travelers with inbound international or domestic air travel, a positive SARS-CoV-2 lab result, and a surveillance categorization of SARS-CoV-2 infection reported during January 2020 to December 2021. Travelers were categorized as infectious during travel if they had arrival dates from 2 days before to 10 days after symptom onset or a positive viral test. Results. We identified 80 715 persons meeting our inclusion criteria; 67 445 persons (83.6%) had at least 1 symptom reported. Of 67 445 symptomatic passengers, 43 884 (65.1%) reported an initial symptom onset date after their flight arrival date. The number of infectious travelers mirrored the overall number of US SARS-CoV-2 cases. Conclusions. Most travelers in the study were asymptomatic during travel, and therefore unknowingly traveled while infectious. During periods of high community transmission, it is important for travelers to stay up to date with COVID-19 vaccinations and consider wearing a high-quality mask to decrease the risk of transmission. (Am J Public Health. 2023;113(8):904-908. https://doi.org/10.2105/AJPH.2023.307325).

Quantitative Proteomic Analysis on the Slightly Acidic Electrolyzed Water Triggered Viable but Non-Culturable Listeria monocytogenes.

This study undertakes a comprehensive exploration of the impact of slightly acidic electrolyzed water (SAEW) on Listeria monocytogenes, a common foodborne pathogen, with a particular focus on understanding the molecular mechanisms leading to the viable but nonculturable (VBNC) state. Given the widespread application of SAEW as an effective disinfectant in the food industry, uncovering these molecular pathways is crucial for improving food safety measures. We employed tandem mass tags (TMT), labeling proteomic techniques and LC-MS/MS to identify differentially expressed proteins under two doses of SAEW conditions. We indicated 203 differential expressed proteins (DEPs), including 78 up-regulated and 125 down-regulated DEPs. The functional enrichment analysis of these proteins indicated that ribosomes, biosynthesis of secondary metabolites, and aminoacyl-tRNA biosynthesis were enriched functions affected by SAEW. Further, we delved into the role of protein chlorination, a potential consequence of reactive chlorine species generated during the SAEW production process, by identifying 31 chlorinated peptides from 22 proteins, with a dominant sequence motif of Rxxxxx[cY] and functionally enriched in translation. Our findings suggest that SAEW might prompt alterations in the protein translation process and trigger compensatory ribosome biosynthesis. However, an imbalance in the levels of elongation factors and AARSs could hinder recovery, leading to the VBNC state. This research carries substantial implications for food safety and sanitation, as it adds to our understanding of the SAEW-induced VBNC state in L. monocytogenes and offers potential strategies for its control.

Physicochemical and Volatile Flavor Properties of Fish Skin under Conventional Frying, Air Frying and Vacuum Frying.

The aim of this study was to investigate the physicochemical characteristics and volatile flavor of fried tilapia skins under three frying methods. Conventional deep-fat frying usually increases the oil content of the fried fish skin and leads to lipid oxidation, which reduces the product quality. Alternative frying methods, such as air frying for 6 and 12 min under 180 °C (AF6, and AF12) and vacuum frying at 0.085 MPa for 8 and 24 min under 120 °C (VF8, and VF24) were compared to conventional frying for 2 and 8 min under 180 °C (CF2, and CF8) for tilapia skin. Physical properties of fried skin, such as the moisture content, water activity, L* values and breaking force decreased under all frying methods, while the lipid oxidation and a*, b* values increased with the increase in frying time. In general, VF offered higher hardness of product compared to AF which had a lower breaking force. Especially AF12 and CF8 had the lowest breaking force, which indicated higher crispness. For the oil quality inside the product, AF and VF reduced conjugated dienes formation and retarded oxidation compared to CF. The results of the flavor compositions of fish skin measured using gas chromatography mass spectrometry (GC/MS) with solid phase microextraction (SPME) showed that CF obtained higher unpleasant oily odor (nonanal, 2,4-decadienal, etc.), while AF presented greater grilling flavor (pyrazine derivatives). Because fish skin fried by AF only relied on hot air, Maillard reaction derived compounds, such as methylpyrazine, 2,5-dimethylpyrazine, and benzaldehyde were the leading flavors. This made the aroma profiles of AF very different from VF and CF. Among all the approaches, AF and VF developed lower oil content, mild fat oxidation and better flavor attributes, which proves their practical applications for frying tilapia fish skin.

Fusion extracted features from deep learning for identification of multiple positioning errors in dental panoramic imaging.

BACKGROUND: Dental panoramic imaging plays a pivotal role in dentistry for diagnosis and treatment planning. However, correctly positioning patients can be challenging for technicians due to the complexity of the imaging equipment and variations in patient anatomy, leading to positioning errors. These errors can compromise image quality and potentially result in misdiagnoses. OBJECTIVE: This research aims to develop and validate a deep learning model capable of accurately and efficiently identifying multiple positioning errors in dental panoramic imaging. METHODS AND MATERIALS: This retrospective study used 552 panoramic images selected from a hospital Picture Archiving and Communication System (PACS). We defined six types of errors (E1-E6) namely, (1) slumped position, (2) chin tipped low, (3) open lip, (4) head turned to one side, (5) head tilted to one side, and (6) tongue against the palate. First, six Convolutional Neural Network (CNN) models were employed to extract image features, which were then fused using transfer learning. Next, a Support Vector Machine (SVM) was applied to create a classifier for multiple positioning errors, using the fused image features. Finally, the classifier performance was evaluated using 3 indices of precision, recall rate, and accuracy. RESULTS: Experimental results show that the fusion of image features with six binary SVM classifiers yielded high accuracy, recall rates, and precision. Specifically, the classifier achieved an accuracy of 0.832 for identifying multiple positioning errors. CONCLUSIONS: This study demonstrates that six SVM classifiers effectively identify multiple positioning errors in dental panoramic imaging. The fusion of extracted image features and the employment of SVM classifiers improve diagnostic precision, suggesting potential enhancements in dental imaging efficiency and diagnostic accuracy. Future research should consider larger datasets and explore real-time clinical application.

Variations in Intracellular Organometallic Reaction Frequency Captured by Single-Molecule Fluorescence Microscopy.

Studies of organometallic reactions in living cells commonly rely on ensemble-averaged measurements, which can obscure the detection of reaction dynamics or location-specific behavior. This information is necessary to guide the design of bioorthogonal catalysts with improved biocompatibility, activity, and selectivity. By leveraging the high spatial and temporal resolution of single-molecule fluorescence microscopy, we have successfully captured single-molecule events promoted by Ru complexes inside live A549 human lung cells. By observing individual allylcarbamate cleavage reactions in real-time, our results revealed that they occur with greater frequency inside the mitochondria than in the non-mitochondria regions. The estimated turnover frequency of the Ru complexes was at least 3-fold higher in the former than the latter. These results suggest that organelle specificity is a critical factor to consider in intracellular catalyst design, such as in developing metallodrugs for therapeutic applications.

Adapting Longstanding Public Health Collaborations between Government of Kenya and CDC Kenya in Response to the COVID-19 Pandemic, 2020-2021.

Kenya's Ministry of Health (MOH) and the US Centers for Disease Control and Prevention in Kenya (CDC Kenya) have maintained a 40-year partnership during which measures were implemented to prevent, detect, and respond to disease threats. During the COVID-19 pandemic, the MOH and CDC Kenya rapidly responded to mitigate disease impact on Kenya's 52 million residents. We describe activities undertaken jointly by the MOH and CDC Kenya that lessened the effects of COVID-19 during 5 epidemic waves from March through December 2021. Activities included establishing national and county-level emergency operations centers and implementing workforce development and deployment, infection prevention and control training, laboratory diagnostic advancement, enhanced surveillance, and information management. The COVID-19 pandemic provided fresh impetus for the government of Kenya to establish a national public health institute, launched in January 2022, to consolidate its public health activities and counter COVID-19 and future infectious, vaccine-preventable, and emerging zoonotic diseases.

Effects of Luteolin on Human Breast Cancer Using Gene Expression Array: Inferring Novel Genes.

Taraxacum officinale (dandelion) is often used in traditional Chinese medicine for the treatment of cancer; however, the downstream regulatory genes and signaling pathways mediating its effects on breast cancer remain unclear. The present study aimed to explore the effects of luteolin, the main biologically active compound of T. officinale, on gene expression profiles in MDA-MB-231 and MCF-7 breast cancer cells. The results revealed that luteolin effectively inhibited the proliferation and motility of the MDA-MB-231 and MCF-7 cells. The mRNA expression profiles were determined using gene expression array analysis and analyzed using a bioinformatics approach. A total of 41 differentially expressed genes (DEGs) were found in the luteolin-treated MDA-MB-231 and MCF-7 cells. A Gene Ontology analysis revealed that the DEGs, including AP2B1, APP, GPNMB and DLST, mainly functioned as oncogenes. The human protein atlas database also found that AP2B1, APP, GPNMB and DLST were highly expressed in breast cancer and that AP2B1 (cut-off value, 75%) was significantly associated with survival rate (p = 0.044). In addition, a Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the DEGs were involved in T-cell leukemia virus 1 infection and differentiation. On the whole, the findings of the present study provide a scientific basis that may be used to evaluate the potential benefits of luteolin in human breast cancer. Further studies are required, however, to fully elucidate the role of the related molecular pathways.

End-to-end interstitial fibrosis assessment of kidney biopsies with a machine learning-based model.

BACKGROUND: The extent of interstitial fibrosis in the kidney not only correlates with renal function at the time of biopsy but also predicts future renal outcome. However, its assessment by pathologists lacks good agreement. The aim of this study is to construct a machine learning-based model that enables automatic and reliable assessment of interstitial fibrosis in human kidney biopsies. METHODS: Validated cortex, glomerulus and tubule segmentation algorithms were incorporated into a single model to assess the extent of interstitial fibrosis. The model performances were compared with expert renal pathologists and correlated with patients' renal functional data. RESULTS: Compared with human raters, the model had the best agreement [intraclass correlation coefficient (ICC) 0.90] to the reference in 50 test cases. The model also had a low mean bias and the narrowest 95% limits of agreement. The model was robust against colour variation on images obtained at different times, through different scanners, or from outside institutions with excellent ICCs of 0.92-0.97. The model showed significantly better test-retest reliability (ICC 0.98) than humans (ICC 0.76-0.94) and the amount of interstitial fibrosis inferred by the model strongly correlated with 405 patients' serum creatinine (r = 0.65-0.67) and estimated glomerular filtration rate (r = -0.74 to -0.76). CONCLUSIONS: This study demonstrated that a trained machine learning-based model can faithfully simulate the whole process of interstitial fibrosis assessment, which traditionally can only be carried out by renal pathologists. Our data suggested that such a model may provide more reliable results, thus enabling precision medicine.