Artificial Intelligence-Powered Imaging Biomarker Based on Mammography for Breast Cancer Risk Prediction.

The purposes of this study were to develop an artificial intelligence (AI) model for future breast cancer risk prediction based on mammographic images, investigate the feasibility of the AI model, and compare the AI model, clinical statistical risk models, and Mirai, a state of-the art deep learning algorithm based on screening mammograms for 1-5-year breast cancer risk prediction. We trained and developed a deep learning model using a total of 36,995 serial mammographic examinations from 21,438 women (cancer-enriched mammograms, 17.5%). To determine the feasibility of the AI prediction model, mammograms and detailed clinical information were collected. C-indices and area under the receiver operating characteristic curves (AUCs) for 1-5-year outcomes were obtained. We compared the AUCs of our AI prediction model, Mirai, and clinical statistical risk models, including the Tyrer-Cuzick (TC) model and Gail model, using DeLong's test. A total of 16,894 mammograms were independently collected for external validation, of which 4002 were followed by a cancer diagnosis within 5 years. Our AI prediction model obtained a C-index of 0.76, with AUCs of 0.90, 0.84, 0.81, 0.78, and 0.81, to predict the 1-5-year risks. Our AI prediction model showed significantly higher AUCs than those of the TC model (AUC: 0.57; p < 0.001) and Gail model (AUC: 0.52; p < 0.001), and achieved similar performance to Mirai. The deep learning AI model using mammograms and AI-powered imaging biomarkers has substantial potential to advance accurate breast cancer risk prediction.

DEHP (di(2-ethylhexyl)phthalate) stimulates skin pigmentation by perturbing cytoskeletal homeostasis.

Phthalates are extensively employed plasticizers crucial for conferring flexibility and plasticity to polyvinyl chloride. Phthalates, including DEHP (di(2-ethylhexyl)phthalate), present in diverse products, have been identified in fine dust and are capable of infiltrating the body, potentially posing health hazards. Importantly, melanocytes, existing at the basal layer of the epidermis, are susceptible to toxic substances. In our study, we employed the 3D human pigmented epidermis model, MelanoDerm™, along with the B16F10 murine melanoma cell line, to examine the influence of DEHP exposure on melanocytes. The exposure to low concentrations of DEHP (~ 5 µM), resulted in the extension of melanocyte dendrites, indicating the stimulation of melanocytes. Analysis of gene expression and protein profiles unveiled the up-regulation of MITF, Arpc2, and TRP1 genes subsequent to DEHP exposure, indicating alterations in cytoskeletal and melanosome-related genetic and protein components in melanocytes. Notably, increased pigmentation was observed in MelanoDerm™ following DEHP exposure. DEHP-stimulated reactive oxygen species generation appeared to be involved in these events since the antioxidant, ascorbic acid attenuated ROS generation and MITF upregulation. Collectively, our study demonstrated that DEHP exposure can induce cytoskeletal disturbance and skin pigmentation through oxidative stress.

In vivo editing of lung stem cells for durable gene correction in mice.

In vivo genome correction holds promise for generating durable disease cures; yet, effective stem cell editing remains challenging. In this work, we demonstrate that optimized lung-targeting lipid nanoparticles (LNPs) enable high levels of genome editing in stem cells, yielding durable responses. Intravenously administered gene-editing LNPs in activatable tdTomato mice achieved >70% lung stem cell editing, sustaining tdTomato expression in >80% of lung epithelial cells for 660 days. Addressing cystic fibrosis (CF), NG-ABE8e messenger RNA (mRNA)-sgR553X LNPs mediated >95% cystic fibrosis transmembrane conductance regulator (CFTR) DNA correction, restored CFTR function in primary patient-derived bronchial epithelial cells equivalent to Trikafta for F508del, corrected intestinal organoids and corrected R553X nonsense mutations in 50% of lung stem cells in CF mice. These findings introduce LNP-enabled tissue stem cell editing for disease-modifying genome correction.

Graves' orbitopathy development in thyroid cancer patients: a 16-year nationwide cohort study in South Korea.

BACKGROUND/OBJECTIVES: We aimed to investigate the prevalence, risk factors, and prognosis of Graves' orbitopathy (GO) in patients with thyroid cancer without a history of hyperthyroidism. SUBJECTS/METHODS: This retrospective cohort study analysed a sample from the Korean National Health Insurance Service database, which included 1,137,861 subjects from 2002 through 2019. Patients diagnosed with thyroid cancer, without a history of hyperthyroidism, were identified according to the Korean Standard Classification of Disease codes. The study compared the type of surgery, dose of radioactive iodine (RAI), and daily average thyroid hormone dose between patients who developed GO after being diagnosed with thyroid cancer and those who did not develop GO. We analysed the course of GO and the type of treatment. RESULTS: A total of 8499 cancer patients without a history of hyperthyroidism were identified, among whom 7836 underwent thyroidectomy. Of those who underwent thyroidectomy, 12 developed GO postoperatively. Among the 663 patients who did not undergo thyroidectomy, none developed GO. The prevalence of GO among thyroid cancer patients was 0.14%. The GO group received a significantly higher total RAI dose than the non-GO group (p = 0.036). There were no significant differences in sex, age, type of surgery, rate of RAI treatment, or average thyroid hormone dose between the two groups. One of the 12 patients who developed GO required intravenous steroids. CONCLUSIONS: Although GO rarely develops in thyroid cancer patients without coexisting hyperthyroidism, the total RAI dose may increase its risk. Further research would help clarify GO's association with thyroid cancer.

Soft Bioelectronics Using Nanomaterials and Nanostructures for Neuroengineering.

The identification of neural networks for large areas and the regulation of neuronal activity at the single-neuron scale have garnered considerable attention in neuroscience. In addition, detecting biochemical molecules and electrically, optically, and chemically controlling neural functions are key research issues. However, conventional rigid and bulky bioelectronics face challenges for neural applications, including mechanical mismatch, unsatisfactory signal-to-noise ratio, and poor integration of multifunctional components, thereby degrading the sensing and modulation performance, long-term stability and biocompatibility, and diagnosis and therapy efficacy. Implantable bioelectronics have been developed to be mechanically compatible with the brain environment by adopting advanced geometric designs and utilizing intrinsically stretchable materials, but such advances have not been able to address all of the aforementioned challenges.Recently, the exploration of nanomaterial synthesis and nanoscale fabrication strategies has facilitated the design of unconventional soft bioelectronics with mechanical properties similar to those of neural tissues and submicrometer-scale resolution comparable to typical neuron sizes. The introduction of nanotechnology has provided bioelectronics with improved spatial resolution, selectivity, single neuron targeting, and even multifunctionality. As a result, this state-of-the-art nanotechnology has been integrated with bioelectronics in two main types, i.e., bioelectronics integrated with synthesized nanomaterials and bioelectronics with nanoscale structures. The functional nanomaterials can be synthesized and assembled to compose bioelectronics, allowing easy customization of their functionality to meet specific requirements. The unique nanoscale structures implemented with the bioelectronics could maximize the performance in terms of sensing and stimulation. Such soft nanobioelectronics have demonstrated their applicability for neuronal recording and modulation over a long period at the intracellular level and incorporation of multiple functions, such as electrical, optical, and chemical sensing and stimulation functions.In this Account, we will discuss the technical pathways in soft bioelectronics integrated with nanomaterials and implementing nanostructures for application to neuroengineering. We traced the historical development of bioelectronics from rigid and bulky structures to soft and deformable devices to conform to neuroengineering requirements. Recent approaches that introduced nanotechnology into neural devices enhanced the spatiotemporal resolution and endowed various device functions. These soft nanobioelectronic technologies are discussed in two categories: bioelectronics with synthesized nanomaterials and bioelectronics with nanoscale structures. We describe nanomaterial-integrated soft bioelectronics exhibiting various functionalities and modalities depending on the integrated nanomaterials. Meanwhile, soft bioelectronics with nanoscale structures are explained with their superior resolution and unique administration methods. We also exemplified the neural sensing and stimulation applications of soft nanobioelectronics across various modalities, showcasing their clinical applications in the treatment of neurological diseases, such as brain tumors, epilepsy, and Parkinson's disease. Finally, we discussed the challenges and direction of next-generation technologies.

TauFlowNet: Revealing latent propagation mechanism of tau aggregates using deep neural transport equations.

Mounting evidence shows that Alzheimer's disease (AD) is characterized by the propagation of tau aggregates throughout the brain in a prion-like manner. Since current pathology imaging technologies only provide a spatial mapping of tau accumulation, computational modeling becomes indispensable in analyzing the spatiotemporal propagation patterns of widespread tau aggregates from the longitudinal data. However, current state-of-the-art works focus on the longitudinal change of focal patterns, lacking a system-level understanding of the tau propagation mechanism that can explain and forecast the cascade of tau accumulation. To address this limitation, we conceptualize that the intercellular spreading of tau pathology forms a dynamic system where each node (brain region) is ubiquitously wired with other nodes while interacting with the build-up of pathological burdens. In this context, we formulate the biological process of tau spreading in a principled potential energy transport model (constrained by brain network topology), which allows us to develop an explainable neural network for uncovering the spatiotemporal dynamics of tau propagation from the longitudinal tau-PET scans. Specifically, we first translate the transport equation into a GNN (graph neural network) backbone, where the spreading flows are essentially driven by the potential energy of tau accumulation at each node. Conventional GNNs employ a l2-norm graph smoothness prior, resulting in nearly equal potential energies across nodes, leading to vanishing flows. Following this clue, we introduce the total variation (TV) into the graph transport model, where the nature of system's Euler-Lagrange equations is to maximize the spreading flow while minimizing the overall potential energy. On top of this min-max optimization scenario, we design a generative adversarial network (GAN-like) to characterize the TV-based spreading flow of tau aggregates, coined TauFlowNet. We evaluate our TauFlowNet on ADNI and OASIS datasets in terms of the prediction accuracy of future tau accumulation and explore the propagation mechanism of tau aggregates as the disease progresses. Compared to the current counterpart methods, our physics-informed deep model yields more accurate and interpretable results, demonstrating great potential in discovering novel neurobiological mechanisms through the lens of machine learning.

FXR Agonism with Bile Acid Mimetic Reduces Pre-Clinical Triple-Negative Breast Cancer Burden.

Bariatric surgery is associated with improved outcomes for several cancers, including breast cancer (BC), although the mechanisms mediating this protection are unknown. We hypothesized that elevated bile acid pools detected after bariatric surgery may be factors that contribute to improved BC outcomes. Patients with greater expression of the bile acid receptor FXR displayed improved survival in specific aggressive BC subtypes. FXR is a nuclear hormone receptor activated by primary bile acids. Therefore, we posited that activating FXR using an established FDA-approved agonist would induce anticancer effects. Using in vivo and in vitro approaches, we determined the anti-tumor potential of bile acid receptor agonism. Indeed, FXR agonism by the bile acid mimetic known commercially as Ocaliva ("OCA"), or Obeticholic acid (INT-747), significantly reduced BC progression and overall tumor burden in a pre-clinical model. The transcriptomic analysis of tumors in mice subjected to OCA treatment revealed differential gene expression patterns compared to vehicle controls. Notably, there was a significant down-regulation of the oncogenic transcription factor MAX (MYC-associated factor X), which interacts with the oncogene MYC. Gene set enrichment analysis (GSEA) further demonstrated a statistically significant downregulation of the Hallmark MYC-related gene set (MYC Target V1) following OCA treatment. In human and murine BC analyses in vitro, agonism of FXR significantly and dose-dependently inhibited proliferation, migration, and viability. In contrast, the synthetic agonism of another common bile acid receptor, the G protein-coupled bile acid receptor TGR5 (GPBAR1) which is mainly activated by secondary bile acids, failed to significantly alter cancer cell dynamics. In conclusion, agonism of FXR by primary bile acid memetic OCA yields potent anti-tumor effects potentially through inhibition of proliferation and migration and reduced cell viability. These findings suggest that FXR is a tumor suppressor gene with a high potential for use in personalized therapeutic strategies for individuals with BC.

Screening mammography performance according to breast density: a comparison between radiologists versus standalone intelligence detection.

BACKGROUND: Artificial intelligence (AI) algorithms for the independent assessment of screening mammograms have not been well established in a large screening cohort of Asian women. We compared the performance of screening digital mammography considering breast density, between radiologists and AI standalone detection among Korean women. METHODS: We retrospectively included 89,855 Korean women who underwent their initial screening digital mammography from 2009 to 2020. Breast cancer within 12 months of the screening mammography was the reference standard, according to the National Cancer Registry. Lunit software was used to determine the probability of malignancy scores, with a cutoff of 10% for breast cancer detection. The AI's performance was compared with that of the final Breast Imaging Reporting and Data System category, as recorded by breast radiologists. Breast density was classified into four categories (A-D) based on the radiologist and AI-based assessments. The performance metrics (cancer detection rate [CDR], sensitivity, specificity, positive predictive value [PPV], recall rate, and area under the receiver operating characteristic curve [AUC]) were compared across breast density categories. RESULTS: Mean participant age was 43.5 ± 8.7 years; 143 breast cancer cases were identified within 12 months. The CDRs (1.1/1000 examination) and sensitivity values showed no significant differences between radiologist and AI-based results (69.9% [95% confidence interval [CI], 61.7-77.3] vs. 67.1% [95% CI, 58.8-74.8]). However, the AI algorithm showed better specificity (93.0% [95% CI, 92.9-93.2] vs. 77.6% [95% CI, 61.7-77.9]), PPV (1.5% [95% CI, 1.2-1.9] vs. 0.5% [95% CI, 0.4-0.6]), recall rate (7.1% [95% CI, 6.9-7.2] vs. 22.5% [95% CI, 22.2-22.7]), and AUC values (0.8 [95% CI, 0.76-0.84] vs. 0.74 [95% CI, 0.7-0.78]) (all P < 0.05). Radiologist and AI-based results showed the best performance in the non-dense category; the CDR and sensitivity were higher for radiologists in the heterogeneously dense category (P = 0.059). However, the specificity, PPV, and recall rate consistently favored AI-based results across all categories, including the extremely dense category. CONCLUSIONS: AI-based software showed slightly lower sensitivity, although the difference was not statistically significant. However, it outperformed radiologists in recall rate, specificity, PPV, and AUC, with disparities most prominent in extremely dense breast tissue.

Disentangling sex-dependent effects of APOE on diverse trajectories of cognitive decline in Alzheimer's disease.

Current diagnostic systems for Alzheimer's disease (AD) rely upon clinical signs and symptoms, despite the fact that the multiplicity of clinical symptoms renders various neuropsychological assessments inadequate to reflect the underlying pathophysiological mechanisms. Since putative neuroimaging biomarkers play a crucial role in understanding the etiology of AD, we sought to stratify the diverse relationships between AD biomarkers and cognitive decline in the aging population and uncover risk factors contributing to the diversities in AD. To do so, we capitalized on a large amount of neuroimaging data from the ADNI study to examine the inflection points along the dynamic relationship between cognitive decline trajectories and whole-brain neuroimaging biomarkers, using a state-of-the-art statistical model of change point detection. Our findings indicated that the temporal relationship between AD biomarkers and cognitive decline may differ depending on the synergistic effect of genetic risk and biological sex. Specifically, tauopathy-PET biomarkers exhibit a more dynamic and age-dependent association with Mini-Mental State Examination scores (p<0.05), with inflection points at 72, 78, and 83 years old, compared with amyloid-PET and neurodegeneration (cortical thickness from MRI) biomarkers. In the landscape of health disparities in AD, our analysis indicated that biological sex moderates the rate of cognitive decline associated with APOE4 genotype. Meanwhile, we found that higher education levels may moderate the effect of APOE4, acting as a marker of cognitive reserve.

Associations between Chronic Kidney Disease and Migraine Incidence: Findings from a Korean Longitudinal Big Data Study.

While headaches frequently occur in individuals with chronic kidney disease (CKD), there are few statistical evaluations of their connection to migraines in population-based studies. In this nationwide longitudinal follow-up study of Korean health examination data (2002-2019), a total of 15,443 participants with CKD and 61,772 matched controls were enrolled. We applied overlap-weighted Cox proportional hazard regression models to assess hazard ratios, examining the correlation between CKD and the development of migraines. After accounting for various factors, we observed a modest reduction of approximately 11% in the likelihood of migraine occurrence among CKD patients (95% confidence intervals = 0.81-0.97) during the 16-year monitoring period. Subgroup analysis revealed a significant association among specific demographic and health conditions, including individuals aged 70 or older, females, overweight individuals, nonsmokers, and those without hypertension or diabetes. Our research may indicate a potential relationship between CKD and the onset of migraines in Korean adults, suggesting a slight reduction in the probability of the occurrence of migraines among those with CKD. These findings emphasize the need for attentive follow-up and preventive management in individuals without the identified protective factors, particularly in male CKD patients under the age of 70 with hypertension.

Investigation of the Approaches to Optimal Exercise Interventions Based on Dementia Type: A Theoretical Review.

The aim of this study is to enhance comprehension of the different types and features of dementia, including their symptoms, diagnosis and medical treatment, and to propose various evidence-based exercise interventions and their clinical applications tailored to each specific type of dementia. The theoretical review includes the analysis of publications in the scientific databases PubMed/Medline, Ebsco, Scielo, and Google. A total of 177 articles were found, of which 84 were studied in depth. With the prevalence of all forms of dementia projected to increase from 57.4 million in 2019 to 152.8 million in 2050, personalized treatment strategies are needed. This review discusses various forms of dementia, including their pathologies, diagnostic criteria, and prevalence rates. The importance of accurate diagnosis and tailored care is emphasized, as well as the effectiveness of physical exercise in improving cognitive function in dementia patients. For Alzheimer's, a combination of drug therapies and exercises is recommended to enhance cerebral blood flow and neurotransmitter activity. To improve cognitive and motor functions in Lewy body dementia, a combination of pharmacological and physical therapies is recommended. For managing frontotemporal dementia, a mix of medication and exercises aimed at emotion regulation, including aerobic exercises, and a unified protocol, is suggested. For mild cognitive impairment, aerobic and functional exercises are important in delaying cognitive decline and enhancing cognitive performance. In conclusion, individualized care and treatment plans tailored to the specific characteristics of each disease type can improve the quality of life for individuals with this condition and effectively manage this growing global health issue.

Combined DNA Methylation and Gastric Microbiome Marker Predicts Helicobacter pylori-Negative Gastric Cancer.

Background/Aims: While DNA methylation and gastric microbiome are each associated with gastric cancer (GC), their combined role in predicting GC remains unclear. This study investigated the potential of a combined DNA methylation and gastric microbiome signature to predict Helicobacter pylori-negative GC. Methods: In this case-control study, we conducted quantitative methylation-specific polymerase chain reaction to measure the methylation levels of DKK3, SFRP1, EMX1, NKX6-1, MIR124-3, and TWIST1 in the gastric mucosa from 75 H. pylori-negative patients, including chronic gastritis (CG), intestinal metaplasia (IM), and GC. A combined analysis of DNA methylation and gastric microbiome, using 16S rRNA gene sequencing, was performed in 30 of 75 patients. Results: The methylation levels of DKK3, SFRP1, EMX1, MIR124-3, and TWIST1 were significantly higher in patients with GC than in controls (all q<0.05). MIR124-3 and TWIST1 methylation levels were higher in patients with IM than those with CG and also in those with GC than in those with IM (all q<0.05). A higher methylation level of TWIST1 was an independent predictor for H. pylori-negative GC after adjusting for age, sex, and atrophy (odds ratio [OR], 15.15; 95% confidence interval [CI], 1.58 to 145.46; p=0.018). The combination of TWIST1 methylation and GC microbiome index (a microbiome marker) was significantly associated with H. pylori-negative GC after adjusting for age, sex, and atrophy (OR, 50.00; 95% CI, 1.69 to 1,476; p=0.024). Conclusions: The combination of TWIST1 methylation and GC microbiome index may offer potential as a biomarker for predicting H. pylori-negative GC.

Association between Gout and Gastric Cancer: A Nested Case-Control Study Using a National Health Sample Cohort.

Given the global significance of gout and gastric cancer (GC) as major health problems with interrelated impacts, we examined the development of GC in Korean patients with gout. We conducted a nested case-control study using data from 10,174 GC patients and 40,696 control patients from the Korean National Health Insurance Service-National Sample Cohort database. Propensity score matching (1:4) with propensity score overlap-weighted adjustment was used to reduce selection bias and estimate the odds ratio (OR) and 95% confidence intervals (CIs) for the association between gout and GC. An adjusted OR for GC was not significantly higher in patients with gout than in control patients (1.02; 95% CI, 0.93-1.12; p = 0.652). Additionally, no association between gout and GC was observed in subgroup analyses such as sex, age, level of income, region of residence, or Charlson Comorbidity Index score. In conclusion, these results suggest that gout is not a significant independent risk factor for GC among the Korean population. Additional investigation is required to establish a causal association between gout and GC, and to generalize these results to general populations.

Native architecture of a human GBP1 defense complex for cell-autonomous immunity to infection.

All living organisms deploy cell-autonomous defenses to combat infection. In plants and animals, large supramolecular complexes often activate immune proteins for protection. In this work, we resolved the native structure of a massive host-defense complex that polymerizes 30,000 guanylate-binding proteins (GBPs) over the surface of gram-negative bacteria inside human cells. Construction of this giant nanomachine took several minutes and remained stable for hours, required guanosine triphosphate hydrolysis, and recruited four GBPs plus caspase-4 and Gasdermin D as a cytokine and cell death immune signaling platform. Cryo-electron tomography suggests that GBP1 can adopt an extended conformation for bacterial membrane insertion to establish this platform, triggering lipopolysaccharide release that activated coassembled caspase-4. Our "open conformer" model provides a dynamic view into how the human GBP1 defense complex mobilizes innate immunity to infection.

Dietary intake is associated with the prevalence of uterine leiomyoma in Korean women: A retrospective cohort study.

OBJECTIVE: Uterine leiomyoma (UL), the most prevalent benign gynecologic tumor among reproductive-aged women, lacks sufficient research on the potential association between dietary intake and its occurrence in Korean women. Addressing this research gap, this study aims to evaluate the potential link between dietary intake and the prevalence of UL in Korean women. METHODS: In this cross-sectional study, a cohort of 672 women, aged 23 to 73, were enrolled, with 383 (57%) being premenopausal. Dietary intake was assessed using a validated food frequency questionnaire (FFQ), and UL presence was determined through ultrasonography. The analysis focused exclusively on items within ten categories, including vegetables/fruit, vegetables, fruits, red meat, processed meat, poultry, fish, dairy product, milk, and alcohol. Multiple logistic regression models were employed to explore the relationship between dietary intake and the prevalence of UL, calculating odds ratios (ORs) and 95% confidence intervals (CIs) while adjusting for confounding factors. RESULTS: Within the total cohort, 220 (32.7%) women were diagnosed with UL. High intakes of fish and poultry showed an association with higher UL prevalence. Odds ratios (95% CIs) for the upper quartiles compared to the lower quartiles were 1.68 (1.01-2.81; p trend = 0.05) for fish intake and 1.87 (1.11-3.17; p trend = 0.06) for poultry intake. Conversely, an inverse relationship emerged between dairy product intake and UL prevalence, with an odds ratio of 0.58 (95% CI 0.35-0.96; p trend = 0.05). Stratifying the analysis by menopausal status revealed a parallel pattern, with heightened UL prevalence with fish intake and reduced prevalence with dairy product intake. However, the link between poultry intake and UL prevalence was primarily observed among postmenopausal women. Among premenopausal women, elevated vegetable intake was linked to a decreased UL prevalence (OR 0.45, 95% CI 0.21-0.97 for top vs. bottom quartiles; p trend = 0.01). CONCLUSION: We found that high consumption of fish and poultry, coupled with low intake of dairy products, correlated with an elevated prevalence of UL. Furthermore, vegetable intake exhibited an inverse relationship with UL prevalence, particularly among premenopausal women.

Potential Molecular Markers Related to Lymph Node Metastasis and Stalk Resection Margins in Pedunculated T1 Colorectal Cancers Using Digital Spatial Profiling: A Pilot Study with a Small Case Series.

There is a debate regarding the prediction of lymph node metastasis (LNM) in pedunculated T1 colorectal cancer (CRC). In this study with four cases of pedunculated T1 CRCs, we aimed to investigate gene expression variations based on the distance from the Haggitt line (HL) and identify potential molecular risk factors for LNM. By leveraging the Cancer Transcriptome Atlas and digital spatial profiling technology, we meticulously analyzed discrete regions, including the head, HL, proximal stalk region (300-1000 µm from HL), and distal stalk region (1500-2000 µm from HL) to identify spatially sequential molecular changes. Our findings showed significant overall gene expression variations among the head, proximal stalk, and distal stalk regions of pedunculated T1 CRCs compared to the control adenoma. Compared to LNM-negative T1 CRCs, LNM-positive T1 CRC showed that the expression of genes involved in immune-related pathways such as B2M, HLA-B, and HLA-E were significantly downregulated in the distal stalk region compared to the proximal stalk region. In summary, our results may tentatively suggest considering endoscopic resection of the stalk with a minimum 2000 µm margin from the HL, taking into account the gene expression alterations related to immune-related pathways. However, we acknowledge the limitations of this pilot study, notably the small case series, which may restrict the depth of interpretation. Further validation is imperative to substantiate these findings.

Millennial-scale variability of Greenland dust provenance during the last glacial maximum as determined by single particle analysis.

Greenland ice core records exhibited 100-fold higher dust concentrations during the Last Glacial Maximum (LGM) than during the Holocene, and dust input temporal variability corresponded to different climate states in the LGM. While East Asian deserts, the Sahara, and European loess have been suggested as the potential source areas (PSAs) for Greenland LGM dust, millennial-scale variability in their relative contributions within the LGM remains poorly constrained. Here, we present the morphological, mineralogical, and geochemical characteristics of insoluble microparticles to constrain the provenance of dust in Greenland NEEM ice core samples covering cold Greenland Stadials (GS)-2.1a to GS-3 (~ 14.7 to 27.1 kyr ago) in the LGM. The analysis was conducted on individual particles in microdroplet samples by scanning electron microscopy with energy dispersive X-ray spectroscopy and Raman microspectroscopy. We found that the kaolinite-to-chlorite (K/C) ratios and chemical index of alteration (CIA) values were substantially higher (K/C: 1.4 ± 0.7, CIA: 74.7 ± 2.9) during GS-2.1a to 2.1c than during GS-3 (K/C: 0.5 ± 0.1, CIA: 65.8 ± 2.8). Our records revealed a significant increase in Saharan dust contributions from GS-2.1a to GS-2.1c and that the Gobi Desert and/or European loess were potential source(s) during GS-3. This conclusion is further supported by distinctly different carbon contents in particles corresponding to GS-2.1 and GS-3. These results are consistent with previous estimates of proportional dust source contributions obtained using a mixing model based on Pb and Sr isotopic compositions in NEEM LGM ice and indicate millennial-scale changes in Greenland dust provenance that are probably linked to large-scale atmospheric circulation variabilities during the LGM.

Glucagon-Like Peptide Receptor Agonist Inhibits Angiotensin II-Induced Proliferation and Migration in Vascular Smooth Muscle Cells and Ameliorates Phosphate-Induced Vascular Smooth Muscle Cells Calcification.

BACKGRUOUND: Glucagon-like peptide-1 receptor agonist (GLP-1RA), which is a therapeutic agent for the treatment of type 2 diabetes mellitus, has a beneficial effect on the cardiovascular system. METHODS: To examine the protective effects of GLP-1RAs on proliferation and migration of vascular smooth muscle cells (VSMCs), A-10 cells exposed to angiotensin II (Ang II) were treated with either exendin-4, liraglutide, or dulaglutide. To examine the effects of GLP-1RAs on vascular calcification, cells exposed to high concentration of inorganic phosphate (Pi) were treated with exendin-4, liraglutide, or dulaglutide. RESULTS: Ang II increased proliferation and migration of VSMCs, gene expression levels of Ang II receptors AT1 and AT2, proliferation marker of proliferation Ki-67 (Mki-67), proliferating cell nuclear antigen (Pcna), and cyclin D1 (Ccnd1), and the protein expression levels of phospho-extracellular signal-regulated kinase (p-Erk), phospho-c-JUN N-terminal kinase (p-JNK), and phospho-phosphatidylinositol 3-kinase (p-Pi3k). Exendin-4, liraglutide, and dulaglutide significantly decreased the proliferation and migration of VSMCs, the gene expression levels of Pcna, and the protein expression levels of p-Erk and p-JNK in the Ang II-treated VSMCs. Erk inhibitor PD98059 and JNK inhibitor SP600125 decreased the protein expression levels of Pcna and Ccnd1 and proliferation of VSMCs. Inhibition of GLP-1R by siRNA reversed the reduction of the protein expression levels of p-Erk and p-JNK by exendin-4, liraglutide, and dulaglutide in the Ang II-treated VSMCs. Moreover, GLP-1 (9-36) amide also decreased the proliferation and migration of the Ang II-treated VSMCs. In addition, these GLP-1RAs decreased calcium deposition by inhibiting activating transcription factor 4 (Atf4) in Pi-treated VSMCs. CONCLUSION: These data show that GLP-1RAs ameliorate aberrant proliferation and migration in VSMCs through both GLP-1Rdependent and independent pathways and inhibit Pi-induced vascular calcification.

Coffee consumption affects kidney function based on GCKR polymorphism in a Korean population.

Kidney function can be preserved through pharmacological interventions and nonpharmacological strategies, such as lifestyle and dietary adjustments. Among these, coffee has been linked to protective effects on kidney function. However, few studies have investigated the effect of coffee consumption on kidney function according to specific genes. We hypothesized that the impact of coffee consumption on kidney function might vary depending on GCKR polymorphism. GCKR rs1260326 polymorphism was examined using the Korean genome and epidemiology data from 656 chronic kidney disease (CKD) cases and 38,540 individuals without CKD (non-CKD). GCKR polymorphism has been previously associated with both coffee consumption and kidney function in Europeans. We replicated the associations between GCKR rs1260326 and coffee consumption and kidney function in Korean individuals. We also explored the effect of coffee consumption on kidney function by multivariate logistic regression analysis. Individuals with the rs1260326 (TC/CC) genotype did not experience significant changes in CKD risk based on their coffee consumption habits. In contrast, individuals with the TT genotype exhibited a significantly lower risk of CKD based on coffee consumption. Interestingly, in the non-CKD group, a beneficial effect on estimated glomerular filtration rate was observed in individuals with the T allele as coffee consumption increased. Our findings supported the hypothesis and revealed that the impact of coffee consumption habits on kidney function may vary based on the GCKR rs1260326 genotype of Korean individuals.

Dysregulation of autophagy activation induced by atorvastatin contributes to new-onset diabetes mellitus in western diet-fed mice.

BACKGROUND AND AIMS: The incidence of statin-induced new-onset diabetes (NOD) is increasing but its underlying mechanisms remain unclear. We aimed to investigate the effects of various doses of atorvastatin (ATO)-induced autophagy on the development of NOD. METHODS AND RESULTS: The isolated rat islets and MIN6 cells-treated with ATO, exhibited impaired glucose-stimulated insulin secretion, reduced insulin content, and induced apoptosis. Additionally, autophagy was induced at all doses (in vitro: 5, 10, 20 µM; in vivo: 10, 15, 20 mg/kg) in ATO-treated MIN6 cells or western diet (WD)-fed mice. In contrast to normal glucose-tolerant mice administered a low-dose (10 mg/kg) ATO, those treated with high-doses (15 or 20 mg/kg) exhibited impaired glucose tolerance. Furthermore, high-dose ATO-treated mice showed decreased ß-cell mass and increased apoptosis compared to that of vehicle-treated mice. We also observed that the number of vesicophagous cells in the pancreas of 20 mg/kg ATO-treated WD-fed mice was higher than in vehicle-treated WD-fed mice. Inhibiting autophagy using 3-methyladenine (3-MA) and siAtg5 improved glucose tolerance in vivo and in vitro by preventing apoptotic ß-cell death and restoring insulin granules. CONCLUSION: These results indicate that high doses of ATO induced hyperactivated autophagy in pancreatic cells, leading to impaired insulin storage, decreased cell viability, and reduced functional cell mass, ultimately resulting in NOD development.