Comparison between R2'-based and R2*-based χ-separation methods: A clinical evaluation in individuals with multiple sclerosis.

Susceptibility source separation, or χ-separation, estimates diamagnetic (χdia) and paramagnetic susceptibility (χpara) signals in the brain using local field and R2' (= R2* - R2) maps. Recently proposed R2*-based χ-separation methods allow for χ-separation using only multi-echo gradient echo (ME-GRE) data, eliminating the need for additional data acquisition for R2 mapping. Although this approach reduces scan time and enhances clinical utility, the impact of missing R2 information remains a subject of exploration. In this study, we evaluate the viability of two previously proposed R2*-based χ-separation methods as alternatives to their R2'-based counterparts: model-based R2*-χ-separation versus χ-separation and deep learning-based χ-sepnet-R2* versus χ-sepnet-R2'. Their performances are assessed in individuals with multiple sclerosis (MS), comparing them with their corresponding R2'-based counterparts (i.e., R2*-χ-separation vs. χ-separation and χ-sepnet-R2* vs. χ-sepnet-R2'). The evaluations encompass qualitative visual assessments by experienced neuroradiologists and quantitative analyses, including region of interest analyses and linear regression analyses. Qualitatively, R2*-χ-separation tends to report higher χpara and χdia values compared with χ-separation, leading to less distinct lesion contrasts, while χ-sepnet-R2* closely aligns with χ-sepnet-R2'. Quantitative analysis reveals a robust correlation between both R2*-based methods and their R2'-based counterparts (r ≥ 0.88). Specifically, in the whole-brain voxels, χ-sepnet-R2* exhibits higher correlation and better linearity than R2*-χ-separation (χdia/χpara from R2*-χ-separation: r = 0.88/0.90, slope = 0.79/0.86; χdia/χpara from χ-sepnet-R2*: r = 0.90/0.92, slope = 0.99/0.97). In MS lesions, both R2*-based methods display comparable correlation and linearity (χdia/χpara from R2*-χ-separation: r = 0.90/0.91, slope = 0.98/0.91; χdia/χpara from χ-sepnet-R2*: r = 0.88/0.88, slope = 0.91/0.95). Notably, χ-sepnet-R2* demonstrates negligible offsets, whereas R2*-χ-separation exhibits relatively large offsets (0.02 ppm in the whole brain and 0.01 ppm in the MS lesions), potentially indicating the false presence of myelin or iron in MS lesions. Overall, both R2*-based χ-separation methods demonstrated their viability as alternatives to their R2'-based counterparts. χ-sepnet-R2* showed better alignment with its R2'-based counterpart with minimal susceptibility offsets, compared with R2*-χ-separation that reported higher χpara and χdia values compared with R2'-based χ-separation.

Comparison of Breast Fine-Needle Aspiration Cytology and Tissue Sampling for High-Throughput Proteomic Analysis and Cancer Biomarker Detection.

INTRODUCTION: Fine-needle aspiration cytology (FNAC) specimens are widely utilized for the diagnosis and molecular testing of various cancers. We performed a comparative proteomic analysis of three different sample types, including breast FNAC, core needle biopsy (CNB), and surgical resection tissues. Our goal was to evaluate the suitability of FNAC for in-depth proteomic analysis and for identifying potential therapeutic biomarkers in breast cancer. METHODS: High-throughput proteomic analysis was conducted on matched FNAC, CNB, and surgical resection tissue samples obtained from breast cancer patients. The protein identification, including currently established or promising therapeutic targets, was compared among the three different sample types. Gene Ontology (GO) enrichment analysis was also performed on all matched samples. RESULTS: Compared to tissue samples, FNAC testing revealed a comparable number of proteins (7,179 in FNAC; 7,196 in CNB; and 7,190 in resection samples). Around 85% of proteins were mutually identified in all sample types. FNAC, along with CNB, showed a positive correlation between the number of enrolled tumor cells and identified proteins. In the GO analysis, the FNAC samples demonstrated a higher number of genes for each pathway and GO terms than tissue samples. CCND1, CDK6, HER2, and IGF1R were found in higher quantities in the FNAC compared to tissue samples, while TUBB2A was only detected in the former. CONCLUSION: FNAC is suitable for high-throughput proteomic analysis, in addition to an emerging source that could be used to identify and quantify novel cancer biomarkers.

Quantitative proteomics identifies TUBB6 as a biomarker of muscle-invasion and poor prognosis in bladder cancer.

Muscle-invasive urothelial carcinoma (MIUC) of the bladder shows highly aggressive tumor behavior, which has prompted the quest for robust biomarkers predicting invasion. To discover such biomarkers, we first employed high-throughput proteomic method and analyzed tissue biopsy cohorts from patients with bladder urothelial carcinoma (BUC), stratifying them according to their pT stage. Candidate biomarkers were selected through bioinformatic analysis, followed by validation. The latter comprised 2D and 3D invasion and migration assays, also a selection of external public datasets to evaluate mRNA expression and an in-house patient-derived tissue microarray (TMA) cohort to evaluate protein expression with immunohistochemistry (IHC). Our multilayered platform-based analysis identified tubulin beta 6 class V (TUBB6) as a promising prognostic biomarker predicting MIUC of the bladder. The in vitro 2D and 3D migration and invasion assays consistently showed that inhibition of TUBB6 mRNA significantly reduced cell migration and invasion ability in two BUC cell lines with aggressive phenotype (TUBB6 migration, P = .0509 and P < .0001; invasion, P = .0002 and P = .0044; TGFBI migration, P = .0214 and P = .0026; invasion, P < .0001 and P = .0001; T24 and J82, respectively). Validation through multiple public datasets, including The Cancer Genome Atlas (TCGA) and selected GSE (Genomic Spatial Event) databases, confirmed TUBB6 as a potential biomarker predicting MIUC. Further protein-based validation with our TMA cohort revealed concordant results, highlighting the clinical implication of TUBB6 expression in BUC patients (overall survival: P < .001). We propose TUBB6 as a novel IHC biomarker to predict invasion and poor prognosis, also select the optimal treatment in BUC patients.

χ-Separation Imaging for Diagnosis of Multiple Sclerosis versus Neuromyelitis Optica Spectrum Disorder.

Background Use of χ-separation imaging can provide surrogates for iron and myelin that relate closely to abnormal changes in multiple sclerosis (MS) lesions. Purpose To evaluate the appearances of MS and neuromyelitis optica spectrum disorder (NMOSD) brain lesions on χ-separation maps and explore their diagnostic value in differentiating the two diseases in comparison with previously reported diagnostic criteria. Materials and Methods This prospective study included individuals with MS or NMOSD who underwent χ-separation imaging from October 2017 to October 2020. Positive (χpos) and negative (χneg) susceptibility were estimated separately by using local frequency shifts and calculating R2' (R2' = R2* - R2). R2 mapping was performed with a machine learning approach. For each lesion, presence of the central vein sign (CVS) and paramagnetic rim sign (PRS) and signal characteristics on χneg and χpos maps were assessed and compared. For each participant, the proportion of lesions with CVS, PRS, and hypodiamagnetism was calculated. Diagnostic performances were assessed using receiver operating characteristic (ROC) curve analysis. Results A total of 32 participants with MS (mean age, 34 years ± 10 [SD]; 25 women, seven men) and 15 with NMOSD (mean age, 52 years ± 17; 14 women, one man) were evaluated, with a total of 611 MS and 225 NMOSD brain lesions. On the χneg maps, 80.2% (490 of 611) of MS lesions were categorized as hypodiamagnetic versus 13.8% (31 of 225) of NMOSD lesions (P < .001). Lesion appearances on the χpos maps showed no evidence of a difference between the two diseases. In per-participant analysis, participants with MS showed a higher proportion of hypodiamagnetic lesions (83%; IQR, 72-93) than those with NMOSD (6%; IQR, 0-14; P < .001). The proportion of hypodiamagnetic lesions achieved excellent diagnostic performance (area under the ROC curve, 0.96; 95% CI: 0.91, 1.00). Conclusion On χ-separation maps, multiple sclerosis (MS) lesions tend to be hypodiamagnetic, which can serve as an important hallmark to differentiate MS from neuromyelitis optica spectrum disorder. © RSNA, 2022 Supplemental material is available for this article.

Discrepancies in Hormone Receptor and HER2 Expression between Malignant Serous Effusions and Paired Tissues from Primary or Recurrent Breast Cancers.

OBJECTIVES: Immunohistochemistry (IHC) for the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) biomarkers has prognostic and therapeutic value in breast cancer, while it facilitates molecular subtyping. This study aimed to identify subtype discordance and its clinical significance among different phases of breast cancer evolution, focusing on effusion cytology samples diagnosed with malignancy. METHODS: Our electronic archive was searched for all effusion cases diagnosed as breast carcinomas within a pre-defined period (January 2018-October 2021), and their cell blocks (CBs) were subjected to ER, PR, and HER2 IHC or in situ hybridization. Furthermore, information regarding the same biomarkers from previously obtained tissue specimens of these patients was extracted. RESULTS: Only 2/76 (2.6%) of the breast cancer patients analyzed showed a malignant effusion at their initial presentation. The triple negative breast cancer (TNBC) phenotype was found significantly more often at effusion CBs, compared to their paired biopsies received during initial diagnosis (30/70 vs 16/70; p<0.001). In addition, the presence of TNBC subtype was significantly associated with an earlier development of a malignant effusion, more specifically at initial diagnosis (P<0.001; log-rank test), at first recurrence/metastasis (either solid or effusion) (P=0.012; log-rank test), at effusion (P=0.007; log-rank test), and at any tumor evolution phase (P=0.009; log-rank test). CONCLUSION: Serous effusion cytology provides high-quality material for ancillary techniques, especially when CBs are prepared, reflecting cancer heterogeneity.

Dual Oxidase 2 (DUOX2) as a Proteomic Biomarker for Predicting Treatment Response to Chemoradiation Therapy for Locally Advanced Rectal Cancer: Using High-Throughput Proteomic Analysis and Machine Learning Algorithm.

High-throughput mass-spectrometry-based quantitative proteomic analysis was performed using formalin-fixed, paraffin-embedded (FFPE) biopsy samples obtained before treatment from 13 patients with locally advanced rectal cancer (LARC), who were treated with concurrent chemoradiation therapy (CCRT) followed by surgery. Patients were divided into complete responder (CR) and non-complete responder (nCR) groups. Immunohistochemical (IHC) staining of 79 independent FFPE tissue samples was performed to validate the predictive ability of proteomic biomarker candidates. A total of 3637 proteins were identified, and the expression of 498 proteins was confirmed at significantly different levels (differentially expressed proteins-DEPs) between two groups. In Gene Ontology enrichment analyses, DEPs enriched in biological processes in the CR group included proteins linked to cytoskeletal organization, immune response processes, and vesicle-associated protein transport processes, whereas DEPs in the nCR group were associated with biosynthesis, transcription, and translation processes. Dual oxidase 2 (DUOX2) was selected as the most predictive biomarker in machine learning algorithm analysis. Further IHC validation ultimately confirmed DUOX2 as a potential biomarker for predicting the response of nCR to CCRT. In conclusion, this study suggests that the treatment response to RT may be affected by the pre-treatment tumor microenvironment. DUOX2 is a potential biomarker for the early prediction of nCR after CCRT.

Defect spectroscopy of sidewall interfaces in gate-all-around silicon nanosheet FET.

Through time-dependent defect spectroscopy and low-frequency noise measurements, we investigate and characterize the differences of carrier trapping processes occurred by different interfaces (top/sidewall) of the gate-all-around silicon nanosheet field-effect transistor (GAA SiNS FET). In a GAA SiNS FET fabricated by the top-down process, the traps at the sidewall interface significantly affect the device performance as the width decreases. Compare to expectations, as the width of the device decreases, the subthreshold swing (SS) increases from 120 to 230 mV/dec, resulting in less gate controllability. In narrow-width devices, the effect of traps located at the sidewall interface is significantly dominant, and the 1/f 2 noise, also known as generation-recombination (G-R) noise, is clearly appeared with an increased time constant (τ i ). In addition, the probability density distributions for the normalized current fluctuations (ΔI D) show only one Gaussian in wide-width devices, whereas they are separated into four Gaussians with increased in narrow-width devices. Therefore, fitting is performed through the carrier number fluctuation-correlated with mobility fluctuations model that separately considered the effects of sidewall. In narrow-width GAA SiNS FETs, consequently, the extracted interface trap densities (N T ) distribution becomes more dominant, and the scattering parameter ([Formula: see text]) distribution increases by more than double.

Investigation of Pathogenic Escherichia coli Contamination of Vegetables Distributed in a Korean Agricultural Wholesale Market.

The purpose of this study was to investigate the monthly contamination rate of pathogenic Escherichia coli, a major cause of food poisoning, in vegetables sold in agricultural wholesale markets, which distribute vegetables from all over the country, in the Incheon Metropolitan City area, South Korea, and to identify a source of the pathogen. In total, 1739 vegetables of 80 types, along with 109 soil, 67 manure, and 33 livestock feces samples, were tested for pathogenic E. coli using polymerase chain reaction, from September 2016 through August 2017. The average annual prevalence rate of vegetables was 5.8%, and the prevalence rate was above 5% from June through October. The highest prevalence rate (15.7%) was recorded in July. Water dropwort showed the highest prevalence rate (28.6%) among the vegetables examined. Pathogenic E. coli was detected in >20 types of the vegetables that were to be consumed without cooking. Among these, the prevalence rates of ponytail radish (n = 21), crown daisy (n = 86), young radish (n = 68), romaine lettuce (n = 133), perilla leaf (n = 103), Korean leek (n = 43), young Chinese cabbage (n = 68), and Chinese cabbage (n = 30) were 9.5%, 8.1%, 7.4%, 6.8%, 4.9%, 4.7%, 4.4%, and 3.3%, respectively. Among the vegetables cooked before consumption, prevalence rates were 28.6%, 27.3%, and 25.0% in wormwood, sweet potato stalk, and edible mountain vegetables (Saussurea sp., etc.), respectively. In soil, manure, and livestock feces, 36.7%, 26.9%, and 90.6% prevalence rates were confirmed, respectively. This study confirmed the pathogenic E. coli contamination of vegetables to be consumed without cooking. Therefore, to produce agricultural products that do not induce food poisoning and are safe for consumption, it is important to develop a process for killing the pathogenic microorganisms and set up a sanitary environment for effectively managing compost. In addition, it is necessary to establish surveillance systems to monitor the production chain.

Combined the SMAC mimetic and BCL2 inhibitor sensitizes neoadjuvant chemotherapy by targeting necrosome complexes in tyrosine aminoacyl-tRNA synthase-positive breast cancer.

BACKGROUND: Chemotherapy is the standard treatment for breast cancer; however, the response to chemotherapy is disappointingly low. Here, we investigated the alternative therapeutic efficacy of novel combination treatment with necroptosis-inducing small molecules to overcome chemotherapeutic resistance in tyrosine aminoacyl-tRNA synthetase (YARS)-positive breast cancer. METHODS: Pre-chemotherapeutic needle biopsy of 143 invasive ductal carcinomas undergoing the same chemotherapeutic regimen was subjected to proteomic analysis. Four different machine learning algorithms were employed to determine signature protein combinations. Immunoreactive markers were selected using three common candidate proteins from the machine-learning algorithms and verified by immunohistochemistry using 123 cases of independent needle biopsy FFPE samples. The regulation of chemotherapeutic response and necroptotic cell death was assessed using lentiviral YARS overexpression and depletion 3D spheroid formation assay, viability assays, LDH release assay, flow cytometry analysis, and transmission electron microscopy. The ROS-induced metabolic dysregulation and phosphorylation of necrosome complex by YARS were assessed using oxygen consumption rate analysis, flow cytometry analysis, and 3D cell viability assay. The therapeutic roles of SMAC mimetics (LCL161) and a pan-BCL2 inhibitor (ABT-263) were determined by 3D cell viability assay and flow cytometry analysis. Additional biologic process and protein-protein interaction pathway analysis were performed using Gene Ontology annotation and Cytoscape databases. RESULTS: YARS was selected as a potential biomarker by proteomics-based machine-learning algorithms and was exclusively associated with good response to chemotherapy by subsequent immunohistochemical validation. In 3D spheroid models of breast cancer cell lines, YARS overexpression significantly improved chemotherapy response via phosphorylation of the necrosome complex. YARS-induced necroptosis sequentially mediated mitochondrial dysfunction through the overproduction of ROS in breast cancer cell lines. Combination treatment with necroptosis-inducing small molecules, including a SMAC mimetic (LCL161) and a pan-BCL2 inhibitor (ABT-263), showed therapeutic efficacy in YARS-overexpressing breast cancer cells. CONCLUSIONS: Our results indicate that, before chemotherapy, an initial screening of YARS protein expression should be performed, and YARS-positive breast cancer patients might consider the combined treatment with LCL161 and ABT-263; this could be a novel stepwise clinical approach to apply new targeted therapy in breast cancer patients in the future.

Real-time effect of electron beam on MoS2 field-effect transistors.

Irradiation of MoS2 field-effect transistors (FETs) fabricated on Si/SiO2 substrates with electron beams (e-beams) below 30 keV creates electron-hole pairs (EHP) in the SiO2, which increase the interface trap density (Nit ) and change the current path in the channel, resulting in performance changes. In situ measurements of the electrical characteristics of the FET performed using a nano-probe system mounted inside a scanning electron microscope show that e-beam irradiation enables both multilayer and monolayer MoS2 channels act as conductors. The e-beams mostly penetrate the channel owing to their large kinetic energy, while the EHPs formed in the SiO2 layer can contribute to the conductance by flowing into the MoS2 channel or inducing the gate bias effect. The analysis of the device parameters in the initial state and the vent-evacuation state after e-beam irradiation can clarify the effect of the interplay between the e-beam-induced EHPs and ambient adsorbates on the carrier behavior, which depends on the thickness of the MoS2 layer. DC and low frequency noise analysis reveals that the e-beam-induced EHPs increase Nit from 109-1010 to 1011 cm-2 eV-1 in both monolayer and multilayer devices, while the interfacial Coulomb scattering parameter αSC increases by three times in the monolayer and decreases to one-tenth of its original value in the multilayer. In other words, an MoS2 layer with a thickness of ∼30 nm is less sensitive to adsorbates by surface screening. Thus, the carrier mobility in the monolayer device decreases from 45.7 to 40 cm2 V-1 s-1, while in the 30 nm-thick multilayer device, it increases from 4.9 to 5.6 cm2 V-1 s-1. This is further evidenced by simulations of the distribution of interface traps and channel carriers in the MoS2 FET before and after e-beam irradiation, demonstrating that Coulomb scattering decreases as the effective channel moves away from the interface.

Consumption of salt leads to ameliorate symptoms of metabolic disorder and change of gut microbiota.

PURPOSE: Metabolic diseases caused by high-carbohydrate and/or high-salt diets are becoming major public health concerns. However, the effects of salt on high-carbohydrate diet-induced obesity are unclear. Accordingly, in this study, we investigated the effects of high-salt intake on high-carbohydrate diet-induced obesity. METHODS: We performed a 12-week study on gut microbiota and metabolic changes in high-rice diet (HRD) or HRD supplemented with high-salt (HRS)-fed C57BL/6 J mice by 16S rRNA analysis, glucose and insulin tolerance testing, gut barrier function, western blot and histological analysis. Moreover, the effects of salt on lipid metabolism were confirmed in vitro using 3T3-L1 cells. RESULTS: High salt intake decreased HRD-induced increases in body and white adipose tissue (WAT) weight. Alternatively, HRS did not reverse the observed increases in glucose intolerance and insulin resistance. Moreover, HRD caused changes in the gut microbiota, thereby impairing gut barrier function and increasing inflammation in the liver. HRS altered HRD-induced microbial composition, however, did not ameliorate gut barrier dysfunction or hepatic inflammation. HRS diets regulated the HRD-induced increase in peroxisome proliferator-activated receptor-γ (PPAR-γ) and lipid metabolism-related protein expression. Moreover, within WAT, HRS was found to reverse the observed decrease in adiponectin and increase in PPAR-γ expression induced by HRD. In vitro, high NaCl concentration also significantly reduced 3T3-L1 cell differentiation and modulated lipid metabolism without causing cytotoxicity. CONCLUSION: These results indicate that high salt intake ameliorates metabolic changes associated with a high-rice diet, including changes in fecal microbiota composition.

Quantitative Proteomic Analysis Identifies AHNAK (Neuroblast Differentiation-associated Protein AHNAK) as a Novel Candidate Biomarker for Bladder Urothelial Carcinoma Diagnosis by Liquid-based Cytology.

Cytological examination of urine is the most widely used noninvasive pathologic screen for bladder urothelial carcinoma (BLCA); however, inadequate diagnostic accuracy remains a major challenge. We performed mass spectrometry-based proteomic analysis of urine samples of ten patients with BLCA and ten paired patients with benign urothelial lesion (BUL) to identify ancillary proteomic markers for use in liquid-based cytology (LBC). A total of 4,839 proteins were identified and 112 proteins were confirmed as expressed at significantly different levels between the two groups. We also performed an independent proteomic profiling of tumor tissue samples where we identified 7,916 proteins of which 758 were differentially expressed. Cross-platform comparisons of these data with comparative mRNA expression profiles from The Cancer Genome Atlas identified four putative candidate proteins, AHNAK, EPPK1, MYH14 and OLFM4. To determine their immunocytochemical expression levels in LBC, we examined protein expression data from The Human Protein Atlas and in-house FFPE samples. We further investigated the expression of the four candidate proteins in urine cytology samples from two independent validation cohorts. These analyses revealed AHNAK as a unique intracellular protein differing in immunohistochemical expression and subcellular localization between tumor and non-tumor cells. In conclusion, this study identified a new biomarker, AHNAK, applicable to discrimination between BLCA and BUL by LBC. To our knowledge, the present study provides the first identification of a clinical biomarker for LBC based on in-depth proteomics.

Pretreatment clinical mediastinal nodal bulk and extent do not influence survival in N2-positive stage IIIA non-small cell lung cancer patients treated with trimodality therapy.

BACKGROUND: Treatment for patients with N2-positive stage IIIA non-small cell lung cancer has been a controversial issue. The current study evaluated the outcomes in patients treated with trimodality therapy, which consisted of neoadjuvant radiation therapy concurrent with chemotherapy followed by surgical resection, with emphasis on clinical and pathologic nodal status. METHODS: We reviewed the records of 355 patients who were treated with trimodality therapy between 1997 and 2011. RESULTS: After completion of neoadjuvant chemoradiation, overall down-staging and complete response rates were 50.4 % (179 patients), and 13.2 % (47 patients), respectively. With median follow-up of 35.3 months, median times of progression-free survival (PFS) and overall survival (OS) were 16.3 months and 45.5 months, respectively. Seventeen patients (4.8 %) died of postoperative complications, and the remaining 338 patients were analyzed on prognostic factors. Old age (p = 0.032), pneumonectomy (p < 0.001), and ypN+ (p < 0.001) were found to be the significant prognosticators for worse PFS, and old age (p = 0.013), pneumonectomy (p < 0.001), and ypN+ (p < 0.001) were related to worse OS. Clinical N2 status did not influence either OS or PFS: the number of involved stations (single station vs. multi-station; p = 0.187 for PFS; p = 0.492 for OS), and bulk (clinically evident vs. microscopic; p = 0.902 for PFS; p = 0.915 for OS). CONCLUSION: ypN stage was the most important prognosticator for both PFS and OS; however, neither initial bulk nor extent of cN2 disease influenced prognosis. Surgery following neoadjuvant chemoradiation should have contributed to improved clinical outcomes regardless of clinical nodal bulk and extent.

Automated Quantification of Total Cerebral Blood Flow from Phase-Contrast MRI and Deep Learning.

Knowledge of input blood to the brain, which is represented as total cerebral blood flow (tCBF), is important in evaluating brain health. Phase-contrast (PC) magnetic resonance imaging (MRI) enables blood velocity mapping, allowing for noninvasive measurements of tCBF. In the procedure, manual selection of brain-feeding arteries is an essential step, but is time-consuming and often subjective. Thus, the purpose of this work was to develop and validate a deep learning (DL)-based technique for automated tCBF quantifications. To enhance the DL segmentation performance on arterial blood vessels, in the preprocessing step magnitude and phase images of PC MRI were multiplied several times. Thereafter, a U-Net was trained on 218 images for three-class segmentation. Network performance was evaluated in terms of the Dice coefficient and the intersection-over-union (IoU) on 40 test images, and additionally, on externally acquired 20 datasets. Finally, tCBF was calculated from the DL-predicted vessel segmentation maps, and its accuracy was statistically assessed with the correlation of determination (R2), the intraclass correlation coefficient (ICC), paired t-tests, and Bland-Altman analysis, in comparison to manually derived values. Overall, the DL segmentation network provided accurate labeling of arterial blood vessels for both internal (Dice=0.92, IoU=0.86) and external (Dice=0.90, IoU=0.82) tests. Furthermore, statistical analyses for tCBF estimates revealed good agreement between automated versus manual quantifications in both internal (R2=0.85, ICC=0.91, p=0.52) and external (R2=0.88, ICC=0.93, p=0.88) test groups. The results suggest feasibility of a simple and automated protocol for quantifying tCBF from neck PC MRI and deep learning.

Lactococcus lactis KF140 Ameliorates Nonalcoholic Fatty Liver Disease Induced by Nε-Carboxymethyl-Lysine and High-Fat Diet.

SCOPE: Long-term consumption of excessive dietary advanced glycation end-products such as Nε-carboxymethyl-lysine (CML), which are produced by the Maillard reaction during food thermal processing, leads to nonalcoholic fatty liver disease (NAFLD) along with high fat consumption. The study previously finds that administration of Lactococcus lactis KF140 (LL-KF140) detoxifies CML by decreasing CML absorption both in a rat model and clinical trial. METHODS AND RESULTS: The present study evaluates the ameliorative effect of LL-KF140 on NAFLD and fatty liver-related biomarkers in a mouse model induced by CML and high fat. LL-KF140 is orally administered to mice at a concentration of 1 × 107 or 1 × 108 colony-forming unit (CFU) per mouse for 8 weeks. LL-KF140 administration ameliorates the NAFLD-related symptoms by reducing body weight and fat mass gain along with levels of serum aspartate transaminase, alanine transferase, and lipids as well as glucose intolerance and insulin resistance in CML-treated mice. In addition, histological analysis including staining and western blotting shows that LL-KF140 suppresses the lipogenesis pathway and CML absorption, thereby suppressing CML-induced NAFLD. CONCLUSION: These findings suggest that LL-KF140 attenuates dietary CML-induced NAFLD by suppressing the de novo lipogenesis pathway, and it may be used as a probiotic strain.

Ameliorating effects of Orostachys japonica against high-fat diet-induced obesity and gut dysbiosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Orostachys japonica (rock pine) has been used as a folk remedy to treat inflammation, hepatitis, and cancer in East Asia. AIM OF THE STUDY: The aim of this study was to investigate the effect of rock pine extract (RPE) on high-fat diet-induced obesity in mice and to examine its effects on gut dysbiosis. MATERIALS AND METHODS: The characteristic compound of RPE, kaempferol-3-O-rutinoside, was quantified using high-performance liquid chromatography. The prebiotic potential of RPE was evaluated by assessing the prebiotic activity score obtained using four prebiotic strains and high-fat (HF)-induced obesity C57BL/6 mice model. Analysis included examining the lipid metabolism and inflammatory proteins and evaluating the changes in gut permeability and metabolites to elucidate the potential signaling pathways involved. RESULTS: In vitro, RPE enhanced the proliferation of beneficial probiotic strains, including Lactiplantibacillus and Bifidobacterium. HF-induced model showed that the administration of 100 mg/kg/day of RPE for 8 weeks significantly (p < 0.05) reduced the body weight, serum lipid levels, and insulin resistance, which were associated with notable changes in lipid metabolism and inflammation-related markers. CONCLUSIONS: Our results demonstrate that rock pine consumption could mitigate obesity and metabolic endotoxemia in HF-fed mice through enhancing intestinal environment.

Resistant starch-enriched brown rice exhibits prebiotic properties and enhances gut health in obese mice.

Resistant starch serves as a prebiotic in the large intestine, aiding in the maintenance of a healthy intestinal environment and mitigating associated chronic illnesses. This study aimed to investigate the impact of resistant starch-enriched brown rice (RBR) on intestinal health and functionality. We assessed changes in resistant starch concentration, structural alterations, and branch chain length distribution throughout the digestion process using an in vitro model. The efficacy of RBR in the intestinal environment was evaluated through analyses of its prebiotic potential, effects on intestinal microbiota, and intestinal function-related proteins in obese animals fed a high-fat diet. RBR exhibited a higher yield of insoluble fraction in both the small and large intestines compared to white and brown rice. The total digestible starch content decreased, while the resistant starch content significantly increased during in vitro digestion. Furthermore, RBR notably enhanced the growth of four probiotic strains compared to white and brown rice, displaying higher proliferation activity than the positive control, FOS. Notably, consumption of RBR by high-fat diet-induced obese mice suppressed colon shortening, increased Bifidobacteria growth, and improved intestinal permeability. These findings underscore the potential prebiotic and gut health-promoting attributes of RBR, offering insights for the development of functional foods aimed at preventing gastrointestinal diseases.

Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional study.

PURPOSE: To quantify interobserver variation (IOV) in target volume and organs-at-risk (OAR) contouring across 31 institutions in breast cancer cases and to explore the clinical utility of deep learning (DL)-based auto-contouring in reducing potential IOV. METHODS AND MATERIALS: In phase 1, two breast cancer cases were randomly selected and distributed to multiple institutions for contouring six clinical target volumes (CTVs) and eight OAR. In Phase 2, auto-contour sets were generated using a previously published DL Breast segmentation model and were made available for all participants. The difference in IOV of submitted contours in phases 1 and 2 was investigated quantitatively using the Dice similarity coefficient (DSC) and Hausdorff distance (HD). The qualitative analysis involved using contour heat maps to visualize the extent and location of these variations and the required modification. RESULTS: Over 800 pairwise comparisons were analysed for each structure in each case. Quantitative phase 2 metrics showed significant improvement in the mean DSC (from 0.69 to 0.77) and HD (from 34.9 to 17.9 mm). Quantitative analysis showed increased interobserver agreement in phase 2, specifically for CTV structures (5-19 %), leading to fewer manual adjustments. Underlying IOV differences causes were reported using a questionnaire and hierarchical clustering analysis based on the volume of CTVs. CONCLUSION: DL-based auto-contours improved the contour agreement for OARs and CTVs significantly, both qualitatively and quantitatively, suggesting its potential role in minimizing radiation therapy protocol deviation.

Cytomorphological factors and BRAF mutation predicting risk of lymph node metastasis in preoperative liquid-based fine needle aspirations of papillary thyroid carcinoma.

OBJECTIVE: Preoperative fine needle aspiration biopsy (FNAB) has become the initial diagnostic method for papillary thyroid carcinoma (PTC). Identification of cytomorphologic factors predicting lymph node metastasis (LNM) is clinically important for determining the appropriate treatment regimen due to the high rate of lymph node involvement in PTC at the time of diagnosis. Hobnail features (HF) have previously been described as potential histomorphologic features in the histological examination of PTC. This study evaluated the value of HF as a predictor of LNM. STUDY DESIGN: Histologically confirmed FNABs (n = 111) of papillary thyroid microcarcinoma prepared by the liquid-based method were enrolled. Along with other cytomorphologic parameters, HF were evaluated for their value in predicting LNM. RESULTS: Although HF were closely correlated with cytoplasmic vacuoles of tumor cells and background macrophages (p < 0.05), which were considered diagnostic indicators of PTC with cystic changes, HF were only found to be significantly correlated with LNM (p = 0.008). The BRAF(V660E) mutation was not associated with LNM. All combinations including HF were revealed as stronger predictors of LNM (odds ratios: 2.254-2.524, p < 0.05). CONCLUSIONS: HF, a distinctive cytomorphologic feature, may be used as a factor predicting LNM in preoperative FNAB of PTC.

The unique liquid-based cytologic findings of thyroid signet-ring follicular adenoma: a report of two cases with fine needle aspiration cytology.

BACKGROUND: Signet-ring follicular adenoma is a rare variant of follicular neoplasm, which has only been described using the conventional smear cytologic preparation. Here we report the unique cytologic findings of two cases of signet-ring follicular adenoma using liquid-based samples and corresponding histologic features and results of ancillary tests. CASES: Case 1: A 65-year-old man presented with a solitary nodule in the right lobe of the thyroid. Ultrasound-guided fine needle aspiration (FNA) yielded several groups of microfollicles containing colloid or mucin-like globules. The tumor cells had eccentrically located nuclei compressed by distended luminal globules. Case 2: A 51-year-old woman presented with a nodule in the left lobe of the thyroid. On liquid-based cytology, cord-like arrangements of microfollicules were noted. The tumor cells had large, clear vacuoles, but the nuclei maintained their round shape and central location. CONCLUSION: The liquid-based cytologic characteristics are quite different from those encountered in the conventional smear of FNA; therefore, pathologists must also be familiar with the cytomorphologic characteristics of liquid-based preparations. In addition, given the distinctive cytological and histological appearance and the benign clinical course, signet-ring follicular adenoma should be distinguished from other metastatic neoplasms displaying signet-ring cell features.