Deciphering Breast Origin in Malignant Effusions: The Diagnostic Utility of an MGP, GATA-3, and TRPS-1 Immunocytochemical Panel.

INTRODUCTION: Defining the origin of metastatic cancer is crucial for establishing an optimal treatment strategy, especially when obtaining sufficient tissue from secondary malignancies is limited. While cytological examination is often used in this diagnostic setting, morphologic analysis alone often fails to differentiate metastases derived from the breast from other primaries. The hormone receptor, human epidermal growth factor receptor-2 (HER2), gross cystic disease fluid protein 15 (GCDFP-15), and mammaglobin immunohistochemistry are often used to diagnose metastatic breast cancer. But their effectiveness decreases in estrogen-receptor (ER)-negative breast cancers, including the triple-negative breast cancer (TNBC) subtype. METHODS: We conducted a comprehensive evaluation of GATA-binding protein 3 (GATA-3), trichorhinophalangeal syndrome type 1 (TRPS-1), and Matrix Gla Protein (MGP) immunochemistry across 140 effusion cytology specimens with metastatic adenocarcinoma derived from various primaries, including the breast, colon, pancreaticobiliary, lung, ovary, and stomach. RESULTS: The expression rates of these immunomarkers were significantly higher in metastatic cancers originating from the breast than in other primaries. In TNBC, TRPS-1 (80.00%) and MGP (65.00%) exhibited higher positivity rates compared to GATA-3 (40.00%). Additionally, our data suggests that an immunohistochemical panel comprising MGP, GATA-3, and TRPS-1 significantly enhances the detection of metastatic breast cancer in effusion cytology specimens, including TNBC in particular. When considering dual-marker positivity, the diagnostic accuracy was calculated to be 89.29% across all breast cancer subtypes and 92.93% for TNBC. CONCLUSIONS: MGP appears to be a robust marker for identifying metastatic breast cancer in malignant effusions, especially TNBC. MGP notably enhances diagnostic accuracy when incorporated together with GATA-3 and TRPS-1 in an immunohistochemical panel.

KRT18 as a Novel Biomarker of Urothelial Papilloma while Evaluating Low-Grade Papillary Urothelial Neoplasms: Bi-Center Analysis.

INTRODUCTION: Although urothelial papilloma (UP) is an indolent papillary neoplasm that can mimic the morphology of low-grade papillary urothelial carcinoma (PUC), there is no immunomarker to differentiate reliably these two entities. In addition, the molecular characteristics of UP are not fully understood. METHODS: We conducted an in-depth proteomic analysis of papillary urothelial lesions (n = 31), including UP and PUC along with normal urothelium. Protein markers distinguishing UP and PUC were selected with machine learning analysis, followed by internal and external validation using immunohistochemistry. RESULTS: In the proteomic analysis, UP and PUC showed overlapping proteomic profiles. We identified EHD4 and KRT18 as candidate diagnostic biomarkers of UP. Through immunohistochemical validation in two independent cohorts (n = 120), KRT18 was suggested as a novel UP diagnostic marker, able to differentiate UP from low-grade PUC. We also found that 3.5% of patients with UP developed urothelial carcinoma in subsequent resections, supporting the malignant potential of UP. KRT18 downregulation was significantly associated with UPs subsequently progressing to urothelial carcinoma, following their initial diagnosis. CONCLUSION: This is the first study that successfully revealed UPs comprehensive proteomic landscape, while it also identified KRT18 as a potential diagnostic biomarker of UP.

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.

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.

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.

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.

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.

Thyme Extract Alleviates High-Fat Diet-Induced Obesity and Gut Dysfunction.

Prolonged intake of a high-fat diet (HFD) disturbs the composition of gut microbiota, contributing to the development of metabolic diseases, notably obesity and increased intestinal permeability. Thyme (Thymus vulgaris L.), an aromatic plant, is known for its several therapeutic properties. In this study, we explored the potential of thyme extract (TLE) to mitigate HFD-induced metabolic derangements and improve the gut environment. Eight-week-old C57BL/6 mice were administered 50 or 100 mg/kg TLE for eight weeks. Administration of 100 mg/kg TLE resulted in decreased weight gain and body fat percentage, alongside the regulation of serum biomarkers linked to obesity induced by a HFD. Moreover, TLE enhanced intestinal barrier function by increasing the expression of tight junction proteins and ameliorated colon shortening. TLE also altered the levels of various metabolites. Especially, when compared with a HFD, it was confirmed that 2-hydroxypalmitic acid and 3-indoleacrylic acid returned to normal levels after TLE treatment. Additionally, we investigated the correlation between fecal metabolites and metabolic parameters; deoxycholic acid displayed a positive correlation with most parameters, except for colon length. In contrast, hypoxanthine was negatively correlated with most parameters. These results suggest a promising role for thyme in ameliorating obesity and related gut conditions associated with a HFD.

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.

Dietary Nε-(carboxymethyl)lysine is a trigger of non-alcoholic fatty liver disease under high-fat consumption.

The irreversible glycation of proteins produces advanced glycation end products (AGEs) which are triggered to bind the receptor for AGE (RAGE), thereby activating mitogen-activated protein kinase/nuclear factor-κB signaling pathway and stimulating proinflammatory cytokines, ultimately leading to chronic disorders. In this study, we focus the promoting effect of Nε-carboxymethyl-lysine (CML), one of the most dietary AGEs, on non-alcoholic fatty liver disease (NAFLD) and evaluated NAFLD-related biomarkers. Oxidative stress and hepatic steatosis were assessed in oleic acid (OA)-induced HepG2 cells. Using OA-induced HepG2 cells, we show that CML results in oxidative stress and steatosis and drives major changes in hepatic lipid metabolism. Administration of CML exacerbated NAFLD-related symptoms by increasing body and liver weight gain, serum alanine aminotransferase and lipid levels, and insulin resistance in mild high-fat diet-induced mice. Moreover, hepatic histological analysis data, such as staining, western blotting, and RNA-seq, indicate that CML aggravates NAFLD in association with activation of the de novo lipogenesis pathway, consistent with the in vitro assays. Our findings could contribute to model studies related to the prevention and treatment of NAFLD progression due to excessive consumption of dietary AGEs.

Prebiotic and Anti-Adipogenic Effects of Radish Green Polysaccharide.

Radish (Raphanus sativus L.) greens are consumed as a source of nutrition, and their polysaccharides such as rhamnogalacturonan-I possess certain beneficial properties. This study investigated the prebiotic effects of a radish green polysaccharide (RGP) on gut health and obesity. The prebiotic activity of RGP was evaluated based on the pH changes and short-chain fatty acids (SCFAs) concentration. The results showed that 0.5% RGP had a higher prebiotic activity score than inulin and increased SCFAs production in all five prebiotic strains. Moreover, RGP inhibited fat accumulation in 3T3-L1 adipocytes, indicating its potential to reduce obesity. Overall, these findings suggested that the polysaccharide of radish greens has prebiotic effects and may serve as a beneficial prebiotic for gut health and obesity.

Structural characteristics of resistant starch-enriched rice during digestion and its effects on gut barrier function in high-fat induced obese mice.

Dietary supplementation with indigestible carbohydrates is known to improve the gut environment and prevent obesity and inflammatory diseases by modulating the gut microbiota. In previous work, we established a method for the production of resistant starch (RS)-enriched high-amylose rice (R-HAR) using citric acid. The present study aimed to evaluate changes in structural characteristics during digestion of R-HAR and its effects on the gut health. A three-step in vitro digestion and fermentation model was used, then, RS content, scanning electron microscopy, and branch chain length distribution were analyzed during in vitro digestion. During the digestion of R-HAR, the RS content increased, and the structure was predicted to have a greater impact on the gut microbiota and gut environment. To study the intestinal health effects of R-HAR, its anti-inflammatory and gut barrier integrity activities were assayed in HFD-induced mice. Intake of R-HAR suppressed colonic shortening and inflammatory responses induced by HFD. Furthermore, R-HAR exhibited gut barrier protective activity with an increase in tight junction protein levels. We determined that R-HAR may be a potentially beneficial intestinal environment improver, which may have various implications in the food industry as rice.

Deep learning-based classification system of bacterial keratitis and fungal keratitis using anterior segment images.

Introduction: Infectious keratitis is a vision threatening disease. Bacterial and fungal keratitis are often confused in the early stages, so right diagnosis and optimized treatment for causative organisms is crucial. Antibacterial and antifungal medications are completely different, and the prognosis for fungal keratitis is even much worse. Since the identification of microorganisms takes a long time, empirical treatment must be started according to the appearance of the lesion before an accurate diagnosis. Thus, we developed an automated deep learning (DL) based diagnostic system of bacterial and fungal keratitis based on the anterior segment photographs using two proposed modules, Lesion Guiding Module (LGM) and Mask Adjusting Module (MAM). Methods: We used 684 anterior segment photographs from 107 patients confirmed as bacterial or fungal keratitis by corneal scraping culture. Both broad- and slit-beam images were included in the analysis. We set baseline classifier as ResNet-50. The LGM was designed to learn the location information of lesions annotated by ophthalmologists and the slit-beam MAM was applied to extract the correct feature points from two different images (broad- and slit-beam) during the training phase. Our algorithm was then externally validated using 98 images from Google image search and ophthalmology textbooks. Results: A total of 594 images from 88 patients were used for training, and 90 images from 19 patients were used for test. Compared to the diagnostic accuracy of baseline network ResNet-50, the proposed method with LGM and MAM showed significantly higher accuracy (81.1 vs. 87.8%). We further observed that the model achieved significant improvement on diagnostic performance using open-source dataset (64.2 vs. 71.4%). LGM and MAM module showed positive effect on an ablation study. Discussion: This study demonstrated that the potential of a novel DL based diagnostic algorithm for bacterial and fungal keratitis using two types of anterior segment photographs. The proposed network containing LGM and slit-beam MAM is robust in improving the diagnostic accuracy and overcoming the limitations of small training data and multi type of images.

Comparative insight of pesticide transformations between river and wetland systems.

The widespread use of pesticides threatens the environment and ecosystems. Despite the positive effects of plant protection products, pesticides also have unexpected negative effects on nontarget organisms. The microbial biodegradation of pesticides is one of the major pathways for reducing their risks at aquatic ecosystems. The objective of this study was to compare the biodegradability of pesticides in simulated wetland and river systems. Parallel experiments were conducted with 17 pesticides based on the OECD 309 guidelines. A comprehensive analytical method, such as target screening combined with suspect and non-target screening, was performed to evaluate the biodegradation via identification of transformation products (TPs) using LC-HRMS. As evidence of biodegradation, we identified 97 TPs for 15 pesticides. Metolachlor and dimethenamid had 23 and 16 TPs, respectively, including Phase II glutathione conjugates. The analysis of 16S rRNA sequences for microbials characterized operational taxonomic units. Rheinheimera and Flavobacterium, which have the potential for glutathione S-transferase, were dominant in wetland systems. Estimation of toxicity, biodegradability, and hydrophobicity using QSAR prediction indicated lower environmental risks of detected TPs. We conclude that the wetland system is more favorable for pesticide degradation and risk mitigation mainly attributed to the abundance and variety of the microbial communities.

Alkyl chain length of quaternized SBA-15 and solution conditions determine hydrophobic and electrostatic interactions for carbamazepine adsorption.

Santa Barbara Amorphous-15 (SBA) is a stable and mesoporous silica material. Quaternized SBA-15 with alkyl chains (QSBA) exhibits electrostatic attraction for anionic molecules via the N+ moiety of the ammonium group, whereas its alkyl chain length determines its hydrophobic interactions. In this study, QSBA with different alkyl chain lengths were synthesized using the trimethyl, dimethyloctyl, and dimethyoctadecyl groups (C1QSBA, C8QSBA, and C18QSBA, respectively). Carbamazepine (CBZ) is a widely prescribed pharmaceutical compound, but is difficult to remove using conventional water treatments. The CBZ adsorption characteristics of QSBA were examined to determine its adsorption mechanism by changing the alkyl chain length and solution conditions (pH and ionic strength). A longer alkyl chain resulted in slower adsorption (up to 120 min), while the amount of CBZ adsorbed was higher for longer alkyl chains per unit mass of QSBA at equilibrium. The maximum adsorption capacities of C1QSBA, C8QSBA, and C18QSBA, were 3.14, 6.56, and 24.5 mg/g, respectively, as obtained using the Langmuir model. For the tested initial CBZ concentrations (2-100 mg/L), the adsorption capacity increased with increasing alkyl chain length. Because CBZ does not dissociate readily (pKa = 13.9), stable hydrophobic adsorption was observed despite the changes in pH (0.41-0.92, 1.70-2.24, and 7.56-9.10 mg/g for C1QSBA, C8QSBA, and C18QSBA, respectively); the exception was pH 2. Increasing the ionic strength from 0.1 to 100 mM enhanced the adsorption capacity of C18QSBA from 9.27 ± 0.42 to 14.94 ± 0.17 mg/g because the hydrophobic interactions were increased while the electrostatic attraction of the N+ was reduced. Thus, the ionic strength was a stronger control factor determining hydrophobic adsorption of CBZ than the solution pH. Based on the changes in hydrophobicity, which depends on the alkyl chain length, it was possible to enhance CBZ adsorption and investigate the adsorption mechanism in detail. Thus, this study aids the development of adsorbents suitable for pharmaceuticals with controlling molecular structure of QSBA and solution conditions.

Evaluation of Pretreatment Albumin-Bilirubin Grade as a Better Prognostic Factor Compared to Child-Pugh Classification in Patients with Hepatocellular Carcinoma Receiving Transarterial Chemoembolization Combined with Radiotherapy.

This study assessed the use of pretreatment albumin--bilirubin (ALBI) grade as a prognostic factor in patients with hepatocellular carcinoma (HCC) receiving combined transarterial chemoembolization (TACE) and radiotherapy (RT). Patients who underwent RT following TACE between January 2011 and December 2020 were analyzed retrospectively. The survival outcomes of patients in regard to the ALBI grade and Child-Pugh (C-P) classification were evaluated. A total of 73 patients with a median follow-up of 16.3 months were included. Thirty-three (45.2%) and forty patients (54.8%) were categorized into ALBI grades 1 and 2-3, respectively, while sixty-four (87.7%) and nine (12.3%) were C-P classes A and B, respectively (p = 0.003). The median progression-free survival (PFS) and overall survival (OS) for ALBI grade 1 vs. 2-3 were 8.6 months vs. 5.0 months (p = 0.016) and 27.0 months vs. 15.9 months (p = 0.006), respectively. The median PFS and OS for C-P class A vs. B were 6.3 months vs. 6.1 months (p = 0.265) and 24.8 months vs. 19.0 months (p = 0.630), respectively. A multivariate analysis showed that ALBI grades 2-3 were significantly associated with worse PFS (p = 0.035) and OS (p = 0.021). In conclusion, the ALBI grade could be a good prognosticator in HCC patients who were treated with combined TACE-RT.

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.