Maid gene dysfunction promotes hyperobesity via the reduction of adipose tissue inflammation in Mc4r gene-deficient mice.

The onset and progression mechanisms of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) are being studied. We developed and analyzed a new mouse model of obesity by combining maternal Id-like molecule (Maid) and melanocortin-4 receptor (Mc4r) gene deletions. Four mice, each at 12 and 28 weeks of age, were analyzed for each genotype: Maid gene knockout, Mc4r gene knockout, combined Mc4r and Maid gene knockout, and Mc4r gene knockout with a high-fat diet. Mice with a combined deficiency of Mc4r and Maid gene showed significantly more severe obesity compared to all other genotypes, but no liver fibrosis or a decline in metabolic status were observed. In visceral white adipose tissue, Maid and Mc4r gene knockout mice had fewer CD11c-positive cells and lower mRNA expression of both inflammatory and anti-inflammatory cytokines. Furthermore, Maid and Mc4r gene knockout mice showed lower expression of adipocytokines in visceral white adipose tissue and uncoupling protein-1 in scapular brown adipose tissue. The expression of adipocytokines and uncoupling protein-1 is regulated by sympathetic nerve signaling that contribute severe obesity in Maid and Mc4r gene knockout mice. These mechanisms contribute hyperobesity in Maid and Mc4r gene knockout mice.

[A case of long-term efficacy of minocycline hydrochloride sclerotherapy combined with intra-cystic lavage for a symptomatic giant liver cyst].

Herein, we report a case of a man with a large symptomatic hepatic cyst that gradually enlarged over a follow-up period of 15 years, which eventually caused epigastric fullness and obstructive jaundice. The patient underwent percutaneous cystic drainage followed by sclerotherapy using minocycline hydrochloride combined with intracystic lavage. The treatment resulted in a significant reduction in the hepatic cyst size, symptom improvement, and absence of recurrence for 670 days.

A Case of Tiopronin-induced Membranous Nephropathy Presenting with IgG4-predominant Staining Pattern.

Tiopronin is a key drug used to treat cystinuria. A 41-year-old Japanese woman with cystinuria presented with eyelid edema and weight gain after the administration of tiopronin. Her serum albumin was 1.8 g/dL and her urinary protein level was 5.5 g/gCre. After cessation of tiopronin, she achieved remission of nephrotic syndrome (NS). Secondary NS due to tiopronin was evident based on the clinical course and laboratory values. A kidney biopsy showed membranous nephropathy (MN), and an immunofluorescence analysis revealed strong deposition of immunoglobulin G4 (IgG4). However, a previous case report of tiopronin-induced MN showed staining for IgG1 and IgG3. This case report suggests a novel etiology for tiopronin-induced MN.

Diagnostic Performance of GPT-4o and Claude 3 Opus in Determining Causes of Death From Medical Histories and Postmortem CT Findings.

INTRODUCTION: This study evaluates the diagnostic performance of the latest large language models (LLMs), GPT-4o (OpenAI, San Francisco, CA, USA) and Claude 3 Opus (Anthropic, San Francisco, CA, USA), in determining causes of death from medical histories and postmortem CT findings. METHODS: We included 100 adult cases whose postmortem CT scans were diagnosable for the causes of death using the gold standard of autopsy results. Their medical histories and postmortem CT findings were compiled, and clinical and imaging diagnoses of both the underlying and immediate causes of death, as well as their personal information, were carefully separated from the database to be shown to the LLMs. Both GPT-4o and Claude 3 Opus generated the top three differential diagnoses for each of the underlying or immediate causes of death based on the following three prompts: 1) medical history only; 2) postmortem CT findings only; and 3) both medical history and postmortem CT findings. The diagnostic performance of the LLMs was compared using McNemar's test. RESULTS: For the underlying cause of death, GPT-4o achieved primary diagnostic accuracy rates of 78%, 72%, and 78%, while Claude 3 Opus achieved 72%, 56%, and 75% for prompts 1, 2, and 3, respectively. Including any of the top three differential diagnoses, GPT-4o's accuracy rates were 92%, 90%, and 92%, while Claude 3 Opus's rates were 93%, 69%, and 93% for prompts 1, 2, and 3, respectively. For the immediate cause of death, GPT-4o's primary diagnostic accuracy rates were 55%, 58%, and 62%, while Claude 3 Opus's rates were 60%, 62%, and 63% for prompts 1,2, and 3, respectively. For any of the top three differential diagnoses, GPT-4o's accuracy rates were 88% for prompt 1 and 91% for prompts 2 and 3, whereas Claude 3 Opus's rates were 92% for all three prompts. Significant differences between the models were observed for prompt two in diagnosing the underlying cause of death (p = 0.03 and <0.01 for the primary and top three differential diagnoses, respectively). CONCLUSION: Both GPT-4o and Claude 3 Opus demonstrated relatively high performance in diagnosing both the underlying and immediate causes of death using medical histories and postmortem CT findings.

A Case of Cerebral Infarction due to Internal Carotid Artery Occlusion Accompanied by Persistent Primitive Trigeminal Artery.

An 85-year-old woman with a history of diabetes mellitus became aware of motor weakness of the left lower extremity. Magnetic resonance imaging showed multiple small cerebral infarctions in the right corona radiata. Angiography revealed persistent primitive trigeminal artery (PPTA) originating from the right internal carotid artery (ICA) and connecting to basilar artery, and the right ICA occluded distal to PPTA. Collateral blood circulation had developed, and sufficient collateral blood flow was expected. From these findings, the right ICA was considered to show stenosis due to atherosclerotic changes before occlusion. Conservative treatment was conducted with the transoral administration of rivaroxaban. It is important to correctly diagnose the anatomy and existence of an anomalous vessel in a stroke patient, not only when endovascular treatment is planned, but also for conservative medical treatment. Rapid and accurate radiological examinations facilitate safe and effective treatment.

Vaccine Therapy for Heart Failure Targeting the Inflammatory Cytokine Igfbp7.

BACKGROUND: The heart comprises many types of cells such as cardiomyocytes, endothelial cells (ECs), fibroblasts, smooth muscle cells, pericytes, and blood cells. Every cell type responds to various stressors (eg, hemodynamic overload and ischemia) and changes its properties and interrelationships among cells. To date, heart failure research has focused mainly on cardiomyocytes; however, other types of cells and their cell-to-cell interactions might also be important in the pathogenesis of heart failure. METHODS: Pressure overload was imposed on mice by transverse aortic constriction and the vascular structure of the heart was examined using a tissue transparency technique. Functional and molecular analyses including single-cell RNA sequencing were performed on the hearts of wild-type mice and EC-specific gene knockout mice. Metabolites in heart tissue were measured by capillary electrophoresis-time of flight-mass spectrometry system. The vaccine was prepared by conjugating the synthesized epitope peptides with keyhole limpet hemocyanin and administered to mice with aluminum hydroxide as an adjuvant. Tissue samples from heart failure patients were used for single-nucleus RNA sequencing to examine gene expression in ECs and perform pathway analysis in cardiomyocytes. RESULTS: Pressure overload induced the development of intricately entwined blood vessels in murine hearts, leading to the accumulation of replication stress and DNA damage in cardiac ECs. Inhibition of cell proliferation by a cyclin-dependent kinase inhibitor reduced DNA damage in ECs and ameliorated transverse aortic constriction-induced cardiac dysfunction. Single-cell RNA sequencing analysis revealed upregulation of Igfbp7 (insulin-like growth factor-binding protein 7) expression in the senescent ECs and downregulation of insulin signaling and oxidative phosphorylation in cardiomyocytes of murine and human failing hearts. Overexpression of Igfbp7 in the murine heart using AAV9 (adeno-associated virus serotype 9) exacerbated cardiac dysfunction, while EC-specific deletion of Igfbp7 and the vaccine targeting Igfbp7 ameliorated cardiac dysfunction with increased oxidative phosphorylation in cardiomyocytes under pressure overload. CONCLUSIONS: Igfbp7 produced by senescent ECs causes cardiac dysfunction and vaccine therapy targeting Igfbp7 may be useful to prevent the development of heart failure.

Successful treatment of fulminant and recurrent lymphocytic myocarditis with calcineurin inhibitors.

Lymphocytic myocarditis (LM) is primarily triggered by various factors including viral infections and subsequent immune responses. While rare, some patients with LM experience recurrence with a life-threatening fulminant form. Although combining steroids and immunosuppressants, such as azathioprine and mycophenolate mofetil, has demonstrated favourable outcomes in patients with LM, their efficacy is limited to the chronic phase. Indeed, various immunosuppressants have been used for LM with fulminant manifestation; however, their evidence remains lacking. In our case series, two patients with LM experienced fulminant relapses during steroid tapering, and another presented persistent cardiac enzymes elevation despite steroid therapies. Consequently, we initiated calcineurin inhibitors alongside steroids, resulting in well-controlled clinical courses without further recurrence of LM and significant adverse effects. Our cases suggest calcineurin inhibitors as therapeutic options for managing steroid-resistant LM with fulminant relapse.

Cutoff CT value can identify upper gastrointestinal bleeding on postmortem CT: Development and validation study.

This study aimed to establish the diagnostic criteria for upper gastrointestinal bleeding (UGIB) using postmortem computed tomography (PMCT). This case-control study enrolled 27 consecutive patients with autopsy-proven UGIB and 170 of the 566 patients without UGIB who died in a university hospital in Japan after treatment and underwent both noncontrast PMCT and conventional autopsy between 2009 and 2020. Patients were randomly allocated to two groups: derivation and validation sets. Imaging findings of the upper gastrointestinal contents, including CT values, were recorded and evaluated for their power to diagnose UGIB in the derivation set and validated in the validation set. In the derivation set, the mean CT value of the upper gastrointestinal contents was 48.2 Hounsfield units (HU) and 22.8 HU in cases with and without UGIB. The optimal cutoff CT value for diagnosing UGIB was ≥27.7 HU derived from the receiver operating characteristic curve analysis (sensitivity, 91.7%; specificity, 81.2%; area under the curve, 0.898). In the validation set, the sensitivity and specificity in diagnosing UGIB for the CT cutoff value of ≥27.7 HU were 84.6% and 77.6%, respectively. In addition to the CT value of ≥27.7 HU, PMCT findings of solid-natured gastrointestinal content and intra/peri-content bubbles ≥4 mm, extracted from the derivation set, increased the specificity for UGIB (96.5% and 98.8%, respectively) but decreased the sensitivity (61.5% and 38.5%, respectively) in the validation set. In diagnosing UGIB on noncontrast PMCT, the cutoff CT value of ≥27.7 HU and solid gastrointestinal content were valid and reproducible diagnostic criteria.

Fibulin-4 as a potential extracellular vesicle marker of fibrosis in patients with cirrhosis.

Chronic liver injury leads to decreased liver function and increased fibrosis. Fibrosis is not only associated with the development of portal hypertension and carcinogenesis, but with the occurrence of events and a poor prognosis, highlighting the importance of non-invasive fibrosis assessment in patients. In the present study, we searched for markers related to liver fibrosis via proteomic analysis of small extracellular vesicles (sEVs). In the discovery cohort, proteomic analysis was carried out in the sEVs extracted from the sera of 5 patients with decompensated cirrhosis, 5 patients with compensated cirrhosis, and 5 controls without liver disease. Interestingly, in this cohort, fibulin-4 was significantly associated with cirrhosis while in the validation cohort [formed by 191 patients: 7 patients without disease, 16 patients without liver disease (other diseases), 38 patients with chronic liver disease (CLD), 75 patients with cirrhosis of Child-Pugh class A (36 without hepatocellular carcinoma [HCC], 29 with HCC), and 65 patients with cirrhosis of Child-Pugh class B-C (39 without HCC, 26 with HCC)], fibulin-4/CD9 levels increased with cirrhosis progression. Furthermore, the fibulin-4/CD9 ratio was significantly higher in patients with varices. Immunostaining also revealed strong fibulin-4 expression in cholangiocytes within the fibrous areas and mesothelial cells in liver tissue blood vessels. Taken together, our results suggest that fibulin-4, essential for lysyl oxidase activation, might be a new liver fibrosis marker found in the sEVs of patients with cirrhosis.

Claudin-18 status and its correlation with HER2 and PD-L1 expression in gastric cancer with peritoneal dissemination.

BACKGROUND: Gastric cancer with peritoneal dissemination (PD) has a dismal prognosis, and current treatments have shown little efficacy. CLDN18.2-targeted therapies have shown promising efficacy against gastric cancers that express high levels of CLDN18. Because of the limited information regarding CLDN18.2 status in PD, we analyzed PD-positive gastric cancers for CLDN18 status in both primary and PD, along with HER2 and PD-L1 combined positive score (CPS). METHODS: Immunohistochemical analyses were performed on 84 gastric cancer cases using paired primary and PD tissue samples. RESULTS: At 40% cut-off, CLDN18 was positive in 57% (48/84) primary tumors and in 44% (37/84) PDs. At 75% cut-off, 28.6% (24/84) primary tumors and 20.2% (17/84) PDs were CLDN18-positive. The concordance rate between primary tumors and PD was 79.8% at 40% cut-off and 75% at 75% cut-off. When comparing biopsy and surgical specimens, the concordance rates were 87.5% at 40% cut-off and 81.3% at 75% cut-off. Within a tumor, the superficial area tended to have a higher CLDN18-positive rate than the invasive front (P = 0.001). Although HER2 -positivity was only 11.9% in this cohort, CLDN18 positivity in HER2-negative tumors (n = 74) was relatively high: 60.8% at 40% cut-off and 28.4% at 75% cut-off. Among double-negative (HER2 - and PD-L1 CPS < 1) tumors, CLDN18 positivity was 67.6% at 40% cut-off and 26.5% at 75% cut-off. CONCLUSIONS: CLDN18 expression is generally maintained in PD and is relatively high even in double-negative tumors, making it a promising therapeutic target for PD-positive gastric cancer.

Computerized assessment of background parenchymal enhancement on breast dynamic contrast-enhanced-MRI including electronic lesion removal.

Purpose: Current clinical assessment qualitatively describes background parenchymal enhancement (BPE) as minimal, mild, moderate, or marked based on the visually perceived volume and intensity of enhancement in normal fibroglandular breast tissue in dynamic contrast-enhanced (DCE)-MRI. Tumor enhancement may be included within the visual assessment of BPE, thus inflating BPE estimation due to angiogenesis within the tumor. Using a dataset of 426 MRIs, we developed an automated method to segment breasts, electronically remove lesions, and calculate scores to estimate BPE levels. Approach: A U-Net was trained for breast segmentation from DCE-MRI maximum intensity projection (MIP) images. Fuzzy c-means clustering was used to segment lesions; the lesion volume was removed prior to creating projections. U-Net outputs were applied to create projection images of both, affected, and unaffected breasts before and after lesion removal. BPE scores were calculated from various projection images, including MIPs or average intensity projections of first- or second postcontrast subtraction MRIs, to evaluate the effect of varying image parameters on automatic BPE assessment. Receiver operating characteristic analysis was performed to determine the predictive value of computed scores in BPE level classification tasks relative to radiologist ratings. Results: Statistically significant trends were found between radiologist BPE ratings and calculated BPE scores for all breast regions (Kendall correlation, p<0.001). Scores from all breast regions performed significantly better than guessing (p<0.025 from the z-test). Results failed to show a statistically significant difference in performance with and without lesion removal. BPE scores of the affected breast in the second postcontrast subtraction MIP after lesion removal performed statistically greater than random guessing across various viewing projections and DCE time points. Conclusions: Results demonstrate the potential for automatic BPE scoring to serve as a quantitative value for objective BPE level classification from breast DCE-MR without the influence of lesion enhancement.

Integrated enhancer regulatory network by enhancer-promoter looping in gastric cancer.

Enhancer cis-regulatory elements play critical roles in gene regulation at many stages of cell growth. Enhancers in cancer cells also regulate the transcription of oncogenes. In this study, we performed a comprehensive analysis of long-range chromatin interactions, histone modifications, chromatin accessibility and expression in two gastric cancer (GC) cell lines compared to normal gastric epithelial cells. We found that GC-specific enhancers marked by histone modifications can activate a population of genes, including some oncogenes, by interacting with their proximal promoters. In addition, motif analysis of enhancer-promoter interacting enhancers showed that GC-specific transcription factors are enriched. Among them, we found that MYB is crucial for GC cell growth and activated by the enhancer with an enhancer-promoter loop and TCF7 upregulation. Clinical GC samples showed epigenetic activation of enhancers at the MYB locus and significant upregulation of TCF7 and MYB, regardless of molecular GC subtype and clinicopathological factors. Single-cell RNA sequencing of gastric mucosa with intestinal metaplasia showed high expression of TCF7 and MYB in intestinal stem cells. When we inactivated the loop-forming enhancer at the MYB locus using CRISPR interference (dCas9-KRAB), GC cell growth was significantly inhibited. In conclusion, we identified MYB as an oncogene activated by a loop-forming enhancer and contributing to GC cell growth.

Changes in SARS-CoV-2 viral load and titers over time in SARS-CoV-2-infected human corpses.

High viral titers of infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been detected in human corpses long after death. However, little is known about the kinetics of infectious SARS-CoV-2 in corpses. In this case series study, we investigated the postmortem kinetics of infectious SARS-CoV-2 in human corpses by collecting nasopharyngeal swab samples at multiple time points from six SARS-CoV-2-infected patients after their death. SARS-CoV-2 RNA was detected by quantitative reverse transcription-polymerase chain reaction from nasopharyngeal swab samples collected from all six deceased patients. A viral culture showed the presence of infectious virus in one deceased patient up to 12 days after death. Notably, this patient had a shorter time from symptom onset to death than the other patients, and autopsy samples showed pathological findings consistent with viral replication in the upper respiratory tract. Therefore, this patient died during the viral shedding phase, and the amount of infectious virus in the corpse did not decrease over time up to the date of autopsy (12 days after death). The findings of this study indicate that the persistence of SARS-CoV-2 in corpses can vary among individuals and may be associated with the stage of the disease at the time of death. These important results complement many previously reported findings on the infectivity of SARS-CoV-2 at postmortem.

Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI.

BACKGROUND: Artificial intelligence/computer-aided diagnosis (AI/CADx) and its use of radiomics have shown potential in diagnosis and prognosis of breast cancer. Performance metrics such as the area under the receiver operating characteristic (ROC) curve (AUC) are frequently used as figures of merit for the evaluation of CADx. Methods for evaluating lesion-based measures of performance may enhance the assessment of AI/CADx pipelines, particularly in the situation of comparing performances by classifier. PURPOSE: The purpose of this study was to investigate the use case of two standard classifiers to (1) compare overall classification performance of the classifiers in the task of distinguishing between benign and malignant breast lesions using radiomic features extracted from dynamic contrast-enhanced magnetic resonance (DCE-MR) images, (2) define a new repeatability metric (termed sureness), and (3) use sureness to examine if one classifier provides an advantage in AI diagnostic performance by lesion when using radiomic features. METHODS: Images of 1052 breast lesions (201 benign, 851 cancers) had been retrospectively collected under HIPAA/IRB compliance. The lesions had been segmented automatically using a fuzzy c-means method and thirty-two radiomic features had been extracted. Classification was investigated for the task of malignant lesions (81% of the dataset) versus benign lesions (19%). Two classifiers (linear discriminant analysis, LDA and support vector machines, SVM) were trained and tested within 0.632 bootstrap analyses (2000 iterations). Whole-set classification performance was evaluated at two levels: (1) the 0.632+ bias-corrected area under the ROC curve (AUC) and (2) performance metric curves which give variability in operating sensitivity and specificity at a target operating point (95% target sensitivity). Sureness was defined as 1-95% confidence interval of the classifier output for each lesion for each classifier. Lesion-based repeatability was evaluated at two levels: (1) repeatability profiles, which represent the distribution of sureness across the decision threshold and (2) sureness of each lesion. The latter was used to identify lesions with better sureness with one classifier over another while maintaining lesion-based performance across the bootstrap iterations. RESULTS: In classification performance assessment, the median and 95% CI of difference in AUC between the two classifiers did not show evidence of difference (ΔAUC = -0.003 [-0.031, 0.018]). Both classifiers achieved the target sensitivity. Sureness was more consistent across the classifier output range for the SVM classifier than the LDA classifier. The SVM resulted in a net gain of 33 benign lesions and 307 cancers with higher sureness and maintained lesion-based performance. However, with the LDA there was a notable percentage of benign lesions (42%) with better sureness but lower lesion-based performance. CONCLUSIONS: When there is no evidence for difference in performance between classifiers using AUC or other performance summary measures, a lesion-based sureness metric may provide additional insight into AI pipeline design. These findings present and emphasize the utility of lesion-based repeatability via sureness in AI/CADx as a complementary enhancement to other evaluation measures.

Development and validation of machine learning model for predicting treatment responders in patients with primary biliary cholangitis.

AIMS: Ursodeoxycholic acid is the first-line treatment for primary biliary cholangitis, and treatment response is one of the factors predicting the outcome. To prescribe alternative therapies, clinicians might need additional information before deciphering the treatment response to ursodeoxycholic acid, contributing to a better patient prognosis. In this study, we developed and validated machine learning (ML) algorithms to predict treatment responses using pretreatment data. METHODS: This multicenter cohort study included collecting datasets from two data samples. Data 1 included 245 patients from 18 hospitals for ML development, and was divided into (i) training and (ii) development sets. Data 2 (iii: test set) included 51 patients from our hospital for validation. An extreme gradient boosted tree predicted the treatment response in the ML model. The area under the curve was used to evaluate the efficacy of the algorithm. RESULTS: Data 1 showed that patients complying with the Paris II treatment response had significantly lower serum alkaline phosphatase and total bilirubin levels than those who did not respond. Three factors, total bilirubin, total protein, and alanine aminotransferase levels were selected as essential variables for prediction. Data 2 showed that patients complying with the Paris II criteria had significantly high prothrombin time and low total bilirubin levels. The area under the curve of extreme gradient boosted tree was good for (ii) (0.811) and (iii) (0.856). CONCLUSIONS: We demonstrated the efficacy of ML in predicting the treatment response for patients with primary biliary cholangitis. Early identification of cases requiring additional treatment with our novel ML model may improve prognosis.

External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population.

Purpose: To externally evaluate a mammography-based deep learning (DL) model (Mirai) in a high-risk racially diverse population and compare its performance with other mammographic measures. Materials and Methods: A total of 6435 screening mammograms in 2096 female patients (median age, 56.4 years ± 11.2 [SD]) enrolled in a hospital-based case-control study from 2006 to 2020 were retrospectively evaluated. Pathologically confirmed breast cancer was the primary outcome. Mirai scores were the primary predictors. Breast density and Breast Imaging Reporting and Data System (BI-RADS) assessment categories were comparative predictors. Performance was evaluated using area under the receiver operating characteristic curve (AUC) and concordance index analyses. Results: Mirai achieved 1- and 5-year AUCs of 0.71 (95% CI: 0.68, 0.74) and 0.65 (95% CI: 0.64, 0.67), respectively. One-year AUCs for nondense versus dense breasts were 0.72 versus 0.58 (P = .10). There was no evidence of a difference in near-term discrimination performance between BI-RADS and Mirai (1-year AUC, 0.73 vs 0.68; P = .34). For longer-term prediction (2-5 years), Mirai outperformed BI-RADS assessment (5-year AUC, 0.63 vs 0.54; P < .001). Using only images of the unaffected breast reduced the discriminatory performance of the DL model (P < .001 at all time points), suggesting that its predictions are likely dependent on the detection of ipsilateral premalignant patterns. Conclusion: A mammography DL model showed good performance in a high-risk external dataset enriched for African American patients, benign breast disease, and BRCA mutation carriers, and study findings suggest that the model performance is likely driven by the detection of precancerous changes.Keywords: Breast, Cancer, Computer Applications, Convolutional Neural Network, Deep Learning Algorithms, Informatics, Epidemiology, Machine Learning, Mammography, Oncology, Radiomics Supplemental material is available for this article. © RSNA, 2023See also commentary by Kontos and Kalpathy-Cramer in this issue.

Stomach encyclopedia: Combined single-cell and spatial transcriptomics reveal cell diversity and homeostatic regulation of human stomach.

The stomach is an important digestive organ with various biological functions. However, because of the complexity of its cellular and glandular composition, its precise cellular biology has yet to be elucidated. In this study, we conducted single-cell RNA sequencing (scRNA-seq) and subcellular-level spatial transcriptomics analysis of the human stomach and constructed the largest dataset to date: a stomach encyclopedia. This dataset consists of approximately 380,000 cells from scRNA-seq and the spatial transcriptome, enabling integrated analyses of transcriptional and spatial information of gastric and metaplastic cells. This analysis identified LEFTY1 as an uncharacterized stem cell marker, which was confirmed through lineage tracing analysis. A wide variety of cell-cell interactions between epithelial and stromal cells, including PDGFRA+BMP4+WNT5A+ fibroblasts, was highlighted in the developmental switch of intestinal metaplasia. Our extensive dataset will function as a fundamental resource in investigations of the stomach, including studies of development, aging, and carcinogenesis.

Analysis of distribution, collection, and confirmation of capacity dependency of small extracellular vesicles toward a therapy for liver cirrhosis.

BACKGROUND: The progression of liver fibrosis leads to portal hypertension and liver dysfunction. However, no antifibrotic agents have been approved for cirrhosis to date, making them an unmet medical need. Small extracellular vesicles (sEVs) of mesenchymal stem cells (MSCs) are among these candidate agents. In this study, we investigated the effects of sEVs of MSCs, analyzed their distribution in the liver post-administration, whether their effect was dose-dependent, and whether it was possible to collect a large number of sEVs. METHODS: sEVs expressing tdTomato were generated, and their uptake into constituent liver cells was observed in vitro, as well as their sites of uptake and cells in the liver using a mouse model of liver cirrhosis. The efficiency of sEV collection using tangential flow filtration (TFF) and changes in the therapeutic effects of sEVs in a volume-dependent manner were examined. RESULTS: The sEVs of MSCs accumulated mostly in macrophages in damaged areas of the liver. In addition, the therapeutic effect of sEVs was not necessarily dose-dependent, and it reached a plateau when the dosage exceeded a certain level. Furthermore, although ultracentrifugation was commonly used to collect sEVs for research purposes, we verified that TFF could be used for efficient sEV collection and that their effectiveness is not reduced. CONCLUSION: In this study, we identified some unknown aspects regarding the dynamics, collection, and capacity dependence of sEVs. Our results provide important fundamentals for the development of therapies using sEVs and hold potential implications for the therapeutic applications of sEV-based therapies for liver cirrhosis.

Solid pseudopapillary neoplasm in a woman presenting with acute pancreatitis: a case report and review of literature.

Solid pseudopapillary neoplasm (SPN) is a rare pancreatic tumor that typically affects young women in the body and tail of the pancreas. SPN is often asymptomatic in the early stages, so it is initially discovered as a large tumor. In this report, we experienced a case of a relatively small SPN discovered in the setting of acute pancreatitis. Because there have been few reports of SPN being discovered in the situation like our case, we report this case based on a review of the literature.

Apoptosis-related Prognostic Factors in Advanced Colorectal Cancer Determined Using Tissue Microarrays.

BACKGROUND/AIM: Cancer cells evade apoptosis in colorectal cancer (CRC); however, overlap between apoptosis and poor prognosis marker proteins in the invasive front of tumors has not been reported. Here, we aimed to clarify the relationship between apoptosis, apoptosis-related protein expression, and prognosis in the central and invasive front regions of CRC using tissue microarrays. PATIENTS AND METHODS: Data of 207 patients with pathological stage 3 CRC, who underwent radical surgery between October 2010 and November 2014, were retrospectively reviewed. We assessed apoptosis using M30 CytoDEATH, CD163, and p53 immunostaining in tumor sections in the center and invasive front using tissue microarrays and correlated the results with the survival outcomes. RESULTS: M30 CytoDEATH staining was negative; 134 cases (64.7%) were apoptosis-negative in the center and 103 (49.8%) were apoptosis-negative at the invasive front. CD163 positivity was observed in 16 cases (7.8%) in the center and in 36 cases (17.6%) at the invasive front; p53 positivity was observed in 33 (15.9%) and 64 (30.9%) cases in the center and invasive front, respectively. CD163 and p53 expression was not associated with survival outcomes; however, the apoptosis-negative group at the invasive front had significantly poorer survival outcomes (overall survival: p=0.044, relapse-free survival: p=0.001). We identified cases with a poor prognosis by combining apoptosis and CD163 expression. CONCLUSION: A lower apoptosis percentage at the invasive front is associated with a poorer prognosis. CRC cases with a poor prognosis can be identified by evaluating apoptosis and CD163 expression in the invasive front.