nSMase2-mediated exosome secretion shapes the tumor microenvironment to immunologically support pancreatic cancer.

The pleiotropic roles of nSMase2-generated ceramide include regulation of intracellular ceramide signaling and exosome biogenesis. We investigated the effects of eliminating nSMase2 on early and advanced PDA, including its influence on the microenvironment. Employing the KPC mouse model of pancreatic cancer, we demonstrate that pancreatic epithelial nSMase2 ablation reduces neoplasia and promotes a PDA subtype switch from aggressive basal-like to classical. nSMase2 elimination prolongs survival of KPC mice, hinders vasculature development, and fosters a robust immune response. nSMase2 loss leads to recruitment of cytotoxic T cells, N1-like neutrophils, and abundant infiltration of anti-tumorigenic macrophages in the pancreatic preneoplastic microenvironment. Mechanistically, we demonstrate that nSMase2-expressing PDA cell small extracellular vesicles (sEVs) reduce survival of KPC mice; PDA cell sEVs generated independently of nSMase2 prolong survival of KPC mice and reprogram macrophages to a proinflammatory phenotype. Collectively, our study highlights previously unappreciated opposing roles for exosomes, based on biogenesis pathway, during PDA progression.

Evaluation of cryoablation using a prototype cryoablation needle in swine liver.

BACKGROUND/AIMS: Pancreatic cancer poses significant challenges due to its tendency for late-stage diagnosis and high mortality rates. Cryoablation, a technique used to treat various types of cancer, has shown potential in enhancing the prognosis of pancreatic cancer when combined with other therapies. However, its implementation is often limited by the need for lengthy procedures and specialized equipment. This study aims to develop a cryoablation needle optimized for endoscopic ultrasonography to simplify its application in treating pancreatic cancer. METHODS: The study involved conducting cryoablation experiments on swine liver tissue. It utilized cryo-needles to evaluate the extent of cell death across various temperatures and durations of cryoablation. RESULTS: The cryoablation system, which employed liquid carbon dioxide, achieved rapid cooling, reaching temperatures below -60 °C within 30 seconds and maintained the cryoablation process for 200 seconds. These conditions resulted in necrosis of the liver tissue. Notable cellular changes were observed up to 15 mm away from the cryoablation needle. CONCLUSIONS: This experimental study successfully demonstrated the efficacy of using a cryo-needle for cryoablation in swine liver tissue. Further trials involving pancreatic tissue are expected to verify its effectiveness, underscoring the importance of continued research to establish its role as a complementary therapy in pancreatic cancer treatment.

A Historical Review of the Prevalence of Job Stress Theories.

Job stress theories have been developed and refined to better understand employee wellbeing. Now that the field is maturing, it is appropriate to review the theoretical trends and developments for future research and practical guidance. The current paper provides a historical review, with both objective (i.e., counts of published theories) and subjective evaluation of job stress theory. In Study 1, two trained raters coded theories used in job stress journals. The job demand-control (-support; JDCS) model was initially well-represented, but has been superseded more recently by theories that focus on multiple resources (e.g., the job demand-resource - JDR - model). Among non-job stress theories, motivation and affective theories have been well-represented within job stress research. Study 2 expanded the results of Study 1 through review of two international applied psychology journals with additional coding categories. Specifically, we identified empirical support for theories and researcher characteristics (i.e., national and professional affiliation). The JDCS model had the least full support according to a vote counting method, and resource models (e.g., JDR) the most. Germany and the Netherlands were the most represented locations, with the United States having the most international collaborations. Psychology and management were the most represented affiliations.

A Preliminary Study of a Prototype Cryoablation Needle on Porcine Livers for Pancreatic Cancer Treatment.

Background and Aims: Despite its relatively low incidence rate compared to others, pancreatic cancer has a poor prognosis owing to its late detection and poor response to systemic chemotherapy. Because the effectiveness of chemotherapy is still restricted, the need for locoregional treatment is increasing. Cryoablation is an effective and minimally invasive treatment for some cancers, but its efficiency in pancreatic cancer is limited. Despite recent reports about promising outcomes, the optimal method and conditions of treatment are not known. In this preliminary study, we aimed to develop a cryoablation needle which can control the ablated area considering application through endoscopic ultrasonography. Methods: Here, we used a novel cryoneedle cooling system which can adjust the ablation range based on a liquid carbon dioxide refrigerant. Applied to the livers of swine, the cryoablation needle rapidly reached -60 °C within 30 s and cryoablation was performed for approximately 240 s. Based on the distance and depth, we collected real-time temperature data during the procedure. To compare the extent of cell death over time, tissue samples were collected hourly from 3 to 6 h after the procedure. Results: Approximately 4-5 mm of tissue was ablated via cryoablation, and cell death progressed over time after cryoablation. Moreover, the ablated lesions could be regulated using an insulating agent on the needle. Conclusions: This preliminary study on a novel surgical cooling needle system compatible with endoscopic ultrasound for cryoablation-based pancreatic cancer treatment confirmed the efficacy of cryoablation and identified the conditions necessary to induce necrosis. Additionally, this study evaluated the effectiveness of the insulation component of the system in protecting normal cells and assessed the extent of necrosis over time after the procedure.

New Method of Papillectomy May Decrease Recurrence: Anchoring Method versus Conventional Method.

Background/Objectives: Endoscopic papillectomy (EP) is the preferred treatment for ampullary tumors because it has fewer side effects than surgical removal. This study retrospectively compared a new anchoring EP method (A-EP) with the conventional (C-EP) approach. Methods: Ninety-nine patients who underwent EP at a single medical institution between 2009 and 2021 were retrospectively reviewed. In all patients, the indications for EP were pathological adenoma with <10 mm of biliary invasion and a tumor diameter <30 mm on endoscopic ultrasonography. The exclusion criteria were antiplatelet/anticoagulant use, previous upper GI surgery, or prior biliary/pancreatic endoscopic therapy. One expert endoscopist performed the two types of EPs, A-EP and C-EP. Results: Sixty-two patients underwent A-EP, and 37 underwent C-EP. There were no significant differences in baseline characteristics, such as sex, age, tumor size, and ductal invasion on endoscopic ultrasound. The A-EP group had higher en bloc resection rates (95.2% vs. 78.4%, p = 0.010). Although the difference was not statistically significant, it tended towards fewer incidences of pancreatitis (p = 0.081) and duct stricture (p = 0.081). The recurrence rate was lower in the A-EP group (8.1% vs. 37.8%, p = 0.000). There were no significant differences between the two groups regarding the follow-up period (A-EP vs. C-EP, 725 vs. 1045 days, p = 0.109) or the days of recurrence (A-EP vs. C-EP, 341 vs. 562 days, p = 0.551). Conclusions: A-EP showed better outcomes than C-EP in terms of en bloc resection and recurrence rates, providing evidence for the efficacy of this novel EP method.

Prognostic Impact of Mucin Expression in Curatively Resected Ampulla of Vater Cancer.

Introduction: Mucins play a pivotal role in epithelial carcinogenesis; however, their role remains elusive in ampulla of Vater (AoV) cancer, regardless of histological subtype. Therefore, we investigated the clinical significance of MUC1, MUC2, MUC5AC, and MUC6 expression in AoV cancer. Methods: Using samples from 68 patients with AoV cancer, we performed immunohistochemical staining for MUC1, MUC2, MUC5AC, and MUC6 using a tissue microarray. Subsequently, we analyzed their expression patterns in relation to clinicopathological parameters and patient outcomes. Results: Of the patients, 98.5% exhibited positive expression for MUC1, while MUC2, MUC5AC, and MUC6 were expressed in 44.1%, 47.1%, and 41.2% of the patients, respectively. Correlation analyses between mucin expression and clinicopathological factors revealed no significant associations, except between MUC5AC expression and N stage. Univariate analysis demonstrated significant associations between MUC5AC expression and overall survival (OS). Multivariate analysis further confirmed that MUC5AC expression was a significant predictor of OS, along with the N stage. However, MUC5AC expression was not meaningfully associated with recurrence-free survival (RFS). The patients positive for MUC5AC expression had a considerably shorter OS than those with negative expression. Conclusions: Our study provides insights into the clinical impact of mucins on AoV cancer, regardless of the histological subtype. Although MUC1 expression is universal, MUC5AC expression is a significant prognostic indicator that correlates with lymph node metastasis and poor OS. These results emphasize the possible utility of MUC5AC as a biomarker for extensive lymph node dissection and the prognostic evaluation of patients with AoV cancer.

Effects of Inclusive Leadership on the Diversity Climate and Change-Oriented Organizational Citizenship Behavior.

This study investigates the impact of inclusive leadership on diversity, climate, and change-oriented organizational citizenship behavior in hotel work. It also examines whether the diversity climate mediates the relationship between inclusive leadership and change-oriented organizational citizenship behavior. An online survey was conducted among hotel employees. It was found that inclusive leadership had a significant positive effect on the diversity climate. The diversity climate was found to have a significant positive effect on change-oriented organizational citizenship behavior, and inclusive leadership had a significant positive effect on change-oriented organizational citizenship behavior. Finally, inclusive leadership had a significant positive effect on change-oriented organizational citizenship behavior through a diversity climate. The results of this study have academic and practical implications for human resource management with respect to inclusive leadership in hotel workers' work environment according to changes in hotels' environmental factors for a new generation of employees flowing into the organizational mainstream.

Molecular Classification of Breast Cancer Using Weakly Supervised Learning.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusions: The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

Exploring empathic engagement in immersive media: An EEG study on mu rhythm suppression in VR.

This study investigates the influence of immersive media, particularly Virtual Reality (VR), on empathic responses, in comparison to traditional television (TV), using electroencephalography (EEG). We employed mu rhythm suppression as a measurable neural marker to gauge empathic engagement, as its increase generally signifies heightened empathic responses. Our findings exhibit a greater mu rhythm suppression in VR conditions compared to TV conditions, suggesting a potential enhancement in empathic responses with VR. Furthermore, our results revealed that the strength of empathic responses was not confined to specific actions depicted in the video clips, underscoring the possibility of broader implications. This research contributes to the ongoing discourse on the effects of different media environments on empathic engagement, particularly emphasizing the unique role of immersive technologies such as VR. It invites further investigation into how such technologies can shape and potentially enhance the empathic experience.

Prediction of immunochemotherapy response for diffuse large B-cell lymphoma using artificial intelligence digital pathology.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous and prevalent subtype of aggressive non-Hodgkin lymphoma that poses diagnostic and prognostic challenges, particularly in predicting drug responsiveness. In this study, we used digital pathology and deep learning to predict responses to immunochemotherapy in patients with DLBCL. We retrospectively collected 251 slide images from 216 DLBCL patients treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), with their immunochemotherapy response labels. The digital pathology images were processed using contrastive learning for feature extraction. A multi-modal prediction model was developed by integrating clinical data and pathology image features. Knowledge distillation was employed to mitigate overfitting on gigapixel histopathology images to create a model that predicts responses based solely on pathology images. Based on the importance derived from the attention mechanism of the model, we extracted histological features that were considered key textures associated with drug responsiveness. The multi-modal prediction model achieved an impressive area under the ROC curve of 0.856, demonstrating significant associations with clinical variables such as Ann Arbor stage, International Prognostic Index, and bulky disease. Survival analyses indicated their effectiveness in predicting relapse-free survival. External validation using TCGA datasets supported the model's ability to predict survival differences. Additionally, pathology-based predictions show promise as independent prognostic indicators. Histopathological analysis identified centroblastic and immunoblastic features to be associated with treatment response, aligning with previous morphological classifications and highlighting the objectivity and reproducibility of artificial intelligence-based diagnosis. This study introduces a novel approach that combines digital pathology and clinical data to predict the response to immunochemotherapy in patients with DLBCL. This model shows great promise as a diagnostic and prognostic tool for clinical management of DLBCL. Further research and genomic data integration hold the potential to enhance its impact on clinical practice, ultimately improving patient outcomes.

Higher sclerostin is associated with pulmonary hypertension in pre-dialysis end-stage kidney disease patients: a cross-sectional prospective observational cohort study.

BACKGROUND: Pulmonary hypertension (PH) is a complication of chronic kidney disease (CKD) that contributes to mortality. Sclerostin, a SOST gene product that reduces osteoblastic bone formation by inhibiting Wnt/ß-catenin signaling, is involved in arterial stiffness and CKD-bone mineral disease, but scanty evidence to PH. This study explored the relationship between sclerostin and PH in CKD 5, pre-dialysis end-stage kidney disease (ESKD) patients. METHODS: This cross-sectional prospective observational cohort study included 44 pre-dialysis ESKD patients between May 2011 and May 2015. Circulating sclerostin levels were measured using an enzyme-linked immunosorbent assay. PH was defined as an estimated pulmonary artery systolic pressure > 35 mmHg on echocardiography. RESULTS: Patients with higher sclerostin levels ≥ 218.18pmol/L had echocardiographic structural cardiac abnormalities, especially PH (P < 0.01). On multivariate logistic analysis, sclerostin over 218.19pmol/L was significantly associated with PH (odds ratio [OR], 41.14; 95% confidence interval [CI], 4.53-373.89, P < 0.01), but multivariate Cox regression analysis showed the systemic vascular calcification score over 1 point (Hazard ratio [HR] 11.49 95% CI 2.48-53.14, P = 0.002) and PH ([HR] 5.47, 95% CI 1.30-23.06, P = 0.02) were risk factors for all-cause mortality in pre-dialysis ESKD patients. CONCLUSIONS: Serum sclerostin and PH have a positive correlation in predialysis ESKD patients. The higher systemic vascular calcification score and PH have an association to increase all-cause mortality in pre-dialysis ESKD patients.

Resource analysis and modifications of quantum computing with noisy qubits for elliptic curve discrete logarithms.

We estimate the number of physical qubits and execution time by decomposing an implementation of Shor's algorithm for elliptic curve discrete logarithms into universal gate units at the logical level when surface codes are used. We herein also present modified quantum circuits for elliptic curve discrete logarithms and compare our results with those of the original quantum circuit implementations at the physical level. Through the analysis, we show that the use of more logical qubits in quantum algorithms does not always lead to the use of more physical qubits. We assumed using rotated surface code and logical qubits with all-to-all connectivity. The number of physical qubits and execution time are expressed in terms of bit length, physical gate error rate, and probability of algorithm failure. In addition, we compare our results with the number of physical qubits and execution time of Shor's factoring algorithm to assess the risk of attack by quantum computers in RSA and elliptic curve cryptography.

Removal of intrahepatic bile duct stone could reduce the risk of cholangiocarcinoma: A single-center retrospective study in South Korea.

BACKGROUND: Intrahepatic duct (IHD) stones are among the most important risk factors for cholangiocarcinoma (CCC). Approximately 10% of patients with IHD stones develop CCC; however, there are limited studies regarding the effect of IHD stone removal on CCC development. AIM: To investigate the association between IHD stone removal and CCC development. METHODS: We retrospectively analyzed 397 patients with IHD stones at a tertiary referral center between January 2011 and December 2020. RESULTS: CCC occurred in 36 of the 397 enrolled patients. In univariate analysis, chronic hepatitis B infection (11.1% vs 3.0%, P = 0.03), carbohydrate antigen 19-9 (CA19-9, 176.00 vs 11.96 II/mL, P = 0.010), stone located in left or both lobes (86.1% vs 70.1%, P = 0.042), focal atrophy (52.8% vs 26.9%, P = 0.001), duct stricture (47.2% vs 24.9%, P = 0.004), and removal status of IHD stone (33.3% vs 63.2%, P < 0.001) were significantly different between IHD stone patients with and without CCC. In the multivariate analysis, CA19-9 > upper normal limit, carcinoembryonic antigen > upper normal limit, stones located in the left or both lobes, focal atrophy, and complete removal of IHD stones without recurrence were independent factors influencing CCC development. However, the type of removal method was not associated with CCC risk. CONCLUSION: Complete removal of IHD stones without recurrence could reduce CCC risk.

High-dimensional single photon based quantum secure direct communication using time and phase mode degrees.

Quantum secure direct communication (QSDC) can guarantee security using the characteristics of quantum mechanics even when a message is directly transmitted through a quantum channel without using a secret key. However, the transmission rate of the QSDC is limited by the dead time of a single photon detector (SPD) as well as channel loss over the distance. To overcome this limited transmission rate, we propose a high-dimensional single photon-based QSDC protocol that applies two optical degrees of freedom: time and phase state. First, an N-dimensional time and phase state generation method that considers the dead time is proposed to minimize the measurement loss of a transmitted message. Second, among the two types of quantum states, the phase state with relatively low measurement efficiency is used only for eavesdropping detection, and the time state is used for sending messages with differential delay time bin-based encoding techniques. Lastly, we propose an efficient method for measuring N-dimensional time and phase-based quantum states and recovering classical bit information. This study performs security analysis against various attacks, and verifies the transmission rate improvement effect through simulation. The result indicates that our proposal can guarantee higher security and transmission rates compared to the conventional DL04 QSDC.

Ensemble Deep Learning Model to Predict Lymphovascular Invasion in Gastric Cancer.

Lymphovascular invasion (LVI) is one of the most important prognostic factors in gastric cancer as it indicates a higher likelihood of lymph node metastasis and poorer overall outcome for the patient. Despite its importance, the detection of LVI(+) in histopathology specimens of gastric cancer can be a challenging task for pathologists as invasion can be subtle and difficult to discern. Herein, we propose a deep learning-based LVI(+) detection method using H&E-stained whole-slide images. The ConViT model showed the best performance in terms of both AUROC and AURPC among the classification models (AUROC: 0.9796; AUPRC: 0.9648). The AUROC and AUPRC of YOLOX computed based on the augmented patch-level confidence score were slightly lower (AUROC: -0.0094; AUPRC: -0.0225) than those of the ConViT classification model. With weighted averaging of the patch-level confidence scores, the ensemble model exhibited the best AUROC, AUPRC, and F1 scores of 0.9880, 0.9769, and 0.9280, respectively. The proposed model is expected to contribute to precision medicine by potentially saving examination-related time and labor and reducing disagreements among pathologists.

DLM-DTI: a dual language model for the prediction of drug-target interaction with hint-based learning.

The drug discovery process is demanding and time-consuming, and machine learning-based research is increasingly proposed to enhance efficiency. A significant challenge in this field is predicting whether a drug molecule's structure will interact with a target protein. A recent study attempted to address this challenge by utilizing an encoder that leverages prior knowledge of molecular and protein structures, resulting in notable improvements in the prediction performance of the drug-target interactions task. Nonetheless, the target encoders employed in previous studies exhibit computational complexity that increases quadratically with the input length, thereby limiting their practical utility. To overcome this challenge, we adopt a hint-based learning strategy to develop a compact and efficient target encoder. With the adaptation parameter, our model can blend general knowledge and target-oriented knowledge to build features of the protein sequences. This approach yielded considerable performance enhancements and improved learning efficiency on three benchmark datasets: BIOSNAP, DAVIS, and Binding DB. Furthermore, our methodology boasts the merit of necessitating only a minimal Video RAM (VRAM) allocation, specifically 7.7GB, during the training phase (16.24% of the previous state-of-the-art model). This ensures the feasibility of training and inference even with constrained computational resources.

A robust model training strategy using hard negative mining in a weakly labeled dataset for lymphatic invasion in gastric cancer.

Gastric cancer is a significant public health concern, emphasizing the need for accurate evaluation of lymphatic invasion (LI) for determining prognosis and treatment options. However, this task is time-consuming, labor-intensive, and prone to intra- and interobserver variability. Furthermore, the scarcity of annotated data presents a challenge, particularly in the field of digital pathology. Therefore, there is a demand for an accurate and objective method to detect LI using a small dataset, benefiting pathologists. In this study, we trained convolutional neural networks to classify LI using a four-step training process: (1) weak model training, (2) identification of false positives, (3) hard negative mining in a weakly labeled dataset, and (4) strong model training. To overcome the lack of annotated datasets, we applied a hard negative mining approach in a weakly labeled dataset, which contained only final diagnostic information, resembling the typical data found in hospital databases, and improved classification performance. Ablation studies were performed to simulate the lack of datasets and severely unbalanced datasets, further confirming the effectiveness of our proposed approach. Notably, our results demonstrated that, despite the small number of annotated datasets, efficient training was achievable, with the potential to extend to other image classification approaches used in medicine.

Metastatic pancreatic solitary fibrous tumor: A case report.

BACKGROUND: Solitary fibrous tumor (SFT) is a rare mesenchymal tumor that is most commonly found in the pleura but can also originate from non-pleural sites. Among the non-pleural localizations, the pancreas is extremely rare. In particular, metastasis to the pancreas from the central nervous system (CNS) is extremely rare, with only two cases reported so far. We report a case of recurrence in the pancreas 14 years after the initial complete surgical removal of a tumor in the CNS. CASE SUMMARY: A 68-year-old man with a past medical history of recurrent meningeal hemangiopericytoma, currently referred to as SFT, presented to the hospital with jaundice. The patient was first diagnosed with an 8cm-sized meningeal hemangiopericytoma fourteen years ago and underwent osteoplastic craniotomy. After 16 mo, imaging showed recurrence and he underwent gamma knife radiosurgery (GKRS). 2 years later, imaging showed recurrence again leading to a second GKRS. 5 years later, recurrence was again suspected leading to a second craniotomy. Since then 3 years had passed, and imaging showed a 3.5cm-sized mass lesion on the pancreatic head with obstruction of the pancreatic and bile ducts. Endosonography with fine-needle aspiration biopsy was done preoperatively and aided in the diagnosis of SFT. The patient underwent pylorus-preserving pancreaticoduodenectomy. Pathologic findings of the resected pancreatic specimen, consistent with the previously resected brain specimen, confirmed the diagnosis of SFT. CONCLUSION: The rarity and lack of knowledge about SFTs make suspecting and diagnosing this disease challenging. We believe that a report of metastatic pancreatic SFT from the CNS will contribute to a better understanding of this rare disease.

Evidence integration on health damage for humidifier disinfectant exposure and legal presumption of causation.

OBJECTIVES: Inhalation exposure to humidifier disinfectants has resulted to various types of health damages in Korea. To determine the epidemiological correlation necessary for presuming the legal causation, we aimed to develop a method to synthesize the entire evidence. METHODS: Epidemiological and toxicological studies are systematically reviewed. Target health problems are selected by criteria such as frequent complaints of claimants. Relevant epidemiologic studies are reviewed and the risk of bias and confidence level of the total evidence are evaluated. Toxicological literature reviews are conducted on three lines of evidence including hazard information, animal studies, and mechanistic studies, considering the source-to-exposure-to-outcome continuum. The confidence level of the body of evidence is then translated into the toxicological evidence levels for the causality between humidifier disinfectant exposure and health effects. Finally, the levels of epidemiological and toxicological evidence are synthesized. RESULTS: Under the Special Act revised in 2020, if the history of exposure and the disease occurred/worsened after exposure were approved, and the epidemiological correlation between the exposure and disease was verified, the legal causation is presumed unless the company proves the evidence against it. The epidemiological correlation can be verified through epidemiological investigations, health monitoring, cohort investigations and/or toxicological studies. It is not simply as statistical association as understood in judicial precedents, but a general causation established by the evidence as a whole, i.e., through weight-of-the-evidence approach. CONCLUSIONS: The weight-of-the-evidence approach differs from the conclusive single study approach and this systematic evidence integration can be used in presumption of causation.