Heterogeneous Entity Research Articles

Clinical implications of DNA methylation-based integrated classification of histologically defined grade 2 meningiomas

The combination of DNA methylation analysis with histopathological and genetic features allows for a more accurate risk stratification and classification of meningiomas. Nevertheless, the implications of this classification for patients with grade 2 meningiomas, a particularly heterogeneous tumor entity, are only partially understood. We correlate the outcomes of histopathologically confirmed grade 2 meningioma with an integrated molecular-morphologic risk stratification and determine its clinical implications. Grade 2 meningioma patients treated at our institution were re-classified using an integrated risk stratification involving DNA methylation array-based data, copy number assessment and TERT promoter mutation analyses. Grade 2 meningioma cases according to the WHO 2021 criteria treated between 2007 and 2021 (n = 100) were retrospectively analyzed. The median clinical and radiographic follow-up periods were 59.8 and 54.4 months. A total of 38 recurrences and 17 deaths were observed. The local control rates of the entire cohort after 2-, 4-, and 6-years were 84.3%, 68.5%, and 50.8%, with a median local control time of 77.2 months. The distribution of the integrated risk groups were as follows: 31 low, 54 intermediate, and 15 high risk cases. In the multivariable Cox regression analysis, integrated risk groups were significantly associated with the risk of local recurrence (hazard ratio (HR) intermediate: 9.91, HR high-risk: 7.29, p < 0.01). Gross total resections decreased the risk of local tumor progression (HR gross total resection: 0.19, p < 0.01). The comparison of 1p status and integrated risk groups (low vs. intermediate/high) revealed nearly identical local control rates within their respective subgroups. In summary, only around 50% of WHO 2021 grade 2 meningiomas have an intermediate risk profile. Integrated molecular risk stratification is crucial to guide the management of patients with grade 2 tumors and should be routinely applied to avoid over- and undertreatment, especially concerning the use of adjuvant radiotherapy.

P155 Gene expression in hypermobility and the role of inflammation

Abstract Background/Aims Hypermobile conditions, including Ehlers-Danlos syndrome and joint hypermobility syndrome, encompass a broad spectrum of heterogenous clinical entities characterised by excessive range of joint movements and variable extra-articular features. The etiological basis of these conditions is thought to relate to abnormal collagen assembly, which impairs the structural integrity of connective tissue, although precise mechanisms remain both debated and incompletely understood. Despite the established strong heritability of hypermobility, a definitive genetic cause remains unidentifiable in most hypermobile patients, highlighting the need to further characterize the genetic landscape of hypermobile conditions. In this study, we therefore employ transcriptomic analysis as an alternate means of elucidating the genetic basis of hypermobility. Methods We tested for the effects of hypermobility on gene expression, at baseline and following an inflammatory challenge, by re-analysing existing transcriptomic data gathered from healthy subjects and patients with fibromyalgia and chronic fatigue using total RNA sequencing of blood samples (Illumina NextSeq 500). From each participant, two blood samples were taken on separate occasions: one after a saline injection and the other after an inflammatory challenge, the typhoid vaccination, in a cross-over design. Participants were assigned to hypermobile or non-hypermobile conditions in accordance with criterion 1: generalized joint hypermobility of the Diagnostic Criteria for Hypermobile Ehlers-Danlos Syndrome (hEDS) produced by the International Consortium on Ehlers-Danlos Syndromes &amp; Related disorders. Differential gene expression analysis comparing hypermobile and non-hypermobile participants was performed using EdgeR software in R studio. Baseline differences were determined by comparing post-saline samples between groups. Differential responses to the inflammatory challenge were detected by comparison of post-typhoid samples between groups. Gene ontology on differentially expressed genes was performed using DAVID’s Functional Annotation Clustering tool. Results We found 288 differentially expressed genes post-saline (i.e at baseline) and 1113 post-typhoid at p &amp;lt; 0.05 although none passed false discovery rate. At baseline, differentially expressed genes were significantly enriched for nuclear, endoplasmic reticulum, and microtubular genes (enrichment score = 2.96, 2.02, 1.3 respectively); and post-typhoid, for 24 clusters, the three most significant being synaptic, ion transport, and plasma membrane genes (enrichment score = 11.34, 8.71, and 7.3 respectively). Conclusion These data demonstrate distinct patterns of gene expression, both at baseline and during inflammation, which implicate potential biological pathways in the pathophysiology of hypermobility. These results also contribute to a growing understanding of the genetic basis of hypermobility and may inform future higher-powered studies to validate our findings. Disclosure J. Porter: None. M. Amato: None. K. Themelis: None. H. Critchley: None. S. Newbury: None. K. Davies: None. N. Harrison: None. B. Towler: None. J. Eccles: Grants/research support; J.E. has received funding from Versus Arthritis, National Institute for Health Research and the Fibroduck Foundation.

Bottom-up hierarchical and categorical metacomputing for automating composition and deployment of directly computable multiphysics models

The present paper describes a proposed solution for reducing the complexity and time required by experienced users of legacy codes for solving multiphysics problems. A bottom-up hierarchical specification-driven metacomputing framework was developed to automate the composition and deployment of necessary resources, and the generation of all necessary code, files, and parameter selections required for solving multiphysics problems. Utilization of the framework amounts to the generation of directly computable multiphysics models. The user’s role is reduced to providing (through a graphical user interface) the specification of the problem and its associated physics every time a new problem arises, while the rest of the resources are specified once at the beginning of the process. The proposed approach requires enabling and implementing transformation and composition of specifications describing seemingly heterogeneous entities such as problem (physics, boundary and initial conditions) and computational resources specifications. This is achieved by the utilization of Category Theory constructs and software that can implement them. This framework features a graphical user interface for capturing physics problem specifications at the meta-meta level, generating runtime scripts and input files for problem solving, and capturing problem specifications intuitively. Finally, the framework is demonstrated with its application to a conjugate heat transfer challenge problem associated with an aerobraking structure under hypersonic conditions.

Pathogenesis of Alopecia Areata and Vitiligo: Commonalities and Differences.

Both alopecia areata (AA) and vitiligo are distinct, heterogenous, and complex disease entities, characterized by nonscarring scalp terminal hair loss and skin pigment loss, respectively. In AA, inflammatory cell infiltrates are in the deep reticular dermis close to the hair bulb (swarm of bees), whereas in vitiligo the inflammatory infiltrates are in the epidermis and papillary dermis. Immune privilege collapse has been extensively investigated in AA pathogenesis, including the suppression of immunomodulatory factors (e.g., transforming growth factor-β (TGF-β), programmed death-ligand 1 (PDL1), interleukin-10 (IL-10), α-melanocyte-stimulating hormone (α-MSH), and macrophage migration inhibitory factor (MIF)) and enhanced expression of the major histocompatibility complex (MHC) throughout hair follicles. However, immune privilege collapse in vitiligo remains less explored. Both AA and vitiligo are autoimmune diseases that share commonalities in pathogenesis, including the involvement of plasmacytoid dendritic cells (and interferon-α (IFN- α) signaling pathways) and cytotoxic CD8+ T lymphocytes (and activated IFN-γ signaling pathways). Blood chemokine C-X-C motif ligand 9 (CXCL9) and CXCL10 are elevated in both diseases. Common factors that contribute to AA and vitiligo include oxidative stress, autophagy, type 2 cytokines, and the Wnt/β-catenin pathway (e.g., dickkopf 1 (DKK1)). Here, we summarize the commonalities and differences between AA and vitiligo, focusing on their pathogenesis.

Cytogenomic characterization of small supernumerary marker chromosomes in patients with pigmentary mosaicism.

The combination of gene content on the marker chromosome, chromosomal origin, level of mosaicism, origin mechanism (chromothripsis), and uniparental disomy can influence the final characterization of sSMCs. Several chromosomal aberrations, including sSMCs, have been observed in 30%-60% of patients with pigmentary mosaicism, and in more than 80%, chromosomal abnormalities are present in the mosaic state. In patients with pigmentary mosaicism the most representative chromosomes involved in sSMCs are 3, 5, 6, 9, 10, 13, 15, 18, 20, and X. In this study, we included the complete clinical, cytogenetic, and molecular characterization of seven patients with pigmentary mosaicism associated with the presence of SMCs of different chromosomal origins. The patients were diagnosed by the Genetics and Dermatology Department of three different hospitals. Cytogenetic and FISH analyses were performed on peripheral blood, light skin, and dark skin. FISH analysis was performed using different probes, depending on the marker chromosome description. Different array analysis was performed. To date, of the seven cases studied, the chromosomal origins of six were successfully identified by FISH or array analysis. The chromosomes involved in SMCs were 6, 9, 15, and 18, X. The most frequently found was the centric minute structure. To date, this group of seven patients constitutes the largest clinical and cytogenetically finely described study of cases with pigmentary mosaicism associated with sSMCs. Undoubtedly, analysis of the two skin types is a fundamental part of our study, as numerical differences may occur in the cell lines found in each skin type. The knowledge generated in this study will help delineate a very heterogeneous entity more accurately, and in the future, analyzing more patients with PM will likely establish a more definite association with the presence of this genetic alteration.

Mutation landscape in Chinese nodal diffuse large B-cell lymphoma by targeted next generation sequencing and their relationship with clinicopathological characteristics

BackgroundDiffuse large B-cell lymphoma (DLBCL), an aggressive and heterogenic malignant entity, is still a challenging clinical problem, since around one-third of patients are not cured with primary treatment. Next-generation sequencing (NGS) technologies have revealed common genetic mutations in DLBCL. We devised an NGS multi-gene panel to discover genetic features of Chinese nodal DLBCL patients and provide reference information for panel-based NGS detection in clinical laboratories.MethodsA panel of 116 DLBCL genes was designed based on the literature and related databases. We analyzed 96 Chinese nodal DLBCL biopsy specimens through targeted sequencing.ResultsThe most frequently mutated genes were KMT2D (30%), PIM1 (26%), SOCS1 (24%), MYD88 (21%), BTG1 (20%), HIST1H1E (18%), CD79B (18%), SPEN (17%), and KMT2C (16%). SPEN (17%) and DDX3X (6%) mutations were highly prevalent in our study than in Western studies. Thirty-three patients (34%) were assigned as genetic classification by the LymphGen algorithm, including 12 cases MCD, five BN2, seven EZB, seven ST2, and two EZB/ST2 complex. MYD88 L265P mutation, TP53 and BCL2 pathogenic mutations were unfavorable prognostic biomarkers in DLBCL.ConclusionsThis study presents the mutation landscape in Chinese nodal DLBCL, highlights the genetic heterogeneity of DLBCL and shows the role of panel-based NGS to prediction of prognosis and potential molecular targeted therapy in DLBCL. More precise genetic classification needs further investigations.

Human Papilloma Virus (HPV) driven oropharyngeal cancer in current or previous heavy smokers: should we look for a different treatment paradigm?

Human papillomavirus Virus (HPV)-associated oropharyngeal squamous cell carcinoma (OSCC) has increased in incidence in recent decades and represents a heterogeneous disease entity in the context of Head and Neck Squamous Cell Carcinoma (HNSCC), in terms of disease prognosis. Treatment of locoregionally advanced OSCC is mainly based on concurrent chemoradiotherapy. Given the younger age of patients, if compared with HPV-negative counterparts, and the high cure rates, the acute- and long-term toxicity in survivors represents a field of interest. However, patient selection for de-escalation trials remains a major challenge due to the lack of robust validated prognostic indicators within the HPV-associated OSCC. The impact of smoking status on HPV-associated OSCC prognosis has been demonstrated in the majority of studies. However, the magnitude of the association is unclear due to variability in smoking metrics and study outcomes. Smoking status has been identified as a potential confounding factor in HPV-positive de-escalation trials. Smokers with HPV-positive OSCC have a worse prognosis in most studies than non-smokers and may require different and more aggressive therapeutic strategies.

Chronic nonspecific multiple-sites pain [CNMSP] of unknown etiology: Biopsychosocial method of evaluation for the primary care level.

Understanding and dealing with chronic nonspecific pain (CNP) is the important entity at primary care hospital. Chronic nonspecific multiple-site pain [CNMSP] of unknown etiology creates diagnostic and therapeutic challenges for primary care physicians due to lack of guidance regarding evaluation and treatment. To classify and formulate the evaluation, treatment strategies, and prediction of prognosis of patients with CNMSP of unknown etiology. Patients present with CNMSP of more than 3-month duration without any obvious medical cause. The biopsychosocial [BPS] model with 3P model was applied to see the biological, psychological, and social factors behind persistence. Finally, patients were classified into four groups for evaluation response to treatment and relapse rates in 12-month follow-up. Of the total 243 patients of CNMSP, 243 [96.3%] were females. Sixty [24.7%] patients had short duration, and 183 [75.3%] had long duration. Headache was in 115 [47%], low back pain ± leg pain in 96 [39.4%], cervical pain ± shoulder/arm pain in 83 [34.1%], and diffuse body pain in 50 [20.5%] in various combinations. A total of 155 [63.8%] patients had high somatization-sensitization index (SSI), and 144 [59.3%] had low ferritin level. Group 1 [high SSI and low ferritin] had 37.9% of patients, group 2 [high SSI and normal ferritin] had 25.9% of patients, group 3 [low to medium SSI with low ferritin] had 21.4% of patients, and group 4 [low to medium SSI with normal ferritin] had 14.8% of patients. Response to pain symptoms was better in group 1, and relapse rate was higher in group 2. CNMSP of unknown etiology itself is a heterogeneous entity, and assessment based on the BPS model can be very useful to understand the treatment plan and outcome of these patients.

Frequency of Complete Remission With R-CHOP Therapy in Patients With Diffuse Large B Cell Lymphoma.

Background Diffuse large B-cell lymphoma (DLBCL) exhibits notable heterogeneity in clinical presentations and treatment responses, posing challenges in predicting outcomes and tailoring therapeutic strategies for affected patients. Despite advancements in molecular subtyping and prognostic assessment, uncertainties persist regarding the optimal management of DLBCL, highlighting the need for localized investigations to better understand treatment responses and outcomes within specific patient populations. Objective To assess the frequency of complete remission (CR) in diffuse large B-cell lymphoma (DLBCL) patients undergoing first-line rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP) therapy within a specific adult population. Material and methods This descriptive study was conducted within the Department of Oncology Hayatabad Medical Complex, Peshawar, Pakistan from August 8, 2022, to April 8, 2023. The study included newly diagnosed DLBCL patients aged 20-70 years, excluding those who had received prior treatment. There were 55 (57.9%) males and 40 (42.1%) females. Data on demographic characteristics, disease duration, and CR outcomes were collected using a predefined data collection form. Results The majority of patients (80, 84.2%) achieved CR following R-CHOP therapy. In terms of age distribution, 43 (45.3%) patients were aged ≤45 years, while the remaining belonged to the >45 years age group. The duration of the disease was ≤ 3 months in 60 (63.2%) cases, whereas it exceeded three months in 35 (36.8%) cases. With regards to BMI classification, nine (9.5%) patients had a BMI < 18.5 kg/m2, 49 (51.6%) fell within the range of 18.5-24.9 kg/m2, and the remaining 37 (38.9%) patients had a BMI between 25-30 kg/m2. Conclusion Diffuse large B-cell lymphoma (DLBCL) remains a heterogeneous disease entity with variable clinical outcomes. While R-CHOP therapy demonstrates promising efficacy in achieving CR, concerns regarding late adverse effects persist. Addressing these challenges requires continued research efforts to validate novel prognostic markers and develop alternative treatment approaches, ultimately improving patient outcomes and reducing the global burden of DLBCL.

Implementing a New Algorithm for Reinterpretation of Ambiguous Variants in Genetic Dilated Cardiomyopathy.

Dilated cardiomyopathy is a heterogeneous entity that leads to heart failure and malignant arrhythmias. Nearly 50% of cases are inherited; therefore, genetic analysis is crucial to unravel the cause and for the early identification of carriers at risk. A large number of variants remain classified as ambiguous, impeding an actionable clinical translation. Our goal was to perform a comprehensive update of variants previously classified with an ambiguous role, applying a new algorithm of already available tools. In a cohort of 65 cases diagnosed with dilated cardiomyopathy, a total of 125 genetic variants were classified as ambiguous. Our reanalysis resulted in the reclassification of 12% of variants from an unknown to likely benign or likely pathogenic role, due to improved population frequencies. For all the remaining ambiguous variants, we used our algorithm; 60.9% showed a potential but not confirmed deleterious role, and 24.5% showed a potential benign role. Periodically updating the population frequencies is a cheap and fast action, making it possible to clarify the role of ambiguous variants. Here, we perform a comprehensive reanalysis to help to clarify the role of most of ambiguous variants. Our specific algorithms facilitate genetic interpretation in dilated cardiomyopathy.

Primitive-Based 3D Human-Object Interaction Modelling and Programming

Embedding Human and Articulated Object Interaction (HAOI) in 3D is an important direction for a deeper human activity understanding. Different from previous works that use parametric and CAD models to represent humans and objects, in this work, we propose a novel 3D geometric primitive-based language to encode both humans and objects. Given our new paradigm, humans and objects are all compositions of primitives instead of heterogeneous entities. Thus, mutual information learning may be achieved between the limited 3D data of humans and different object categories. Moreover, considering the simplicity of the expression and the richness of the information it contains, we choose the superquadric as the primitive representation. To explore an effective embedding of HAOI for the machine, we build a new benchmark on 3D HAOI consisting of primitives together with their images and propose a task requiring machines to recover 3D HAOI using primitives from images. Moreover, we propose a baseline of single-view 3D reconstruction on HAOI. We believe this primitive-based 3D HAOI representation would pave the way for 3D HAOI studies. Our code and data are available at https://mvig-rhos.com/p3haoi.

SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter

In the dynamic and rapidly evolving world of social media, detecting anomalous users has become a crucial task to address malicious activities such as misinformation and cyberbullying. As the increasing number of anomalous users improves the ability to mimic normal users and evade detection, existing methods only focusing on bot detection are ineffective in terms of capturing subtle distinctions between users. To address these challenges, we proposed SeGA, preference-aware self-contrastive learning for anomalous user detection, which leverages heterogeneous entities and their relations in the Twittersphere to detect anomalous users with different malicious strategies. SeGA utilizes the knowledge of large language models to summarize user preferences via posts. In addition, integrating user preferences with prompts as pseudo-labels for preference-aware self-contrastive learning enables the model to learn multifaceted aspects for describing the behaviors of users. Extensive experiments on the proposed TwBNT benchmark demonstrate that SeGA significantly outperforms the state-of-the-art methods (+3.5% ∼ 27.6%) and empirically validate the effectiveness of the model design and pre-training strategies. Our code and data are publicly available at https://github.com/ying0409/SeGA.

The Brazilian diaspora: Intra‐community dynamics and differentiating factors among Brazilian migrants worldwide

AbstractWhile the Brazilian diaspora scholarship is a vibrant literature that emerged in the 1980s and has gained prominence over the years, it remains geographically dispersed. Most studies focus on Brazilian migrants' experiences in a specific country or region of destination, and less attention has been paid to issues that influence the Brazilian diaspora transnationally. While the experiences of Brazilian migrants in different regions are varied and dependent on exogenous factors in the host society, this article reviews and discusses common markers of identity and positioning that shape intra‐community social dynamics between Brazilians who reside in different regions of the world. These ‘endogenous differentiating factors’ often produce tensions and intra‐community stratification, and may be carried from Brazil to the host community or produced in the host society. This article aims to integrate the geographically dispersed literature and emphasise commonalities experienced by Brazilians worldwide. It also argues that the focus on endogenous differentiating factors relates to a scholarly trend to frame the ‘Brazilian community’ as a heterogeneous entity with its own social dynamics rather than a homogenous ethnic group.

TAFRO Syndrome: A Syndrome or a Subtype of Multicentric Castleman Disease?

TAFRO (thrombocytopenia, anasarca, fever, reticulin fibrosis of bone marrow/renal dysfunction, organomegaly) syndrome is a systemic inflammatory disorder of unknown etiology. It has been recognized as a subtype of idiopathic multicentric Castleman disease (iMCD), and the international diagnostic criteria for iMCD-TAFRO require a lymph node histopathology consistent with iMCD. Furthermore, TAFRO syndrome is defined as a heterogeneous clinical entity caused by underlying diseases such as malignancy, autoimmune diseases, or infections. However, the cases that led to the proposal of TAFRO syndrome lacked recognizable lymphadenopathy and were inconsistent with any other diseases, despite vigorous efforts in differential diagnosis. Irrespective of the presence or absence of Castleman disease (CD)-like histology, TAFRO syndrome exhibits homogeneous clinical, laboratory, and prognostic features, setting it apart from iMCD without TAFRO syndrome. Defining iMCD-TAFRO apart from TAFRO syndrome is deemed meaningless and confusing. MCD is a heterogeneous lymphoproliferative disorder consisting of several subtypes with different pathogenesis, clinical manifestations, and histological features. Typical MCD in Japan, characterized by the histology of plasma cell type and marked polyclonal hypergammaglobulinemia, is identical to idiopathic plasmacytic lymphadenopathy with polyclonal hyperimmunoglobulinemia (IPL). Although IPL is classified into iMCD-NOS (not otherwise specified), it should be recognized as a distinct clinicopathological entity. Furthermore, we propose to separate TAFRO syndrome from the MCD category as a defined disorder.

Submucosal gland differentiation and implications in esophageal basaloid squamous cell carcinomas.

Esophageal basaloid squamous cell carcinoma (BSCC) is a heterogenous entity with multilineage differentiation. It lacks systematical analysis on submucosal gland differentiation (SGD) due to the histological diversity and low incidence of esophageal BSCC. This study aims to find the correlation of SGD and clinicopathological features. A total of 152 esophageal BSCCs were separated into three histological groups: pure, mixed, and borderline group. The clinicopathological features were compared between different groups. The prevalence of SGD was also compared between cases of different groups. A panel of antibodies were used to identify SGD. The pure group differed from the mixed and borderline groups in many aspects, lymph node metastasis (LNM), cancer embolus, perineural invasion, and advanced stage occurred less frequently in the pure group (P<0.01). The pure group had a better but statistically insignificant overall survival (P=0.097). The squamous cell carcinoma (SCC) component or focal squamous differentiation was present in metastatic lymph nodes in almost all mixed BSCCs (95.7%, 22/23) with LNM. The LNM rate of superficial (T1b) BSCCs (17.6%, 6/34) was comparable to that of superficial (T1b) SCCs (18.5%, 57/308). However, LNM exclusively occurred in superficial mixed (3/5) and borderline (3/10) BSCCs. The IHC results demonstrated a prevalence of SGD in pure group (77%, 43/56). SGD is considered to be a favorable factor, while the squamous differentiation or invasive SCC component is an adverse factor in esophageal BSCCs. Refinement of classification is a promising way to improve patient management.

Enhancing security mechanisms for robot-fog computing networks

&lt;p&gt;The evolution from conventional Internet usage to the internet of things (IoT) is reshaping communication norms significantly. Cloud computing, while prevalent, faces challenges like limited capacity, high latency, and network failures, especially when handling connected objects, leading to the emergence of fog computing as a more suitable approach for IoT. However, establishing secure connections among heterogeneous IoT entities is complex due to resource disparities and the unsuitability of existing security protocols for resource-constrained devices. This article explores fog computing's architecture, drawing comparisons with cloud computing while emphasizing its significance within the realm of IoT. Moreover, it delves into the practical application of fog computing within the context of the robot teacher project. Subsequently, our exploration introduces an advanced mutual authentication protocol, centered around hashed message authentication code (HMAC), aimed at enhancing the security infrastructure between the robot and the fog computing server.&lt;/p&gt;

Human-Agent Team Based on Decision Matrices: Application to Road Traffic Management in Participatory Simulation

The main motivation for this work is the design of context-sensitive systems, involving a human-agent team. More precisely, the participants in the current context, are human beings and software agents, who have to coordinate themselves for the collaborative achievement of a complex task. We propose a model of interaction between these heterogeneous entities (humans, software agents) based on decision matrices inspired from game theory. The case study concerns the traffic management through intersections, involving several groups composed of human operators and software agents (playing the role of assistants), in a participatory simulation. An evaluation of the results obtained is presented in order to show the feasibility of the proposed approach. We show that despite its simplicity, the interaction model is relatively efficient, because it takes into account context characteristics and the potential availability of software agents.

Silent neuroendocrine tumor of biliary confluence

Neuroendocrine tumors (NETs) of the extrahepatic bile ducts are extremely rare. They are heterogeneous entities of varied histopathological features. The pathological types vary greatly with regards to biological behavior and prognosis. We presented such a case of silent tumor of the biliary tract of neuroendocrine origin in a middle-aged female with nonspecific abdominal pain without any clinically obvious signs which on radiological imaging revealed a tumor of hepatic confluence with metastatic deposits in liver for which she underwent left trisectionectomy with segment 7 metastatectomy. As per the literature reviews regarding extrahepatic bile duct NET these tumors are more common in the middle age population with a female preponderance. The tumors were symptomatic in majority of patients and the symptoms are mostly related to tumor mass and its invasion of adjacent structures or metastases rather than hormone and vasoactive peptide secretions. The low incidence and uncommon modes of presentation makes the diagnosis tough and management challenging.

From flocking to glassiness in dense disordered polar active matter

AbstractLiving materials such as biological tissues or bacterial colonies are collections of heterogeneous entities of different sizes, capable of autonomous motion, and often capable of cooperating. Such a degree of complexity brings to collective motion on large scales. However, how the competition between geometrical frustration, autonomous motion, and the tendency to move cooperatively impact large-scale behavior remains an open question. We implement those three ingredients in a model of active matter and show that the system, in forming migratory patterns, can arrange in bands or develop long-range order, depending on the density of the system. We also show that the active material undergoes a reentrant glass transition triggered by the alignment interaction that typically causes only collective migratory motion. Finally, we observe that polar order destroys active phase separation, producing homogeneous, disordered moving configurations.

Assessing financial distress of SMEs through event propagation: An adaptive interpretable graph contrastive learning model

Accurate assessment of financial distress of SMEs is critical as it has strong implications for various stakeholders to understand the firm's financial health. Recent studies start to leverage network data and suggest the effect of event propagation for predicting financial distress. Yet such methods face methodological challenges in determining and explaining event propagation due to heterogeneous entities and events. In this research, we propose to extend graph contrastive learning and interpretable machine learning in the context of a firm network formed by distinct entities (e.g., firms and persons) and events (i.e., positive and negative), and employ the propagation influence of events in firm networks for financial distress assessment of SMEs. To this end, we design a novel artifact, i.e., adaptive interpretable heterogeneous graph contrastive learning, by drawing on homophily and social learning theories. Our experimental results demonstrate the effectiveness of the proposed artifacts and suggest the differing effects of positive vs. negative events on the financial distress of SMEs. This research contributes to the IS and explainable graph AI literature by improving the assessment and interpretability of network-based financial distress of SMEs.