Specific Information Research Articles

Pitfalls in Implementing the EU Whistleblower Directive

Abstract In this paper, we focus on two conceptual problems associated with the EU Whistleblower Directive and point out issues that may undermine or even frustrate the successful implementation of the Directive in a national context. While fully acknowledging strong arguments for, and undeniable benefits of, speaking in favour of EU whistleblower protection, it has to be noted that a specific form of forced gold-plating calling for the extension of the material scope of protection may complicate the interpretation of the autonomous part of legislation and lead to legal insecurity. Moreover, new elements of whistleblower protection as introduced by the Directive diverge from the case law of the European Court of Human Rights. The introduction of higher standards of protection in favour of whistleblowers does not raise problems in relations between the state and the individual, but some EU rules may cause problems in horizontal relations between private individuals, since fair balancing of interests as required by Strasbourg jurisprudence may be not always guaranteed.

Insight into systematic development of ALK (anaplastic lymphoma kinase) inhibitors towards NSCLC treatment

Among cancer-related disorders, lung carcinoma is one of the leading causes of mortality. Anaplastic lymphoma kinase (ALK) belongs to tyrosine kinase receptor family and exhibits similar characteristics to insulin type receptors. The treatment of advanced non-small cell lung cancer (NSCLC) associates with ALK gene rearrangement has significantly improved since the approval of Crizotinib in 2011 as the first generation ALK inhibitor. In continuation, the second-generation drugs like ceritinib, alectinib, and brigatinib were developed to address and counteract resistance that was associated with the first-generation agents. However, resistance can develop over time, necessitating ongoing research to enhance their effectiveness. Therefore, the third-generation drug lorlatinib, which has demonstrated broad-spectrum potency against the majority of known resistance mutations and better lipophilicity, has been developed. According to current reports, the USFDA has approved five ALK-TKIs crizotinib, ceritinib, alectinib, brigatinib, and lorlatinib for ALK-associated lung cancer. Currently, several clinical trials are underway in search of better ALK inhibitors. Trials such as TPX-0131 and NVL-655 are considered fourth-generation ALK inhibitors for the treatment of patients with advanced ALK-positive or metastatic NSCLC. This review aims to provide specifics information on research works involving various ALK tyrosine kinase inhibitors, clinical studies, and the development of ALK TKIs. Additionally, we suggest potential future strategies involving sequential therapy and combination techniques for managing non-small cell carcinoma.

Decoupled representation for multi-view learning

Learning multi-view data is a central topic for advanced deep model applications. Existing efforts mainly focus on exploring shared information to maximize the consensus among all the views. However, after reasonably discarding superfluous task-irrelevant noise, the view-specific information is equally essential to downstream tasks. In this paper, we propose to decouple the multi-view representation learning into the shared and specific information extractions with parallel branches, and seamlessly adopt feature fusion in end-to-end models. The common feature is obtained based on the view-agnostic contrastive learning and view-discriminative training to minimize the discrepancy within the views. Simultaneously, the specific feature is learned with orthogonality constraints to minimize the view-level correlation. Besides, the semantic information in the features is reserved with supervised training. After disentangling the representations, we fuse the mutually complementary common and specific features for downstream tasks. Particularly, we provide a theoretical explanation for our method from an information bottleneck perspective. Compared with state-of-the-art multi-view models on benchmark datasets, we empirically demonstrate the advantage of our method in several downstream tasks, such as ordinary classification and few-shot learning. In addition, extensive experiments validate the robustness and transferability of our approach, when applying the learned representation on the source dataset to several target datasets.

Information needs for general practitioners on type 2 diabetes in Western countries. A systematic review.

Most people with type 2 diabetes receive treatment in primary care by general practitioners who are not specialised in diabetes. Thus, it is important to uncover the most essential information needs regarding type 2 diabetes in general practice. To identify information needs related to type 2 diabetes for general practitioners. A systematic review focused on literature relating to Western countries. We searched the databases MEDLINE, Embase, PsycInfo and CINAHL from inception to January 2024. Two researchers conducted the selection process, and citation searches were performed to identify any relevant articles missed by the database search. Quality appraisal was conducted with the Mixed Methods Appraisal Tool. Meaning units were coded individually, grouped into categories, and then studies were summarized within the context of these categories using narrative synthesis. An evidence map was created to highlight research gaps. Thirty-nine included studies revealed eight main categories and 37 subcategories of information needs. Categories were organised into a comprehensive hierarchical model of information needs, suggesting that 'Knowledge of guidelines' and 'Reasons for referral' encompass more specific information needs. The evidence map shows geographical distribution of categories and knowledge gaps in qualitative research on management and risk factors. This systematic review provides GPs, policy makers, and researchers with a hierarchical model of information and educational needs for GPs, and an evidence map showing gaps in the current literature. Information needs about clinical guidelines and reasons for referral to specialised care overlapped with needs for more specific information.

INTERNATIONALIZATION AS AN INTERDISCIPLINARY CATEGORY: EVOLUTION OF THEORETICAL CONCEPT

Purpose. The aim of the article is to research the evolution of the interdisciplinary scientific category "internationalization", identification of its subject and formal specificity in various spheres of implementation. Methodology of research. The key research methods are dialectical methods of induction and deduction, analysis and synthesis, which made it possible to determine the essence of the category "internationalization", abstracting from the specifics of the sphere; and conceptual identity (forms and subjects of practical implementation) of internationalization in the economy, public administration and social sphere. Findings. It was established that "internationalization" is an interdisciplinary scientific category, the evolution of the theoretical and methodological understanding of which took place in accordance with the deepening and diversification of its practical implementation forms. Internationalization is identified as a diversified process of expanding the activities of subjects beyond national borders, by adapting the endogenous potential to the conditions of the global environment in order to gain access to new opportunities not inherent in the national space. It has been proven that the processes of internationalization in various social spheres are differentiated by forms and subjects, the priority of individual and national interests. Originality. Within the framework of a single study, the conceptual understanding of "internationalization" as an interdisciplinary scientific category was identified, and its essence was identified as a universal process that acquires specific forms, goals and priorities depending on the field of implementation. Practical value. A deep theoretical understanding of internationalization forms the basis for improving the practical mechanisms of its implementation at the local and national levels. Key words: internationalization, scientific category, conceptual essence, definition, public administration, education, business internationalization.

Synchronization of differential equations driven by linear multiplicative fractional Brownian motion

This paper is devoted to the synchronization of stochastic differential equations driven by the linear multiplicative fractional Brownian motion with Hurst parameter H∈(12,1). We use equivalent transformations to prove that the differential equation has a unique stationary solution, which generates a random dynamical system. Moreover, the system has the pathwise singleton set random attractor. We then establish the synchronization of the coupled differential equations and provide numerical simulation results. At the end, we discuss two specific noise forms and present the corresponding synchronization results.

Abstract B019: Assessing Circulating TumOur DNA as a prognostic biomarker in endometrial cancer (The CODEC Study)

Abstract Introduction/Background: Endometrial cancer (EC) is the most common gynecological cancer in the developing world. While significant progress has been made through molecular sub-classification, the treatment of EC for many women remains contentious and better biomarkers are required to guide therapy selection. Circulating tumor DNA (ctDNA) a ‘liquid biopsy’, involves collection of tumor specific DNA via a blood test and can quantify cancer burden and detect tumor specific genomic information. The CODEC study is a prospective pilot study to assess the utility of ctDNA as a prognostic biomarker in EC with the hope that it may help predict relapse and guide selection of adjuvant therapy. Methodology: Women with Type 2 EC planned for surgery and consenting to the collection of biospecimens were enrolled prior to surgery and followed prospectively. Blood was collected perioperatively and then every three months for up to two years and at relapse. Broad sequencing of participants’ tumors was performed, the results of which guided the design of personalized droplet digital PCR (ddPCR) assays for ctDNA analysis. ctDNA was extracted from 5ml of plasma and tested in quadruplicate. PET defined metabolic tumor volume was compared to ctDNA and analysis of ctDNA and relapse free survival (RFS) performed using a Cox proportional hazards regression model. Results: Somatic mutations to guide ddPCR analysis were detected in 45 enrolled women stages 1- 4 including pathogenic variants in POLE. ctDNA results are currently available for 30 participants (remaining results awaited). 12/30 participants had detectable ctDNA preoperatively and 5/25 at Time Point 3 (2-6 weeks post-surgery). ctDNA levels varied significantly across the cohort but results to date indicate that perioperative ctDNA positivity is associated with relapse. Interestingly in those that had detectable ctDNA preoperatively, the majority had a rise in ctDNA intraoperatively. Conclusion: This proof-of-concept analysis showed that ctDNA can successfully be detected in the perioperative setting and is the first study in EC to compare ctDNA with PET findings. Although testing is still underway, the early results indicate that ctDNA maybe a useful biomarker to predict relapse and guide the selection of adjuvant therapy. Citation Format: Rachel Delahunty, Rainier Arnolda, Thuan Tzen Koh, Michael Hofman, Hayley Johnston, Patricia Wojtowicz, Caitlyn Nguyen, Nicole Brooks, Kym Reid, Julie Lamont, Thomas Jobling, Deborah Neesham, Vanessa Obers, Clair Shadbolt, Brooke Sawyer, Paul Smith, Jennifer Ellis, Geradline Goss, Mila Volcheck, Madawa Jayawardana, Sandun Silva, Chelsee Hewitt, Kate Jones, Andrew Fellowes, Orla McNally, Stephen Wong, Elizabeth Christie, Costas Yannakou. Assessing Circulating TumOur DNA as a prognostic biomarker in endometrial cancer (The CODEC Study) [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr B019.

SirT7-mediated transcription of fascin in hyperglycemic glomerular endothelial cells contributes to EndMT in diabetic nephropathy.

Diabetic nephropathy (DN) is the main cause of end-stage renal disease worldwide. It is reported that the endothelial-to-mesenchymal transition (EndMT) in glomerular endothelial cells plays an important role in DN. As a specific form of epithelial-to-mesenchymal transition, EndMT may involve common regulators of epithelial-to-mesenchymal transition. Fascin has been shown to mediate epithelial-to-mesenchymal transition. In addition, SirT7 has been confir med to contribute to inflammation in hyperglycemic endothelial cells via the modulation of gene transcription. In this study, we speculate that SirT7 modulates fascin transcription and is thus involved in EndMT in hyperglycemic glomerular endothelial cells. Our data indicate that α-smooth muscle actin (α-SMA) and fascin levels are increased, while CD31 levels are decreased in the kidneys of DN rats. Consistently, our cellular experiments reveal that high glucose treatment elevates fascin levels and induces EndMT in human glomerular endothelial cells (HGECs). Moreover, silencing of fascin inhibits EndMT in hyperglycaemic HGECs. In addition, SirT7 is found to be decreased in hyperglycemic cells and in the kidneys of DN mice. Moreover, the inhibition of SirT7 increases fascin level and mediates EndMT. An increase in SirtT7 expression decreases fascin expression, inhibits EndMT, and improves renal function in hyperglycemic cells and DN mice. SirT7 is found to bind to the promoter region of fascin. In summary, the present study indicates that SirT7 transcribes fascin to contribute to hyperglycemia-induced EndMT in DN patients.

Evidence of Geopolitical Risk and Economic Policy Uncertainty on Equity Prices in Emerging Markets

This paper presents evidence of the impact of changes in downside risk , economic policy uncertainty ( ), the geopolitical risk ( ) in six Asian equity markets while controlling for COVIDE-19. Applying the month data for the period of 1990.01– 2021.12 to Asian markets, evidence shows that national stock returns are negatively correlated with and , suggesting that these risk/uncertainty factors harmfully affect stock markets. Evidence shows that a rise in U.S. geopolitical risk adversely spillovers to Asia stock markets. Spreads of COVID-19 damage local stock returns via interacting with changes in EPU and GPR. Purpose: Present evidence of COVIDE-19 and the impact of changes in downside risk , economic policy uncertainty ( ), the geopolitical risk ( ) with different forms of nonlinear specifications in six Asian equity markets. Design/methodology/approach: The rolling regression method is used to derive time-varying coefficients of investors’ response to changes of policy uncertainty, which is sensitive to react to other uncertainty variables. Findings: Evidence shows that national stock returns are negatively correlated with and , suggesting that these risk/uncertainty factors adversely affect local stock markets. In addition, the evidence shows that a rise in U.S. geopolitical risk ( ) can adversely spillover to domestic stock markets. A spillover effect is found from COVID_19 development. Research limitations/implications: The findings are based on data from six Asian markets. More data may be collected, which would expand the analysis to a broader coverage of the global market. Practical implications: Evidence suggests that in addition to the risk from financial markets, the geopolitical risk (GPR) and COVID-19 are important factors in determining whether a risk premium should be received. From a policymaker’s point of view, geopolitical stability is the foundation for maintaining financial market stability. Originality/value: This paper presents evidence on the time-varying behavior of investors’ response to In addition to and the , the nonlinear components of , U.S. and interaction to COVID-19 have a harmful effect on national stock prices in Asian markets.

A pilot study on childhood trauma and love addiction: Exploring the mediation of unbalanced family functioning.

The general aim of the present study was the exploration of the relationships between childhood trauma subdimensions (physical abuse, emotional abuse, sexual abuse, physical neglect, and emotional neglect), unbalanced family functioning patterns (disengaged, enmeshed, rigid, and chaotic), and love addiction. A sample of 910 individuals (76.6% female; Mage = 30 years, SD = 10.55) engaged in a romantic relationship participated in the research and completed the Love Addiction Inventory-Short Form, Family Adaptability and Cohesion Evaluation Scales-IV, and Childhood Trauma Questionnaire-Short Form. Among the childhood trauma subdimensions, emotional and physical abuse showed significant and positive associations with love addiction levels. Furthermore, the path analysis showed that unbalanced family functioning patterns parallelly mediated the relationship between emotional (enmeshed, rigid, and chaotic patterns) and physical abuse (chaotic patterns) and love addiction. Gender as a covariate was controlled for. The present study offers insight into the mechanisms by which specific forms of childhood trauma could lead to love addiction in adulthood. The findings offer valuable insights for developing customized interventions when working with individuals struggling with love addiction, as well as for implementing effective preventive activities for the condition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Adult Outcome After Partial Androgen Insensitivity Syndrome: Diagnosed and Assigned Female in Infancy.

This patient, now in her 40s, was evaluated because of genital ambiguity and diagnosed with pAIS in infancy based upon elevated testosterone and gonadotropin levels and significantly reduced binding affinity of the androgen receptor. Such reduced binding is consistent with a structural abnormality of the receptor protein precluding expected activity of the androgen receptor. Based on this information and counseling, her parents chose a female sex assignment. She had clitoral recession and testes removal as an infant and neovaginal surgery using a distal ileum segment at age 11 years and was begun on estrogen therapy at age 12 years. She is being reported now to point out that the data known at her birth provided as specific information to guide sex assignment and genital surgery as is currently available. More importantly, long-term outcome data is very positive showing clear female gender identity, successful marriage of more than 20 years, excellent social relationships including family and friends, an active social life. Since this diagnosis is lifelong, it is inevitable that there will be reminders, hopefully rare, that may be traumatizing. Unfortunately, in this patient, such reminders have been related to access to health care.

Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms.

Deep learning models have been shown to accurately predict protein structure from sequence, allowing researchers to explore protein space from the structural viewpoint. In this paper we explore whether "novel" features, such as distinct loop conformations can arise from these predictions despite not being present in the training data. Here we have used ABodyBuilder2, a deep learning antibody structure predictor, to predict the structures of ~1.5M paired antibody sequences. We examined the predicted structures of the canonical CDR loops and found that most of these predictions fall into the already described CDR canonical form structural space. We also found a small number of "new" canonical clusters composed of heterogeneous sequences united by a common sequence motif and loop conformation. Analysis of these novel clusters showed their origins to be either shapes seen in the training data at very low frequency or shapes seen at high frequency but at a shorter sequence length. To evaluate explicitly the ability of ABodyBuilder2 to extrapolate, we retrained several models whilst withholding all antibody structures of a specific CDR loop length or canonical form. These "starved" models showed evidence of generalisation across CDRs of different lengths, but they did not extrapolate to loop conformations which were highly distinct from those present in the training data. However, the models were able to accurately predict a canonical form even if only a very small number of examples of that shape were in the training data. Our results suggest that deep learning protein structure prediction methods are unable to make completely out-of-domain predictions for CDR loops. However, in our analysis we also found that even minimal amounts of data of a structural shape allow the method to recover its original predictive abilities. We have made the ~1.5 M predicted structures used in this study available to download at https://doi.org/10.5281/zenodo.10280181.

An adaptive h-refinement method for the boundary element fast multipole method for quasi-static electromagnetic modeling

Objective. In our recent work pertinent to modeling of brain stimulation and neurophysiological recordings, substantial modeling errors in the computed electric field and potential have sometimes been observed for standard multi-compartment head models. The goal of this study is to quantify those errors and, further, eliminate them through an adaptive mesh refinement (AMR) algorithm. The study concentrates on transcranial magnetic stimulation (TMS), transcranial electrical stimulation (TES), and electroencephalography (EEG) forward problems. Approach. We propose, describe, and systematically investigate an AMR method using the boundary element method with fast multipole acceleration (BEM-FMM) as the base numerical solver. The goal is to efficiently allocate additional unknowns to critical areas of the model, where they will best improve solution accuracy. The implemented AMR method’s accuracy improvement is measured on head models constructed from 16 Human Connectome Project subjects under problem classes of TES, TMS, and EEG. Errors are computed between three solutions: an initial non-adaptive solution, a solution found after applying AMR with a conservative refinement rate, and a ‘silver-standard’ solution found by subsequent 4:1 global refinement of the adaptively-refined model. Main results. Excellent agreement is shown between the adaptively-refined and silver-standard solutions for standard head models. AMR is found to be vital for accurate modeling of TES and EEG forward problems for standard models: an increase of less than 25% (on average) in number of mesh elements for these problems, efficiently allocated by AMR, exposes electric field/potential errors exceeding 60% (on average) in the solution for the unrefined models. Significance. This error has especially important implications for TES dosing prediction—where the stimulation strength plays a central role—and for EEG lead fields. Though the specific form of the AMR method described here is implemented for the BEM-FMM, we expect that AMR is applicable and even required for accurate electromagnetic simulations by other numerical modeling packages as well.

Virtual Tour Using Telepresence Robot and MQTT Protocol

We often face obstacles to visit certain places, facilities, and institutions. This was especially noticeable during the COVID-19 pandemic. In this period telepresence applications were of exceptional importance. They supported communications and provided social interactions, enriching our lives during isolation. In this paper, we propose a solution for telepresence using Padbot U1 robot and the MQTT protocol. The idea is to use this solution for virtual tours in museums, art galleries, historical sites, etc. We have developed two different applications. One is a client application used by the visitor, for controlling the robot remotely. The other application is for the mobile device (tablet) attached to the robot, which is used to enable telepresence and to forward control commands to the robot. By scanning the QR codes placed on the objects, visitors can also get specific information about each of objects. Communication between applications (sending commands and receiving information for objects) is realized with the MQTT protocol. For the developed solution, we also conducted experiments to evaluate some basic criteria for VTs.

Acromegaly, an Exceptional Cause of High-Grade Heart Blocks

Acromegaly is a rare disorder resulting from the excessive secretion of growth hormone (GH) and causing a specific form of cardiomyopathy. Until now, it has been widely recognized that individuals with acromegaly face an elevated risk of arrhythmias. However, high-grade atrioventricular blocks are a very rare complication of acromegaly. We report the clinical observation of a 75 years old acromegalic male presenting with high-grade atrioventricular block requiring permanent stimulation with a pacemaker.

SLAM Meets NeRF: A Survey of Implicit SLAM Methods

In recent years, Simultaneous Localization and Mapping (SLAM) systems have shown significant performance, accuracy, and efficiency gains, especially when Neural Radiance Fields (NeRFs) are implemented. NeRF-based SLAM in mapping aims to implicitly understand irregular environmental information using large-scale parameters of deep learning networks in a data-driven manner so that specific environmental information can be predicted from a given perspective. NeRF-based SLAM in tracking jointly optimizes camera pose and implicit scene network parameters through inverse rendering or combines VO and NeRF mapping to achieve real-time positioning and mapping. This paper firstly analyzes the current situation of NeRF and SLAM systems and then introduces the state-of-the-art in NeRF-based SLAM. In addition, datasets and system evaluation methods used by NeRF-based SLAM are introduced. In the end, current issues and future work are analyzed. Based on an investigation of 30 related research articles, this paper provides in-depth insight into the innovation of SLAM and NeRF methods and provides a useful reference for future research.

Cross-modality person re-identification based on intermediate modal generation

In the context of cross-modal person re-identification, researchers often employ methods that utilize visible modality information to generate both an ‘X’ modality and a grayscale modality, enhancing the accuracy of person re-identification models. A lightweight network causes the ‘X’ modality through self-supervised learning of labels from visible images. In contrast, the grayscale modality is obtained through simple linear accumulation of the three RGB color channels from visual images. It can be observed that both the ‘X’ modality and grayscale modality are derived from visible images, which fails to establish a connection between the visible and infrared modalities. Therefore, this paper proposes an intermediate modality generation module to produce intermediate modality representations dynamically. By combining information from the visible, infrared, and intermediate modalities, the model is encouraged to capture modality-invariant features with cross-modal consistency. This enables person of the same identity to exhibit similar feature representations across different modalities, thereby mitigating the impact of distribution differences between visible and infrared modalities. Additionally, to facilitate the learning of appropriate intermediate modality representations, a distribution migration strategy is introduced. It guides the intermediate modality to maintain the correct distance from the visible and infrared modalities by optimizing the weights of the loss functions, preventing inadequate feature learning caused by an excessive focus on specific modality information. Furthermore, a mixed augmentation approach is proposed to alleviate disparities among multiple modalities further. By randomly cropping and combining regions of visible (infrared) modality images with infrared (visible) modality images, the generalization ability of the model in heterogeneous modalities is enhanced. Extensive comparative experiments are conducted on the SYSU-MM01 and RegDB datasets, yielding mAP values of 57.2% and 85.82%, respectively. The superior mAP performance on the RegDB dataset compared to most existing methods validates the effectiveness of the proposed approach.

‘It Matters How They See You’: ‘Maternal Activation’ As a Strategy to Navigate Contradictory Discourses of Motherhood and Neoliberal Activism in the Welsh Homelessness System

Abstract Despite increasing attention to the importance of gender as an analytic to understanding neoliberal welfare reform, little attention has been paid to how motherhood operates to structure experiences. We propose the term ‘maternal activation’ to describe how homeless mothers as a group are subject to, and yet repurpose and resist, specific forms of social control characterising neoliberal paternalistic welfare structures. Drawing on a Critical Discourse Analysis of semi-structured interviews with fifty-four frontline homelessness workers, and eighteen homeless mothers, within the newly conditionalised Welsh homelessness system, we argue that homeless mothers have distinct experiences of neoliberal welfare governance. They navigate contradictory demands of attentive caregiving and economically engaged citizenship, amid devaluation of care created by a neoliberal emphasis on entrepreneurialism. However, performing intense motherhood offers strategic advantage for homeless mothers by enabling them to be read as ‘legible’. This highlights the utility of motherhood as a framework to understand welfare citizenship.

Hemochromatosis: Ferroptosis, ROS, Gut Microbiome, and Clinical Challenges with Alcohol as Confounding Variable.

Hemochromatosis represents clinically one of the most important genetic storage diseases of the liver caused by iron overload, which is to be differentiated from hepatic iron overload due to excessive iron release from erythrocytes in patients with genetic hemolytic disorders. This disorder is under recent mechanistic discussion regarding ferroptosis, reactive oxygen species (ROS), the gut microbiome, and alcohol abuse as a risk factor, which are all topics of this review article. Triggered by released intracellular free iron from ferritin via the autophagic process of ferritinophagy, ferroptosis is involved in hemochromatosis as a specific form of iron-dependent regulated cell death. This develops in the course of mitochondrial injury associated with additional iron accumulation, followed by excessive production of ROS and lipid peroxidation. A low fecal iron content during therapeutic iron depletion reduces colonic inflammation and oxidative stress. In clinical terms, iron is an essential trace element required for human health. Humans cannot synthesize iron and must take it up from iron-containing foods and beverages. Under physiological conditions, healthy individuals allow for iron homeostasis by restricting the extent of intestinal iron depending on realistic demand, avoiding uptake of iron in excess. For this condition, the human body has no chance to adequately compensate through removal. In patients with hemochromatosis, the molecular finetuning of intestinal iron uptake is set off due to mutations in the high-FE2+ (HFE) genes that lead to a lack of hepcidin or resistance on the part of ferroportin to hepcidin binding. This is the major mechanism for the increased iron stores in the body. Hepcidin is a liver-derived peptide, which impairs the release of iron from enterocytes and macrophages by interacting with ferroportin. As a result, iron accumulates in various organs including the liver, which is severely injured and causes the clinically important hemochromatosis. This diagnosis is difficult to establish due to uncharacteristic features. Among these are asthenia, joint pain, arthritis, chondrocalcinosis, diabetes mellitus, hypopituitarism, hypogonadotropic hypogonadism, and cardiopathy. Diagnosis is initially suspected by increased serum levels of ferritin, a non-specific parameter also elevated in inflammatory diseases that must be excluded to be on the safer diagnostic side. Diagnosis is facilitated if ferritin is combined with elevated fasting transferrin saturation, genetic testing, and family screening. Various diagnostic attempts were published as algorithms. However, none of these were based on evidence or quantitative results derived from scored key features as opposed to other known complex diseases. Among these are autoimmune hepatitis (AIH) or drug-induced liver injury (DILI). For both diseases, the scored diagnostic algorithms are used in line with artificial intelligence (AI) principles to ascertain the diagnosis. The first-line therapy of hemochromatosis involves regular and life-long phlebotomy to remove iron from the blood, which improves the prognosis and may prevent the development of end-stage liver disease such as cirrhosis and hepatocellular carcinoma. Liver transplantation is rarely performed, confined to acute liver failure. In conclusion, ferroptosis, ROS, the gut microbiome, and concomitant alcohol abuse play a major contributing role in the development and clinical course of genetic hemochromatosis, which requires early diagnosis and therapy initiation through phlebotomy as a first-line treatment.

Translating interdisciplinary knowledge for gender equity: Quantifying the impact of NSF ADVANCE

AbstractBackgroundInterdisciplinarity is often hailed as a necessity for tackling real‐world challenges. We examine the prevalence and impact of interdisciplinarity in the NSF ADVANCE program, which addresses gender equity in STEM.MethodsThrough a quantitative analysis of authorship, references, and citations in ADVANCE publications, we compare the interdisciplinarity of knowledge produced within the program to traditional disciplinary knowledge. We use Simpon's Diversity Index to test for differences across disciplines, and we use negative binomial regression to capture the potential influences of interdisciplinarity on the long‐term impact of ADVANCE publications.ResultsADVANCE publications exhibit higher levels of interdisciplinarity across three dimensions of knowledge integration, and cross‐disciplinary ties within ADVANCE successfully integrate social science knowledge into diverse disciplines. Additionally, the interdisciplinarity of publication references positively influences the impact of ADVANCE work, while the interdisciplinarity of authorship teams does not.ConclusionsThese findings emphasize the significance of interdisciplinarity in problem‐oriented knowledge production, indicating that specific forms of interdisciplinarity can lead to broader impact. By shedding light on the interplay between interdisciplinary approaches, disciplinary structures, and academic recognition, this article contributes to programmatic design to generate impactful problem‐solving knowledge that also adds to the academic community.