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Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably drive this patient-centered transformation in healthcare. Through the provision of various services, including diagnosis, personalized lifestyle recommendations, dynamic scheduling of follow-ups, and mental health support, the objective is to substantially augment patient health outcomes, all the while mitigating the workload burden on healthcare providers. The life-critical nature of healthcare applications necessitates establishing a unified and comprehensive set of evaluation metrics for conversational models. Existing evaluation metrics proposed for various generic large language models (LLMs) demonstrate a lack of comprehension regarding medical and health concepts and their significance in promoting patients’ well-being. Moreover, these metrics neglect pivotal user-centered aspects, including trust-building, ethics, personalization, empathy, user comprehension, and emotional support. The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare. Subsequently, we present a comprehensive set of evaluation metrics designed to thoroughly assess the performance of healthcare chatbots from an end-user perspective. These metrics encompass an evaluation of language processing abilities, impact on real-world clinical tasks, and effectiveness in user-interactive conversations. Finally, we engage in a discussion concerning the challenges associated with defining and implementing these metrics, with particular emphasis on confounding factors such as the target audience, evaluation methods, and prompt techniques involved in the evaluation process.

Developmental Coordination Disorder (DCD), also known as Dyspraxia, is an often overlooked or misdiagnosed disorder and little research exists on how it manifests among cognitively gifted children. The purpose of this study was to examine clinical profiles among 25 children diagnosed with DCD and identified as cognitively gifted to explore the twice exceptional profile of DCD among gifted children. We explore how DCD manifests among children with cognitive gifts, considerations for identification, and gifted education services.

Abstract Patients with high-grade glioma (HGG) have an extremely poor prognosis compounded by a lack of advancement in clinical care over the past few decades. Regardless of classification, most newly diagnosed patients receive the same treatment, radiation and temozolomide (RT/TMZ). We developed a functional precision oncology test that prospectively identifies individual patient’s response to this treatment regimen. Tumor tissues isolated from patients with newly diagnosed HGG enrolled in 3D PREDICT REGISTRY were evaluated for response to chemotherapeutic agents using the 3D Predict™ Glioma test. Patients receiving RT/TMZ were followed for 2 years. Clinical outcomes including imaging, assessments, and biomarker measurements were compared to patient matched test-predicted therapy response. Median survival between test-predicted temozolomide responders and test-predicted temozolomide non-responders revealed a statistically significant increase in progression-free survival when using the test to predict response across multiple subgroups including HGG (5.8 months), glioblastoma (4.7 months), and MGMT unmethylated glioblastoma (4.7 months). Overall survival was also positively separated across the subgroups at 7.6, 5.1, and 6.3 months respectively. The strong correlation of 3D Predict Glioma test results with clinical outcomes demonstrates that this functional test is prognostic in patients treated with RT/TMZ and supports aligning clinical treatment to test-predicted response across varying HGG subgroups.

Abstract To survive extreme desiccation, seeds enter a period of quiescence that can last millennia. Seed quiescence involves the accumulation of protective storage proteins and lipids through unknown adjustments in protein homeostasis (proteostasis). Here, we show that mutation of all six type–II metacaspase (MCA–II) proteases in Arabidopsis thaliana disturbs proteostasis in seeds. MCA–II mutant seeds fail to restrict the AAA ATPase CELL DIVISION CYCLE 48 (CDC48) at the endoplasmic reticulum to discard misfolded proteins, compromising seed storability. Endoplasmic reticulum (ER) localization of CDC48 relies on the MCA–IIs-dependent cleavage of PUX10 (ubiquitination regulatory X domain–containing 10), the adaptor protein responsible for titrating CDC48 to lipid droplets. PUX10 cleavage enables the shuttling of CDC48 between lipid droplets and the ER, providing an important regulatory mechanism sustaining spatiotemporal proteolysis, lipid droplet dynamics, and protein homeostasis. In turn, the removal of the PUX10 adaptor in MCA–II mutant seeds partially restores proteostasis, CDC48 localization, and lipid droplet dynamics prolonging seed lifespan. Taken together, we uncover a proteolytic module conferring seed longevity.

Background and objective: The tumor microenvironment (TME) in non–muscle-invasive bladder cancer (NMIBC) plays an important role in the anticancer response. We aimed to identify the prognostic biomarkers in the TME of patients with NMIBC for progression to ≥T2. Methods: From our institutional database, 40 patients with T1 high-risk NMIBC who progressed were pair matched for Club Urologico Español de Tratamiento Oncologico (CUETO) progression variables with 80 patients who never progressed despite longer follow-up. Progression was defined as ≥T2 or extravesical disease. Patients were treated at least with bacillus Calmette-Guérin (BCG) induction (five or more of six doses). Immunohistochemical (IHC) markers for the TME were used on tissue at first T1 diagnosis: CD8-PanCK, GZMB-CD8-FOXP3, CD163, PD-L1 SP142/SP263, fibroblast activation protein-α (FAP), and CK5-GATA3. Full tissue slides were annotated digitally. Relative marker area (IHC-positive area/total area) or density (IHC-positive cells per area; n/mm2) was calculated, differentiating between regions of interest (ROIs; T1, Ta, and carcinoma in situ) and between compartments (stromal, epithelial, and combined). Differences in IHC variables were assessed using the t test, for continuous variables using analysis of variance and comparisons of more than two groups using Tukey’s test. Conditional logistic regression for progression at 5-yr follow-up was performed with clusters based on pair matching. Key findings and limitations: Only FAP expression (increase per 50%) in T1 (odds ratio [OR]: 1.33; 95% confidence interval [CI]: 1.04–1.70) and all ROIs combined (OR: 1.62; 95% CI: 1.14–2.29) correlated significantly with progression. None of the other clinicopathological/IHC variables correlated with progression. Conclusions and clinical implications: FAP is a potential prognostic biomarker for progression in high-risk NMIBC. FAP is a marker for cancer-associated fibroblasts and is linked to immunosuppression and neoangiogenesis, which makes future investigation clinically relevant. Patient summary: We found that progression of high-risk non–muscle-invasive bladder cancer to muscle-invasive disease is less in patients with lower fibroblast activation protein-α (FAP) expression, which is a marker for cancer-associated fibroblasts.

Abstract Background European beech (Fagus sylvatica L.) trees produce seeds irregularly; therefore, it is necessary to store beech seeds for forestation. Despite the acquisition of desiccation tolerance during development, beech seeds are classified as intermediate because they lose viability during long-term storage faster than typical orthodox seeds. In this study, beech seeds stored for short (3 years) or long (20 years) periods under optimal conditions and displaying 92 and 30% germination capacity, respectively, were compared. Results Aged seeds displayed increased membrane damage, manifested as electrolyte leakage and lipid peroxidation levels. Analyses have been based on embryonic axes, which contained higher levels of reactive oxygen species (ROS) and higher levels of protein-bound methionine sulfoxide (MetO) in aged seeds. Using label-free quantitative proteomics, 3,949 proteins were identified, of which 2,442 were reliably quantified pointing to 24 more abundant proteins and 35 less abundant proteins in beech seeds under long-term storage conditions. Functional analyses based on gene ontology annotations revealed that nucleic acid binding activity (molecular function), ribosome organization or biogenesis and transmembrane transport (cellular processes), translational proteins (protein class) and membranous anatomical entities (cellular compartment) were affected in aged seeds. To verify whether MetO, the oxidative posttranslational modification of proteins that can be reversed via the action of methionine sulfoxide reductase (Msr) enzymes, is involved in the aging of beech seeds, we identified and quantified 226 MetO-containing proteins, among which 9 and 19 exhibited significantly up- and downregulated MetO levels, respectively, in beech seeds under long-term storage conditions. Several Msr isoforms were identified and recognized as MsrA1-like, MsrA4, MsrB5 and MsrB5-like in beech seeds. Only MsrA1-like displayed decreased abundance in aged seeds. Conclusions We demonstrated that the loss of membrane integrity reflected in the elevated abundance of membrane proteins had a higher impact on seed aging progress than the MetO/Msr system. Proteome analyses enabled us to propose protein Sec61 and glyceraldehyde-3-phosphate dehydrogenase as potential longevity modulators in beech seeds.

Abstract Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing multimodal data using unsupervised and supervised sparse linear methods in a COVID-19 patient cohort. This prospective cohort study of 149 adult patients was conducted in a tertiary care academic center. First, we used sparse canonical correlation analysis (CCA) to identify and quantify relationships across different data modalities, including viral genome sequencing, imaging, clinical data, and laboratory results. Then, we used cooperative learning to predict the clinical outcome of COVID-19 patients: Intensive care unit admission. We show that serum biomarkers representing severe disease and acute phase response correlate with original and wavelet radiomics features in the LLL frequency channel (cor(Xu 1, Zv 1) = 0.596, p value

BackgroundThe incidence of oropharyngeal cancer (OPC) is increasing, due mainly to a rise in Human Papilloma Virus (HPV)-mediated disease. HPV-mediated OPC has significantly better prognosis compared with HPV-negative OPC, stimulating interest in treatment de-intensification approaches to reduce long-term sequelae. Routine clinical testing frequently utilises immunohistochemistry to detect upregulation of p16 as a surrogate marker of HPV-mediation. However, this does not detect discordant p16-/HPV+ cases and incorrectly assigns p16+/HPV- cases, which, given their inferior prognosis compared to p16+/HPV+, may have important clinical implications. The biology underlying poorer prognosis of p16/HPV discordant OPC requires exploration.MethodsGeoMx digital spatial profiling was used to compare the expression patterns of selected immuno-oncology-related genes/gene families (n=73) within the tumour and stromal compartments of formalin-fixed, paraffin-embedded OPC tumour tissues (n=12) representing the three subgroups, p16+/HPV+, p16+/HPV- and p16-/HPV-.ResultsKeratin (multi KRT) and HIF1A, a key regulator of hypoxia adaptation, were upregulated in both p16+/HPV- and p16-/HPV- tumours relative to p16+/HPV+. Several genes associated with tumour cell proliferation and survival (CCND1, AKT1 and CD44) were more highly expressed in p16-/HPV- tumours relative to p16+/HPV+. Conversely, multiple genes with potential roles in anti-tumour immune responses (immune cell recruitment/trafficking, antigen processing and presentation), such as CXCL9, CXCL10, ITGB2, PSMB10, CD74, HLA-DRB and B2M, were more highly expressed in the tumour and stromal compartments of p16+/HPV+ OPC versus p16-/HPV- and p16+/HPV-. CXCL9 was the only gene showing significant differential expression between p16+/HPV- and p16-/HPV- tumours being upregulated within the stromal compartment of the former.ConclusionsIn terms of immune-oncology-related gene expression, discordant p16+/HPV- OPCs are much more closely aligned with p16-/HPV-OPCs and quite distinct from p16+/HPV+ tumours. This is consistent with previously described prognostic patterns (p16+/HPV+ >> p16+/HPV- > p16-/HPV-) and underlines the need for dual p16 and HPV testing to guide clinical decision making.

Background Half of patients with heart failure with preserved ejection fraction (HFpEF) remain undiagnosed by resting evaluation alone. Therefore, exercise testing is proposed. The diastolic stress test (DST), however, has limited sensitivity. We aimed to determine the clinical significance of adding the mean pulmonary artery pressure over cardiac output (mPAP/CO) slope to the DST in suspected HFpEF. Methods and Results In this prospective cohort study, consecutive patients (n=1936) with suspected HFpEF underwent exercise echocardiography with simultaneous respiratory gas analysis. These patients were stratified by exercise E over e′ (exE/e′) and mPAP/CO slope, and peak oxygen uptake, natriuretic peptides (NT‐proBNP [N‐terminal pro‐B‐type natriuretic peptide]), and score‐based HFpEF likelihood were compared. Twenty‐two percent of patients (n=428) had exE/e′3 mm Hg/L per min, 24% (n=464) had a positive DST (exE/e′≥15), and 54% (n=1044) had a normal DST and slope. Percentage of predicted oxygen uptake was similar in the group with exE/e′3 mm Hg/L per min despite a negative DST. These patients had HFpEF characteristics and a peak oxygen uptake as low as patients with a positive DST. Therefore, an elevated mPAP/CO slope might indicate HFpEF irrespective of the DST result.

Abstract Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably drive this patient-centered transformation in healthcare. Through the provision of various services, including diagnosis, personalized lifestyle recommendations, dynamic scheduling of follow-ups, and mental health support, the objective is to substantially augment patient health outcomes, all the while mitigating the workload burden on healthcare providers. The life-critical nature of healthcare applications necessitates establishing a unified and comprehensive set of evaluation metrics for conversational models. Existing evaluation metrics proposed for various generic large language models (LLMs) demonstrate a lack of comprehension regarding medical and health concepts and their significance in promoting patients’ well-being. Moreover, these metrics neglect pivotal user-centered aspects, including trust-building, ethics, personalization, empathy, user comprehension, and emotional support. The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare. Subsequently, we present a comprehensive set of evaluation metrics designed to thoroughly assess the performance of healthcare chatbots from an end-user perspective. These metrics encompass an evaluation of language processing abilities, impact on real-world clinical tasks, and effectiveness in user-interactive conversations. Finally, we engage in a discussion concerning the challenges associated with defining and implementing these metrics, with particular emphasis on confounding factors such as the target audience, evaluation methods, and prompt techniques involved in the evaluation process.

The presence of biases has been demonstrated in a wide range of machine learning applications; however, it is not yet widespread in the case of geospatial datasets. This study illustrates the importance of auditing geospatial datasets for biases, with a particular focus on disaster risk management applications, as a lack of local data may direct humanitarian actors to utilize global building datasets to estimate damage and the distribution of aid efforts. It is important to ensure that there are no biases against the representation of vulnerable populations and that they are not missed in the distribution of aid. This manuscript audits four global building datasets [Google Open Buildings, Microsoft Bing Maps Building Footprints, Overture Maps Foundation (OMF), and OpenStreetMap (OSM)] for biases regarding the relative wealth index (RWI), population density, urban/rural proportions, and building size in Tanzania and the Philippines. The dataset accuracies for these two countries are lower than expected. Google Open Buildings (with a confidence above 0.7) and OSM demonstrated the best combinations of false negative and false discovery, though Google Open Buildings was more consistent across tiles. The equality of opportunity was lowest for the urban/rural proportions, whereas the OSM and OMF displayed particularly low equality of opportunity for population density and RWI in Tanzania. These results demonstrate that biases exist in these geospatial datasets. The types of biases are not consistent across the datasets and the two study areas, which emphasizes the importance of auditing these datasets for biases in new applications and study areas.

ABSTRACTPlants express an array of receptor-like kinases (RLKs) to control development and communicate with their environment. Many RLKs are uncharacterized and some of them are expected to regulate plant responses to plant growth-promoting rhizobacteria (PGPR). Despite documented effects induced by Caulobacter RHG1, the underlying signaling pathways and the involved RLKs remain uncharted. Through a targeted RLK mutant screening, we aimed to decipher the receptors that steer the Caulobacter RHG1-induced growth promotion in Arabidopsis thaliana. We identified four RLKs that are pivotal in the RHG1-Arabidopsis interaction, including the coreceptors SOMATIC EMBRYOGENESIS RECEPTOR-LIKE KINASE 1 (SERK1) and BRASSINOSTEROID INSENSITIVE 1-ASSOCIATED KINASE 1 (BAK1/SERK3), which act redundantly in the RHG1-Arabidopsis interaction, possibly by interplaying with the unknown RLK AT3G28040 and the immunity-related ELONGATION FACTOR-TU RECEPTOR (EFR). These results shed new light on the molecular dynamics orchestrating plant responses to PGPR, and concurrently contribute a crucial piece to the intricate puzzle of RLK interactions.Key policy highlights Four RLKs; BAK1, SERK1, EFR, and AT3G28040 (RRHG) are involved in the RHG1-Arabidopsis interaction.BAK1 and SERK1, two well-described co-receptors, act redundantly and play a pivotal role in the RHG1-driven growth promotion, possibly by interplaying with the unknown RLK AT3G28040 and the immunity-related RLK EFR.Most known development – and immunity-related RLKs barely influence RHG1-driven plant growth promotion in Arabidopsis.

Abstract Background Chronic rhinosinusitis (CRS) is a heterogeneous disorder with a wide range of validated subjective and objective assessment tools to assess disease severity. However, a comprehensive and easy‐to‐use tool that integrates these measures for determining disease severity and response to treatment is still obscure. The objective of this study was to develop a standardized assessment tool that facilitates diagnosis, uniform patient monitoring, and comparison of treatment outcomes between different centers both in routine clinical practice and in research. Methods To develop this tool, published literature on assessment tools was searched on various databases. A panel of 12 steering committee members conducted an advisory board meeting to review the findings. Specific outcome measures to be included in a comprehensive assessment tool and follow‐up sheet were then collated following consensus approval from the panel. The tool was further validated for content and revised with expert recommendations to arrive at the finalized Nasal Polyp Patient Assessment Scoring Sheet (N‐PASS) tool. Results The N‐PASS tool was developed by integrating the subjective and objective measures for CRS assessment. Based on expert opinions, N‐PASS was revised to be used as an easy‐to‐use guidance tool that captures patient‐reported and physician‐assessed components for comprehensively assessing disease status and response to treatment. Conclusion The N‐PASS tool can be used to aid in the diagnosis and management of CRS cases with nasal polyps. The tool would also aid in improved monitoring of patients and pave the way for an international disease registry. Level of evidence Oxford Level 3.

Little is known either about either physical activity patterns, or other lifestyle-related prevention measures in heart transplantation (HTx) recipients. The history of HTx started more than 50 years ago but there are still no guidelines or position papers highlighting the features of prevention and rehabilitation after HTx. The aims of this scientific statement are (i) to explain the importance of prevention and rehabilitation after HTx, and (ii) to promote the factors (modifiable/non-modifiable) that should be addressed after HTx to improve patients’ physical capacity, quality of life and survival. All HTx team members have their role to play in the care of these patients and multidisciplinary prevention and rehabilitation programmes designed for transplant recipients. HTx recipients are clearly not healthy disease-free subjects yet they also significantly differ from heart failure patients or those who are supported with mechanical circulatory support. Therefore, prevention and rehabilitation after HTx both need to be specifically tailored to this patient population and be multidisciplinary in nature. Prevention and rehabilitation programmes should be initiated early after HTx and continued during the entire post-transplant journey. This clinical consensus statement focuses on the importance and the characteristics of prevention and rehabilitation designed for HTx recipients.

AimsMiR-181c-5p overexpression associates with heart failure (HF) and cardiac damage, but the underlying pathophysiology remains unclear. This study investigated the effect of miR-181c-5p inhibition on cardiac function and fibrosis in a rodent model of diastolic dysfunction, and evaluated additional effects on kidney as relevant comorbid organ.Methods and resultsDiastolic dysfunction was induced in male C57/BL6J mice (n = 20) by combining high-fat diet, L-NG-nitroarginine methyl ester, and angiotensin II administration, and was compared to sham controls (n = 18). Mice were randomized to subcutaneous miR-181c-5p antagomiR (INH) or scrambled antagomiR injections (40 mg/kg/week). HF mice demonstrated diastolic dysfunction and increased fibrosis, which was attenuated by INH treatment. Remarkably, HF + INH animals had a threefold higher mortality rate (60%) compared to HF controls (20%). Histological examination revealed increased glomerular damage in all INH treated mice, and signs of thrombotic microangiopathy (TMA) in mice who died prematurely. Quantitative polymerase chain reaction demonstrated a miR-181c-5p-related downregulation of cardiac but not renal Tgfbr1 in HF + INH mice, while INH treatment reduced renal but not cardiac Vegfa expression in all mice.ConclusionThis study demonstrates cardiac anti-fibrotic effects of miR-181c-5p inhibition in a rodent HF model through targeting of Tgfbr1 in the heart. Despite improved diastolic function, HF + INH mice had higher mortality due to increased predisposition for TMA, increased renal fibrosis and glomerular damage, associated with Vegfa downregulation in kidneys.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is predominantly a type 2 inflammatory disease associated with type 2 (T2) cell responses and epithelial barrier, mucociliary, and olfactory dysfunction. The inflammatory cytokines interleukin (IL)-4, IL-13, and IL-5 are key mediators driving and perpetuating type 2 inflammation. The inflammatory responses driven by these cytokines include the recruitment and activation of eosinophils, basophils, mast cells, goblet cells, M2 macrophages, and B cells. The activation of these immune cells results in a range of pathologic effects including immunoglobulin E production, an increase in the number of smooth muscle cells within the nasal mucosa and a reduction in their contractility, increased deposition of fibrinogen, mucus hyperproduction, and local edema. The cytokine-driven structural changes include nasal polyp formation and nasal epithelial tissue remodeling, which perpetuate barrier dysfunction. Type 2 inflammation may also alter the availability or function of olfactory sensory neurons contributing to loss of sense of smell. Targeting these key cytokine pathways has emerged as an effective approach for the treatment of type 2 inflammatory airway diseases, and a number of biologic agents are now available or in development for CRSwNP. In this review, we provide an overview of the inflammatory pathways involved in CRSwNP and describe how targeting key drivers of type 2 inflammation is an effective therapeutic option for patients.

Abstract Transglutaminase 1 (TGM1) plays an essential role in skin barrier formation by cross-linking proteins in differentiated keratinocytes. Here, we established a protocol for the antibody-dependent detection of TGM1 protein and the parallel detection of TGM activity. TGM1 immunoreactivity initially increased and co-localized with membrane-associated TGM activity during keratinocyte differentiation. TGM activity persisted upon further differentiation of keratinocytes, whereas TGM1 immunoreactivity was lost under standard assay conditions. Pretreatment of tissue sections with the proteases trypsin or proteinase K enabled immunodetection of TGM1 in cornified keratinocytes, indicating that removal of other proteins was a prerequisite for TGM1 immunolabeling after cornification. The increase of TGM activity and subsequent loss of TGM1 immunoreactivity could be replicated in HEK293T cells transfected with TGM1, suggesting that protein cross-linking mediated by TGM1 itself may lead to reduced recognition of TGM1 by antibodies. To screen for proteins potentially regulating TGM1, we performed Virotrap experiments and identified the CAPNS1 subunit of calpain as an interaction partner of TGM1. Treatment of keratinocytes and TGM1-transfected HEK293T cells with chemical inhibitors of calpain suppressed transglutamination. Our findings suggest that calpain contributes to the control of TGM1-mediated transglutamination and proteins cross-linked by transglutamination mask epitopes of TGM1.

Abstract Aims Diagnosis of heart failure with preserved ejection fraction (HFpEF) can be challenging. This study aimed to evaluate the potential of a webtool to enhance the scoring accuracy when applying the complex HFA‐PEFF and H2FPEF algorithms, which are commonly used for diagnosing HFpEF. Methods and results We developed an online tool, the HFpEF calculator, that enables the automatic calculation of current HFpEF algorithms. We assessed the accuracy of manual vs. automatic scoring, defined as the percentage of correct scores, in a cohort of cardiologists with varying clinical experience. Cardiologists scored eight online clinical cases using a triple cross‐over design (i.e. two manual–two automatic–two manual–two automatic). Data were analysed in study completers (n = 55, 29% heart failure specialists, 42% general cardiologists, and 29% cardiology residents). Manually calculated scores were correct in 50% (HFA‐PEFF: 50% [50–75]; H2FPEF: 50% [38–50]). Correct scoring improved to 100% using the HFpEF calculator (HFA‐PEFF: 100% [88–100], P

The concept of Digital Earth (DE) was formalized by Al Gore in 1998. At that time the technologies needed for its implementation were in an embryonic stage and the concept was quite visionary. Since then digital technologies have progressed significantly and their speed and pervasiveness have generated and are still causing the digital transformation of our society. This creates new opportunities and challenges for the realization of DE. ‘What is DE today?’, ‘What could DE be in the future?’, and ‘What is needed to make DE a reality?’. To answer these questions it is necessary to examine DE considering all the technological, scientific, social, and economic aspects, but also bearing in mind the principles that inspired its formulation. By understanding the lessons learned from the past, it becomes possible to identify the remaining scientific and technological challenges, and the actions needed to achieve the ultimate goal of a ‘Digital Earth for all’. This article reviews the evolution of the DE vision and its multiple definitions, illustrates what has been achieved so far, explains the impact of digital transformation, illustrates the new vision, and concludes with possible future scenarios and recommended actions to facilitate full DE implementation.

Abstract Patients experiencing mental health crises often seek help through messaging-based platforms, but may face long wait times due to limited message triage capacity. Here we build and deploy a machine-learning-enabled system to improve response times to crisis messages in a large, national telehealth provider network. We train a two-stage natural language processing (NLP) system with key word filtering followed by logistic regression on 721 electronic medical record chat messages, of which 32% are potential crises (suicidal/homicidal ideation, domestic violence, or non-suicidal self-injury). Model performance is evaluated on a retrospective test set (4/1/21–4/1/22, N = 481) and a prospective test set (10/1/22–10/31/22, N = 102,471). In the retrospective test set, the model has an AUC of 0.82 (95% CI: 0.78–0.86), sensitivity of 0.99 (95% CI: 0.96–1.00), and PPV of 0.35 (95% CI: 0.309–0.4). In the prospective test set, the model has an AUC of 0.98 (95% CI: 0.966–0.984), sensitivity of 0.98 (95% CI: 0.96–0.99), and PPV of 0.66 (95% CI: 0.626–0.692). The daily median time from message receipt to crisis specialist triage ranges from 8 to 13 min, compared to 9 h before the deployment of the system. We demonstrate that a NLP-based machine learning model can reliably identify potential crisis chat messages in a telehealth setting. Our system integrates into existing clinical workflows, suggesting that with appropriate training, humans can successfully leverage ML systems to facilitate triage of crisis messages.

Abstract Background The prognosis for patients with head and neck cancer (HNC) is poor and has improved little in recent decades, partially due to lack of therapeutic options. To identify effective therapeutic targets, we sought to identify molecular pathways that drive metastasis and HNC progression, through large-scale systematic analyses of transcriptomic data. Methods We performed meta-analysis across 29 gene expression studies including 2074 primary HNC biopsies to identify genes and transcriptional pathways associated with survival and lymph node metastasis (LNM). To understand the biological roles of these genes in HNC, we identified their associated cancer pathways, as well as the cell types that express them within HNC tumor microenvironments, by integrating single-cell RNA-seq and bulk RNA-seq from sorted cell populations. Results Patient survival-associated genes were heterogenous and included drivers of diverse tumor biological processes: these included tumor-intrinsic processes such as epithelial dedifferentiation and epithelial to mesenchymal transition, as well as tumor microenvironmental factors such as T cell-mediated immunity and cancer-associated fibroblast activity. Unexpectedly, LNM-associated genes were almost universally associated with epithelial dedifferentiation within malignant cells. Genes negatively associated with LNM consisted of regulators of squamous epithelial differentiation that are expressed within well-differentiated malignant cells, while those positively associated with LNM represented cell cycle regulators that are normally repressed by the p53-DREAM pathway. These pro-LNM genes are overexpressed in proliferating malignant cells of TP53 mutated and HPV + ve HNCs and are strongly associated with stemness, suggesting that they represent markers of pre-metastatic cancer stem-like cells. LNM-associated genes are deregulated in high-grade oral precancerous lesions, and deregulated further in primary HNCs with advancing tumor grade and deregulated further still in lymph node metastases. Conclusions In HNC, patient survival is affected by multiple biological processes and is strongly influenced by the tumor immune and stromal microenvironments. In contrast, LNM appears to be driven primarily by malignant cell plasticity, characterized by epithelial dedifferentiation coupled with EMT-independent proliferation and stemness. Our findings postulate that LNM is initially caused by loss of p53-DREAM-mediated repression of cell cycle genes during early tumorigenesis.

Abstract Public proteomics data often lack essential metadata, limiting its potential. To address this, we present lesSDRF, a tool to simplify the process of metadata annotation, thereby ensuring that data leave a lasting, impactful legacy well beyond its initial publication.

Abstract Most eukaryotic proteins are N-terminally acetylated, but the functional impact on a global scale has remained obscure. Using genome-wide CRISPR knockout screens in human cells, we reveal a strong genetic dependency between a major N-terminal acetyltransferase and specific ubiquitin ligases. Biochemical analyses uncover that both the ubiquitin ligase complex UBR4-KCMF1 and the acetyltransferase NatC recognize proteins bearing an unacetylated N-terminal methionine followed by a hydrophobic residue. NatC KO-induced protein degradation and phenotypes are reversed by UBR knockdown, demonstrating the central cellular role of this interplay. We reveal that loss of Drosophila NatC is associated with male sterility, reduced longevity, and age-dependent loss of motility due to developmental muscle defects. Remarkably, muscle-specific overexpression of UbcE2M, one of the proteins targeted for NatC KO-mediated degradation, suppresses defects of NatC deletion. In conclusion, NatC-mediated N-terminal acetylation acts as a protective mechanism against protein degradation, which is relevant for increased longevity and motility.

Abstract Background Long-term drug evaluation heavily relies upon rodent models. Drug discovery methods to reduce animal models in oncology may include three-dimensional (3D) cellular systems that take into account tumor microenvironment (TME) cell types and biomechanical properties. Methods In this study we reconstructed a 3D tumor using an elastic polymer (acrylate-endcapped urethane-based poly(ethylene glycol) (AUPPEG)) with clinical relevant stiffness. Single cell suspensions from low-grade serous ovarian cancer (LGSOC) patient-derived early passage cultures of cancer cells and cancer-associated fibroblasts (CAF) embedded in a collagen gel were introduced to the AUPPEG scaffold. After self-organization in to a 3D tumor, this model was evaluated by a long-term (> 40 days) exposure to a drug combination of MEK and HSP90 inhibitors. The drug-response results from this long-term in vitro model are compared with drug responses in an orthotopic LGSOC xenograft mouse model. Results The in vitro 3D scaffold LGSOC model mimics the growth ratio and spatial organization of the LGSOC. The AUPPEG scaffold approach allows to test new targeted treatments and monitor long-term drug responses. The results correlate with those of the orthotopic LGSOC xenograft mouse model. Conclusions The mechanically-tunable scaffolds colonized by a three-dimensional LGSOC allow long-term drug evaluation and can be considered as a valid alternative to reduce, replace and refine animal models in drug discovery. Graphical Abstract