Structure and supramolecular organization of the canine distemper virus attachment glycoprotein.

Canine distemper virus (CDV) is an enveloped RNA morbillivirus that triggers respiratory, enteric, and high incidence of severe neurological disorders. CDV induces devastating outbreaks in wild and endangered animals as well as in domestic dogs in countries associated with suboptimal vaccination programs. The receptor-binding tetrameric attachment (H)-protein is part of the morbilliviral cell entry machinery. Here, we present the cryo-electron microscopy (cryo-EM) structure and supramolecular organization of the tetrameric CDV H-protein ectodomain. The structure reveals that the morbilliviral H-protein is composed of three main domains: stalk, neck, and heads. The most unexpected feature was the inherent asymmetric architecture of the CDV H-tetramer being shaped by the neck, which folds into an almost 90° bent conformation with respect to the stalk. Consequently, two non-contacting receptor-binding H-head dimers, which are also tilted toward each other, are located on one side of an intertwined four helical bundle stalk domain. Positioning of the four protomer polypeptide chains within the neck domain is guided by a glycine residue (G158), which forms a hinge point exclusively in two protomer polypeptide chains. Molecular dynamics simulations validated the stability of the asymmetric structure under near physiological conditions and molecular docking showed that two receptor-binding sites are fully accessible. Thus, this spatial organization of the CDV H-tetramer would allow for concomitant protein interactions with the stalk and head domains without steric clashes. In summary, the structure of the CDV H-protein ectodomain provides new insights into the morbilliviral cell entry system and offers a blueprint for next-generation structure-based antiviral drug discovery.

SLC16 Family: From Atomic Structure to Human Disease.

The solute carrier 16 (SLC16) family represents a diverse group of membrane proteins mediating the transport of monocarboxylates across biological membranes. Family members show a variety of functional roles ranging from nutrient transport and intracellular pH regulation to thyroid hormone homeostasis. Changes in the expression levels and transport function of certain SLC16 transporters are manifested in severe health disorders including cancer, diabetes, and neurological disorders. L-Lactate-transporting SLC16 family members play essential roles in the metabolism of certain tumors and became validated drug targets. This review illuminates the SLC16 family under a new light using structural information obtained from a SLC16 homolog. Furthermore, the role of these transporters in cancer metabolism and how their inhibition can contribute to anticancer therapy are discussed.

Comparison of pulmonary and small airways function between idiopathic inflammatory myopathies patients with and without interstitial lung disease.

OBJECTIVES: To evaluate pulmonary and small airway function in patients with idiopathic inflammatory myopathies (IIM) and make comparisons between patients with and without interstitial lung disease (ILD). METHODS: Newly diagnosed IIM patients with and without ILD determined by high resolution computed tomography were included in the study. Pulmonary and small airway function was assessed by spirometry, diffusing capacity for carbon monoxide (DLCO), body plethysmography, single and multiple breath nitrogen washout, impulse oscillometry and measurement of respiratory resistance by the interrupter technique (Rint) using the Q-box system. We used discrepancies between lung volumes measured by multiple breath nitrogen washout and body plethysmography to evaluate for small airway dysfunction. RESULTS: Study cohort comprised of 26 IIM patients, 13 with and 13 without ILD. IIM-ILD patients presented more frequently with dyspnoea, fever, arthralgias and positive anti-synthetase antibodies, compared to IIM patients without ILD. Classic spirometric parameters and most lung physiology parameters assessing small airway function did not differ between the two groups. Predicted total lung capacity and residual volume (TLCN2WO, RVN2WO) measured by multiple breath nitrogen washout and the TLCN2WO/TLCpleth ratio were significantly lower in IIM-ILD patients compared to those without ILD (mean: 111.1% vs. 153.4%, p=0.034, median: 171% vs. 210%, p=0.039 and median: 1.28 vs. 1.45, p=0.039, respectively). Rint tended to be higher among IIM-ILD patients (mean:100.5% vs. 76.6%, p=0.053). CONCLUSIONS: Discrepancies between lung volumes measured by multiple breath nitrogen washout and body plethysmography in IIM-ILD patients indicate an early small airways dysfunction in these patients.

Synthetic Biology: Bottom-Up Assembly of Molecular Systems.

The bottom-up assembly of biological and chemical components opens exciting opportunities to engineer artificial vesicular systems for applications with previously unmet requirements. The modular combination of scaffolds and functional building blocks enables the engineering of complex systems with biomimetic or new-to-nature functionalities. Inspired by the compartmentalized organization of cells and organelles, lipid or polymer vesicles are widely used as model membrane systems to investigate the translocation of solutes and the transduction of signals by membrane proteins. The bottom-up assembly and functionalization of such artificial compartments enables full control over their composition and can thus provide specifically optimized environments for synthetic biological processes. This review aims to inspire future endeavors by providing a diverse toolbox of molecular modules, engineering methodologies, and different approaches to assemble artificial vesicular systems. Important technical and practical aspects are addressed and selected applications are presented, highlighting particular achievements and limitations of the bottom-up approach. Complementing the cutting-edge technological achievements, fundamental aspects are also discussed to cater to the inherently diverse background of the target audience, which results from the interdisciplinary nature of synthetic biology. The engineering of proteins as functional modules and the use of lipids and block copolymers as scaffold modules for the assembly of functionalized vesicular systems are explored in detail. Particular emphasis is placed on ensuring the controlled assembly of these components into increasingly complex vesicular systems. Finally, all descriptions are presented in the greater context of engineering valuable synthetic biological systems for applications in biocatalysis, biosensing, bioremediation, or targeted drug delivery.

Structural and biochemical insights into His-tag-induced higher-order oligomerization of membrane proteins by cryo-EM and size exclusion chromatography.

Structural and functional characterization of proteins as well as the design of targeted drugs heavily rely on recombinant protein expression and purification. The polyhistidine-tag (His-tag) is among the most prominent examples of affinity tags used for the isolation of recombinant proteins from their expression hosts. Short peptide tags are commonly considered not to interfere with the structure of the tagged protein and tag removal is frequently neglected. This study demonstrates the formation of higher-order oligomers based on the example of two His-tagged membrane proteins, the dimeric arginine-agmatine antiporter AdiC and the pentameric light-driven proton pump proteorhodopsin. Size exclusion chromatography revealed the formation of tetrameric AdiC and decameric as well as pentadecameric proteorhodopsin through specific interactions between their His-tags. In addition, single particle cryo-electron microscopy (cryo-EM) allowed structural insights into the three-dimensional arrangement of the higher-order oligomers and the underlying His-tag-mediated interactions. These results reinforce the importance of considering the length and removal of affinity purification tags and illustrate how neglect can lead to potential interference with downstream biophysical or biochemical characterization of the target protein.

Predicting lymphoma in Sjögren's syndrome and the pathogenetic role of parotid microenvironment through precise parotid swelling recording.

OBJECTIVE: Parotid swelling (PSW) is a major predictor of non-Hodgkin's lymphoma (NHL) in primary SS (pSS). However, since detailed information on the time of onset and duration of PSW is scarce, this was investigated to verify whether it may lead to further improved prediction. NHL localization was concomitantly studied to evaluate the role of the parotid gland microenvironment in pSS-related lymphomagenesis. METHODS: A multicentre study was conducted among patients with pSS who developed B cell NHL during follow-up and matched controls that did not develop NHL. The study focused on the history of salivary gland and lachrymal gland swelling, evaluated in detail at different times and for different durations, and on the localization of NHL at onset. RESULTS: PSW was significantly more frequent among the cases: at the time of first referred pSS symptoms before diagnosis, at diagnosis and from pSS diagnosis to NHL. The duration of PSW was evaluated starting from pSS diagnosis, and the NHL risk increased from PSW of 2-12 months to >12 months. NHL was prevalently localized in the parotid glands of the cases. CONCLUSION: A more precise clinical recording of PSW can improve lymphoma prediction in pSS. PSW as a very early symptom is a predictor, and a longer duration of PSW is associated with a higher risk of NHL. Since lymphoma usually localizes in the parotid glands, and not in the other salivary or lachrymal glands, the parotid microenvironment appears to be involved in the whole history of pSS and related lymphomagenesis.

Incidence of autoantibodies related to systemic autoimmunity in patients with severe COVID-19 admitted to the intensive care unit.

OBJECTIVES: To assess the prevalence of autoantibodies (AAbs) in mechanically ventilated COVID-19 patients and to investigate whether AAbs influence the clinical outcome. METHODS: Serum samples were drawn within the first 48 hours upon admission to the intensive care unit (ICU) from 217 consecutive patients, from January 1st, 2021, to May 10th, 2021, and investigated for the presence of AAbs using conventional techniques. Serum samples (n=117) of age- and sex-matched healthy individuals collected before COVID-19 pandemic were used as controls. RESULTS: COVID-19 patients in the ICU had more commonly AAbs compared to age- and sex-matched controls (174/217, 80.2% vs. 73/117, 62.4%, p<0.001). Patients expressed more frequently ANAs (48.4% vs. 21.4%, p<0.001), anti-dsDNA (5.1% vs. 0%, p=0.01), anti-CCP (8.3% vs. 1.7%, p=0.014) and anti-CL IgM AAbs (21.7% vs. 9.4%, p=0.005) than controls, respectively. Simultaneous reactivity against at least three autoantigens, occurred in 144 out of 174 (82.8%) patients. The two groups did not differ in terms of clinicoepidemiologic characteristics or the mortality ratio within the ICU. Patients who died compared to convalescents were older, had higher ferritin, D-dimers levels, APACHE II score, lower oxygen saturation, higher prevalence of comorbidities and cognitive dysfunction. However, AAbs were not found to correlate with the clinical outcome. CONCLUSIONS: Patients with severe COVID-19 express AAbs more commonly compared to controls. No correlation was found between AAbs and disease outcome.

Utilisation of primary healthcare services by Sjögren's syndrome patients in the Community of Madrid and associated factors: a population-based cross-sectional study.

OBJECTIVES: To describe the utilisation of primary health care (PHC) services and factors associated with its use by patients diagnosed with Sjögren's syndrome (SS). METHODS: Population-based cross-sectional cohort of SS patients in Madrid, Spain (SIERMA). Sociodemographic, diagnostic, clinical and PHC service utilisation variables were studied by bivariate analyses and regression models. RESULTS: A total of 4,778 SS patients were included, 65.2% classified as primary SS (pSS), while 34.8% associated with another autoimmune disease (associated SS). Mean age was 64.3 years, and 92.8% of the patients were women. A total of 87.5% used PHC services, with a mean of 19.8 consultations/year. The general practitioner was the most visited health professional, with a mean of 10.9 consultations/year, followed by the nurse, with a mean of 5.7. Characteristics associated with a greater use of PHC services in SS patients were associated SS, higher adjusted morbidity groups (AMG) risk level and older age. Additional factors included symptoms such as dry mouth, fatigue, dry vagina and joint and muscle pain; comorbidities such as atrial fibrillation, diabetes, hypertension, solid malignant neoplasms, coronary heart disease and chronic obstructive pulmonary disease; and treatments such as sterile saline solution, corticosteroids, opioids and biologic disease-modifying anti-rheumatic drugs. CONCLUSIONS: Most SS patients used PHC services during the study period, and the mean number of consultations was remarkably high. Utilisation was mainly associated with AMG risk level, ageing, glandular and extra-glandular symptoms, substantial comorbidities and various treatments. An optimised design of PHC policies will facilitate early diagnosis, improved management and better quality of life for SS patients.

Personalized Risk Analysis to Improve the Psychological Resilience of Women Undergoing Treatment for Breast Cancer: Development of a Machine Learning-Driven Clinical Decision Support Tool.

BACKGROUND: Health professionals are often faced with the need to identify women at risk of manifesting poor psychological resilience following the diagnosis and treatment of breast cancer. Machine learning algorithms are increasingly used to support clinical decision support (CDS) tools in helping health professionals identify women who are at risk of adverse well-being outcomes and plan customized psychological interventions for women at risk. Clinical flexibility, cross-validated performance accuracy, and model explainability permitting person-specific identification of risk factors are highly desirable features of such tools. OBJECTIVE: This study aimed to develop and cross-validate machine learning models designed to identify breast cancer survivors at risk of poor overall mental health and global quality of life and identify potential targets of personalized psychological interventions according to an extensive set of clinical recommendations. METHODS: A set of 12 alternative models was developed to improve the clinical flexibility of the CDS tool. All models were validated using longitudinal data from a prospective, multicenter clinical pilot at 5 major oncology centers in 4 countries (Italy, Finland, Israel, and Portugal; the Predicting Effective Adaptation to Breast Cancer to Help Women to BOUNCE Back [BOUNCE] project). A total of 706 patients with highly treatable breast cancer were enrolled shortly after diagnosis and before the onset of oncological treatments and were followed up for 18 months. An extensive set of demographic, lifestyle, clinical, psychological, and biological variables measured within 3 months after enrollment served as predictors. Rigorous feature selection isolated key psychological resilience outcomes that could be incorporated into future clinical practice. RESULTS: Balanced random forest classifiers were successful at predicting well-being outcomes, with accuracies ranging between 78% and 82% (for 12-month end points after diagnosis) and between 74% and 83% (for 18-month end points after diagnosis). Explainability and interpretability analyses built on the best-performing models were used to identify potentially modifiable psychological and lifestyle characteristics that, if addressed systematically in the context of personalized psychological interventions, would be most likely to promote resilience for a given patient. CONCLUSIONS: Our results highlight the clinical utility of the BOUNCE modeling approach by focusing on resilience predictors that can be readily available to practicing clinicians at major oncology centers. The BOUNCE CDS tool paves the way for personalized risk assessment methods to identify patients at high risk of adverse well-being outcomes and direct valuable resources toward those most in need of specialized psychological interventions.

Evaluating Gait Impairment in Parkinson's Disease from Instrumented Insole and IMU Sensor Data.

Parkinson's disease (PD) is characterized by a variety of motor and non-motor symptoms, some of them pertaining to gait and balance. The use of sensors for the monitoring of patients' mobility and the extraction of gait parameters, has emerged as an objective method for assessing the efficacy of their treatment and the progression of the disease. To that end, two popular solutions are pressure insoles and body-worn IMU-based devices, which have been used for precise, continuous, remote, and passive gait assessment. In this work, insole and IMU-based solutions were evaluated for assessing gait impairment, and were subsequently compared, producing evidence to support the use of instrumentation in everyday clinical practice. The evaluation was conducted using two datasets, generated during a clinical study, in which patients with PD wore, simultaneously, a pair of instrumented insoles and a set of wearable IMU-based devices. The data from the study were used to extract and compare gait features, independently, from the two aforementioned systems. Subsequently, subsets comprised of the extracted features, were used by machine learning algorithms for gait impairment assessment. The results indicated that insole gait kinematic features were highly correlated with those extracted from IMU-based devices. Moreover, both had the capacity to train accurate machine learning models for the detection of PD gait impairment.

Clinical Evaluation in Parkinson's Disease: Is the Golden Standard Shiny Enough?

Parkinson's disease (PD) has become the second most common neurodegenerative condition following Alzheimer's disease (AD), exhibiting high prevalence and incident rates. Current care strategies for PD patients include brief appointments, which are sparsely allocated, at outpatient clinics, where, in the best case scenario, expert neurologists evaluate disease progression using established rating scales and patient-reported questionnaires, which have interpretability issues and are subject to recall bias. In this context, artificial-intelligence-driven telehealth solutions, such as wearable devices, have the potential to improve patient care and support physicians to manage PD more effectively by monitoring patients in their familiar environment in an objective manner. In this study, we evaluate the validity of in-office clinical assessment using the MDS-UPDRS rating scale compared to home monitoring. Elaborating the results for 20 patients with Parkinson's disease, we observed moderate to strong correlations for most symptoms (bradykinesia, rest tremor, gait impairment, and freezing of gait), as well as for fluctuating conditions (dyskinesia and OFF). In addition, we identified for the first time the existence of an index capable of remotely measuring patients' quality of life. In summary, an in-office examination is only partially representative of most PD symptoms and cannot accurately capture daytime fluctuations and patients' quality of life.

Co-Designing Digital Technologies for Improving Clinical Care in People with Parkinson's Disease: What Did We Learn?

The healthcare model is shifting towards integrated care approaches. This new model requires patients to be more closely involved. The iCARE-PD project aims to address this need by developing a technology-enabled, home-based, and community-centered integrated care paradigm. A central part of this project is the codesign process of the model of care, exemplified by the active participation of patients in the design and iterative evaluation of three sensor-based technological solutions. We proposed a codesign methodology used for testing the usability and acceptability of these digital technologies and present initial results for one of them, MooVeo. Our results show the usefulness of this approach in testing the usability and acceptability as well as the opportunity to incorporate patients' feedback into the development. This initiative will hopefully help other groups incorporate a similar codesign approach and develop tools that are well adapted to patients' and care teams' needs.

Aptamers Targeting Membrane Proteins for Sensor and Diagnostic Applications.

Many biological processes (physiological or pathological) are relevant to membrane proteins (MPs), which account for almost 30% of the total of human proteins. As such, MPs can serve as predictive molecular biomarkers for disease diagnosis and prognosis. Indeed, cell surface MPs are an important class of attractive targets of the currently prescribed therapeutic drugs and diagnostic molecules used in disease detection. The oligonucleotides known as aptamers can be selected against a particular target with high affinity and selectivity by iterative rounds of in vitro library evolution, known as Systematic Evolution of Ligands by EXponential Enrichment (SELEX). As an alternative to antibodies, aptamers offer unique features like thermal stability, low-cost, reuse, ease of chemical modification, and compatibility with various detection techniques. Particularly, immobilized-aptamer sensing platforms have been under investigation for diagnostics and have demonstrated significant value compared to other analytical techniques. These "aptasensors" can be classified into several types based on their working principle, which are commonly electrochemical, optical, or mass-sensitive. In this review, we review the studies on aptamer-based MP-sensing technologies for diagnostic applications and have included new methodological variations undertaken in recent years.

Clinical picture, outcome and predictive factors of lymphoma in primary Sjögren's syndrome: results from a harmonized dataset (1981-2021).

OBJECTIVES: Primary Sjögren's Syndrome (pSS) carries the highest risk for non-Hodgkin's lymphoma (NHL) development among systemic autoimmune diseases. However, the paucity of data on the long-term survival of those patients and the lack of established predictors for each lymphoma histologic subtype prompted our present study. METHODS: We retrospectively analysed 121 patients diagnosed with NHL according to the WHO classification criteria. All patients fulfilled the 2016 ACR-EULAR classification criteria for pSS. Cumulative clinical, laboratory, radiologic, treatment regimens and histologic data were recorded, harmonized and analysed. Overall survival (OS) and event-free survival (EFS) curves were calculated. A mucosa-associated lymphoid tissue lymphoma (MALTL) prediction model was developed by applying innovative data-driven analysis of clinical features present at the time of pSS diagnosis. RESULTS: MALTLs constituted the majority of lymphomas (92/121, 76.0%) followed by diffuse large B-cell lymphomas (DLBCL) (11/121, 9.0%) and nodal marginal zone lymphomas (NMZL) (8/121, 7%). MALTLs show salivary glands localization, limited disease and often bone marrow and nodal involvement. The 10-year OS and EFS rates were 79% and 45.5% for MALTLs, 40.9% and 24.2% for DLBCL and 46% and 31% for NMZL. Cryoglobulinemia, focus score and the total EULAR SS Disease Activity Index (ESSDAI) composite index at pSS diagnosis were proven independent MALTL predictors. Even though MALTLs have a comparatively good survival outlook, they are accompanied by frequent events throughout their clinical course. CONCLUSIONS: Common features of pSS, present at diagnosis, can predict future lymphomagenesis meriting a more intensive follow-up plan.

Clinical and laboratory findings of primary Sjögren's syndrome patients without sicca symptoms.

OBJECTIVES: Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease characterised by oral and eye dryness. A minority of patients can present without dryness but studies on their clinico-laboratory manifestations are scarce. Our purpose was to describe the clinical phenotype of pSS patients lacking sicca symptoms. METHODS: From a total of 1738 consecutive pSS patients fulfilling the 2016 ACR-EULAR criteria, those who presented without sicca symptoms were identified (non-dryness group). Their medical data was collected and compared with 2 control groups: a) the remaining unmatched sicca pSS patients with both oral and eye dryness (unmatched dryness group) and b) matched sicca pSS patients according to age, sex, and disease duration, in 1:2 ratio (matched dryness group). RESULTS: Thirty-eight (2.19%) patients lacked sicca manifestations presenting mainly with arthralgias (47%), parotid enlargement (24%), Raynaud's phenomenon (11%) and persistent lymphadenopathy (11%) that led them to be evaluated for pSS. Non-dryness pSS patients were younger than the unmatched sicca controls, displaying a higher frequency of anti-Ro/SSA antibodies (100% vs. 79.7%, p<0.001), ANA positivity (100% vs. 90.4%, p<0.001), neutropenia (20.8% vs. 7.5%, p=0.04) and thrombocytopenia (13.8% vs. 4.2%, p=0.04). They also had lower frequency of positive ocular tests compared to both unmatched and matched dryness patients. No differences were found between non-dryness pSS patients and both control groups regarding focus score or any other extraglandular manifestation. CONCLUSIONS: pSS patients without sicca complaints constitute a distinct phenotype involving younger patients, sharing common immunopathologic mechanisms with typical sicca patients.

High-resolution structure of the amino acid transporter AdiC reveals insights into the role of water molecules and networks in oligomerization and substrate binding.

BACKGROUND: The L-arginine/agmatine transporter AdiC is part of the arginine-dependent extreme acid resistance system of the bacterium Escherichia coli and its pathogenic varieties such as strain E. coli O157:H7. At the present time, there is a lack of knowledge concerning the role of water molecules and networks for the structure and function of AdiC, and solute transporters in general. RESULTS: The structure of the L-arginine/agmatine transporter AdiC was determined at 1.7 Å resolution by X-ray crystallography. This high resolution allowed for the identification of numerous water molecules buried in the structure. In combination with molecular dynamics (MD) simulations, we demonstrate that water molecules play an important role for stabilizing the protein and key residues, and act as placeholders for atoms of the AdiC substrates L-arginine and agmatine. MD simulations unveiled flexibility and restrained mobility of gating residues W202 and W293, respectively. Furthermore, a water-filled cavity was identified at the dimer interface of AdiC. The two monomers formed bridging interactions through water-mediated hydrogen bonds. The accessibility and presence of water molecules in this cavity was confirmed with MD simulations. Point mutations disrupting the interfacial water network validated the importance of water molecules for dimer stabilization. CONCLUSIONS: This work gives new insights into the role and importance of water molecules in the L-arginine/agmatine transporter AdiC for protein stabilization and substrate-binding site shaping and as placeholders of substrate atoms. Furthermore, and based on the observed flexibility and restrained mobility of gating residues, a mechanistic role of the gate flexibility in the transport cycle was proposed. Finally, we identified a water-filled cavity at the dimeric interface that contributes to the stability of the amino acid transporter oligomer.

Can Gait Features Help in Differentiating Parkinson's Disease Medication States and Severity Levels? A Machine Learning Approach.

Parkinson's disease (PD) is one of the most prevalent neurological diseases, described by complex clinical phenotypes. The manifestations of PD include both motor and non-motor symptoms. We constituted an experimental protocol for the assessment of PD motor signs of lower extremities. Using a pair of sensor insoles, data were recorded from PD patients, Elderly and Adult groups. Assessment of PD patients has been performed by neurologists specialized in movement disorders using the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS)-Part III: Motor Examination, on both ON and OFF medication states. Using as a reference point the quantified metrics of MDS-UPDRS-Part III, severity levels were explored by classifying normal, mild, moderate, and severe levels of PD. Elaborating the recorded gait data, 18 temporal and spatial characteristics have been extracted. Subsequently, feature selection techniques were applied to reveal the dominant features to be used for four classification tasks. Specifically, for identifying relations between the spatial and temporal gait features on: PD and non-PD groups; PD, Elderly and Adults groups; PD and ON/OFF medication states; MDS-UPDRS: Part III and PD severity levels. AdaBoost, Extra Trees, and Random Forest classifiers, were trained and tested. Results showed a recognition accuracy of 88%, 73% and 81% for, the PD and non-PD groups, PD-related medication states, and PD severity levels relevant to MDS-UPDRS: Part III ratings, respectively.

Structure, Function and Pharmacology of SLC7 Family Members and Homologues.

Amino acids are essential components of all living cells serving as building blocks of proteins, as energy source, and as precursors of metabolites and signaling molecules. Amino acid transporters are membrane proteins that mediate the transfer of amino acids across the plasma membrane, and between compartments in cells, different cells and organs. The absence, overexpression or malfunction of specific amino acid transporters have been associated with human disease. One of the projects within the Swiss National Centre of Competence in Research (NCCR) TransCure was directed at SLC7 family amino acid transporters, with a particular focus on the heteromeric amino acid transporters 4F2hc-LAT1 (SLC3A2-SLC7A5) and 4F2hc-LAT2 (SLC3A2-SLC7A8), and the bacterial homologue AdiC. The project addressed questions of basic research (function and structure), pharmacology (identification of potent inhibitors and activators), and pre-clinical medicine (e.g., physiological role in the placenta) and disease models (e.g., tumor progression) of specific SLC7 family amino acid transporters. This review presents, summarizes and discusses selected main results obtained in this NCCR TransCure project.

Relationship of Endothelial Shear Stress with Plaque Features with Coronary CT Angiography and Vasodilating Capability with PET.

Background Advances in three-dimensional reconstruction techniques and computational fluid dynamics of coronary CT angiography (CCTA) data sets make feasible evaluation of endothelial shear stress (ESS) in the vessel wall. Purpose To investigate the relationship between CCTA-derived computational fluid dynamics metrics, anatomic and morphologic characteristics of coronary lesions, and their comparative performance in predicting impaired coronary vasodilating capability assessed by using PET myocardial perfusion imaging (MPI). Materials and Methods In this retrospective study, conducted between October 2019 and September 2020, coronary vessels in patients with stable chest pain and with intermediate probability of coronary artery disease who underwent both CCTA and PET MPI with oxygen 15-labeled water or nitrogen 13 ammonia and quantification of myocardial blood flow were analyzed. CCTA images were used in assessing stenosis severity, lesion-specific total plaque volume (PV), noncalcified PV, calcified PV, and plaque phenotype. PET MPI was used in assessing significant coronary stenosis. The predictive performance of the CCTA-derived parameters was evaluated by using area under the receiver operating characteristic curve (AUC) analysis. Results There were 92 coronary vessels evaluated in 53 patients (mean age, 65 years ± 7; 31 men). ESS was higher in lesions with greater than 50% stenosis versus those without significant stenosis (mean, 15.1 Pa ± 30 vs 4.6 Pa ± 4 vs 3.3 Pa ± 3; P = .004). ESS was higher in functionally significant versus nonsignificant lesions (median, 7 Pa [interquartile range, 5-23 Pa] vs 2.6 Pa [interquartile range, 1.8-5 Pa], respectively; P ≤ .001). Adding ESS to stenosis severity improved prediction (change in AUC, 0.10; 95% CI: 0.04, 0.17; P = .002) for functionally significant lesions. Conclusion The combination of endothelial shear stress with coronary CT angiography (CCTA) stenosis severity improved prediction of an abnormal PET myocardial perfusion imaging result versus CCTA stenosis severity alone. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Kusmirek and Wieben in this issue.

A biomarker for lymphoma development in Sjogren's syndrome: Salivary gland focus score.

The aim of this study is to explore the role of labial minor salivary gland (LMSG) focus score (FS) in stratifying Sjögren's Syndrome (SS) patients, lymphoma development prediction and to facilitate early lymphoma diagnosis. Ιn an integrated cohort of 1997 patients, 618 patients with FS ≥ 1 and at least one-year elapsing time interval from SS diagnosis to lymphoma diagnosis or last follow up were identified. Clinical, laboratory and serological features were recorded. A data driven logistic regression model was applied to identify independent lymphoma associated risk factors. Furthermore, a FS threshold maximizing the difference of time interval from SS until lymphoma diagnosis between high and low FS lymphoma subgroups was investigated, to develop a follow up strategy for early lymphoma diagnosis. Of the 618 patients, 560 were non-lymphoma SS patients while the other 58 had SS and lymphoma. FS, cryoglobulinemia and salivary gland enlargement (SGE) were proven to be independent lymphoma associated risk factors. Lymphoma patients with FS ≥ 4 had a statistically significant shorter time interval from SS to lymphoma diagnosis, compared to those with FS < 4 (4 vs 9 years, respectively, p = 0,008). SS patients with FS ≥ 4 had more frequently B cell originated manifestations and lymphoma, while in patients with FS < 4, autoimmune thyroiditis was more prevalent. In the latter group SGE was the only lymphoma independent risk factor. A second LMSG biopsy is patients with a FS ≥ 4, 4 years after SS diagnosis and in those with FS < 4 and a history of SGE, at 9-years, may contribute to an early lymphoma diagnosis. Based on our results we conclude that LMSG FS, evaluated at the time of SS diagnosis, is an independent lymphoma associated risk factor and may serve as a predictive biomarker for the early diagnosis of SS-associated lymphomas.