Comparative proteomic analysis of the ovarian fluid and eggs of Siberian sturgeon.

BACKGROUND: Sturgeon species are living fossils that exhibit unique reproductive characteristics, and elucidation of the molecular processes governing the formation and quality of sturgeon eggs is crucial. However, comprehensive data on the protein composition of sturgeon ovarian fluid (OF) and eggs and their functional significance are lacking. To address this knowledge gap, the aim of the present study was to conduct a comprehensive comparative proteomic analysis of Siberian sturgeon OF and eggs using liquid chromatography-mass spectrometry (LC-MS/MS). RESULTS: A total of 617 proteins were identified in OF, and 565 proteins were identified in eggs. A total of 772 proteins showed differential abundance. Among the differentially abundant proteins, 365 were more abundant in OFs, while 407 were more abundant in eggs. We identified 339 proteins unique to OFs and 287 proteins specific to eggs, and further investigated the top 10 most abundant proteins in each. The functional annotation of the OF proteins highlighted their predominant association with immune system processes, including the complement and coagulation cascade, neutrophil and leukocyte-mediated immunity, cholesterol metabolism, and regulation of the actin cytoskeleton. Analysis of egg proteins revealed enrichment in metabolic pathways, such as oxidative phosphorylation and fatty acid metabolism, and protein ubiquitination and translation. OF-specific proteins included extracellular matrix and secretory vesicles, and eggs were enriched in proteins localized to mitochondria and ribosome components. CONCLUSIONS: This study presents the first comprehensive characterization of the protein composition of sturgeon OF and eggs and elucidates their distinct functional roles. These findings advance our understanding of sturgeon reproduction, OF-egg signaling and the origin of OF proteins. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium with the dataset identifier PXD044168 to ensure accessibility for further research.

Whole exome sequencing and proteomics-based investigation of the pathogenesis of coronary artery disease with diffuse long lesion.

OBJECTIVES: The long-term prognosis of patients with coronary artery disease (CAD) with diffuse long lesion underwent coronary artery bypass graft (CABG) or percutaneous coronary intervention (PCI) remains worse. Here, we aimed to identify distinctive genes involved and offer novel insights into the pathogenesis of diffuse long lesion. MATERIALS AND METHODS: Whole exome sequencing was performed on peripheral blood samples from 20 CAD patients with diffuse long lesion (CAD-DLL) and from 10 controls with focal lesion (CAD-FL) through a uniform pipeline. Proteomics analysis was conducted on the serum samples from 10 CAD-DLL patients and from 10 controls with CAD-FL by mass spectrometry. Bioinformatics analysis was performed to elucidate the involved genes, including functional annotation and protein-protein interaction analysis. RESULTS: A total of 742 shared variant genes were found in CAD-DLL patients but not in controls. Of these, 46 genes were identified as high-frequency variant genes (≥ 4/20) distinctive genes. According to the consensus variant site, 148 shared variant sites were found in the CAD-DLL group. The lysosome and cellular senescence-related pathway may be the most significant pathway in diffuse long lesion. Following the DNA-protein combined analysis, eight genes were screened whose expression levels were altered at both DNA and protein levels. Among these genes, the MAN2A2 gene, the only one that was highly expressed at the protein level, was associated with metabolic and immune-inflammatory dysregulation. CONCLUSIONS: Compared to individuals with CAD-FL, patients with CAD-DLL show additional variants. These findings contribute to the understanding of the mechanism of CAD-DLL and provide potential targets for the diagnosis and treatment of CAD-DLL.

REMEMProt: a resource of membrane-enriched proteome profiles, their disease associations, and biomarker status.

The differential expression of plasma membrane proteins is integrally analyzed for their diagnosis, prognosis, and therapeutic applications in diverse clinical manifestations. Necessarily, distinct membrane protein enrichment methods and mass spectrometry platforms are employed for their global and relative quantitation. First of its kind to explore, we compiled membrane-associated proteomes in human and mouse systems into a database named, Resource of Experimental Membrane-Enriched Mass spectrometry-derived Proteome (REMEMProt). It currently hosts 14,626 proteins (9,507 proteins in Homo sapiens; 5,119 proteins in Mus musculus) with information on their membrane-protein enrichment methods, experimental/physiological context of detection in cells or tissues, transmembrane domain analysis, and their current attribution as biomarkers. Based on these annotations and the transmembrane domain analysis in proteins or their binary/complex protein-protein interactors, REMEMProt facilitates the assessment of the plasma membrane localization potential of proteins through batch query. A cross-study enrichment analysis platform is enabled in REMEMProt for comparative analysis of proteomes using novel/modified membrane enrichment methods and evaluation of methods for targeted enrichment of membrane proteins. REMEMProt data are made freely accessible to explore and download at https://rememprot.ciods.in/.

Insights into modifiers effects in differential mobility spectrometry: A data science approach for metabolomics and peptidomics.

Utilizing a data-driven approach, this study investigates modifier effects on compensation voltage in differential mobility spectrometry-mass spectrometry (DMS-MS) for metabolites and peptides. Our analysis uncovers specific factors causing signal suppression in small molecules and pinpoints both signal suppression mechanisms and the analytes involved. In peptides, machine learning models discern a relationship between molecular weight, topological polar surface area, peptide charge, and proton transfer-induced signal suppression. The models exhibit robust performance, offering valuable insights for the application of DMS to metabolites and tryptic peptides analysis by DMS-MS.

Probing the Immunoreceptor Tyrosine-Based Inhibition Motif Interaction Protein Partners with Proteomics.

Phosphorylation of tyrosine is the basic mode of protein function and signal transduction in organisms. This process is regulated by protein tyrosine kinases (PTKs) and protein tyrosinases (PTPs). Immunoreceptor tyrosine-based inhibition motif (ITIM) has been considered as regulating the PTP activity through the interaction with the partner proteins in the cell signal pathway. The ITIM sequences need to be phosphorylated first to active the downstream signaling proteins. To explore potential regulatory mechanisms, the ITIM sequences of two transmembrane immunoglobulin proteins, myelin P0 protein-related protein (PZR) and programmed death 1 (PD-1), were analyzed to investigate their interaction with proteins involved in regulatory pathways. We discovered that phosphorylated ITIM sequences can selectively interact with the tyrosine phosphatase SHP2. Specifically, PZR-N-ITIM (pY) may be critical in the interaction between the ITIM and SH2 domains of SHP2, while PD1-C-ITSM (pY) may play a key role in the interaction between the ITIM and SH2 domains of SHP2. Quite a few proteins were identified containing the SH2 domain, exhibiting phosphorylation-mediated interaction with PZR-ITIM. In this study, 14 proteins with SH2 structural domains were identified by GO analysis on 339 proteins associated to the affinity pull-down of PZR-N-ITIM (pY). Through the SH2 domains, these proteins may interact with PZR-ITIM in a phosphorylation-dependent manner.

High-confidence 3D template matching for cryo-electron tomography.

Visual proteomics attempts to build atlases of the molecular content of cells but the automated annotation of cryo electron tomograms remains challenging. Template matching (TM) and methods based on machine learning detect structural signatures of macromolecules. However, their applicability remains limited in terms of both the abundance and size of the molecular targets. Here we show that the performance of TM is greatly improved by using template-specific search parameter optimization and by including higher-resolution information. We establish a TM pipeline with systematically tuned parameters for the automated, objective and comprehensive identification of structures with confidence 10 to 100-fold above the noise level. We demonstrate high-fidelity and high-confidence localizations of nuclear pore complexes, vaults, ribosomes, proteasomes, fatty acid synthases, lipid membranes and microtubules, and individual subunits inside crowded eukaryotic cells. We provide software tools for the generic implementation of our method that is broadly applicable towards realizing visual proteomics.

Plasma proteome profiling reveals dynamic of cholesterol marker after dual blocker therapy.

Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

Temperature effects on plasmalogen profile and quality characteristics in Pacific oyster (Crassostrea gigas) during depuration.

The quality of Pacific oyster (Crassostrea gigas) can be affected by many factors during depuration, in which temperature is the major element. In this study, we aim to determine the quality and plasmalogen changes in C. gigas depurated at different temperatures. The quality was significantly affected by temperature, represented by varying survival rate, glycogen content, total antioxidant capacity, alkaline phosphatase activity between control and stressed groups. Targeted MS analysis demonstrated that plasmalogen profile was significantly changed during depuration with PUFA-containing plasmalogen species being most affected by temperature. Proteomics analysis and gene expression assay further verified that plasmalogen metabolism is regulated by temperature, specifically, the plasmalogen synthesis enzyme EPT1 was significantly downregulated by high temperature and four plasmalogen-related genes (GPDH, PEDS, Pex11, and PLD1) were transcriptionally regulated. The positive correlations between the plasmalogen level and quality characteristics suggested plasmalogen could be regarded as a quality indicator of oysters during depuration.

A study protocol to characterise pathophysiological and molecular markers of rheumatic heart disease and degenerative aortic stenosis using multiparametric cardiovascular imaging and multiomics techniques.

INTRODUCTION: Rheumatic heart disease (RHD), degenerative aortic stenosis (AS), and congenital valve diseases are prevalent in sub-Saharan Africa. Many knowledge gaps remain in understanding disease mechanisms, stratifying phenotypes, and prognostication. Therefore, we aimed to characterise patients through clinical profiling, imaging, histology, and molecular biomarkers to improve our understanding of the pathophysiology, diagnosis, and prognosis of RHD and AS. METHODS: In this cross-sectional, case-controlled study, we plan to recruit RHD and AS patients and compare them to matched controls. Living participants will undergo clinical assessment, echocardiography, CMR and blood sampling for circulatory biomarker analyses. Tissue samples will be obtained from patients undergoing valve replacement, while healthy tissues will be obtained from cadavers. Immunohistology, proteomics, metabolomics, and transcriptome analyses will be used to analyse circulatory- and tissue-specific biomarkers. Univariate and multivariate statistical analyses will be used for hypothesis testing and identification of important biomarkers. In summary, this study aims to delineate the pathophysiology of RHD and degenerative AS using multiparametric CMR imaging. In addition to discover novel biomarkers and explore the pathomechanisms associated with RHD and AS through high-throughput profiling of the tissue and blood proteome and metabolome and provide a proof of concept of the suitability of using cadaveric tissues as controls for cardiovascular disease studies.

Proteomic Analysis of Primary Graft Dysfunction in Porcine Lung Transplantation Reveals Alveolar-Capillary Barrier Changes Underlying the High Particle Flow Rate in Exhaled Breath.

Primary graft dysfunction (PGD) remains a challenge for lung transplantation (LTx) recipients as a leading cause of poor early outcomes. New methods are needed for more detailed monitoring and understanding of the pathophysiology of PGD. The measurement of particle flow rate (PFR) in exhaled breath is a novel tool to monitor and understand the disease at the proteomic level. In total, 22 recipient pigs underwent orthotopic left LTx and were evaluated for PGD on postoperative day 3. Exhaled breath particles (EBPs) were evaluated by mass spectrometry and the proteome was compared to tissue biopsies and bronchoalveolar lavage fluid (BALF). Findings were confirmed in EBPs from 11 human transplant recipients. Recipients with PGD had significantly higher PFR [686.4 (449.7-8,824.0) particles per minute (ppm)] compared to recipients without PGD [116.6 (79.7-307.4) ppm, p = 0.0005]. Porcine and human EBP proteins recapitulated proteins found in the BAL, demonstrating its utility instead of more invasive techniques. Furthermore, adherens and tight junction proteins were underexpressed in PGD tissue. Histological and proteomic analysis found significant changes to the alveolar-capillary barrier explaining the high PFR in PGD. Exhaled breath measurement is proposed as a rapid and non-invasive bedside measurement of PGD.

[Multi-omics prediction of lymph node metastasis status in breast cancer].

Lymph node metastasis status stands as a pivotal prognostic indicator in forecasting the outlook for breast cancer patients. Consequently, precise evaluation of this status holds paramount importance in the staging, treatment, and prognosis of breast cancer. The utilization of radiomics, genomics, proteomics, transcriptomics, and histopathology methodologies has notably enhanced the precision of lymph node metastasis status prediction in breast cancer. This review provides an overview of recent advancements in omics-based lymph node metastasis prediction for breast cancer, elucidating the significance of various omics prediction models and integrated multi-omics models in this predictive endeavor. The overarching goal is to augment the accuracy of preoperative lymph node metastasis status prediction in breast cancer, thereby aiding clinicians in the selection of efficacious personalized treatment strategies, while concurrently averting undertreatment of patients with a heightened risk of metastasis.

A novel multi-stage enrichment workflow and comprehensive characterization for HEK293F-derived extracellular vesicles.

Extracellular vesicles (EVs) are emerging as a promising drug delivery vehicle as they are biocompatible and capable of targeted delivery. However, clinical translation of EVs remains challenging due to the lack of standardized and scalable manufacturing protocols to consistently isolate small EVs (sEVs) with both high yield and high purity. The heterogenous nature of sEVs leading to unknown composition of biocargos causes further pushback due to safety concerns. In order to address these issues, we developed a robust quality-controlled multi-stage process to produce and isolate sEVs from human embryonic kidney HEK293F cells. We then compared different 2-step and 3-step workflows for eliminating protein impurities and cell-free nucleic acids to meet acceptable limits of regulatory authorities. Our results showed that sEV production was maximized when HEK293F cells were grown at high-density stationary phase in semi-continuous culture. The novel 3-step workflow combining tangential flow filtration, sucrose-cushion ultracentrifugation and bind-elute size-exclusion chromatography outperformed other methods in sEV purity while still preserved high yield and particle integrity. The purified HEK293F-derived sEVs were thoroughly characterized for identity including sub-population analysis, content profiling including proteomics and miRNA sequencing, and demonstrated excellent preclinical safety profile in both in-vitro and in-vivo testing. Our rigorous enrichment workflow and comprehensive characterization will help advance the development of EVs, particularly HEK293F-derived sEVs, to be safe and reliable drug carriers for therapeutic applications.

Cystatin C loaded in brain-derived extracellular vesicles rescues synapses after ischemic insult in vitro and in vivo.

Synaptic loss is an early event in the penumbra area after an ischemic stroke. Promoting synaptic preservation in this area would likely improve functional neurological recovery. We aimed to detect proteins involved in endogenous protection mechanisms of synapses in the penumbra after stroke and to analyse potential beneficial effects of these candidates for a prospective stroke treatment. For this, we performed Liquid Chromatography coupled to Mass Spectrometry (LC-MS)-based proteomics of synaptosomes isolated from the ipsilateral hemispheres of mice subjected to experimental stroke at different time points (24 h, 4 and 7 days) and compared them to sham-operated mice. Proteomic analyses indicated that, among the differentially expressed proteins between the two groups, cystatin C (CysC) was significantly increased at 24 h and 4 days following stroke, before returning to steady-state levels at 7 days, thus indicating a potential transient and intrinsic rescue mechanism attempt of neurons. When CysC was applied to primary neuronal cultures subjected to an in vitro model of ischemic damage, this treatment significantly improved the preservation of synaptic structures. Notably, similar effects were observed when CysC was loaded into brain-derived extracellular vesicles (BDEVs). Finally, when CysC contained in BDEVs was administered intracerebroventricularly to stroked mice, it significantly increased the expression of synaptic markers such as SNAP25, Homer-1, and NCAM in the penumbra area compared to the group supplied with empty BDEVs. Thus, we show that CysC-loaded BDEVs promote synaptic protection after ischemic damage in vitro and in vivo, opening the possibility of a therapeutic use in stroke patients.

Inflammatory and neurodegenerative serum protein biomarkers increase sensitivity to detect clinical and radiographic disease activity in multiple sclerosis.

The multifaceted nature of multiple sclerosis requires quantitative biomarkers that can provide insights related to diverse physiological pathways. To this end, proteomic analysis of deeply-phenotyped serum samples, biological pathway modeling, and network analysis were performed to elucidate inflammatory and neurodegenerative processes, identifying sensitive biomarkers of multiple sclerosis disease activity. Here, we evaluated the concentrations of > 1400 serum proteins in 630 samples from three multiple sclerosis cohorts for association with clinical and radiographic new disease activity. Twenty proteins were associated with increased clinical and radiographic multiple sclerosis disease activity for inclusion in a custom assay panel. Serum neurofilament light chain showed the strongest univariate correlation with gadolinium lesion activity, clinical relapse status, and annualized relapse rate. Multivariate modeling outperformed univariate for all endpoints. A comprehensive biomarker panel including the twenty proteins identified in this study could serve to characterize disease activity for a patient with multiple sclerosis.

High-throughput proteomic analysis of extracellular vesicles from saliva by chemical probe-based array.

Extracellular vesicles (EVs) are cell-released, nucleus-free particles with a double-membrane structure that effectively prevents degradation of internal components by a variety of salivary enzymes. Saliva is an easily accessible biofluid that contains a wealth of valuable information for disease diagnosis and monitoring and especially reflect respiratory and digestive tract diseases. However, the lack of efficient and high-throughput methods for proteomic analysis of salivary biomarkers poses a significant challenge. Herein, we designed a salivary EV amphiphile-dendrimer supramolecular probe (SEASP) array which enables efficient enrichment and in situ detection of EVs protein biomarkers. Detergent Tween-20 washing of SEASP arrays removes high abundance of heteroproteins from saliva well. This array shows good analytical performance in the linear range of 10 µL-150 µL (LOD = 0.4 µg protein, or 10 µL saliva), exhibiting a good recovery (80.0 %). Compared to ultracentrifugation (UC), this procedure provides simple and convenient access to high-purity EVs (1.3 × 109 particles per mg protein) with good physiological status and structure. Coupling with mass spectrometry based proteomic analysis, differentially expressed proteins as selected asthma biomarkers have been screened. Then, we validated the proteomics primary screening results through clinical samples (100 µL each) using the SEASP array. Utilizing the dual antibody fluorescence technology, SEASP enables the simultaneous high-throughput detection of two proteins. Therefore, the EVs marker protein CD81 could be used as an internal standard to normalize the number of EVs, which was stably expressed in EVs. Proteomics and array results suggested that HNRNPU (P = 4.9 * 10-6) and MUC5B (P = 4.7 * 10-11) are promising protein biomarkers for infantile asthma. HNRNPU and MUC5B may be associated with disease onset and subtypes. The SEASP arrays provide a significant advancement in the field of salivary biomarker. The array enables high-throughput in situ protein detection for highly viscous and complex biological samples. It provides a rapid, low-cost, highly specific screening procedure and experimental basis for early disease screening and diagnosis in the field of liquid biopsy.

Proteomic Analysis of Prehypertensive and Hypertensive Patients: Exploring the Role of the Actin Cytoskeleton.

Hypertension is a pervasive and widespread health condition that poses a significant risk factor for cardiovascular disease, which includes conditions such as heart attack, stroke, and heart failure. Despite its widespread occurrence, the exact cause of hypertension remains unknown, and the mechanisms underlying the progression from prehypertension to hypertension require further investigation. Recent proteomic studies have shown promising results in uncovering potential biomarkers related to disease development. In this study, serum proteomic data collected from Qatar Biobank were analyzed to identify altered protein expression between individuals with normal blood pressure, prehypertension, and hypertension and to elucidate the biological pathways contributing to this disease. The results revealed a cluster of proteins, including the SRC family, CAMK2B, CAMK2D, TEC, GSK3, VAV, and RAC, which were markedly upregulated in patients with hypertension compared to those with prehypertension (fold change ≥ 1.6 or ≤-1.6, area under the curve ≥ 0.8, and q-value < 0.05). Pathway analysis showed that the majority of these proteins play a role in actin cytoskeleton remodeling. Actin cytoskeleton reorganization affects various biological processes that contribute to the maintenance of blood pressure, including vascular tone, endothelial function, cellular signaling, inflammation, fibrosis, and mechanosensing. Therefore, the findings of this study suggest a potential novel role of actin cytoskeleton-related proteins in the progression from prehypertension to hypertension. The present study sheds light on the underlying pathological mechanisms involved in hypertension and could pave the way for new diagnostic and therapeutic approaches for the treatment of this disease.

Interleukin-13 Treatment of Living Lung Tissue Model Alters the Metabolome and Proteome-A Nano-DESI MS Metabolomics and Shotgun Proteomics Study.

Asthma is a chronic respiratory disease with one of the largest numbers of cases in the world; thus, constant investigation and technical development are needed to unravel the underlying biochemical mechanisms. In this study, we aimed to develop a nano-DESI MS method for the in vivo characterization of the cellular metabolome. Using air-liquid interface (ALI) cell layers, we studied the role of Interleukin-13 (IL-13) on differentiated lung epithelial cells acting as a lung tissue model. We demonstrate the feasibility of nano-DESI MS for the in vivo monitoring of basal-apical molecular transport, and the subsequent endogenous metabolic response, for the first time. Conserving the integrity of the ALI lung-cell layer enabled us to perform temporally resolved metabolomic characterization followed by "bottom-up" proteomics on the same population of cells. Metabolic remodeling was observed upon histamine and corticosteroid treatment of the IL-13-exposed lung cell monolayers, in correlation with alterations in the proteomic profile. This proof of principle study demonstrates the utility of in vivo nano-DESI MS for characterizing ALI tissue layers, and the new markers identified in our study provide a good starting point for future, larger-scale studies.

Iron Supplementation Increases Tumor Burden and Alters Protein Expression in a Mouse Model of Human Intestinal Cancer.

Iron supplements are widely consumed. However, excess iron may accelerate intestinal tumorigenesis. To determine the effect of excess iron on intestinal tumor burden and protein expression changes between tumor and normal tissues, ApcMin/+ mice were fed control (adequate) and excess iron (45 and 450 mg iron/kg diet, respectively; n = 9/group) for 10 wk. Tumor burden was measured, and two-dimensional fluorescence difference gel electrophoresis was used to identify differentially expressed proteins in tumor and normal intestinal tissues. There was a significant increase (78.3%; p ≤ 0.05) in intestinal tumor burden (mm2/cm) with excess iron at wk 10. Of 980 analyzed protein spots, 69 differentially expressed (p ≤ 0.05) protein isoforms were identified, representing 55 genes. Of the isoforms, 56 differed (p ≤ 0.05) between tumor vs. normal tissues from the adequate iron group and 23 differed (p ≤ 0.05) between tumors from the adequate vs. excess iron. Differentially expressed proteins include those involved in cell integrity and adaptive response to reactive oxygen species (including, by gene ID: ANPEP, DPP7, ITGB1, PSMA1 HSPA5). Biochemical pathway analysis found that iron supplementation modulated four highly significant (p ≤ 0.05) functional networks. These findings enhance our understanding of interplay between dietary iron and intestinal tumorigenesis and may help develop more specific dietary guidelines regarding trace element intake.

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs for atlas-scale datasets like Human Pancreas Analysis Program (HPAP), we develop AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX shows the higher performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulates known islet pathobiology and shows differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.