The purpose of this study was to assess the predictive and prognostic value of interim FDG PET (iPET) in evaluating early response to immuno-chemotherapy after two cycles (PET-2) in diffuse large B-cell lymphoma (DLBCL) by applying two different methods of interpretation: the Deauville visual five-point scale (5-PS) and a change in standardised uptake value by semi-quantitative evaluation. Methods: 145 patients with newly diagnosed DLBCL underwent pre-treatment PET (PET-0) and PET-2 assessment. PET-2 was classified according to both the visual 5-PS and percentage SUV changes (SUV). Receiver operating characteristic (ROC) analysis was performed to compare the accuracy of the two methods for predicting progression-free survival (PFS). Survival estimates, based on each method separately and combined, were calculated for iPET-positive (iPET+) and iPET-negative (iPET–) groups and compared. Results: Both with visual and SUV-based evaluations significant differences were found between the PFS of iPET– and iPET+ patient groups (p<0.001). Visually the best negative (NPV) and positive predictive value (PPV) occurred when iPET was defined as positive if Deauville score 4-5 (89% and 59%, respectively). Using the 66% SUV cut-off value, reported previously, NPV and PPV were 80 and 76%, respectively. SUV at 48.9% cut-off point, reported for the first time here, produced 100% specificity along with the highest sensitivity (24%). Visual and semi-quantitative SUV<48.9% assessment of each PET-2 gave the same PET-2 classification (positive or negative) in 70% (102/145) of all patients. This combined classification delivered NPV and PPV of 89% and 100% respectively, and all iPET+ patients failed to achieve or remain in remission. Conclusion: In this large consistently treated and assessed series of DLBCL, iPET had good prognostic value interpreted either visually or semi-quantitatively. We determined that the most effective SUV cut-off was at 48.9%, and that when combined with visual 5-PS assessment, a positive PET-2 was highly predictive of treatment failure.

Purpose: To assess the performance of full dose (FD) positron emission tomography (PET) image synthesis in both image and projection space from low-dose (LD) PET images/sinograms without sacrificing diagnostic quality using deep learning techniques. Methods: Clinical brain PET/CT studies of 140 patients were retrospectively employed for LD to FD PET conversion. 5% of the events were randomly selected from the FD list-mode PET data to simulate a realistic LD acquisition. A modified 3D U-Net model was implemented to predict FD sinograms in the projection-space (PSS) and FD images in image-space (PIS) from their corresponding LD sinograms/images, respectively. The quality of the predicted PET images was assessed by two nuclear medicine specialists using a five-point grading scheme. Quantitative analysis using established metrics including the peak signal-to-noise ratio (PSNR), structural similarity index metric (SSIM), region-wise standardized uptake value (SUV) bias, as well as first-, second- and high-order texture radiomic features in 83 brain regions for the test and evaluation dataset was also performed. Results: All PSS images were scored 4 or higher (good to excellent) by the nuclear medicine specialists. PSNR and SSIM values of 0.96 ± 0.03, 0.97 ± 0.02 and 31.70 ± 0.75, 37.30 ± 0.71 were obtained for PIS and PSS, respectively. The average SUV bias calculated over all brain regions was 0.24 ± 0.96% and 1.05 ± 1.44% for PSS and PIS, respectively. The Bland-Altman plots reported the lowest SUV bias (0.02) and variance (95% CI: -0.92, +0.84) for PSS compared with the reference FD images. The relative error of the homogeneity radiomic feature belonging to the Grey Level Co-occurrence Matrix category was -1.07 ± 1.77 and 0.28 ± 1.4 for PIS and PSS, respectively Conclusion: The qualitative assessment and quantitative analysis demonstrated that the FD PET prediction in projection space led to superior performance, resulting in higher image quality and lower SUV bias and variance compared to FD PET prediction in the image domain.

Respiratory motion during the CT and PET parts of a PET/CT scan leads to imperfect alignment of anatomical features seen by the two modalities. In this work, we concentrate on the effects of motion during CT. We propose a novel approach for improving the alignment. Methods: Respiratory waveform data were gathered during the CT and PET parts of 28 PET/CT scans of cancer patients with 40 lesions up to 3 cm size in the lung or upper abdomen. PET list-mode data were reconstructed by three reconstruction methods: PET/static, PET/EX or end of expiration (OncoFreeze), and a novel PET/matched method that used both waveforms. The three methods were compared. The distance between tumor positions in PET and CT were characterized in visual interpretation by physicians as well as quantitatively. Tumor standardized uptake values (SUV_max and SUVpeak) were determined relative to SUV based on the static method. Image noise was evaluated in the liver and compared to PET/static. Results: In visual interpretation, the rate of good alignment was 13/21, 13/23 and 18/21 for PET/static, PET/EX and PET/matched methods, respectively, and the mean PET-CT distances were 3.5, 5.1 and 2.8 mm. In visual comparison with PET/EX, the rate of good alignment was increased in 1/10 and 7/10 cases for PET/static and PET/matched. SUV_max was on average 21% higher than PET/static when either PET/EX or PET/matched was used. SUVpeak was 12% higher. Image noise in the liver was 15% higher than static for the PET/EX method, and 40% higher for PET/matched; that is, noise was much lower than in gated PET. Conclusion: Acquiring respiratory waveforms both in PET (as in the current state of the art) and in CT (an unusual key step in this approach) has the potential to improve the alignment of PET and CT images. A proposed method for using this information was tested. Improved alignment was demonstrated.

Latest digital whole-body PET scanners provide a combination of higher sensitivity and improved spatial and timing resolution. We performed a lesion detectability study on two generations of Siemens Biograph PET/CT scanners, the mCT and Vision, to study the impact of improved physical performance on clinical performance. Our hypothesis is that the improved performance of the Vision will result in improved lesion detectability, allowing shorter imaging times or equivalently, lower injected dose. Methods: Data were acquired with the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network torso phantom combined with a 20-cm diameter cylindrical phantom. Spherical lesions were emulated by acquiring spheres-in-air data, and combining it with the phantom data to generate combined datasets with embedded lesions of known contrast. Two sphere sizes and uptakes were used: 9.89 mm diameter spheres with 6:1 (lung) and 3:1 (cylinder) and 4.95 mm diameter spheres with 9.6:1 (lung) and 4.5:1 (cylinder) local activity concentration uptakes. Standard image reconstruction was performed: ordinary Poisson ordered subsets expectation maximization algorithm with point spread function and time-of-flight modeling and post-reconstruction smoothing with a 5 mm Gaussian filter. The Vision images were also generated without any post-reconstruction smoothing. Generalized scan statistics methodology was used to estimate the area under the localization receiver operating characteristic curve (ALROC). Results: Higher sensitivity and improved TOF performance of Vision leads to reduced contrast in the background noise nodule distribution. Measured lesion contrast is also higher on the Vision due to its improved spatial resolution. Hence, the ALROC values are noticeably higher for the Vision relative to the mCT. Conclusion: Improved overall performance of the Vision provides a factor of 4-6 reduction in imaging time (or injected dose) over the mCT when using the ALROC metric for lesions >9.89 mm in diameter. Smaller lesions are barely detected in the mCT, leading to even higher ALROC gains with the Vision. Improved spatial resolution of the Vision also leads to a higher measured contrast that is closer to the real uptake, implying improved quantification. Post-reconstruction smoothing, however, reduces this improvement in measured contrast, thereby reducing the ALROC values for small, high uptake lesions.

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.

We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.

Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

State-of-the-art proteomics-grade mass spectrometers can measure peptide precursors and their fragments with ppm mass accuracy at sequencing speeds of tens of peptides per second with attomolar sensitivity. Here we describe a compact and robust quadrupole-orbitrap mass spectrometer equipped with a front-end High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Interface. The performance of the Orbitrap Exploris 480 mass spectrometer is evaluated in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes in combination with FAIMS. We demonstrate that different compensation voltages (CVs) for FAIMS are optimal for DDA and DIA, respectively. Combining DIA with FAIMS using single CVs, the instrument surpasses 2500 peptides identified per minute. This enables quantification of >5000 proteins with short online LC gradients delivered by the Evosep One LC system allowing acquisition of 60 samples per day. The raw sensitivity of the instrument is evaluated by analyzing 5 ng of a HeLa digest from which >1000 proteins were reproducibly identified with 5 min LC gradients using DIA-FAIMS. To demonstrate the versatility of the instrument, we recorded an organ-wide map of proteome expression across 12 rat tissues quantified by tandem mass tags and label-free quantification using DIA with FAIMS to a depth of >10,000 proteins.

An experimental and computational approach for identification of protein-protein interactions by ex vivo chemical crosslinking and mass spectrometry (CLMS) has been developed that takes advantage of the specific characteristics of cyanurbiotindipropionylsuccinimide (CBDPS), an affinity-tagged isotopically coded mass spectrometry (MS)-cleavable crosslinking reagent. Utilizing this reagent in combination with a crosslinker-specific data-dependent acquisition strategy based on MS2 scans, and a software pipeline designed for integrating crosslinker-specific mass spectral information led to demonstrated improvements in the application of the CLMS technique, in terms of the detection, acquisition, and identification of crosslinker-modified peptides. This approach was evaluated on intact yeast mitochondria, and the results showed that hundreds of unique protein-protein interactions could be identified on an organelle proteome-wide scale. Both known and previously unknown protein-protein interactions were identified. These interactions were assessed based on their known sub-compartmental localizations. Additionally, the identified crosslinking distance constraints are in good agreement with existing structural models of protein complexes involved in the mitochondrial electron transport chain.

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100x) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

As the capability of mass spectrometry-based proteomics has matured, tens of thousands of peptides can be measured simultaneously, which has the benefit of offering a systems view of protein expression. However, a major challenge is that with an increase in throughput, protein quantification estimation from the native measured peptides has become a computational task. A limitation to existing computationally-driven protein quantification methods is that most ignore protein variation, such as alternate splicing of the RNA transcript and post-translational modifications or other possible proteoforms, which will affect a significant fraction of the proteome. The consequence of this assumption is that statistical inference at the protein level, and consequently downstream analyses, such as network and pathway modeling, have only limited power for biomarker discovery. Here, we describe a Bayesian model (BP-Quant) that uses statistically derived peptides signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. It is a research-driven approach that utilizes the objectives of the experiment, defined in the context of a standard statistical hypothesis, to identify a set of peptides exhibiting similar statistical behavior relating to a protein. This approach infers that changes in relative protein abundance can be used as a surrogate for changes in function, without necessarily taking into account the effect of differential post-translational modifications, processing, or splicing in altering protein function. We verify the approach using a dilution study from mouse plasma samples and demonstrate that BP-Quant achieves similar accuracy as the current state-of-the-art methods at proteoform identification with significantly better specificity. BP-Quant is available as a MatLab ® and R packages at https://github.com/PNNL-Comp-Mass-Spec/BP-Quant.

In bottom-up mass spectrometry-based proteomics, relative protein quantification is often achieved with data-dependent acquisition (DDA), data-independent acquisition (DIA), or selected reaction monitoring (SRM). These workflows quantify proteins by summarizing the abundances of all the spectral features of the protein (e.g., precursor ions, transitions or fragments) in a single value per protein per run. When abundances of some features are inconsistent with the overall protein profile (for technological reasons such as interferences, or for biological reasons such as post-translational modifications), the protein-level summaries and the downstream conclusions are undermined. We propose a statistical approach that automatically detects spectral features with such inconsistent patterns. The detected features can be separately investigated, and if necessary removed from the dataset. We evaluated the proposed approach on a series of benchmark controlled mixtures and biological investigations with DDA, DIA and SRM data acquisitions. The results demonstrated that it can facilitate and complement manual curation of the data. Moreover, it can improve the estimation accuracy, sensitivity and specificity of detecting differentially abundant proteins, and reproducibility of conclusions across different data processing tools. The approach is implemented as an option in the open-source R-based software MSstats.

Elevated levels of triglyceride-rich lipoproteins (TRLs), both fasting and postprandial, are associated with increased risk for atherosclerosis. However, guidelines for treatment are defined solely by fasting lipid levels, even though postprandial lipids may be more informative. In the postprandial state, circulating lipids consist of dietary fat transported from the intestine in chylomicrons (CMs; containing ApoB48) and fat transported from the liver in VLDL (containing ApoB100). Research into the roles of endogenous versus dietary fat has been hindered because of the difficulty in separating these particles by ultracentrifugation. CM fractions have considerable contamination from VLDL (purity, 10%). To separate CMs from VLDL, we produced polyclonal antibodies against ApoB100 and generated immunoaffinity columns. TRLs isolated by ultracentrifugation of plasma were applied to these columns, and highly purified CMs were collected (purity, 90–94%). Overall eight healthy unmedicated adult volunteers (BMI, 27.2 ± 1.4 kg/m²; fasting triacylglycerol, 102.6 ± 19.5 mg/dl) participated in a feeding study, which contained an oral stable-isotope tracer (1-¹³C acetate). We then used this technique on plasma samples freshly collected during an 8 h human feeding study from a subset of four subjects. We analyzed fractionated lipoproteins by Western blot, isolated and derivatized triacylglycerols, and calculated fractional de novo lipogenesis. The results demonstrated effective separation of postprandial lipoproteins and substantially improved purity compared with ultracentrifugation protocols, using the immunoaffinity method. This method can be used to better delineate the role of dietary sugar and fat on postprandial lipids in cardiovascular risk and explore the potential role of CM remnants in atherosclerosis.

Atherosclerosis-related CVD causes nearly 20 million deaths annually. Most patients are treated after plaques develop, so therapies must regress existing lesions. Current therapies reduce plaque volume, but targeting all apoB-containing lipoproteins with intensive combinations that include alirocumab or evinacumab, monoclonal antibodies against cholesterol-regulating proprotein convertase subtilisin/kexin type 9 and angiopoietin-like protein 3, may provide more benefit. We investigated the effect of such lipid-lowering interventions on atherosclerosis in APOE*3-Leiden.CETP mice, a well-established model for hyperlipidemia. Mice were fed a Western-type diet for 13 weeks and thereafter matched into a baseline group (euthanized at 13 weeks) and five groups that received diet alone (control) or with treatment [atorvastatin; atorvastatin and alirocumab; atorvastatin and evinacumab; or atorvastatin, alirocumab, and evinacumab (triple therapy)] for 25 weeks. We measured effects on cholesterol levels, plaque composition and morphology, monocyte adherence, and macrophage proliferation. All interventions reduced plasma total cholesterol (37% with atorvastatin to 80% with triple treatment; all P < 0.001). Triple treatment decreased non-HDL-C to 1.0 mmol/l (91% difference from control; P < 0.001). Atorvastatin reduced atherosclerosis progression by 28% versus control (P < 0.001); double treatment completely blocked progression and diminished lesion severity. Triple treatment regressed lesion size versus baseline in the thoracic aorta by 50% and the aortic root by 36% (both P < 0.05 vs. baseline), decreased macrophage accumulation through reduced proliferation, and abated lesion severity. Thus, high-intensive cholesterol-lowering triple treatment targeting all apoB-containing lipoproteins regresses atherosclerotic lesion area and improves lesion composition in mice, making it a promising potential approach for treating atherosclerosis.

Objective:

GPR40 is a G protein-coupled receptor regulating free fatty acid-induced insulin secretion. We have generated transgenic mice overexpressing the human GPR40 gene (hGPR40-Tg) under control of the mouse insulin II promoter and have used them to examine the role of GPR40 in the regulation of insulin secretion and glucose homeostasis.

Obesity is a risk factor for type 2 diabetes (T2D), however not all obese individuals develop the disease. In this study, we aimed to investigate the cause of differential insulin secretion capacity of pancreatic islets from T2D and non-T2D (ND) especially obese donors (BMI ≥30 kg/m²). Islets from obese T2D donors had reduced insulin secretion, decreased β-cell exocytosis and higher expression of fatty acid translocase CD36. We tested the hypothesis that CD36 is a key molecule in the reduced insulin secretion capacity. Indeed, CD36 overexpression led to decreased insulin secretion, impaired exocytosis and reduced granule docking. This was accompanied with reduced expression of the exocytotic proteins, SNAP25, STXBP1 and VAMP2, likely because CD36 induced down-regulation of the IRS proteins, suppressed insulin signaling PI3K-AKT pathway and increased nuclear localization of the transcription factor FoxO1. CD36 antibody treatment of the human β-cell line, EndoC-βH1, increased IRS1 and exocytotic protein levels, improved granule docking and enhanced insulin secretion. Our results demonstrate that β-cells from obese T2D donors have dysfunctional exocytosis likely due to an abnormal lipid handling represented by differential CD36 expression. Hence, CD36 could be a key molecule to limit β-cell function in T2D associated with obesity.

Optic atrophy 1 (OPA1) is a dynamin protein that mediates mitochondrial fusion at the inner membrane. OPA1 is also necessary for maintaining the cristae and thus essential for supporting cellular energetics. OPA1 exists as membrane-anchored long form (L-OPA1) and short form (S-OPA1) that lacks the transmembrane region and is generated by cleavage of L-OPA1. Mitochondrial dysfunction and cellular stresses activate the inner membrane–associated zinc metallopeptidase OMA1 that cleaves L-OPA1, causing S-OPA1 accumulation. The prevailing notion has been that L-OPA1 is the functional form, whereas S-OPA1 is an inactive cleavage product in mammals, and that stress-induced OPA1 cleavage causes mitochondrial fragmentation and sensitizes cells to death. However, S-OPA1 contains all functional domains of dynamin proteins, suggesting that it has a physiological role. Indeed, we recently demonstrated that S-OPA1 can maintain cristae and energetics through its GTPase activity, despite lacking fusion activity. Here, applying oxidant insult that induces OPA1 cleavage, we show that cells unable to generate S-OPA1 are more sensitive to this stress under obligatory respiratory conditions, leading to necrotic death. These findings indicate that L-OPA1 and S-OPA1 differ in maintaining mitochondrial function. Mechanistically, we found that cells that exclusively express L-OPA1 generate more superoxide and are more sensitive to Ca2+-induced mitochondrial permeability transition, suggesting that S-OPA1, and not L-OPA1, protects against cellular stress. Importantly, silencing of OMA1 expression increased oxidant-induced cell death, indicating that stress-induced OPA1 cleavage supports cell survival. Our findings suggest that S-OPA1 generation by OPA1 cleavage is a survival mechanism in stressed cells.

Looking to preempt questions about his work ethic in a nightmare 2018 season, Chris Davis reported to Spring Training in Florida more than a week before Orioles position players were required to. That's when his efforts to rebound hit their first minor snag.

Or, the one where Fiona Moss and Don Berwick tells us what they think quality improvement is. Fiona Moss is dean, Royal Society of Medicine, and Don Berwick is president emeritus and senior fellow, Institute for Healthcare Improvement. Don's talk and the interview with Fiona were both recorded at the International Forum on Quality and Safety in...

The BMJ has published a series of articles, taking an in-depth look at health in South Asia. In this collection, authors from India, Pakistan, Nepal, Bangladesh, Sri Lanka, and Afghanistan collaborate to identify evidence-based solutions to shape health policy and interventions, and drive innovations and research in the region. In this podcast,...

15s30m is a social movement to reduce frustration & increase joy - the idea is to spend 15 seconds of your time now, and save someone else 30 minutes down the line. To talk about their movement we're joined by the founders, Rachel Pilling, consultant ophthalmologist, and Dan Wadsworth, transformation manager - both from Bradford Teaching...

Blockchain is the digital technology that underpins cryptocurrencies such as bitcoin, and has been proposed as the digital panacea of our times. But Leeza Osipenko, from the London School of Economics, has thought about how it could actually be used in clinical trials, and what else would need to change in our regulatory environment to make that...

In October 2019, Mary Dixon-Woods, director of the THIS Institute, dedicated to healthcare improvement. In that she explained how she believed healthcare improvement could be improved. The essay took the position that "Quality Improvement" isn't necessarily the best way to improve healthcare, and that more rigour needs to be brought to the field....

G Xu
Dec 1, 1999; 48:2270-2276
Articles

Even before the Reds underscored their determination to improve by making major offseason acquisitions for the club, first baseman Joey Votto was already working to improve his hitting and his overall game.

Current therapeutic strategies for diabetic foot ulcer (DFU) have focused on developing topical healing agents, but few agents have controlled prospective data to support their effectiveness in promoting wound healing. We tested a stem cell mobilizing therapy for DFU using a combination of AMD3100 and low-dose FK506 (tacrolimus) (AF) in streptozocin-induced type 1 diabetic (T1DM) rats and type 2 diabetic Goto-Kakizaki (GK) rats that had developed peripheral artery disease and neuropathy. Here, we show that the time for healing back wounds in T1DM rats was reduced from 27 to 19 days, and the foot wound healing time was reduced from 25 to 20 days by treatment with AF (subcutaneously, every other day). Similarly, in GK rats treated with AF, the healing time on back wounds was reduced from 26 to 21 days. Further, this shortened healing time was accompanied by reduced scar and by regeneration of hair follicles. We found that AF therapy mobilized and recruited bone marrow–derived CD133⁺ and CD34⁺ endothelial progenitor cells and Ym1/2⁺ M2 macrophages into the wound sites, associated with enhanced capillary and hair follicle neogenesis. Moreover, AF therapy improved microcirculation in diabetic and neuropathic feet in GK rats. This study provides a novel systemic therapy for healing DFU.

This volume from MPI's Transatlantic Council on Migration aims to fill the analytical gap regarding the question of what greater global cooperation on governing the flow of international migrants could achieve. The book focuses on a set of fundamental questions: What are the key steps to building a better, more cooperative system of governance? What are the goals that can be achieved through greater international cooperation? And, most fundamentally, who (or what) is to be governed?

OBJECTIVE

To improve outcomes of patients with adult type 2 diabetes by decreasing HbA_1c undertesting, reducing the proportion of patients with poor glycemic control, and lowering mean HbA_1c levels using a quality improvement (QI) program.

OBJECTIVE

Dysglycemia, in this survey defined as impaired glucose tolerance (IGT) or type 2 diabetes, is common in patients with coronary artery disease (CAD) and associated with an unfavorable prognosis. This European survey investigated dysglycemia screening and risk factor management of patients with CAD in relation to standards of European guidelines for cardiovascular subjects.

OBJECTIVE

Reparixin is an inhibitor of CXCR1/2 chemokine receptor shown to be an effective anti-inflammatory adjuvant in a pilot clinical trial in allotransplant recipients.

Alan M. Delamater
Apr 1, 2006; 24:71-77
Feature Articles

OBJECTIVE

The effective redesign of primary care delivery systems to improve diabetes care requires an understanding of which particular components of delivery consistently lead to better clinical outcomes. We identified associations between common systems of care management (SysCMs) and the frequency of meeting standardized performance targets for Optimal Diabetes Care (NQF#0729) in primary care practices.

OBJECTIVE

Self-management education and support are essential for improved diabetes control. A 1-year randomized telephonic diabetes self-management intervention (Bronx A1C) among a predominantly Latino and African American population in New York City was found effective in improving blood glucose control. To further those findings, this current study assessed the intervention’s impact in reducing health care utilization and costs over 4 years.

Tina Vilsbøll
Jun 1, 2007; 30:1608-1610
BR Emerging Treatments and Technologies

Dario Giugliano
Oct 1, 1993; 16:1387-1390
Short Report

Dorothee Deiss
Dec 1, 2006; 29:2730-2732
BR Emerging Treatments and Technologies

Franca B. Barton
Jul 1, 2012; 35:1436-1445
Diabetes Care Symposium

A team of researchers at the University of California, Los Angeles School of Dentistry has developed a nanoparticle that could improve treatment for bone defects.

OBJECTIVE

Incorporation of comorbidity burden to inform diabetes management in older adults remains challenging. High-sensitivity cardiac troponins are objective, quantifiable biomarkers that may improve risk monitoring in older adults. We assessed the associations of elevations in high-sensitivity cardiac troponin I (hs-cTnI) and T (hs-cTnT) with comorbidities and improvements in mortality risk stratification.

Best-selling author Harville Hendrix weighs in on improving your relationships while in quarantine. Relationships are one of life’s most beautiful offerings. What may feel like a gift on some days...

For children in U.S. homes where a language other than English is spoken, early childhood programs that are responsive to their needs can be key to later academic success. But as states refine their Quality Rating and Improvement Systems (QRIS) to assess such programs, immigrant early childhood workers with in-demand language and cultural skills may be left behind. This report examines the challenges these workers face and promising practices to serve diverse communities.

Exercise like walking, swimming, and even dancing have been shown to be good for your memory, but the optimal intensity of that exercise has been unclear... until now

-- Read more on ScientificAmerican.com

European countries have ramped up their investments in helping refugees find work and integrate into society. Yet little hard evidence exists of what programs and policies work best. This report proposes a new framework for thinking smartly about integration programming, using cost-benefit analysis to look beyond short-term, economic outcomes to also measure indirect benefits through a social-value concept.

European policymakers are negotiating the blueprint for the next EU funding cycle—a plan that will determine how much money is available for migration and integration aims, what it can be used for, and who can access it. This policy brief explores some of the limitations of EU funds, as well as strategies that could help them more effectively serve migration and integration policy goals.

As states work to build high-quality early childhood systems and implement the federal Workforce Innovation and Opportunity Act (WIOA) and Every Student Succeeds Act (ESSA), having detailed knowledge of the characteristics of immigrant parents can help maximize the effectiveness of programs that seek to improve child and family outcomes, as this commentary explains.

Findings will be discussed during 25 February MPI Europe – SVR webinar

Since the beginning, Inoreader was meant to be a power-user tool, pushing the boundaries of what RSS readers can do.…