74 research outputs found
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Comparative Study of Xenobiotic-Free Media for the Cultivation of Human Limbal Epithelial Stem/Progenitor Cells.
The culture of human limbal epithelial stem/progenitor cells (LSCs) in the presence of animal components poses the risk of cross-species contamination in clinical applications. We quantitatively compared different xenobiotic-free culture media for the cultivation of human LSCs. LSCs were cultured from 2 × 2 mm limbal tissue explants on denuded human amniotic membrane with different xenobiotic-free culture media: CnT-Prime (CnT-PR) supplemented with 0%, 1%, 5%, and 10% human serum (HS), embryonic stem cell medium (ESCM) alone or in combination with the standard supplemented hormonal epithelium medium (SHEM, control) at a 1:1 dilution ratio, and modified SHEM (mSHEM), in which cholera toxin and dimethyl sulfoxide (DMSO) were removed, isoproterenol was added, and the epidermal growth factor concentration was reduced. Several parameters were quantified to assess the LSC phenotype: cell morphology, cell growth, cell size, outgrowth size, and expression of the undifferentiated LSC markers cytokeratin (K) 14, and p63α high-expressing (p63αbright) cells, a mature keratinocyte marker K12, epithelial marker pancytokeratin (PanK), and stromal cell marker vimentin (Vim). Compared with the standard SHEM control, CnT-PR base medium was associated with a lower cell growth and reduction in the proportion of stem cells generated regardless of the amount of HS supplemented (p < 0.05); ESCM resulted in an increased proportion of PanK-/Vim+ stromal cells (p < 0.05) and a decreased proportion of p63αbright cells (p < 0.05); mSHEM supported a similar cell growth (p > 0.05), increased the number of small cells (diameter ≤12 μm; p < 0.05), and provided a similar proportion of p63αbright cells (p > 0.05). Among all the conditions tested, mSHEM was the most efficient and consistent in supporting the LSC phenotype and growth
Adenosine, bridging chronic inflammation and tumor growth
Adenosine (Ado) is a well-known immunosuppressive agent that may be released or generated extracellularly by cells, via degrading ATP by the sequential actions of the ectonucleotides CD39 and CD73. During inflammation Ado is produced by leukocytes and tissue cells by different means to initiate the healing phase. Ado downregulates the activation and the effector functions of different leukocyte (sub-) populations and stimulates proliferation of fibroblasts for re-establishment of intact tissues. Therefore, the anti-inflammatory actions of Ado are already intrinsically triggered during each episode of inflammation. These tissue-regenerating and inflammation-tempering purposes of Ado can become counterproductive. In chronic inflammation, it is possible that Ado-driven anti-inflammatory actions sustain the inflammation and prevent the final clearance of the tissues from possible pathogens. These chronic infections are characterized by increased tissue damage, remodeling and accumulating DNA damage, and are thus prone for tumor formation. Developing tumors may further enhance immunosuppressive actions by producing Ado by themselves, or by “hijacking” CD39+/CD73+ cells that had already developed during chronic inflammation. This review describes different and mostly convergent mechanisms of how Ado-induced immune suppression, initially induced in inflammation, can lead to tumor formation and outgrowth
Serum uromodulin and progression of kidney disease in patients with chronic kidney disease
Abstract
Background
Uromodulin is specifically synthesized and secreted by kidney tubular epithelial cells. Studies on the association of serum uromodulin and outcomes of chronic kidney disease (CKD) are lacking. This study aimed to evaluate whether serum uromodulin was associated with outcomes of patients with CKD.
Methods
We measured serum uromodulin concentrations by ELISA in 2652 CKD patients from the Chinese Cohort Study of Chronic Kidney Disease (C-STRIDE) and investigated the association of serum uromodulin with outcomes of CKD patients, including end-stage kidney disease (ESKD) receiving kidney replacement therapy, cardiovascular events and mortality by Cox proportional hazards regression model.
Results
A total of 2652 CKD patients were enrolled in this study, with an age of 48.7 ± 13.8 years and the baseline eGFR of 49.6 ± 29.4 mL/min/1.73 m2, of whom 58.4% were male. The median level of urinary albumin/creatinine ratio and serum uromodulin was 473.7 mg/g (IQR 134.1–1046.6 mg/g) and 77.2 ng/mL (IQR 48.3–125.9 ng/mL), respectively. Altogether, 404 ESKD, 189 cardiovascular events, and 69 deaths occurred during the median follow-up of 53.6 (IQR 44.0–64.0) months. Lower levels of serum uromodulin were independently associated with higher risk of incident ESKD after adjusting for traditional cardiovascular risk factors, with the hazard ratios (HRs) of 3.23 (95% confidence intervals [CIs] 2.15–4.85) for the middle tertile and 7.47 (95% CI 5.06–11.03) for the bottom tertile, compared with top tertile and 0.31 (95% CI 0.25–0.38) per every standard deviation increase. After further adjustment for the baseline eGFR, the association was greatly attenuated, but still significant, with HRs of 1.92 (95% CI 1.26–2.90) for the bottom tertile compared with top tertile and 0.69 (95% CI 0.55–0.86) per every standard deviation increase.
Conclusions
Serum uromodulin is independently associated with an increased risk of incident ESKD in CKD patients.https://deepblue.lib.umich.edu/bitstream/2027.42/146520/1/12967_2018_Article_1693.pd
Ground and Top of Canopy Extraction From Photon-Counting LiDAR Data Using Local Outlier Factor With Ellipse Searching Area
Seasonality of the transmissibility of hand, foot and mouth disease: a modelling study in Xiamen City, China.
This study attempts to figure out the seasonality of the transmissibility of hand, foot and mouth disease (HFMD). A mathematical model was established to calculate the transmissibility based on the reported data for HFMD in Xiamen City, China from 2014 to 2018. The transmissibility was measured by effective reproduction number (Reff) in order to evaluate the seasonal characteristics of HFMD. A total of 43 659 HFMD cases were reported in Xiamen, for the period 2014 to 2018. The median of annual incidence was 221.87 per 100 000 persons (range: 167.98/100,000-283.34/100 000). The reported data had a great fitting effect with the model (R2 = 0.9212, P < 0.0001), it has been shown that there are two epidemic peaks of HFMD in Xiamen every year. Both incidence and effective reproduction number had seasonal characteristics. The peak of incidence, 1-2 months later than the effective reproduction number, occurred in Summer and Autumn, that is, June and October each year. Both the incidence and transmissibility of HFMD have obvious seasonal characteristics, and two annual epidemic peaks as well. The peak of incidence is 1-2 months later than Reff
Giant Merkel cell carcinoma of the eyelid: a case report and review of the literature
Merkel cell carcinoma (MCC) is a rare cutaneous tumor and cases located in the eyelid have been described, but still its rarity may lead to difficulty in diagnosis and delay in treatment. A 51-year-old female patient that presented with large lesions in the eyelid underwent surgery after the diagnosis of acute chalazion. Following respiratory distress secondary to pulmonary metastasis, the patient's condition deteriorated and was not fit for complete excision treatment. Histopathological investigation of the biopsies, taken from the tumor, revealed that it was undifferentiated small cell carcinoma. Our aim with this paper is to point out that more cases should be reported for more effective diagnosis, histopathological study, clinical investigation, treatment and prognosis of this specific neoplasm
Development of Risk Prediction Equations for Incident Chronic Kidney Disease
IMPORTANCE ‐ Early identification of individuals at elevated risk of developing chronic kidney disease
could improve clinical care through enhanced surveillance and better management of underlying health
conditions.
OBJECTIVE – To develop assessment tools to identify individuals at increased risk of chronic kidney
disease, defined by reduced estimated glomerular filtration rate (eGFR).
DESIGN, SETTING, AND PARTICIPANTS – Individual level data analysis of 34 multinational cohorts from
the CKD Prognosis Consortium including 5,222,711 individuals from 28 countries. Data were collected from April, 1970 through January, 2017. A two‐stage analysis was performed, with each study first
analyzed individually and summarized overall using a weighted average. Since clinical variables were often differentially available by diabetes status, models were developed separately within participants
with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external
cohorts (N=2,253,540).
EXPOSURE Demographic and clinical factors.
MAIN OUTCOMES AND MEASURES – Incident eGFR <60 ml/min/1.73 m2.
RESULTS – In 4,441,084 participants without diabetes (mean age, 54 years, 38% female), there were
660,856 incident cases of reduced eGFR during a mean follow‐up of 4.2 years. In 781,627 participants
with diabetes (mean age, 62 years, 13% female), there were 313,646 incident cases during a mean
follow‐up of 3.9 years. Equations for the 5‐year risk of reduced eGFR included age, sex, ethnicity, eGFR,
history of cardiovascular disease, ever smoker, hypertension, BMI, and albuminuria. For participants
with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction
between the two. The risk equations had a median C statistic for the 5‐year predicted probability of
0.845 (25th – 75th percentile, 0.789‐0.890) in the cohorts without diabetes and 0.801 (25th – 75th
percentile, 0.750‐0.819) in the cohorts with diabetes. Calibration analysis showed that 9 out of 13 (69%)
study populations had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was
similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 out of 18
(89%) had a slope of observed to predicted risk between 0.80 and 1.25.
CONCLUSIONS AND RELEVANCE – Equations for predicting risk of incident chronic kidney disease
developed in over 5 million people from 34 multinational cohorts demonstrated high discrimination and
variable calibration in diverse populations
Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes. An Individual-Participant Data Meta-Analysis
IMPORTANCE: Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US. OBJECTIVE: To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes. DESIGN, SETTING, AND PARTICIPANTS: Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021. EXPOSURES: The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR). MAIN OUTCOMES AND MEASURES: The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses. RESULTS: Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years]). CONCLUSIONS AND RELEVANCE: In this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations
International benchmarking of terrestrial laser scanning approaches for forest inventories
The last two decades have witnessed increasing awareness of the potential of terrestrial laser scanning (TLS) in forest applications in both public and commercial sectors, along with tremendous research efforts and progress. It is time to inspect the achievements of and the remaining barriers to TLS-based forest investigations, so further research and application are clearly orientated in operational uses of TLS. In such context, the international TLS benchmarking project was launched in 2014 by the European Spatial Data Research Organization and coordinated by the Finnish Geospatial Research Institute. The main objectives of this benchmarking study are to evaluate the potential of applying TLS in characterizing forests, to clarify the strengths and the weaknesses of TLS as a measure of forest digitization, and to reveal the capability of recent algorithms for tree-attribute extraction. The project is designed to benchmark the TLS algorithms by processing identical TLS datasets for a standardized set of forest attribute criteria and by evaluating the results through a common procedure respecting reliable references. Benchmarking results reflect large variances in estimating accuracies, which were unveiled through the 18 compared algorithms and through the evaluation framework, i.e., forest complexity categories, TLS data acquisition approaches, tree attributes and evaluation procedures. The evaluation framework includes three new criteria proposed in this benchmarking and the algorithm performances are investigated through combining two or more criteria (e.g., the accuracy of the individual tree attributes are inspected in conjunction with plot-level completeness) in order to reveal algorithms’ overall performance. The results also reveal some best available forest attribute estimates at this time, which clarify the status quo of TLS-based forest investigations. Some results are well expected, while some are new, e.g., the variances of estimating accuracies between single-/multi-scan, the principle of the algorithm designs and the possibility of a computer outperforming human operation. With single-scan data, i.e., one hemispherical scan per plot, most of the recent algorithms are capable of achieving stem detection with approximately 75% completeness and 90% correctness in the easy forest stands (easy plots: 600 stems/ha, 20 cm mean DBH). The detection rate decreases when the stem density increases and the average DBH decreases, i.e., 60% completeness with 90% correctness (medium plots: 1000 stem/ha, 15 cm mean DBH) and 30% completeness with 90% correctness (difficult plots: 2000 stems/ha, 10 cm mean DBH). The application of the multi-scan approach, i.e., five scans per plot at the center and four quadrant angles, is more effective in complex stands, increasing the completeness to approximately 90% for medium plots and to approximately 70% for difficult plots, with almost 100% correctness. The results of this benchmarking also show that the TLS-based approaches can provide the estimates of the DBH and the stem curve at a 1–2 cm accuracy that are close to what is required in practical applications, e.g., national forest inventories (NFIs). In terms of algorithm development, a high level of automation is a commonly shared standard, but a bottleneck occurs at stem detection and tree height estimation, especially in multilayer and dense forest stands. The greatest challenge is that even with the multi-scan approach, it is still hard to completely and accurately record stems of all trees in a plot due to the occlusion effects of the trees and bushes in forests. Future development must address the redundant yet incomplete point clouds of forest sample plots and recognize trees more accurately and efficiently. It is worth noting that TLS currently provides the best quality terrestrial point clouds in comparison with all other technologies, meaning that all the benchmarks labeled in this paper can also serve as a reference for other terrestrial point clouds sources.</p
A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology
The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the development of the community-based Coronavirus Infectious Disease Ontology in early 2020.
As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment.
CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications
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