Quantification Of Indices Research Articles

The Effects of Varied Neutral Detergent Fiber Levels on Blood Parameters, Nutrient Digestibility, Rumen Fermentation Characteristics and Rumen Tissue Morphology in Lambs

Background: Neutral detergent fiber is a common analytical measure of feed fiber content, which could play an important role as an energy source, improve the rumen ecosystem and thus improve growth performance of lambs. The aim of this study was to investigate the effects of different levels of neutral detergent fibers on growth performance, blood parameters, nutrient digestibility, volatile fatty acid concentration, ammonia nitrogen, bacterial quantification, gas production and tissue morphology of growing lambs. Methods: Seventy-two Awassi lambs of weaning age were randomly assigned to three experimental feeds with different levels of neutral detergent fiber: low (210 g/kg), medium (280 g/kg) and high (350 g/kg), each with eight replicates in a completely randomized design. The growth performance parameters were evaluated over a trial period of 84 days. At the end of the trial, hematological and serum biochemical parameters and nutrient digestibility were evaluated. In addition, rumen fermentation characteristics, including pH, ammonia-nitrogen, gas production, volatile fatty acids, bacterial quantification and indices of rumen morphology indices were measured. Result: The results showed that lambs fed a medium-neutral detergent fiber feed had better growth performance (p less than 0.05). In addition, this experimental feed showed improvements in some blood parameters (WBC, RBC, HGB, TP, GLOB and GLU) and nutrient digestibility with the exception of crude protein and ash (p less than 0.05). Rumen fermentation characteristics and rumen morphology were also positively influenced by the medium- neutral detergent fiber level (p less than 0.05). These results indicate that a medium level of neutral detergent fiber (280 g/kg) is essential for optimal growth, health and rumen development in growing lambs.

Quantitative assessment of correlation between compressive strength degradation and microstructural crack information in mortar deteriorated by freeze-thaw cycles

Freeze-thaw cycle (FTC) deterioration poses significant durability challenges to concrete structures. However, the detailed quantitative relationship between FTC-induced internal damage pattern development and mechanical degradation remains underexplored, limiting the accuracy of FTC deterioration assessments. This study aims to provide a comprehensive analysis of microstructural damage progression and its quantitative relationship with mechanical degradation in mortar specimens throughout FTC process. Through establishing an experimental setup applied to specimens at two scales and facilitated by micro-computed tomography (micro-CT), this research concurrently evaluates the microstructural damage progression, mechanical degradation, and expansion of the specimens under various FTC severity levels. The quantification of multiple crack indices reveals a stronger correlation between compressive strength reduction and crack ingression than with increases in crack quantity or width. The findings further highlight the imperative to incorporate both expansion-induced damage and time-dependent fatigue damage in evaluating FTC deterioration, thus laying a foundation for refining FTC prediction models.

Depleting spring sources in the Himalayas: Environmental drivers or just perception?

Study regionRangun Khola Watershed, Mahakali River Basin, Far Western Nepal. Study focusWe mapped and examined the status of 1122 springs in a typical mid-hill watershed in the Sudurpaschim Province of Nepal. Land use/cover trajectory analysis, quantification of climate change indices, analysis of spring flow trends and community perception were used to understand the changing dynamics of the mountain springs. New hydrological insights73% of the springs show a continuous declining trend in flow, with 2% already dried up. Land fragmentation between 1990 and 2018 due to the conversion to agricultural land causes landscape disturbances in the spring vicinities, affecting natural spring flows. Climate data assessment revealed a significant increase in temperature and frequency of localised high-intensity rainfall. Local climate and land use change are concurrent with drying spring sources and consistent with the local community's perceived manifestation of changes. Moreover, the growing population and haphazard rural road expansion are overexploiting and disturbing the spring resources. Drying spring sources are leading to implications on water availability and accessibility for livelihood activities, exacerbating gendered vulnerability to climate change. However, the government and local households are lagging in taking direct actions to mitigate the problem, increasing the likelihood of critical long-term consequences for the ecosystem and the local economy in Rangun Khola and similar watersheds in the Himalayas.

Identification of a Novel Mesenchymal Stem Cell-Related Signature for Predicting the Prognosis and Therapeutic Responses of Bladder Cancer.

Background: Mesenchymal stem cells (MSCs) have been identified to have a unique migratory pattern toward tumor sites across diverse cancer types, playing a crucial role in cancer progression, treatment resistance, and immunosuppression. This study aims to formulate a prognostic model focused on MSC-associated markers to efficiently predict the clinical outcomes and responses to therapy in individuals with bladder cancer (BC). Methods: Clinical and transcriptome profiling data were extracted from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) and GSE31684 databases. Systematic quantification of MSC prevalences and stromal indices was undertaken, culminating in the discernment of genes correlated with stromal MSCs following a thorough application of weighted gene coexpression network analysis techniques. Subsequently, an exhaustive risk signature pertinent to MSC was formulated by amalgamating methods from univariate and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression models. Drugs targeting genes associated with MSCs were screened using molecular docking. Results: The prognostic model for MSC incorporated five critical genes: ZNF165, matrix remodeling-associated 7 (MXRA7), CEMIP, ADP-ribosylation factor-like 4C (ARL4C), and cerebral endothelial cell adhesion molecule (CERCAM). In the case of BC patients, stratification was performed into discrete risk categories, utilizing the median MSC risk score as a criterion. It was striking that those classified within the high-MSC-risk bracket demonstrated correlations with unfavorable prognostic implications. Enhanced responsiveness to immunotherapy in low-MSC-risk patients was delineated compared to their high-MSC-risk counterparts. A heightened receptivity was noted toward particular chemotherapy drugs, encompassing gemcitabine, vincristine, paclitaxel, gefitinib, and sorafenib, within this high-risk group. Conversely, a superior reaction to cisplatin was distinctly evident among those marked by low MSC scores. The results of molecular docking demonstrated that kaempferol exhibited favorable docking with ZNF165, quercetin exhibited favorable docking with MXRA7, mairin exhibited favorable docking with CEMIP, and limonin diosphenol exhibited favorable docking with ARL4C. Conclusions: The five-gene MSC prognostic model demonstrates substantial efficacy in prognosticating clinical outcomes and gauging responsiveness to chemotherapy and immunotherapy regimens. The genes ZNF165, MXRA7, CEMIP, ARL4C, and CERCAM are underscored as promising candidates warranting further exploration for anti-MSC therapeutic strategies, thereby offering novel insights for personalized treatment approaches in BC.

Investigation on bonding behavior between CFRP patch and corrosion-damaged steel associated with surface preparation techniques

To assess the impact of corrosion on steel and the effectiveness of surface preparation techniques on the bonding behavior between carbon fiber reinforced polymer (CFRP) and steel, thirty bonded joint specimens were examined. These specimens were based on three distinct corrosion levels of steel and three conventional surface preparation techniques. Furthermore, various evaluation methods were employed to understand the steel surface characteristics, encompassing macro and microscale observations, analysis of topographical structures, and quantification of surface evaluation indices. These were performed to determine their correlations with the interfacial stress behavior. The findings revealed that when the target for repair shifted from a new steel substrate to a corroded one, the synergistic performance at the steel-adhesive interface decreased. This led to a decrease in the maximum shear stress at the plate end, and there was also an undesirable shift in the mode of failure. Both test parameters (i.e., the corrosion level and surface preparation), synergistically determined the surface cleanliness, topography, and bonding defects, all three of which directly influenced the bonding behavior. Finally, an improved model for predicting the debonding capacity of CFRP-corroded steel bonded joints was introduced, incorporating surface damage (k1) and surface topography (k2) coefficients. This model's applicability was also verified by collecting other test data from available literature.

Anesthetic modulation of water diffusion: Insights from a diffusion tensor imaging study.

Diffusion tensor imaging (DTI) in animal models are essential for translational neuroscience studies. A critical step in animal studies is the use of anesthetics. Understanding the influence of specific anesthesia regimes on DTI-derived parameters, such as fractional anisotropy (FA) and mean diffusivity (MD), is imperative when comparing results between animal studies using different anesthetics. Here, the quantification of FA and MD under different anesthetic regimes, alpha-chloralose and isoflurane, is discussed. We also used a range of b-values to determine whether the anesthetic effect was b-value dependent. The first group of rats (n=6) was anesthetized with alpha-chloralose (80mg/kg), whereas the second group of rats (n=7) was anesthetized with isoflurane (1.5%). DTI was performed with b-values of 500, 1500, and 1500s/mm2, and the MD and FA were assessed individually. Anesthesia-specific differences in MD were apparent, as manifested by the higher estimated MD under isoflurane anesthesia than that under alpha-chloralose anesthesia (P<0.001). MD values increased with decreasing b-value in all regions studied, and the degree of increase when rats were anesthetized with isoflurane was more pronounced than that associated with alpha-chloralose (P<0.05). FA quantitation was also influenced by anesthesia regimens to varying extents, depending on the brain regions and b-values. In conclusion, both scanning parameters and the anesthesia regimens significantly impacted the quantification of DTI indices.

Evidence for microstructural alteration and microvascular disease in subclinical and overt hypertrophic cardiomyopathy

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): British Heart Foundation - Clinical Research Training Fellowship Background Disarray and microvascular disease (MVD) are implicated in adverse events in hypertrophic cardiomyopathy (HCM). Advances in CMR permit quantification of microstructural indices reflecting disarray, and microvascular disease. As novel myosin inhibitors provide promise for disease modification, early and disease-specific biomarkers are a rapidly emerging clinical priority. Purpose Using latest imaging techniques, we investigated MVD and disarray in 3 HCM groups: overt disease, either genotype positive (G+LVH+) or negative (G-LVH+), and subclinical HCM (G+LVH-), exploring relationships to electrical changes and genetic substrate. Methods A 207 subject, multi-centre consortium: 102 patients with overt HCM (52 G+LVH+, 50 G-LVH+), 77 subclinical (G+LVH-) and 28 matched healthy volunteers (HV). All underwent ECG, quantitative perfusion (measuring myocardial blood flow (MBF), perfusion reserve (MPR) and perfusion defects) and cardiac diffusion tensor imaging (cDTI) to investigate for evidence of disarray, measured as fractional anisotropy (FA – the directional variability of diffusion, reflecting myocyte disarray), mean diffusivity (MD – reflecting myocyte packing and intra- and extracellular volume) and absolute second eigenvector angle (E2A –measuring orientation of sheetlets, functional units of myocytes that re-orientate to facilitate wall-thickening). Results Compared to HV, overt HCM had evidence of microstructural alteration (lower FA (suggestive of disarray), higher MD and higher E2A, all p&amp;lt;0.001) and MVD (lower stress MBF and MPR p&amp;lt;0.001). Compared to G+LVH+, G-LVH+ had elevated E2A (64.4°(58.7–66.5) vs 60.1°(55.6–63.7 p = 0.006)). Perfusion defects were found in all G+ but not all G- overt disease (100%(52/52) vs 82%(41/50) p = 0.001). Compared to HV, subclinical HCM (G+LVH-) had evidence of microstructural alteration (lower FA suggestive of disarray, higher MD and higher E2A, all p&amp;lt;0.001) and MVD (reduced stress MBF (2.43±0.52 vs 2.77±0.62ml/g/min p = 0.006) with perfusion defects in 29% (vs 0 HV p = 0.001)). Microstructural markers and MVD were independently associated, in both overt and subclinical disease (overt: E2A and stress MBF: β=-0.29, p = 0.002; subclinical: those with perfusion defects (vs without) had lower FA &amp; higher E2A). Disarray markers and MVD independently associated with pathological ECG abnormalities in both overt and subclinical disease, after adjustment for degree of fibrosis and LVH (overt: FA odds ratio (OR) for abnormal ECG=3.2, p = 0.014; stress MBF OR=2.8, p = 0.013; subclinical: FA OR=3.4, p = 0.006, MPR OR=4.0 p = 0.008). Conclusions In Hypertrophic Cardiomyopathy, sarcomere mutation carriers without hypertrophy have microstructural alterations and microvascular disease that are detectable, correlate, and associate with pathological ECG changes. These are more prominent once LVH is present, with genotype positive and genotype negative overt disease patients having differing phenotypes.

Taphonomical and palaeoenvironmental analyses of the microvertebrate fossil material from the Late Pleistocene cave of Kalamakia (Mani peninsula), Greece

ABSTRACT The present study focuses on the microvertebrate fossil material retrieved from the three fossiliferous units of Kalamakia cave dating from ca. 90–25 kya BP, to identify the accumulation agents of the assemblage and the processes that affected it post-depositionally. This was done through the quantification of specific indices described in the literature concerning breakage, digestion and other types of modifications observed upon the surface of the specimens. Furthermore, the Taxonomic Habitat Index was calculated to reconstruct the possible habitat types in the surrounding area. Regarding the results on taphonomy, significant amounts of post-depositional breakage were observed, possibly resulting from trampling and, secondarily, modifications from the occasionally naturally occurring high humidity within a cave. The main accumulators of the microvertebrate assemblage seem to have been barn owls either independently or jointly with long-eared owls and/or owlets. Concerning the habitats possibly present in the area, the existence of mixed habitats varying between relative expansions of shrublands, grasslands, rocky areas and (limited) deciduous forests was identified, while the occasional presence of water bodies was also revealed. Shifts between the percentages of different habitats were not great but could be correlated with climatic events within a geochronological context.

Maize response to irrigation and nitrogen under center pivot, subsurface drip and furrow irrigation: Water productivity, basal evapotranspiration and yield response factors

Information and data about quantification and comparison of crop water productivity indices for various irrigation levels and methods and nitrogen (N) application timings “simultaneously” under the same conditions do not exist. Unprecedented and extensive field experiments were conducted for maize (Zea mays L.) in 2016 and 2017 under center pivot (CP), subsurface drip irrigation (SDI) and furrow irrigation (FI) methods with full irrigation treatment (FIT), 80 % FIT, 60 % FIT and rainfed treatment (RFT) with three N application timings. N treatments were: (i) traditional (TN), (ii) non-traditional-1 (NT-1) and (iii) non-traditional-2 (NT-2). Irrigation-yield production functions (IYPF); evapotranspiration-yield production functions (ETYPF), basal evapotranspiration (ETb), crop water productivity (CWP), irrigation water use efficiency (IWUE); evapotranspiration water use efficiency (ETWUE) and yield response factors (Ky) were quantified for each treatment and irrigation method. SDI method required the least seasonal irrigation amount in achieving maximum yield, followed by CP (>~30 mm more than SDI) and FI (>~55 mm more than SDI). Average crop water requirement for achieving maximum grain yield varied among the N treatments within and between the irrigation methods. Irrigation amounts for achieving maximum yields were about 160, 175 and 175 mm in TN, NT-1 and NT-2 nitrogen treatments, respectively, in the CP method; 130, 150 and 150 mm in TN, NT-1 and NT-2 nitrogen treatments, respectively, in the SDI method; and 184 mm in TN management in the FI method. The highest grain yield production per 25.4 mm of applied irrigation followed the order of CP-TN (2.07 Mg ha−1)>SDI-NT-2 (1.91 Mg ha−1)>FI-TN (1.22 Mg ha−1). Across all treatments for the given irrigation method, the highest averaged CWP of 3.00 kg m−3 (slope = 0.067 kg m−3) was observed in the SDI method (p < 0.05) followed by 2.84 kg m−3 (slope = 0.052 kg m−3) in the CP method (p < 0.05) and 2.51 kg m−3 (slope = 0.046 kg m−3) in the FI method. The lowest ETb was observed in FI-TN (169 mm), followed by CP-NT-2 (172 mm) and SDI-TN (255 mm). For two consecutive years, N treatments did not have significant (p > 0.05) influence on IWUE in the CP or SDI methods. The highest IWUE, CWP and ETWUE were always obtained with limited irrigation treatments (60 % FIT and/or 80 % FIT) whereas the lowest with FIT. Maize under limited irrigation management had Ky < 1 with CP, SDI and FI along with lower Ky values than the respective TN treatment in CP and SDI, suggesting that the yield reduction is impacted to a lesser degree from the magnitude of water stress. The overall conclusion disclosed that utilizing the combination of limited irrigation (80 % FIT) with NT-1 fertigation under SDI and CP, while 80 % FIT under FI can be viable management practices for achieving high grain yield and CWP in conditions similar to those presented in this research.

Real-time echocardiography image analysis and quantification of cardiac indices.

Deep learning has a huge potential to transform echocardiography in clinical practice and point of care ultrasound testing by providing real-time analysis of cardiac structure and function. Automated echocardiography analysis is benefited through use of machine learning for tasks such as image quality assessment, view classification, cardiac region segmentation, and quantification of diagnostic indices. By taking advantage of high-performing deep neural networks, we propose a novel and eicient real-time system for echocardiography analysis and quantification. Our system uses a self-supervised modality-specific representation trained using a publicly available large-scale dataset. The trained representation is used to enhance the learning of target echo tasks with relatively small datasets. We also present a novel Trilateral Attention Network (TaNet) for real-time cardiac region segmentation. The proposed network uses a module for region localization and three lightweight pathways for encoding rich low-level, textural, and high-level features. Feature embeddings from these individual pathways are then aggregated for cardiac region segmentation. This network is fine-tuned using a joint loss function and training strategy. We extensively evaluate the proposed system and its components, which are echo view retrieval, cardiac segmentation, and quantification, using four echocardiography datasets. Our experimental results show a consistent improvement in the performance of echocardiography analysis tasks with enhanced computational eiciency that charts a path toward its adoption in clinical practice. Specifically, our results show superior real-time performance in retrieving good quality echo from individual cardiac view, segmenting cardiac chambers with complex overlaps, and extracting cardiac indices that highly agree with the experts’ values. The source code of our implementation can be found in the project ‘ s GitHub page.

In vitro measurement of hepatic flow distribution in Fontan vascular conduits: Towards rapid validation techniques

Fontan operation is the last stage of single-ventricle surgical reconstructions that connects superior and inferior vena cava (SVC, IVC) to the pulmonary arteries. The key design objectives in total cavopulmonary connections (TCPC) are to achieve low power loss (PL) and balanced hepatic flow distribution (HFD). Computational fluid dynamics (CFD) played a pivotal role in pre-surgical design of single-ventricle patients. However, the clinical application of current CFD techniques is limited due to their complexity, high computational time and untested accuracy for HFD prediction. This study provides a performance assessment of computationally low-cost steady Reynolds-Averaged Navier-Stokes (RANS) k-ɛ turbulent models for simulation of Fontan hemodynamics. The performance is evaluated based on prediction accuracy for three clinically important Fontan hemodynamic indices: HFD, PL and total pulmonary flow split (TPFS). For this purpose, a low-cost experimental technique is developed for rapid quantification of Fontan performance indices. Experiments and simulations are performed for both an idealized and a complex 3D reconstructed patient-specific TCPC. Time-averaged flow data from phase contrast MRI was used as the boundary conditions for the patient-specific model. For the idealized model, different SVC/IVC flow ratios corresponding to different cardiac outputs and Reynolds’ numbers were examined. This study revealed that steady RANS k-ɛ models are able to estimate the Fontan hemodynamic indices with acceptable accuracy within minutes. Among these, standard k-ɛ two-layer was found to deliver the best agreement with the in vitro data with an average error percentage of 1.7, 2.0 and, 3.9 for HFD, TPFS and, PL, respectively for all cases.

Fully automated quantification of cardiac chamber and function assessment in 2-D echocardiography: clinical feasibility of deep learning-based algorithms

We aimed to compare the segmentation performance of the current prominent deep learning (DL) algorithms with ground-truth segmentations and to validate the reproducibility of the manually created 2D echocardiographic four cardiac chamber ground-truth annotation. Recently emerged DL based fully-automated chamber segmentation and function assessment methods have shown great potential for future application in aiding image acquisition, quantification, and suggestion for diagnosis. However, the performance of current DL algorithms have not previously been compared with each other. In addition, the reproducibility of ground-truth annotations which are the basis of these algorithms have not yet been fully validated. We retrospectively enrolled 500 consecutive patients who underwent transthoracic echocardiogram (TTE) from December 2019 to December 2020. Simple U-net, Res-U-net, and Dense-U-net algorithms were compared for the segmentation performances and clinical indices such as left atrial volume (LAV), left ventricular end diastolic volume (LVEDV), left ventricular end systolic volume (LVESV), LV mass, and ejection fraction (EF) were evaluated. The inter- and intra-observer variability analysis was performed by two expert sonographers for a randomly selected echocardiographic view in 100 patients (apical 2-chamber, apical 4-chamber, and parasternal short axis views). The overall performance of all DL methods was excellent [average dice similarity coefficient (DSC) 0.91 to 0.95 and average Intersection over union (IOU) 0.83 to 0.90], with the exception of LV wall area on PSAX view (average DSC of 0.83, IOU 0.72). In addition, there were no significant difference in clinical indices between ground truth and automated DL measurements. For inter- and intra-observer variability analysis, the overall intra observer reproducibility was excellent: LAV (ICC = 0.995), LVEDV (ICC = 0.996), LVESV (ICC = 0.997), LV mass (ICC = 0.991) and EF (ICC = 0.984). The inter-observer reproducibility was slightly lower as compared to intraobserver agreement: LAV (ICC = 0.976), LVEDV (ICC = 0.982), LVESV (ICC = 0.970), LV mass (ICC = 0.971), and EF (ICC = 0.899). The three current prominent DL-based fully automated methods are able to reliably perform four-chamber segmentation and quantification of clinical indices. Furthermore, we were able to validate the four cardiac chamber ground-truth annotation and demonstrate an overall excellent reproducibility, but still with some degree of inter-observer variability.

Effects of NMDA receptor antagonists on behavioral economic indices of cocaine self-administration

BackgroundCurrently, there are no FDA-approved medications for the treatment of psychostimulant (e.g., cocaine) use disorders. Because the GluN2B subunit of the glutamate N-methyl-D-aspartate (NMDA) receptor is an important mediator of addiction-like behaviors, the goal of the current study was to determine if the GluN2B-selective antagonist Ro 63–1908 is efficacious in attenuating cocaine self-administration. MethodsAdult Sprague Dawley rats (24 males and 11 females) were implanted with indwelling catheters and were trained to self-administer cocaine (0.75 mg/kg/inf). Rats were then trained in a threshold procedure, in which the dose of cocaine decreased across six 6-min blocks (0.75, 0.27, 0.08, 0.03, 0.01, 0.003 mg/kg/inf). This procedure allowed for the quantification of behavioral economic indices of drug self-administration. Following training in the threshold procedure, rats were treated with the GluN2B-selective antagonist Ro 63–1908 (0, 0.1, 0.3, 1.0 mg/kg; s.c.). Rats also received treatments of the NMDA receptor channel blocker MK-801 (0, 0.01, 0.03, 0.06 mg/kg; s.c.). ResultsBlocking NMDA receptors decreased initial intake (i.e., consumption during the first block), although Ro 63–1908 and MK-801 increased area under the curve (global measure of demand) and decreased demand elasticity, an effect observed primarily in males. Neither drug affected demand intensity (i.e., consumption of cocaine at a minimally constrained price). ConclusionsWhile blocking the NMDA receptor decreases initial intake of cocaine, NMDA receptor antagonists make cocaine more inelastic with increasing price. These results suggest that NMDA receptor antagonists can exacerbate addiction-like behaviors during self-administration during extinction-like conditions that are observed in later blocks of the threshold procedure.

Aesthetic and Implication Analysis of the Traditional Poetic Environment Based on Natural Language Emotion Analysis.

The uniqueness of aesthetic implication in Zhou Dynasty poetics lies in that it is the basic forming stage of the concept of formal beauty of the whole Chinese nation, and the aesthetic implication of the Zhou Dynasty poetics art has fundamental significance for the whole ancient Chinese aesthetic implication theory. In the discipline of natural language processing, text emotion analysis is a crucial topic. Artificial neural network research is where the idea of “deep learning” (DL) first emerged. In view of the problems that semantic information is easy to be lost and emotional information may be ignored in the traditional Chinese short text emotion analysis model, this paper introduces the AM (attention mechanism) and proposes a CNN-LSTM (convolutional neural network-long short-term memory) poetic aesthetic implication analysis method based on self-attention. For the IL (input layer), word vectors trained by Word2Vec are used and then input into the CNN-LSTM joint model. Then, the output of the joint model is weighted and summed by self-attention and finally input into the Softmax classifier, so as to realize the emotion classification of the text. By creating and putting into practise pertinent comparative experiments, the usefulness of the proposed model is confirmed. The outcomes demonstrate that this model outperforms the other three comparison models for the quantification of evaluation indices in terms of overall performance. The accuracy and F1 of this paper are 93.362% and 90.886%, respectively, which are higher than other models.

A statistical model of COVID-19 testing in populations: effects of sampling bias andtesting errors.

We develop a statistical model for the testing of disease prevalence in a population. The model assumes a binary test result, positive or negative, but allows for biases in sample selection and both type I (false positive) and type II (false negative) testing errors. Our model also incorporates multiple test types and is able to distinguish between retesting and exclusion after testing. Our quantitative framework allows us to directly interpret testing results as a function of errors and biases. By applying our testing model to COVID-19 testing data and actual case data from specific jurisdictions, we are able to estimate and provide uncertainty quantification of indices that are crucial in a pandemic, such as disease prevalence and fatality ratios.This article is part of the theme issue ‘Data science approach to infectious disease surveillance’.

Abstract 11594: Deep Learning of the Retina Enables Phenome- and Genome- Wide Analyses of the Microvasculature

Introduction: The retinal fundus is a window for non-invasive assessment of the microvasculature. However, the range of phenotypes and inherited genetic variants associated with the retinal microvasculature remain unknown. Hypothesis: Deep learning of retinal fundus images enables large-scale quantification of vascular indices and an unbiased assessment of phenotypes and genetic variants linked to the microvasculature. Methods: We utilized 97,895 retinal fundus images from 54,813 UK Biobank participants (ages 40-70y, 55% female). Using convolutional neural networks to segment vessels, we calculated vascular branching complexity using fractal dimension (FD), and vascular density, and associated these indices with 1,100 incident ICD-based conditions (median 10y follow-up) and 88 quantitative traits, adjusting for age, sex, smoking status, and ethnicity. Genome-wide association study (GWAS) among 38,932 unrelated individuals was performed. Results: Low retinal vascular FD and density were significantly associated with increased risk of incident hypertension, congestive heart failure, renal failure, type 2 diabetes, sleep apnea, anemia, and multiple ocular conditions. Low retinal vascular FD and density were also linked to quantitative traits including elevated blood pressure, anemia indices, abnormal pulmonary function tests, measures of metabolic disease (high HbA1c, % body fat, BMI), and ocular traits (decreased visual acuity and increased intraocular pressure). GWAS of vascular FD and density identified loci enriched among pathways linked to angiogenesis (VEGF, PDGFR, angiopoietin, and WNT signaling pathways), and inflammation (interleukin, cytokine signaling). Conclusions: Through phenotypic and genotypic analyses, our study showed that the retinal vasculature may serve as a biomarker for future cardiometabolic and ocular disease, and provided insights on genes and biological pathways influencing microvascular indices.

Quantitative analysis of retinal microvascular changes in prediabetic and diabetic patients.

Purpose:To evaluate and correlate retinal microvascular changes in prediabetic and diabetic patients with functional and systemic parameters.Methods:Optical coherence tomography angiography (OCTA) was performed on all subjects after medical evaluation and laboratory investigations for blood sugar, glycosylated hemoglobin, and others. Automated quantification of vascular indices of the superficial plexus were analyzed.Results:Hundred and eleven persons (222 eyes) were grouped into prediabetic (PDM) (60 eyes), diabetic without retinopathy (NDR) (56 eyes), diabetic with retinopathy (DR) (66 eyes), and healthy controls (CTR) (40 eyes). The superficial retinal capillary plexus showed no significant changes in the prediabetic and NDR groups; however, central foveal thickness (CFT) was significantly reduced in PDM (P = 0.04). The circularity of the foveal avascular zone (FAZ) (P = 0.03) and the vessel density (VD) (P = 0.01) showed significant reduction from PDM to NDR. All vascular parameters were significantly reduced in DR and correlated with disease severity. The CFT correlated significantly with FAZ area. The VD and perfusion density were seen to correlate significantly with HbA1c and contrast sensitivity. The visual acuity was significantly correlated with the FAZ. Logistic regression revealed VD [OR 20.42 (7.9–53)] and FAZ perimeter [OR 9.8 (4.2–23.2)] as the strongest predictors of DR.Conclusion:The changes in OCTA can help predict onset of DR. FAZ changes are seen in early stages and are correlated well with systemic parameters, making it an easy target to monitor and screen for severity of DR. Significant reduction in the CFT in PDM suggests that neuronal damage precedes vascular changes.

CLINICAL-STATISTICAL STUDY ON THE FREQUENCY AND ETIOLOGICAL FACTORS OF GINGIVAL HYPERPLASIA

Introduction. Gum hyperplasia is clinically translated by growth in gum size, edema and bleeding (over-normal bags). The gum may be thin or fibrous, firm (in pseudotumor forms). In the absence of proper treatment, it will be associated with the bone resorption of the alveolar process, leading to different degrees of dental mobility. Purpose. Through this clinical-statistical study, we aim to analyze patients diagnosed with gum hyperplasia by age, gender, type of gum hyperplasia, etiology and localization. Also, by observing in surgical practice more and more cases of gum hyperplasia in patients with orthodontic treatment, through this clinical-statistical study, we aim to quantify the incidence of gingival hyperplasia in orthodontic treatments carriers and its distribution by gender. Material and method. The study is retrospective type, performed on 172 patients with the diagnosis of gum hyperplasia (K06.1), treated in the Oro-maxillo-facial surgery Clinic in Targu Mures, during Jan.2015-march 2021. Hypocrate concept 3 was used to access patient observation sheets. Results and discussions. Analyzing the descriptive statistical data of this retrospective clinical-statistical study, it is observed that the average age of the subjects is 58 years, the distribution by sex favors the female gender (59%), generally occurs in adults, has affinity for the right hemimaxilla, approx. 25% of patients have gingival hyperplastic lesions caused by orthodontic appliances and mobile/mobilizable prostheses. These types of lesions represent a ratio of 2/1 in favor of females, which indicates that the aesthetic requirements for females are much higher compared to males. Also, interpreting, from a medical point of view, the statistical conclusions of this study, we find that the patient's gender does not influence the location and appearance of the hyperplasic lesion, instead the age of the patients influences the occurrence of the hyperplastic lesion. Conclusion. Orthodontic therapy should be indicated after a correct evaluation of periodontal tissues, quantification of periodontal indices and detection of risk factors.

Novel bionics developments in gastroenterology: fecobionics assessment of lower GI tract function

Biomechatronics (bionics) is an applied science that is interdisciplinary between biology and engineering (mechanical, electrical and electronics engineering). Biomechatronics covers a wide area and is probably best known in development of prosthetic limbs, vision aids, robotics and neuroscience. Although the gastrointestinal tract is difficult to study, it is particularly suited for a bionics approach as demonstrated by recent developments. Ingestible capsules that travel the tract and record physiological variables have been used in the clinic. Other examples include sacral nerve stimulators that seek to restore normal anorectal function. Recently, we developed a simulated stool termed fecobionics. It has the shape of normal stool and records a variety of parameters including pressures, bending (anorectal angle) and shape changes during colonic transit and defecation, i.e. it integrates several current tests. Fecobionics has been used to study defecation patterns in large animals as well as in humans (normal subjects and patient groups including patients with symptoms of obstructed defecation and fecal incontinence). Recently, it was applied in a canine colon model where it revealed patterns consistent with shallow waves originating from slow waves generated by the interstitial cells of Cajal. Furthermore, novel analysis such as the rear-front pressure (preload–afterload) diagram and quantification of defecation indices have been developed that enable mechanistic insight. This paper reviews the fecobionics technology and outlines perspectives for future applications.

Population Disequilibrium as Promoter of Adaptive Explorations in Hepatitis C Virus.

Replication of RNA viruses is characterized by exploration of sequence space which facilitates their adaptation to changing environments. It is generally accepted that such exploration takes place mainly in response to positive selection, and that further diversification is boosted by modifications of virus population size, particularly bottleneck events. Our recent results with hepatitis C virus (HCV) have shown that the expansion in sequence space of a viral clone continues despite prolonged replication in a stable cell culture environment. Diagnosis of the expansion was based on the quantification of diversity indices, the occurrence of intra-population mutational waves (variations in mutant frequencies), and greater individual residue variations in mutant spectra than those anticipated from sequence alignments in data banks. In the present report, we review our previous results, and show additionally that mutational waves in amplicons from the NS5A-NS5B-coding region are equally prominent during HCV passage in the absence or presence of the mutagenic nucleotide analogues favipiravir or ribavirin. In addition, by extending our previous analysis to amplicons of the NS3- and NS5A-coding region, we provide further evidence of the incongruence between amino acid conservation scores in mutant spectra from infected patients and in the Los Alamos National Laboratory HCV data banks. We hypothesize that these observations have as a common origin a permanent state of HCV population disequilibrium even upon extensive viral replication in the absence of external selective constraints or changes in population size. Such a persistent disequilibrium—revealed by the changing composition of the mutant spectrum—may facilitate finding alternative mutational pathways for HCV antiviral resistance. The possible significance of our model for other genetically variable viruses is discussed.