Noninvasive direct bilirubin detection by spectral analysis of color images using a Mini-LED light source

Urine test paper is a standard, noninvasive detection method for direct bilirubin, but this method can only achieve qualitative analysis and cannot achieve quantitative analysis. This study used Mini-LEDs as the light source, and direct bilirubin was oxidized to biliverdin by an enzymatic method with ferric chloride (FeCl₃) for labeling. Images were captured with a smartphone and evaluated for red (R), green (G), and blue (B) colors to analyze the linear relationship between the spectral change of the test paper image and the direct bilirubin concentration. This method achieved noninvasive detection of bilirubin. The experimental results demonstrated that Mini-LEDs can be used as the light source to analyze the grayscale value of the image RGB. For the direct bilirubin concentration range of 0.1-2 mg/dL, the green channel had the highest coefficient of determination coefficient (R²) of 0.9313 and a limit of detection of 0.56 mg/dL. With this method, direct bilirubin concentrations higher than 1.86 mg/dL can be quantitatively analyzed with the advantage of rapid and noninvasive detection.

Implications of gender-based variabilities in bone mineral density and hemoglobin levels

BACKGROUND

Studies reported that there is a relationship between volumetric bone mineral density (vBMD) and hemoglobin (HGB) in sickle cell anemia, chronic obstructive pulmonary disease, inflammatory bowel disease, and chronic kidney disease, it is not clear whether this association exists in normal populations or different genders. In order to further clarify the relationship between vBMD and HGB, and provide the basis for the diagnosis of related diseases, this study was conducted in the physical examination population.

METHODS

A cross-sectional study was conducted on a health check-up population from Wannan area of China from January to December 2018. The study involved 1238 individuals aged 23 to 85 years. Linear regression analysis and smooth curve were applied to determine the relationship of HGB and vBMD.

RESULTS

The average level of vBMD in the population was 130.11 ± 79.51 mg/cm³, after adjusting for age, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), triglycerides (TG), glucose (GLU), high-density lipoprotein (HDL) and low-density lipoprotein (LDL). A U-shape relationship was established between vBMD and HGB, the cut off value of HGB was 130 g/L. After gender stratification, the results showed a U-shaped curve relationship between vBMD and HGB in male group, and a linear relationship between vBMD and HGB in female group. The vBMD decreased with HGB when HGB < 120 g/L, and increased when HGB ≥ 120 g/L in male group.

CONCLUSION

The relationship between vBMD and HGB in the male physical examination population presents a U-shaped curve.

1 T-MoSe2 monolayer supported single Pd atom as a highly-efficient bifunctional catalyst for ORR/OER

The development of highly-efficient catalysts for oxygen reduction reaction (ORR) or oxygen evolution reaction (OER) is highly crucial for the commercial applications of some novel energy-related devices. Herein, using comprehensive first-principles computations, the potential of a variety of single metal-based catalysts supported by MoSe₂ nanosheet to boost the ORR or OER process was evaluated. The computations revealed that these considered metal atoms can be more stably anchored on 1 T-MoSe₂ than those of on 2H-MoSe₂. In particular, the supported Ni and Pd catalysts on 1 T-MoSe₂ exhibit high OER activity due to their quite low overpotential (0.47 and 0.49 V). Meanwhile, the anchored Pd atom on 1 T-MoSe₂ also displays excellent ORR performance with an ultra-low overpotential of 0.32 V, thus implying its superior bifunctional activity for ORR/OER. Our results provide a quite promising avenue to design a new class of MoSe₂-based single atom catalysts for fuel cells, which also further enriches the application fields of MoSe₂ nanosheets in advanced catalysis.

Application of the common base method to regression and analysis of covariance (ANCOVA) in qPCR experiments and subsequent relative expression calculation

Background

Quantitative polymerase chain reaction (qPCR) is the technique of choice for quantifying gene expression. While the technique itself is well established, approaches for the analysis of qPCR data continue to improve.

Results

Here we expand on the common base method to develop procedures for testing linear relationships between gene expression and either a measured dependent variable, independent variable, or expression of another gene. We further develop functions relating variables to a relative expression value and develop calculations for determination of associated confidence intervals.

Conclusions

Traditional qPCR analysis methods typically rely on paired designs. The common base method does not require such pairing of samples. It is therefore applicable to other designs within the general linear model such as linear regression and analysis of covariance. The methodology presented here is also simple enough to be performed using basic spreadsheet software.

Associations of Iron Intake, Serum Iron and Serum Ferritin with Bone Mineral Density in Women: The National Health and Nutrition Examination Survey, 2005-2010

The relationship between iron and bone mineral density (BMD) is still poorly understood. We investigated the associations of iron intake, serum iron and serum ferritin with BMD. This cross-sectional study identified 4000 females aged 12 to 49 years with complete and valid data on iron intake, serum iron, serum ferritin, and femoral neck and lumbar spine BMD from the National Health and Nutrition Examination Survey 2005-2010. Daily iron intake was the mean intake of iron nutrient ascertained from two consecutive 24-h dietary recalls; serum iron and serum ferritin were directly measured with established methods. Femoral neck and lumbar spine BMD were measured by Dual-energy X-ray absorptiometry (DXA). After adjusting for multiple covariates (i.e., age, body mass index and race), we used linear regression and generalized additive models (GAMs) to test the linear and non-linear associations of iron intake, serum iron and serum ferritin with BMD. The mean age of this study was 27.70 years (SD = 11.88 years). Higher serum ferritin was associated with lower femoral neck and lumbar spine BMD (all adjusted P < 0.05); iron intake and serum iron were not associated with femoral neck and lumbar spine BMD. Similar results were found when iron levels were classified as iron deficiency, normal iron and iron overload. There were no obvious non-linear relationships between the above three iron variables and BMD in the GAM analyses. There was a negative and linear association between serum ferritin and BMD; iron intake and serum iron were not associated with BMD. Serum ferritin appeared to be a better iron variable than iron intake and serum iron in relation to BMD.

LinSEM: Linearizing segmentation evaluation metrics for medical images

Numerous algorithms are available for segmenting medical images. Empirical discrepancy metrics are commonly used in measuring the similarity or difference between segmentations by algorithms and "true" segmentations. However, one issue with the commonly used metrics is that the same metric value often represents different levels of "clinical acceptability" for different objects depending on their size, shape, and complexity of form. An ideal segmentation evaluation metric should be able to reflect degrees of acceptability directly from metric values and be able to show the same acceptability meaning by the same metric value for objects of different shape, size, and form. Intuitively, metrics which have a linear relationship with degree of acceptability will satisfy these conditions of the ideal metric. This issue has not been addressed in the medical image segmentation literature. In this paper, we propose a method called LinSEM for linearizing commonly used segmentation evaluation metrics based on corresponding degrees of acceptability evaluated by an expert in a reader study. LinSEM consists of two main parts: (a) estimating the relationship between metric values and degrees of acceptability separately for each considered metric and object, and (b) linearizing any given metric value corresponding to a given segmentation of an object based on the estimated relationship. Since algorithmic segmentations do not usually cover the full range of variability of acceptability, we create a set (SS) of simulated segmentations for each object that guarantee such coverage by using image transformations applied to a set (ST) of true segmentations of the object. We then conduct a reader study wherein the reader assigns an acceptability score (AS) for each sample in SS, expressing the acceptability of the sample on a 1 to 5 scale. Then the metric-AS relationship is constructed for the object by using an estimation method. With the idea that the ideal metric should be linear with respect to acceptability, we can then linearize the metric value of any segmentation sample of the object from a set (SA) of actual segmentations to its linearized value by using the constructed metric-acceptability relationship curve. Experiments are conducted involving three metrics - Dice coefficient (DC), Jaccard index (JI), and Hausdorff Distance (HD) - on five objects: skin outer boundary of the head and neck (cervico-thoracic) body region superior to the shoulders, right parotid gland, mandible, cervical esophagus, and heart. Actual segmentations (SA) of these objects are generated via our Automatic Anatomy Recognition (AAR) method. Our results indicate that, generally, JI has a more linear relationship with acceptability before linearization than other metrics. LinSEM achieves significantly improved uniformity of meaning post-linearization across all tested objects and metrics, except in a few cases where the departure from linearity was insignificant. This improvement is generally the largest for DC and HD reaching 8-25% for many tested cases. Although some objects (such as right parotid gland and esophagus for DC and JI) are close in their meaning between themselves before linearization, they are distant in this meaning from other objects but are brought close to other objects after linearization. This suggests the importance of performing linearization considering all objects in a body region and body-wide.

Real-time combustion rate of wood charcoal in the heating fire basin: Direct measurement and its correlation to CO emissions

Previous studies of solid fuel emissions in household stoves focused more on emission measurements of the overall combustion process instead of the dynamic burning rate and its connection to the emissions. This study put forward a measurement system to monitor the dynamic fuel burning rate and emission rate directly, and explored their relationships during different combustion phases. Experiments were conducted using two types of wood charcoal consumed in a small open pan (i.e. fire basin) used commonly for space heating in rural China. The measured real-time CO emission rate (ER_CO), fuel burning rate (BR_F), and calculated carbon burning rate (BR_C) all rose and then subsided as the combustion progressed. The relationships between ER_CO and BR_F and between ER_CO and BR_C were different for the two charcoals during a phase with rising carbon content in the combusted fuel (Phase I), likely because moisture evaporation and volatile matter release were the dominant processes and the reaction was complex during this phase. ER_CO and BR_F or BR_C had linear relationships during a phase with stable carbon content in the combusted fuel (Phase II) for the two charcoals, which may be generalized to other solid fuels, because this phase is associated to fixed carbon dominating phase which usually exist during solid fuel combustion. The study presented a novel measurement approach to the combustion properties of solid fuels. The results implied that a complex relationship between the combustion and pollutant emissions existed in Phase I, and presented the possibility of estimating the fuel burning rate based on emission measurements in Phase II, or vice versa.

Relationship between the thoracolumbar flexion angle and pelvic posterior movement during trunk flexion

[Purpose] The purpose of this study was to investigate the linear relationship between the thoracolumbar flexion angle and hip posterior displacement. [Subjects and Methods] This study was performed on 15 subjects. The subjects performed three trials of a lumbar flexion–extension task. To quantify the statistical linear relationship between the thoracolumbar flexion angle and hip posterior displacement, Spearman’s rank correlation coefficient was used. [Results] The thoracolumbar flexion angle was significantly correlated with the degree of hip posterior displacement. [Conclusion] According to the results of this study, movement of the thoracolumbar joint and posterior movement of the pelvis must be considered for accurate analysis of the lumbopelvic rhythm.

Heavy metals detection in sediments using PGNAA method

A prompt gamma ray neutron activation analysis detection system was developed to detect the heavy metals in sediments by using an (241)Am-Be neutron source and BGO detector. The samples containing cadmium and mercury were used to test the performance of setup. The linear relationship between prompt gamma ray counts and the concentrations was studied. The results showed the counts of the prompt gamma rays from cadmium do not increase linearly with its concentrations, while the prompt gamma ray counts from Hg vary nearly linearly with the concentrations, due to the neutron self-shielding. Then a method was used to correct the effect and the non-linearly response was restored after the correction. And the minimum detectable concentration of Cd and Hg were 52.8 (at 8.484MeV) and 81.6 (at 5.967MeV) ppm, respectively.

A note on utilising binary features as ligand descriptors

It is common in cheminformatics to represent the properties of a ligand as a string of 1’s and 0’s, with the intention of elucidating, inter alia, the relationship between the chemical structure of a ligand and its bioactivity. In this commentary we note that, where relevant but non-redundant features are binary, they inevitably lead to a classifier capable of capturing only a linear relationship between structural features and activity. If, instead, we were to use relevant but non-redundant real-valued features, the resulting predictive model would be capable of describing a non-linear structure-activity relationship. Hence, we suggest that real-valued features, where available, are to be preferred in this scenario.

N2O production by ammonia oxidizing bacteria in an enriched nitrifying sludge linearly depends on inorganic carbon concentration

The effect of inorganic carbon (IC) on nitrous oxide (N2O) production by ammonia oxidizing bacteria (AOB) was investigated over a concentration range of 0-12 mmol C/L, encompassing typical IC levels in a wastewater treatment reactors. The AOB culture was enriched along with nitrite-oxidizing bacteria (NOB) in a sequencing batch reactor (SBR) to perform complete nitrification. Batch experiments were conducted with continuous carbon dioxide (CO2) stripping or at controlled IC concentrations. The results revealed a linear relationship between N2O production rate (N2OR) and IC concentration (R(2) = 0.97) within the IC range studied, suggesting a substantial effect of IC on N2O production by AOB. Similar results were also obtained with an AOB culture treating anaerobic sludge digestion liquor. The fundamental mechanism responsible for this dependency is unclear; however, in agreement with previous studies, it was observed that the ammonia oxidation rate (AOR) was also influenced by the IC concentration, which could be well described by the Monod kinetics. These resulted in an exponential relationship between N2OR and AOR, as previously observed in experiments where AOR was altered by varying dissolved oxygen and ammonia concentrations. It is therefore possible that IC indirectly affected N2OR by causing a change in AOR. The observation in this study indicates that alkalinity (mostly contributed by IC) could be a significant factor influencing N2O production and should be taken into consideration in estimating and mitigating N2O emissions in wastewater treatment systems.

Study on a linear relationship between limited pressure difference and coil current of on/off valve and its influential factors

On/off solenoid valves with PWM control are widely used in all types of vehicle electro-hydraulic control systems respecting to their desirable properties of reliable, low cost and fast acting. However, it can hardly achieve a linear hydraulic modulation by using on/off valves mainly due to the nonlinear behaviors of valve dynamics and fluid, which affects the control accuracy significantly. In this paper, a linear relationship between limited pressure difference and coil current of an on/off valve in its critical closed state is proposed and illustrated, which has a great potential to be applied to improve hydraulic control performance. The hydraulic braking system of case study is modeled. The linear correspondence between limited pressure difference and coil current of the inlet valve is simulated and further verified experimentally. Based on validated simulation models, the impacts of key parameters are researched. The limited pressure difference affected by environmental temperatures is experimentally studied, and the amended linear relation is given according to the test data.