Surface Area of Hydrous Oxides by Dye Adsorption Method

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LiDARPheno – A Low-Cost LiDAR-Based 3D Scanning System for Leaf Morphological Trait Extraction

The ever-growing world population brings the challenge for food security in the current world. The gene modification tools have opened a new era for fast-paced research on new crop identification and development. However, the bottleneck in the plant phenotyping technology restricts the alignment in geno–pheno development as phenotyping is the key for the identification of potential crop for improved yield and resistance to the changing environment. Various attempts to making the plant phenotyping a “high-throughput” have been made while utilizing the existing sensors and technology. However, the demand for ‘good’ phenotypic information for linkage to the genome in understanding the gene-environment interactions is still a bottleneck in the plant phenotyping technologies. Moreover, the available technologies and instruments are inaccessible, expensive, and sometimes bulky. This work attempts to address some of the critical problems, such as exploration and development of a low-cost LiDAR-based platform for phenotyping the plants in-lab and in-field. A low-cost LiDAR-based system design, LiDARPheno, is introduced in this work to assess the feasibility of the inexpensive LiDAR sensor in the leaf trait (length, width, and area) extraction. A detailed design of the LiDARPheno, based on low-cost and off-the-shelf components and modules, is presented. Moreover, the design of the firmware to control the hardware setup of the system and the user-level python-based script for data acquisition is proposed. The software part of the system utilizes the publicly available libraries and Application Programming Interfaces (APIs), making it easy to implement the system by a non-technical user. The LiDAR data analysis methods are presented, and algorithms for processing the data and extracting the leaf traits are developed. The processing includes conversion, cleaning/filtering, segmentation and trait extraction from the LiDAR data. Experiments on indoor plants and canola plants were performed for the development and validation of the methods for estimation of the leaf traits. The results of the LiDARPheno based trait extraction are compared with the SICK LMS400 (a commercial 2D LiDAR) to assess the performance of the developed system

Fetal ECG Extraction from Maternal ECG using Attention-based CycleGAN

Non-invasive fetal electrocardiogram (FECG) is used to monitor the electrical pulse of the fetal heart. Decomposing the FECG signal from maternal ECG (MECG) is a blind source separation problem, which is hard due to the low amplitude of FECG, the overlap of R waves, and the potential exposure to noise from different sources. Traditional decomposition techniques, such as adaptive filters, require tuning, alignment, or pre-configuration, such as modeling the noise or desired signal. to map MECG to FECG efficiently. The high correlation between maternal and fetal ECG parts decreases the performance of convolution layers. Therefore, the masking region of interest using the attention mechanism is performed for improving signal generators' precision. The sine activation function is also used since it could retain more details when converting two signal domains. Three available datasets from the Physionet, including A&D FECG, NI-FECG, and NI-FECG challenge, and one synthetic dataset using FECGSYN toolbox, are used to evaluate the performance. The proposed method could map abdominal MECG to scalp FECG with an average 98% R-Square [CI 95%: 97%, 99%] as the goodness of fit on A&D FECG dataset. Moreover, it achieved 99.7 % F1-score [CI 95%: 97.8-99.9], 99.6% F1-score [CI 95%: 98.2%, 99.9%] and 99.3% F1-score [CI 95%: 95.3%, 99.9%] for fetal QRS detection on, A&D FECG, NI-FECG and NI-FECG challenge datasets, respectively. These results are comparable to the state-of-the-art; thus, the proposed algorithm has the potential of being used for high-performance signal-to-signal conversion

Association of MBL2 gene polymorphisms with pulmonary tuberculosis susceptibility: Trial sequence meta-analysis as evidence

© 2019 Mandal et al. Background: Mannose-binding lectin (MBL) or mannose-binding protein (MBP), encoded by MBL2 gene and secreted by the liver, activates complement system through lectin pathway in innate immunity against the host’s infection. Conflictingly, a number of MBL2 variants, rs1800450 (A\u3eB), rs1800451 (A\u3eC), rs5030737 (A\u3eD), rs7096206 (Y\u3eX), rs11003125 (H\u3eL), and rs7095891 (P\u3eQ) allele, have been found to be associated with compromised serum levels and pulmonary tuberculosis (PTB) susceptibility. The present meta-analysis study was performed to evaluate the potential association of these MBL2 gene variants with PTB susceptibility. Materials and methods: A quantitative synthesis was performed on PubMed (Medline), EMBASE, and Google Scholar web database searches. A meta-analysis was performed to calculate the pooled odds ratios and 95% CIs for all the genetic models. Results: A total of 14 eligible studies were included to analyze their pooled data for associations between alleles, genotypes, and minor allele carriers. The statistical analysis revealed the significant reduced PTB risk with homozygous variant genotype of rs1800451 polymorphism (CC vs AA: P=0.043; OR =0.828, 95% CI =0.689–0.994). Contrary to this, the variant allele of rs5030737 polymorphism showed association with increased PTB risk (D vs A: P=0.026; OR =1.563, 95% CI =1.054–2.317). However, the other genetic models of rs1800450 (A\u3eB), rs7096206 (Y\u3eX), and rs11003125 (H\u3eL) MBL2 gene polymorphisms did not divulge any association with PTB susceptibility. Conclusion: The current meta-analysis concludes that rs1800451 (A\u3eC) and rs5030737 (A\u3eD) polymorphisms of MBL2 gene play a significant role in PTB susceptibility. Further, well-designed epidemiological studies with larger sample size including consideration of environmental factors are warranted for the future

A trial sequential meta-analysis of TNF-α –308G\u3eA (rs800629) gene polymorphism and susceptibility to colorectal cancer

© 2019 The Author(s). Purpose: Tumor necrosis factor-α (TNF-α), secreted by the activated macrophages, may participate in the onset and progression of colorectal cancer (CRC). The association of TNF-α –308 G\u3eA (rs1800629) single-nucleotide polymorphism (SNP) with CRC risk has been investigated by many studies but the results are inconclusive. A trial sequential meta-analysis was performed for precise estimation of the relationship between TNF-α –308 G\u3eA gene polymorphism with CRC risk. Methods: Medline (PubMed), EMBASE (Excerpta-Medica) and Google Scholar were mined for relevant articles. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the significance of association. Results: The pooled analysis indicated no risk associated with TNF-α –308 G\u3eA SNP and overall CRC risk in five genetic comparison models, i.e. allelic (A vs. G: P = 0.524; OR = 1.074, 95% CI = 0.863–1.335), homozygous (AA vs. GG: P = 0.489; OR = 1.227, 95% CI = 0.688–2.188), heterozygous (AG vs. GG: P = 0.811; OR = 1.024, 95% CI = 0.843–1.244), dominant (AA+AG vs. GG: P = 0.630; OR = 1.055, 95% CI = 0.849–1.311) and recessive (AA vs. AG+GG: P = 0.549; OR = 1.181, 95% CI = 0.686–2.033). Subgroup analysis revealed that TNF-α –308 G\u3eA SNP is associated with reduced risk of CRC in Asian ethnicity. The study showed no publication bias. Conclusions: No association of TNF-α –308 G\u3eA SNP with overall CRC risk was found. This SNP is likely to be protective against CRC in Asian population when compared with Caucasian population. Larger prospective-epidemiological studies are warranted to elucidate the roles of TNF-α –308 G\u3eA SNP in the etiology of CRC and to endorse the present findings

Biophysical, Biochemical, and Molecular Docking Investigations of Anti-Glycating, Antioxidant, and Protein Structural Stability Potential of Garlic.

Garlic has been reported to inhibit protein glycation, a process that underlies several disease processes, including chronic complications of diabetes mellitus. Biophysical, biochemical, and molecular docking investigations were conducted to assess anti-glycating, antioxidant, and protein structural protection activities of garlic. Results from spectral (UV and fluorescence) and circular dichroism (CD) analysis helped ascertain protein conformation and secondary structure protection against glycation to a significant extent. Further, garlic showed heat-induced protein denaturation inhibition activity (52.17%). It also inhibited glycation, advanced glycation end products (AGEs) formation as well as lent human serum albumin (HSA) protein structural stability, as revealed by reduction in browning intensity (65.23%), decrease in protein aggregation index (67.77%), and overall reduction in cross amyloid structure formation (33.26%) compared with positive controls (100%). The significant antioxidant nature of garlic was revealed by FRAP assay (58.23%) and DPPH assay (66.18%). Using molecular docking analysis, some of the important garlic metabolites were investigated for their interactions with the HSA molecule. Molecular docking analysis showed quercetin, a phenolic compound present in garlic, appears to be the most promising inhibitor of glucose interaction with the HSA molecule. Our findings show that garlic can prevent oxidative stress and glycation-induced biomolecular damage and that it can potentially be used in the treatment of several health conditions, including diabetes and other inflammatory diseases

Detection of autoantibodies against reactive oxygen species modified glutamic acid decarboxylase-65 in type 1 diabetes associated complications

<p>Abstract</p> <p>Background</p> <p>Autoantibodies against glutamate decarboxylase-65 (GAD₆₅Abs) are thought to be a major immunological tool involved in pathogenic autoimmunity development in various diseases. GAD₆₅Abs are a sensitive and specific marker for type 1 diabetes (T1D). These autoantibodies can also be found in 6-10% of patients classified with type 2 diabetes (T2D), as well as in 1-2% of the healthy population. The latter individuals are at low risk of developing T1D because the prevalence rate of GAD₆₅Abs is only about 0.3%. It has, therefore, been suggested that the antibody binding to GAD₆₅in these three different GAD₆₅Ab-positive phenotypes differ with respect to epitope specificity. The specificity of reactive oxygen species modified GAD₆₅(ROS-GAD₆₅) is already well established in the T1D. However, its association in secondary complications of T1D has not yet been ascertained. Hence this study focuses on identification of autoantibodies against ROS-GAD₆₅(ROS-GAD₆₅Abs) and quantitative assays in T1D associated complications.</p> <p>Results</p> <p>From the cohort of samples, serum autoantibodies from T1D retinopathic and nephropathic patients showed high recognition of ROS-GAD₆₅as compared to native GAD₆₅(N-GAD₆₅). Uncomplicated T1D subjects also exhibited reactivity towards ROS-GAD₆₅. However, this was found to be less as compared to the binding recorded from complicated subjects. These results were further proven by competitive ELISA estimations. The apparent association constants (AAC) indicate greater affinity of IgG from retinopathic T1D patients (1.90 × 10^-6M) followed by nephropathic (1.81 × 10^-6M) and uncomplicated (3.11 × 10^-7M) T1D patients for ROS-GAD₆₅compared to N-GAD₆₅.</p> <p>Conclusion</p> <p>Increased oxidative stress and blood glucose levels with extended duration of disease in complicated T1D could be responsible for the gradual formation and/or exposing cryptic epitopes on GAD₆₅that induce increased production of ROS-GAD₆₅Abs. Hence regulation of ROS-GAD₆₅Abs could offer novel tools for analysing and possibly treating T1D complications.</p