Composition Analysis Research Articles

Comparative analysis of codon usage bias in chloroplast genomes of ten medicinal species of Rutaceae.

Rutaceae family comprises economically important plants due to their extensive applications in spices, food, oil, medicine, etc. The Rutaceae plants is able to better utilization through biotechnology. Modern biotechnological approaches primarily rely on the heterologous expression of functional proteins in different vectors. However, several proteins are difficult to express outside their native environment. The expression potential of functional genes in heterologous systems can be maximized by replacing the rare synonymous codons in the vector with preferred optimal codons of functional genes. Codon usage bias plays a critical role in biogenetic engineering-based research and development. In the current study, 727 coding sequences (CDSs) obtained from the chloroplast genomes of ten Rutaceae plant family members were analyzed for codon usage bias. The nucleotide composition analysis of codons showed that these codons were rich in A/T(U) bases and preferred A/T(U) endings. Analyses of neutrality plots, effective number of codons (ENC) plots, and correlations between ENC and codon adaptation index (CAI) were conducted, which revealed that natural selection is a major driving force for the Rutaceae plant family's codon usage bias, followed by base mutation. In the ENC vs. CAI plot, codon usage bias in the Rutaceae family had a negligible relationship with gene expression level. For each sample, we screened 12 codons as preferred and high-frequency codons simultaneously, of which GCU encoding Ala, UUA encoding Leu, and AGA encoding Arg were the most preferred codons. Taken together, our study unraveled the synonymous codon usage pattern in the Rutaceae family, providing valuable information for the genetic engineering of Rutaceae plant species in the future.

Cardiopulmonary exercise testing, computed tomography-derived body composition, systemic inflammation and survival after elective abdominal aortic aneurysm repair: A retrospective cohort study.

Cardio-pulmonary exercise testing (CPEX) is selectively used before intervention for abdominal aortic aneurysm (AAA). Sarcopenia, a chronic condition defined by reduced skeletal muscle function and volume, can be assessed radiologically by computed tomography (CT)-derived body composition analysis (CT-BC), and is associated with systemic inflammation. The aim was to describe the association between CT-BC, CPEX, inflammation and survival in patients undergoing elective intervention for AAA. Patients were recruited retrospectively from a single, secondary-care centre-operative database. Cases undergoing elective endovascular aneurysm repair (EVAR) and open surgical repair (OSR) between 31 March 2015 and 25 June 2020 were included. There were 176 patients (130 EVAR, 46 OSR) available for analysis in the final study; median (interquartile range [IQR]) follow-up was 60.5 [27] months, and all completed a minimum of 2 years follow-up. Preoperative CPEX tests were recorded. CT sarcopenia score [CT-SS, range 0 to 2, calculated based on normal/low SMI (0/1) and normal/low SMD (0/1)] assessed radiological sarcopenia. Preoperative modified Glasgow Prognostic score (mGPS) was used to assess systemic inflammation. Mean [95% confidence interval (CI) survival in the CT-SS 0 vs. CT-SS 1 vs. CT-SS 2 subgroups was 80.1 (73.6 to 86.6) months vs. 70.3 (63.5 to 77.1) months vs. 63.8 (53.4 to 74.2) months] (P = 0.01). CT-SS was not associated with CPEX results (P > 0.05). Elevated CT-SS [hazard ratio (HR) 1.83, 95% CI, 1.16 to 2.89, P < 0.01] was independently associated with increased hazard of long-term mortality; however, CPEX results were not (P > 0.05). CPEX test results were not consistently associated with body composition and did not have significant prognostic value in patients undergoing elective treatment for AAA.

Total and H-specific growth/differentiation factor 15 levels are unaffected by liraglutide or naltrexone/bupropion administration.

To investigate growth/differentiation factor 15 (GDF-15) levels in response to antiobesity medications, namely, liraglutide (Lira) and naltrexone/bupropion (N/B), in individuals with overweight or obesity. This was a prospective, non-randomized clinical trial with a two-arm, parallel design. A total of 42 individuals with overweight or obesity without type 1 or type 2 diabetes mellitus were enrolled. The participants received either Lira 3 mg or N/B 32/360 mg, along with diet and exercise, according to comorbidities, cost and method of administration. Participants underwent clinical and laboratory measurements at baseline, as well as at the 3- and 6-month time points. Anthropometric measurements and body composition analysis via bioelectrical impendence analysis were performed. Total blood samples for GDF-15 and H-specific GDF-15 were collected in the fasting state and every 30 min for 3 h after the consumption of a standardized mixed meal. Overall, participants' weight was reduced by 9.29 ± 5.34 kg at Month 3 and 11.52 ± 7.52 kg at Month 6. Total and H-specific GDF-15 levels did not show significant changes during the mixed meal compared to values before the meal when all participants were examined at baseline, and at 3 and 6 month follow-ups. No statistical significance was found when participants were examined by subgroup (Lira vs. N/B). No significant differences between treatment groups in postprandial area under the curve (AUC) or incremental AUC values were found at baseline or in the follow-up months with regard to total and H-specific GDF-15 levels. Neither total nor H-specific GDF-15 levels are affected by Lira or N/B treatment in patients with overweight or obesity.

Enhanced muscle and fat segmentation for CT-based body composition analysis: a comparative study.

Body composition measurements from routine abdominal CT can yield personalized risk assessments for asymptomatic and diseased patients. In particular, attenuation and volume measures of muscle and fat are associated with important clinical outcomes, such as cardiovascular events, fractures, and death. This study evaluates the reliability of an Internal tool for the segmentation of muscle and fat (subcutaneous and visceral) as compared to the well-established public TotalSegmentator tool. We assessed the tools across 900 CT series from the publicly available SAROS dataset, focusing on muscle, subcutaneous fat, and visceral fat. The Dice score was employed to assess accuracy in subcutaneous fat and muscle segmentation. Due to the lack of ground truth segmentations for visceral fat, Cohen's Kappa was utilized to assess segmentation agreement between the tools. Our Internal tool achieved a 3% higher Dice (83.8 vs. 80.8) for subcutaneous fat and a 5% improvement (87.6 vs. 83.2) for muscle segmentation, respectively. A Wilcoxon signed-rank test revealed that our results were statistically different with p < 0.01. For visceral fat, the Cohen's Kappa score of 0.856 indicated near-perfect agreement between the two tools. Our internal tool also showed very strong correlations for muscle volume (R =0.99), muscle attenuation (R =0.93), and subcutaneous fat volume (R =0.99) with a moderate correlation for subcutaneous fat attenuation (R =0.45). Our findings indicated that our Internal tool outperformed TotalSegmentator in measuring subcutaneous fat and muscle. The high Cohen's Kappa score for visceral fat suggests a reliable level of agreement between the two tools. These results demonstrate the potential of our tool in advancing the accuracy of body composition analysis.

Body Composition Analysis Techniques and Its Application in Oncology: A Review.

The oncology community has shown growing interest to understand how body composition measures can be utilized to improve cancer treatment and survivorship care for about 20 million individuals diagnosed with cancer annually. Recent observational studies demonstrate that muscle and adipose tissue distribution are risk factors for clinical outcomes such as postoperative complications, and worse overall survival. There is an emergent recognition that body mass index (BMI) is neither adequate to identify patients with adverse health outcomes due to poor muscle health or excess adiposity, nor does BMI accurately classify the distribution of adiposity. Abdominal CT is a most frequently imaging examination for a wide variety of clinical indications, but it is only used to diagnose the immediate problem. Additionally, each CT examination contains very robust data on body composition which generally goes unused in routine clinical practice. The field is eager to identify therapeutic interventions that modify body composition and reduce the incidence of poor clinical outcomes in this population. Large scale population based screening is feasible now by making all of these relevant biometric measures fully automated through the use of artificial intelligence algorithms, which provide rapid and objective assessment.

Identification of cell-specific epigenetic patterns associated with chondroitin sulfate treatment response in an endemic arthritis, Kashin-Beck disease.

To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment. Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue. This study revealed 21,060 hypermethylated and 44,472 hypomethylated DMRs, and 13,194 hypermethylated and 22,448 hypomethylated CpG islands for differential global methylation for chondroitin sulphate treatment response. A total of 12,666 DMR-related genes containing DMRs were identified in their promoter regions, such as CHL1 (false discovery rate (FDR) = 2.11 × 10-11), RIC8A (FDR = 7.05 × 10-4), and SOX12 (FDR = 1.43 × 10-3). Additionally, RIC8A and CHL1 were hypermethylated in responders, while SOX12 was hypomethylated in responders, all showing decreased gene expression. The patterns of cell-specific differential global methylation associated with chondroitin sulphate response were observed. Specifically, we found that DMRs located in TESPA1 and ATP11A exhibited differential DNA methylation between responders and non-responders in granulocytes, monocytes, and B cells. Our study identified cell-specific changes in DNA methylation associated with chondroitin sulphate response in KBD patients.

Analysis of tumor microenvironment composition in vestibular schwannomas: insights into NF2-associated and sporadic variations and their clinical correlations

Analysis of tumor microenvironment composition in vestibular schwannomas: insights into NF2-associated and sporadic variations and their clinical correlations

Microstructural analysis of nitinol-based self-healing metals matrix composite of A356 alloy produced by high-pressure die casting

Microstructural analysis of nitinol-based self-healing metals matrix composite of A356 alloy produced by high-pressure die casting

METHANOL STEAM REFORMING FOR HYDROGEN PRODUCTION OVER Ni-BASED CATALYSTS: STATE-OF-THE-ART REVIEW AND FUTURE PROSPECTS.

With increasing global emphasis on environmental sustainability, the reliance on traditional energy sources such as coal, natural gas, and oil is encountering significant challenges. H2, known for its high energy content and pollution-free usage, emerges as a promising alternative. However, despite the great potential of H2, approximately 95% of hydrogen production still depends on non-renewable resources. Hence, the shift towards producing H2 from renewable sources, particularly through methods like steam reforming of methanol - a renewable resource - represents a beacon of hope for advancing sustainable energy practices. This review comprehensively examines recent advancements in efficient H2 production using Ni-based catalysts in methanol steam reforming (MSR) and proposes the future prospects. Firstly, the fundamental principles of MSR technology and the significance in clean energy generation are elucidated. Subsequently, the design, synthesis techniques, and optimization strategies for enhancing the catalytic performance of Ni-based catalysts are discussed. Through the analysis of various catalyst compositions, structural adjustments, surface active sites, and modification methods, the review uncovers effective approaches for boosting the activity and durability of MSR reactions.By offering a comprehensive critical analysis, this review serves as a valuable reference to enhance MSR hydrogen production efficiency and catalyst performance.

Improved Compatibility of α-NaMnO2 Cathodes at the Interface with Safer and more Reliable Electrolytes.

The behaviour and compatibility of monoclinic sodium manganite, α-NaMnO2, cathodes at the interface with electrolytes based on the 1-ethyl-3-methylimidazolium bis(fluorosulfonyl)imide (EMIFSI) and N-trimethyl-N-butylammonium bis(fluorosulfonyl)imide (N1114FSI) ionic liquids is presented and discussed. The Na+ insertion process was analysed through cyclic voltammetry tests combined with impedance spectroscopy measurements and the cell performance was tested by charge-discharge cycles. XPS and FIB-SEM measurements allowed analysis of the surface composition and the morphology of post-mortem cathodes. Overall, the α-NaMnO2 cathode showed high reversibility in N1114FSI-based electrolyte, delivering 60 % of the initial capacity after 1200 cycles in conjunction with a Coulombic efficiency above 99%. To our knowledge, these very promising results are the best result obtained till now for monolithic α-NaMnO2 cathodes, are ascribable to the formation of a stable passive layer onto the electrode surface, as confirmed by spectroscopic analysis.

Development of UroSAM: a machine learning model to automatically identify kidney stone composition from endoscopic video.

Introduction Chemical composition analysis is important in prevention counseling for kidney stone disease. Advances in laser technology have made dusting techniques more prevalent, but this offers no consistent way to collect enough material to send for chemical analysis, leading many to forgo this test. We developed a novel machine learning (ML) model to effectively assess stone composition based on intraoperative endoscopic video data. Methods Two endourologists performed ureteroscopy for kidney stones ≥ 10mm. Representative videos were recorded intraoperatively. Individual frames were extracted from the videos and the stone was outlined by human tracing. An ML model, UroSAM, was built and trained to automatically identify kidney stones in the images and predict the majority stone composition: calcium oxalate monohydrate (COM), dihydrate (COD), calcium phosphate (CAP), or uric acid (UA). UroSAM was built on top of the publicly available Segment Anything Model (SAM) and incorporated a U-Net convolutional neural network (CNN). Discussion A total of 78 ureteroscopy videos were collected; 50 were used for the model after exclusions (32 COM, 8 COD, 8 CAP, 2 UA). The ML model segmented the images with 94.77% precision. Dice coefficient (0.9135) and Intersection over Union (0.8496) confirmed good segmentation performance of the ML model. A video-wise evaluation demonstrated 60% correct classification of stone composition. Subgroup analysis showed correct classification in 84.4% of COM videos. A post-hoc adaptive threshold technique was used to mitigate biasing of the model towards COM due to data imbalance - this improved the overall correct classification to 62% while improving the classification of COD, CAP, and UA videos. Conclusions This study demonstrates the successful development of UroSAM, an ML model that precisely identifies kidney stones from natural endoscopic video data. More high quality video data will improve the performance of the model in classifying the majority stone composition.

Event attribution of a midlatitude windstorm using ensemble weather forecasts

The widespread destruction incurred by midlatitude storms every year makes it an imperative to study how storms change with climate. The impact of climate change on midlatitude windstorms, however, is hard to evaluate due to the small signals in variables such as wind speed, as well as the high resolutions required to represent the dynamic processes in the storms. Here, we assess how storm Eunice, which hit the UK in February 2022, was impacted by anthropogenic climate change using the ECMWF ensemble prediction system. This system was demonstrably able to predict the storm, significantly increasing our confidence in its ability to model the key physical processes and their response to climate change. Using modified greenhouse gas concentrations and changed initial conditions for ocean temperatures, we create two counterfactual scenarios of storm Eunice in addition to the forecast for the current climate. We compare the intensity and severity of the storm between the pre-industrial, current, and future climates. Our results robustly indicate that Eunice has become more intense with climate change and similar storms will continue to intensify with further anthropogenic forcing. These results are consistent across forecast lead times, increasing our confidence in them. Analysis of storm composites shows that this process is caused by increased vorticity production through increased humidity in the warm conveyor belt of the storm. This is consistent with previous studies on extreme windstorms. Our approach of combining forecasts at different lead times for event attribution enables combining event specificity and a focus on dynamic changes with the assessment of changing risks from windstorms. Further work is needed to develop methods to adjust the initial conditions of the atmosphere for the use in attribution studies using weather forecasts but we show that this approach is viable for reliable and fast attribution systems.

Molecular composition of clouds: a comparison between samples collected at tropical (Réunion Island, France) and mid-north (Puy de Dôme, France) latitudes

Abstract. The composition of dissolved organic matter of cloud water has been investigated through non-targeted high-resolution mass spectrometry on only a few samples that were mostly collected in the Northern Hemisphere in the USA, Europe and China. There remains, therefore, a lack of measurements for clouds located in the Southern Hemisphere, under tropical conditions and influenced by forest emissions. As a matter of fact, the comparison of the composition of clouds collected in different locations is challenging since the methodology for the analysis and data treatment is not standardized. In this work, the chemical composition of three samples collected at Réunion Island (REU) during the BIO-MAÏDO field campaign, in the Indian Ocean, with influences from marine, anthropogenic and biogenic (tropical) emissions, is investigated and compared to the chemical composition of samples collected at the Puy de Dôme (PUY) observatory in France. The same methodology of analysis and data treatment was employed, producing a unique dataset for the investigation of the molecular composition of organic matter in cloud water. Besides the analysis of elemental composition, we investigated the carbon oxidation state (OSC) of dissolved organic matter, finding that overall samples collected at PUY are more oxidized than those collected at REU. Molecular formulas were also classified based on stoichiometric elemental ratios, showing the high frequency and abundance of reduced organic compounds, classified as lipids (LipidC), in this matrix, which led to a search for terpene oxidation products in cloud water samples. To better discriminate between samples collected at PUY and REU, statistical analysis (principal component analysis and agglomerative hierarchical clustering) was performed on the ensemble of molecular formulas and their intensities. Samples collected at REU have a different composition from samples collected at PUY, which is mainly linked to different primary sources, the processing of organic matter in cloud water and the influence of different primary emissions at the two locations.

A comprehensive approach to phytochemical analysis of macromolecular composites that protect tubers: case studies in suberized potato periderm tissues

A comprehensive approach to phytochemical analysis of macromolecular composites that protect tubers: case studies in suberized potato periderm tissues

Aerosol Mass Spectrometry

Mass spectrometry is widely used in various scientific fields. In atmospheric chemistry, there has been a long call for a detailed on-line analysis of the chemical composition of aerosol particles (i.e., particles in the solid or liquid state) in the atmosphere resulting in the development of the so-called aerosol mass spectrometers in the past 20 years. These instruments allow the measurement of the chemical composition of particles with sizes of ca. 50–800 nm, typically at minute resolution. Their development and possible applications are discussed in this review.

Application of Composite Frequency Data Analysis Model to Forecast the Growth of Vietnam's Coffee Exports

In recent years, mixed-frequency data analysis models have received much attention and application in the fields of economics and finance, especially in forecasting national macroeconomic indicators. However, in Vietnam, there are almost no studies applying these models. Vietnam is a country with a long-standing agricultural production background and the workforce mainly makes a living from farming. There are many types of Vietnamese agricultural products with high export value, bringing a significant source of foreign currency to the country. Coffee is Vietnam's main export product, a product that earns a lot of foreign currency, contributing to the country's socio-economic development. Therefore, applying models with mixed frequency data such as MIDAS to forecast coffee export growth is a promising new research direction.

Theme maximalization through modifiers: A case of Mandarin verbal classifier &lt;i&gt;bian&lt;/i&gt;

Maximalization strategies and their syntactic representations are at the centre of a long debate (Filip &amp; Rothstein 2005; Filip 2008; Martínez Vera 2021; a.o.). Semantically, events can be maximalized with respect to theme, path, degree, etc., and thus maximalization features several types. Syntactically, maximalization has been argued to be exerted by a verb or an argument of the verb. This research offers a novel observation that elements in a modifier position can also introduce maximalization. In particular, I propose that Mandarin verbal classifier bian is a theme-maximalizing element situated in an adjunct of VP. I further provide a compositional analysis within the framework of neo-Davidsonian event semantics. In the end, I compare bian with another theme-maximaling element diao and identify two distinct levels of theme maximalization.

Genomic analysis and phylogenetic characterization of Himalayan snow trout, Schizothorax esocinus based on mitochondrial protein-coding genes.

Mitochondrial DNA (mtDNA) has become a significant tool for exploring genetic diversity and delineating evolutionary links across diverse taxa. Within the group of cold-water fish species that are native to the Indian Himalayan region, Schizothorax esocinus holds particular importance due to its ecological significance and is potentially vulnerable to environmental changes. This research aims to clarify the phylogenetic relationships within the Schizothorax genus by utilizing mitochondrial protein-coding genes. Standard protocols were followed for the isolation of DNA from S. esocinus. For the amplification of mtDNA, overlapping primers were used, and then subsequent sequencing was performed. The genetic features were investigated by the application of bioinformatic approaches. These approaches covered the evaluation of nucleotide composition, codon usage, selective pressure using nonsynonymous substitution /synonymous substitution (Ka/Ks) ratios, and phylogenetic analysis. The study specifically examined the 13 protein-coding genes of Schizothorax species which belongs to the Schizothoracinae subfamily. Nucleotide composition analysis showed a bias towards A + T content, consistent with other cyprinid fish species, suggesting evolutionary conservation. Relative Synonymous Codon Usage highlighted leucine as the most frequent (5.18%) and cysteine as the least frequent (0.78%) codon. The positive AT-skew and the predominantly negative GC-skew indicated the abundance of A and C. Comparative analysis revealed significant conservation of amino acids in multiple genes. The majority of amino acids were hydrophobic rather than polar. The purifying selection was revealed by the genetic distance and Ka/Ks ratios. Phylogenetic study revealed a significant genetic divergence between S. esocinus and other Schizothorax species with interspecific K2P distances ranging from 0.00 to 8.87%, with an average of 5.76%. The present study provides significant contributions to the understanding of mitochondrial genome diversity and genetic evolution mechanisms in Schizothoracinae, hence offering vital insights for the development of conservation initiatives aimed at protecting freshwater fish species.

Body composition analysis using dual-energy x-ray absorptiometry in an Egyptian pediatric sickle cell disease cohort.

Growth failure is commonly encountered in sickle cell disease (SCD). Tissue compartment growth and development are subsequently likely to be altered in such patients. We aimed to analyze body composition in an Egyptian pediatric SCD cohort using dual-energy x-ray absorptiometry (DEXA), one of the most comprehensive and noninvasive assessment methods available. Forty children with SCD ≤18years and 40 healthy youngsters age- and gender-matched were enrolled. Patients' demographic, clinical, and laboratory parameters were obtained from their archived files. All patients and controls were subjected to body composition assessment using a MedixDR-Whole Body DEXA System. In SCD patients; weight and height relative to age Z scores were significantly lower (p<.001), total body lean was significantly higher (p=.006), and total body fat percentage was lower, yet the difference was not statistically significant (p=.09). There were no statistically significant variations in bone mineral density or content, basal metabolic rate, subcutaneous adipose tissue, android/gynoid fat ratio, and visceral adipose tissue. There were no significant gender disparities between SCD patients and controls. Faltering growth in children with SCD should be addressed with a multidisciplinary approach including nutritional support, correction of anemia, and proper medical care. Body composition parameters assessed using DEXA were comparable between cases and controls apart from total body lean. Further clinical studies are needed with multicenter cooperation and a larger sample size to assess the usefulness of DEXA as an assessment tool for body composition in children with SCD.

Comprehensive Analysis of Gallstone Composition and Association with Risk Factors in Bangladesh: Insights into the burden and outlook for prevention and management.

Gallstone is as ancient as human civilization. It has been found in the gallbladders of Egyptian mummies, dating back to 1000 BC. Gallstone is one of the diseases prevalent in developed nations but it is less prevalent in the developing populations that still consume traditional diets. Gallstones are formed in the gallbladder, from the constituents of bile cholesterol and calcium bilirubinate are the main chemical compounds present in gallstones and their precipitation in bile is induced by multiple aetiological factors. The prevalence and the chemical composition of gallstones vary from population to population. This indicates the involvement of multiple risk factors in the pathogenesis of gallstones. Therefore investigation of the chemical composition of gallstones is primarily important to recognize the correlation with the risk factors for gallstones disease in a community. J Shaheed Suhrawardy Med Coll 2022; 14(2): 3-10