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At present the distortion was a commonly found problem for carburizing-quenching gears, and during batch processing, due to different heat transfer boundary of gears in the same furnace, there are also differences in their carburizing-quenching distortion. In this study, by measuring the flow rate at different positions of subway gear in the same furnace and the inverse heat transfer method, the heat transfer coefficient of the gears in the same furnace were obtained. In the established thermal-phase-mechanical coupled numerical model, the distortion of the gears was analyzed by the results of carbon content, temperature, and phase transformation. The differential analysis of the distortion in the same furnace was achieved, and corresponding experiments was used to validate the simulation. The results indicated that the diameter deformation of the upper and lower gears in the same furnace was relatively large, with a smaller taper. The diameter deformation of the middle gear was relatively small, with a larger taper. The placement position of the gears can be reasonably selected based on different accuracy requirements. By comparison with the experiment results, the maximum relative errors of the simulation on diameter and taper deformation were 13 and 11%, respectively. The region of range on diameter deformation in the same furnace is 0.32-0.5 mm, and the region of range on the taper is 0.1-0.2 mm. [ABSTRACT FROM AUTHOR]

BACKGROUND: Oxidative stress is closely associated with the occurrence and progression of intervertebral disc degeneration, but its underlying mechanisms and effective treatment methods remain unclear. OBJECTIVE: To identify key genes associated with intervertebral disc degeneration accompanied by oxidative stress based on bioinformatics and three machine learning algorithms, as well as to conduct an immune infiltration analysis, followed by experimental validation. METHODS: Gene expression profiles related to intervertebral disc degeneration were obtained from the GEO database and oxidative stress-related genes obtained from the GeneCards database. Differential analysis and weighted gene co-expression networks analysis were performed on the intervertebral disc degeneration dataset. The intersection of the two analyses and the intersection with the oxidative stress-related genes were taken to obtain candidate hub genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses on the candidate hub genes were performed. Machine learning algorithms (LASSO regression, SVM-RFE, and random forest) were used to select the optimal feature genes and perform the receiver operator characteristic curve validation. Simultaneously, immune infiltration analysis was conducted. Nucleus pulposus samples from patients with cervical spondylosis who were treated at the Second Hospital of Shanxi Medical University from July to November 2023 were enrolled as the intervertebral disc degeneration group and nucleus pulposus samples from patients with cervical spinal cord injury as the control group. The relative expression of feature genes in the degenerated intervertebral disc was validated using qPCR method. RESULTS AND CONCLUSION: After differential gene analysis, 424 differentially expressed genes were obtained. Weighted gene co-expression networks analysis yielded 5 087 genes, and 1 399 oxidative stress genes were identified, leading to the identification of 23 candidate hub genes. Gene ontology analysis revealed that these candidate hub genes are primarily involved in bacterial defense response, molecular response to bacteria, and other biological processes. In terms of cellular component, they are associated with secretion granule lumen and cytoplasmic vesicle lumen, among others. As for molecular function, they are related to endopeptidase activity and compound binding, including sulfur compounds. Kyoto Encyclopedia of Genes and Genomes analysis demonstrated that these candidate hub genes are associated with neutrophil extracellular trap formation and the renin-angiotensin system pathway, among other signaling pathways. By applying three machine learning algorithms and conducting the receiver operator characteristic curve validation, two key genes, HSPA6 and PKD1, were determined. Immune infiltration analysis revealed a strong correlation between HSPA6 and activated dendritic cells (r=0.88, P < 0.001) as well as activated CD4+ T cells (r=-0.72, P < 0.01). Similarly, PKD1 showed close associations with effector memory CD8+ T cells (r=0.55, P < 0.05) and activated dendritic cells (r=-0.56, P < 0.05). qPCR experimental results indicated that the expression level of HSPA6 was lower in the intervertebral disc degeneration group compared with the control group (P < 0.000 1), while the expression level of PKD1 was higher in the intervertebral disc degeneration group (P < 0.000 1). These findings suggest that HSPA6 and PKD1 can serve as biomarkers for intervertebral disc degeneration accompanied by oxidative stress. Interventions targeting HSPA6 and PKD1 may hold promise for improving intervertebral disc degeneration. [ABSTRACT FROM AUTHOR]

Rice is the staple diet for most of the world's population and is considered a major staple crop in China. Anhui province of China is among the leading provinces for rice production, consumption, and commodities; it is well-known as the "land of fish and rice". Japonica rice cultivation in Anhui Province is mainly categorized into late-maturing medium, early-maturing medium, and early-maturing late japonica. This review explores the suitable ecological zone distribution and corresponding climate characteristics of the three types of japonica rice in Anhui Province. Data on japonica rice varieties approved in the province over the past twenty years were collected, illustrating the development process of japonica rice varieties in the province and their quality and resistance to rice blast disease. The review shows that the yield is positively and significantly correlated with agronomic traits, such as the number of effective panicles and the total number of grains per panicle, plant height, etc. In addition, it elucidates the major problems faced by Anhui's japonica rice breeding and cultivation, such as frequent events of high temperatures, rice blast disease, and medium to low soil fertility levels. Considering the existing issues in breeding japonica rice varieties in Anhui Province, this review proposes a strategy for breeding high-yield and disease-resistant japonica rice varieties, particularly varieties adaptable to medium and low fertility soil conditions. In brief, this article provides a theoretical basis and practical recommendations for the sustainable development of japonica rice in the Anhui Province of China. [ABSTRACT FROM AUTHOR]

Cell fate decision is crucial in biological development and plays fundamental roles in normal development and functional maintenance of organisms. By identifying key regulatory interactions and molecules involved in these fate decisions, we can shed light on the intricate mechanisms underlying the cell fates. This understanding ultimately reveals the fundamental principles driving biological development and the origins of various diseases. In this study, we present an overarching framework which integrates pseudo-trajectory inference and differential analysis to determine critical regulatory interactions and molecules during cell fate transitions. To demonstrate feasibility and reliability of the approach, we employ the differentiation networks of hepatobiliary system and embryonic stem cells as representative model systems. By applying pseudo-trajectory inference to biological data, we aim to identify critical regulatory interactions and molecules during the cell fate transition processes. Consistent with experimental observations, the approach can allow us to infer dynamical cell fate decision processes and gain insights into the underlying mechanisms which govern cell state decisions. [ABSTRACT FROM AUTHOR]

Problem: Significant differences exist between the body dimensions of Chinese and Western individuals, and these differences affect the injury characteristics of passengers in traffic accidents. Most current parametric finite element human models are based on Western body data, which does not adequately assess the injury risks for Chinese individuals. Therefore, it is imperative to establish a digital model that reflects the anatomical features of Chinese humans. This requires comprehensive anthropometric data specific to the Chinese population. Aim: This study aims to collect and analyze skeletal geometric parameters from various representative regions in China across different age groups to fill the gap in Chinese anthropometric data. Additionally, it seeks to explore regional and age-related differences in these parameters, providing a scientific basis for developing finite element models that reflect the characteristics of the Chinese population. Methods: Clinical CT data of skeletal geometric parameters were collected from 224 individuals across seven representative regions of China, including parameters of the head, chest, and lower limbs. Descriptive statistics, K-W tests, and U-tests were used to analyze regional differences. Spearman correlation and linear regression analyses were employed to assess the impact of age. Furthermore, weighted averages and weighted variances of skeletal geometric parameters were calculated to reflect the characteristics of individuals from various regions across the country, which will be applied in the development of Chinese human models. Results: The results indicate significant regional differences in the skeletal geometric parameters of Chinese individuals, exhibiting regional patterns between the north–south and east–west areas. While skeletal geometric parameters showed significant differences with age, no clear statistical pattern was observed. Conclusion: This study systematically extracts and analyzes the skeletal geometric parameters of the Chinese population from regional and age perspectives for the first time. These data will be applied in the development of Chinese human models, providing crucial support for improving passenger safety in traffic accidents, enhancing vehicle safety design, and establishing anthropometric standards suitable for the Chinese context. [ABSTRACT FROM AUTHOR]

Characterizing differences in sequences between two conditions, such as with and without drug exposure, using high-throughput sequencing data is a prevalent problem involving quantifying changes in sequence abundances, and predicting such differences for unobserved sequences. A key shortcoming of current approaches is their extremely limited ability to share information across related but non-identical reads. Consequently, they cannot use sequencing data effectively, nor be directly applied in many settings of interest. We introduce model-based enrichment (MBE) to overcome this shortcoming. We evaluate MBE using both simulated and real data. Overall, MBE improves accuracy compared to current differential analysis methods.

Objective: This study aimed to analyze and compare the quality and flavor of dromedary and bifocal camel yogurt. Methods: Through physicochemical analysis, texture analysis, rheological analysis, SPME-GC-MC, sensory evaluation, etc., the overall differences in quality and flavor of dromedary and bifocal camel yogurt were determined. Results: The viable bacteria count, protein, fat, total solids content, and antioxidant activity of dromedary camel yogurt were lower than those of bifocal camel yogurt （PPPPPP

Background Chromatin loops play a critical role in gene regulation by connecting regulatory loci and gene promoters. The identification of changes in chromatin looping between cell types or biological conditions is an important task for understanding gene regulation; however, the manipulation, statistical analysis, and visualization of data sets describing 3D chromatin structure is challenging due to the large and complex nature of the relevant data sets. Methods Here, we describe a workflow for identifying and visualizing differential chromatin loops from Hi-C data from two biological conditions using the ‘mariner’, ‘DESeq2’ and ‘plotgardener’ Bioconductor/R packages. The workflow assumes that Hi-C data has been processed into ‘.hic’ or ‘.cool’ files and that loops have been identified using an existing loop-calling algorithm. Results First, the ‘mariner’ package is used to merge redundant loop calls and extract interaction frequency counts. Next, ‘DESeq2’ is used to identify loops that exhibit differential contact frequencies between conditions. Finally, ‘plotgardener’ is used to visualize differential loops. Conclusion Chromatin interaction data is an important modality for understanding the mechanisms of transcriptional regulation. The workflow presented here outlines the use of ‘mariner’ as a tool to manipulate, extract, and aggregate chromatin interaction data, ‘DESeq2’ to perform differential analysis of these data across conditions, samples, and replicates, and ‘plotgardener’ to explore and visualize the results.

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Background Chromatin loops play a critical role in gene regulation by connecting regulatory loci and gene promoters. The identification of changes in chromatin looping between cell types or biological conditions is an important task for understanding gene regulation; however, the manipulation, statistical analysis, and visualization of data sets describing 3D chromatin structure is challenging due to the large and complex nature of the relevant data sets. Methods Here, we describe a workflow for identifying and visualizing differential chromatin loops from Hi-C data from two biological conditions using the ‘mariner’, ‘DESeq2’ and ‘plotgardener’ Bioconductor/R packages. The workflow assumes that Hi-C data has been processed into ‘.hic’ or ‘.cool’ files and that loops have been identified using an existing loop-calling algorithm. Results First, the ‘mariner’ package is used to merge redundant loop calls and extract interaction frequency counts. Next, ‘DESeq2’ is used to identify loops that exhibit differential contact frequencies between conditions. Finally, ‘plotgardener’ is used to visualize differential loops. Conclusion Chromatin interaction data is an important modality for understanding the mechanisms of transcriptional regulation. The workflow presented here outlines the use of ‘mariner’ as a tool to manipulate, extract, and aggregate chromatin interaction data, ‘DESeq2’ to perform differential analysis of these data across conditions, samples, and replicates, and ‘plotgardener’ to explore and visualize the results.

Abstract Single-cell technologies offer insights into molecular feature distributions, but comparing them poses challenges. We propose a kernel-testing framework for non-linear cell-wise distribution comparison, analyzing gene expression and epigenomic modifications. Our method allows feature-wise and global transcriptome/epigenome comparisons, revealing cell population heterogeneities. Using a classifier based on embedding variability, we identify transitions in cell states, overcoming limitations of traditional single-cell analysis. Applied to single-cell ChIP-Seq data, our approach identifies untreated breast cancer cells with an epigenomic profile resembling persister cells. This demonstrates the effectiveness of kernel testing in uncovering subtle population variations that might be missed by other methods.

Abstract Background Cancerous cells’ identity is determined via a mixture of multiple factors such as genomic variations, epigenetics, and the regulatory variations that are involved in transcription. The differences in transcriptome expression as well as abnormal structures in peptides determine phenotypical differences. Thus, bulk RNA-seq and more recent single-cell RNA-seq data (scRNA-seq) are important to identify pathogenic differences. In this case, we rely on k-mer decomposition of sequences to identify pathogenic variations in detail which does not need a reference, so it outperforms more traditional Next-Generation Sequencing (NGS) analysis techniques depending on the alignment of the sequences to a reference. Results Via our alignment-free analysis, over esophageal and glioblastoma cancer patients, high-frequency variations over multiple different locations (repeats, intergenic regions, exons, introns) as well as multiple different forms (fusion, polyadenylation, splicing, etc.) could be discovered. Additionally, we have analyzed the importance of less-focused events systematically in a classic transcriptome analysis pipeline where these events are considered as indicators for tumor prognosis, tumor prediction, tumor neoantigen inference, as well as their connection with respect to the immune microenvironment. Conclusions Our results suggest that esophageal cancer (ESCA) and glioblastoma processes can be explained via pathogenic microbial RNA, repeated sequences, novel splicing variants, and long intergenic non-coding RNAs (lincRNAs). We expect our application of reference-free process and analysis to be helpful in tumor and normal samples differential scRNA-seq analysis, which in turn offers a more comprehensive scheme for major cancer-associated events.

Background: Cancerous cells' identity is determined via a mixture of multiple factors such as genomic variations, epigenetics, and the regulatory variations that are involved in transcription. The differences in transcriptome expression as well as abnormal structures in peptides determine phenotypical differences. Thus, bulk RNA-seq and more recent single-cell RNA-seq data (scRNA-seq) are important to identify pathogenic differences. In this case, we rely on k-mer decomposition of sequences to identify pathogenic variations in detail which does not need a reference, so it outperforms more traditional Next-Generation Sequencing (NGS) analysis techniques depending on the alignment of the sequences to a reference. Results: Via our alignment-free analysis, over esophageal and glioblastoma cancer patients, high-frequency variations over multiple different locations (repeats, intergenic regions, exons, introns) as well as multiple different forms (fusion, polyadenylation, splicing, etc.) could be discovered. Additionally, we have analyzed the importance of less-focused events systematically in a classic transcriptome analysis pipeline where these events are considered as indicators for tumor prognosis, tumor prediction, tumor neoantigen inference, as well as their connection with respect to the immune microenvironment. Conclusions: Our results suggest that esophageal cancer (ESCA) and glioblastoma processes can be explained via pathogenic microbial RNA, repeated sequences, novel splicing variants, and long intergenic non-coding RNAs (lincRNAs). We expect our application of reference-free process and analysis to be helpful in tumor and normal samples differential scRNA-seq analysis, which in turn offers a more comprehensive scheme for major cancer-associated events. [ABSTRACT FROM AUTHOR]

BACKGROUND: One of the continuous cultivation methods for acquiring quantitative data on microbial metabolism under various environmental conditions within a single experiment is the accelerostat culture system (A‐stat). It allows the rapid analysis and quantitative evaluation of the effect of environmental on the functional response of microorganisms, which is reflected by the cultural biokinetic parameters. In a classical accelerostat system, equipment and control programs maintain a constant acceleration (a) of the culture's dilution rate D[t] = Do + at. Unlike the conventional A‐stat, in which a linear change in the dilution rate is obtained, a new variant, here named a variable‐volume accelerated (VVA) system, the acceleration is variable (a = f[t]); thus, D[t] = Do + a[t]. This system requires minimal manual intervention and presents operational advantages over the classical A‐stat; the reactor's D[t] change is achieved under a simple condition: the input and output flow rates are unequal; Fin ≠ Fout. RESULTS: Using carbaryl as a study model, the dynamic behavior of the VVA system was evaluated by differential analysis of the experimental data obtained by cultivating a carbaryl‐degrading microbial community. Mathematical analysis of the VVA system established the acceleration profile a[t] for the study, quantifying the impact of dilution rate on the microbial community's biokinetic and stoichiometric parameters. CONCLUSION: The VVA system allowed observation of the effect of the D[t] gradient on the rate of change of kinetic parameters that define the physiological state of the microbial culture, together with the microbial community's macromolecular composition. © 2024 Society of Chemical Industry (SCI). [ABSTRACT FROM AUTHOR]

Copyright of Food & Machinery is the property of Food & Machinery Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to ensure that the design requirements of engineers during the design of surgical instruments meet the actual use requirements of physicians, a differential study of the performance of engineers and physicians in the use of surgical instruments was conducted. Through simulated surgical experiments, critical tasks and non-critical tasks were set up, and oculomotor data ( pupil diameter and average saccades amplitude) and questionnaire data (overall evaluation and evaluation of each index) were collected from 12 engineers and 12 physicians. The results of their differences were obtained through a four-pronged analysis. The results show that in the critical task, doctors have dilated pupils with higher cognitive load. Attention differences: doctors use primary and secondary attention allocation strategies and engineers use average attention allocation strategies. In the critical task, the physician focuses his attention compared to the engineer, with small sweeping amplitude and high information search efficiency. Device attention: in the noncritical device, the engineers design redundancy beyond the actual needs of the physician. Device evaluation index attention: safety is the common concern, comfort-related evaluation variability is large. It can be seen that attention should be paid to the differences existing between the designer’s perspective and the user’s perspective, to find the key points of design and optimization, to optimize and design surgical instruments from the actual clinical needs of physicians, and to improve the usability of surgical instruments. [ABSTRACT FROM AUTHOR]

Xizang boasts a vast and geographically complex landscape with an average elevation surpassing 4000 m. Understanding the spatiotemporal distribution of surface solar radiation is indispensable for simulating surface processes, studying climate change, and designing photovoltaic power generation and solar heating systems. A multi-dimensional, long-term, spatial, and temporal investigation of solar radiation in Xizang was conducted using three unique datasets, including the difference in surface solar radiation (SSR) between high-resolution satellite and ground station data, the annual and monthly distribution of SSR, and the interannual–monthly–daily variation and the coefficient of hourly variability. Combined with high-resolution elevation data, a strong linear correlation was shown between the radiation and the elevation below 4000 m. Furthermore, analysis reveals greater differences in data between east and west compared to the center, as well as between summer and winter seasons. SSR levels vary in steps, reaching the highest from Ngari to Shigatse and the lowest in a U-shaped area formed by southeastern Shannan and southern Nyingchi. In June, high monthly SSR coverage was the highest of the year. Since 1960, the annual mean SSR has generally exhibited a declining trend, displaying distinctive trends across various seasons and datasets. Owing to intricate meteorological factors, some regions exhibited double peaks in monthly SSR. Finally, we have introduced a solar resource assessment standard, along with a multidimensional evaluation of the resources, and categorized all townships. We offer a thorough analysis of Xizang's solar radiation to provide a comprehensive understanding, which will help to prioritize recommendations for PV construction in Xizang. [ABSTRACT FROM AUTHOR]

This article investigated the MGFN algorithm’s ability to resist differential analysis and proposed improved methods. First of all, it modeled this algorithm based on the MILP, and then got a 6-round iterative differential and a full round differential path with a total probability of 2-40, which was much larger than the differential probability of random permutation. Secondly, it gave the branch number of the S-box as an indicator to measure its differential safety.This paper also replaced the S-box of MGFN algorithm with a new S-box and proposed a new MGFN-P algorithm by modifying the key extension algorithm. Finally, through differential path search and analysis, the new algorithm, MGFN-P, was more secure and efficient than the original algorithm. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD), a prevalent histological type of lung cancer and a subtype of non-small cell lung cancer (NSCLC) accounts for 45–55% of all lung cancer cases. Various factors, including environmental influences and genetics, have been identified as contributors to the initiation and progression of LUAD. Recent large-scale analyses have probed into RNASeq, miRNA, and DNA methylation alterations in LUAD. In this study, we devised an innovative deep-learning model for lung cancer detection by integrating markers from mRNA, miRNA, and DNA methylation. The initial phase involved meticulous data preparation, encompassing multiple steps, followed by a differential analysis aimed at identifying genes exhibiting differential expression across different lung cancer stages (Stages I, II, III, and IV). The DESeq2 technique was employed for RNASeq data, while the LIMMA package was utilized for miRNA and DNA methylation datasets during the differential analysis. Subsequently, integration of all prepared omics data types was achieved by selecting common samples, resulting in a consolidated dataset comprising 448 samples and 8228 features (genes). To streamline features, principal components analysis (PCA) was implemented, and the synthetic minority over-sampling technique (SMOTE) algorithm was applied to ensure class balance. The integrated and processed data were then input into the PCA-SMOTE-CNN model for the classification process. The deep learning model, specifically designed for classifying and predicting lung cancer using an integrated omics dataset, was evaluated using various metrics, including precision, recall, F1-score, and accuracy. Experimental results emphasized the superior predictive performance of the proposed model, attaining an accuracy, precision, recall, and F1-score of 0.97 each, surpassing recent competitive methods.

Abstract Characterizing differences in sequences between two conditions, such as with and without drug exposure, using high-throughput sequencing data is a prevalent problem involving quantifying changes in sequence abundances, and predicting such differences for unobserved sequences. A key shortcoming of current approaches is their extremely limited ability to share information across related but non-identical reads. Consequently, they cannot use sequencing data effectively, nor be directly applied in many settings of interest. We introduce model-based enrichment (MBE) to overcome this shortcoming. We evaluate MBE using both simulated and real data. Overall, MBE improves accuracy compared to current differential analysis methods.

Abstract Background Numerous genes, including SOD1, mutated in familial and sporadic amyotrophic lateral sclerosis (f/sALS) share a role in DNA damage and repair, emphasizing genome disintegration in ALS. One possible outcome of chromosomal instability and repair processes is extrachromosomal circular DNA (eccDNA) formation. Therefore, eccDNA might accumulate in f/sALS with yet unknown function. Methods We combined rolling circle amplification with linear DNA digestion to purify eccDNA from the cervical spinal cord of 9 co-isogenic symptomatic hSOD1 G93A mutants and 10 controls, followed by deep short-read sequencing. We mapped the eccDNAs and performed differential analysis based on the split read signal of the eccDNAs, referred as DifCir, between the ALS and control specimens, to find differentially produced per gene circles (DPpGC) in the two groups. Compared were eccDNA abundances, length distributions and genic profiles. We further assessed proteome alterations in ALS by mass spectrometry, and matched the DPpGCs with differentially expressed proteins (DEPs) in ALS. Additionally, we aligned the ALS-specific DPpGCs to ALS risk gene databases. Results We found a six-fold enrichment in the number of unique eccDNAs in the genotoxic ALS-model relative to controls. We uncovered a distinct genic circulome profile characterized by 225 up-DPpGCs, i.e., genes that produced more eccDNAs from distinct gene sequences in ALS than under control conditions. The inter-sample recurrence rate was at least 89% for the top 6 up-DPpGCs. ALS proteome analyses revealed 42 corresponding DEPs, of which 19 underlying genes were itemized for an ALS risk in GWAS databases. The up-DPpGCs and their DEP tandems mainly impart neuron-specific functions, and gene set enrichment analyses indicated an overrepresentation of the adenylate cyclase modulating G protein pathway. Conclusions We prove, for the first time, a significant enrichment of eccDNA in the ALS-affected spinal cord. Our triple circulome, proteome and genome approach provide indication for a potential importance of certain eccDNAs in ALS neurodegeneration and a yet unconsidered role as ALS biomarkers. The related functional pathways might open up new targets for therapeutic intervention. Graphical Abstract

Introduction: Population growth and increasing water demand have exacerbated water resource scarcity. Treated wastewater (TWW) is a valuable alternative resource, but its complex composition, including micropollutants, raises concerns about reuse risks. Reactive barriers (RB) made with natural materials offer a solution to remove TWW contaminants. Evaluating RB process effectiveness and comprehending contaminant fate remain challenging. Recent advances in High-Resolution Mass Spectrometry (HRMS) and non-target analysis (NTA) provide an opportunity to identify contaminants and evaluate RB processes. The study aims to develop an NTA approach to assess RB effectiveness and understand the NTA contribution for broadening perspectives on the impact of reactive barrier treatment.Methods: In a serie of batch experiments, TWW was mixed with a RB under two conditions: TWW in contact with RB (TWW+RB) and TWW alone (TWW). After 1 h of contact, samples were extracted and analyzed using HPLC-HRMS. NTA workflow and statistical comparison between the two sample conditions were applied for data treatment. Additionally, a quantitative method was applied to 28 pharmaceutical residues. Sorption (%) was calculated by comparing concentrations in TWW+RB and TWW experiments. NTA’s applicability for sorption estimation was investigated using intensities from differential analysis.Results: Differential analysis shows significant differences in compounds that decrease or increase after contact with BR. A prioritization workflow identified and annotated 115 compounds. Natural products predominantly increased after RB contact, while compounds exhibited a significant 75% decrease in peak area are mainly pharmaceuticals. Notably, 61% of these molecules were sorbed at more than 50%. The sorption of emerging contaminants (ECs) estimated by NTA correlated satisfactorily with sorption quantified through target analysis, although caution regarding the matrix effect is necessary.Discussion: NTA provides a comprehensive view of RB treatment performance, giving information on the compounds released by the barrier and its sorption capacity. NTA emphasizes the benefits of RB treatment while highlighting the need to study compounds reloaded by RB. It is a powerful tool for understanding the advantages of nature-based reactive barrier treatment in improving the quality of TWW.

Immunoglobulin is an essential component of the body's defense against pathogens, aiding in the recognition and clearance of foreign antigens. Research concerning immunoglobulin gene and its diversity of expression across different breeds within the same species is relatively scarce. In this study, we employed RACE (Rapid Amplification of cDNA Ends) technology, prepared DNA libraries, performed high-throughput sequencing, and conducted related bioinformatics analysis to analyze the differences in immunoglobulin gene diversity and expression at different periods in Hy-line brown hens, Lueyang black-bone chickens, and Beijing-You chickens. The study found that the composition of chicken immunoglobulin genes is relatively simple, with both the light chain and heavy chain having a functional V gene. Additionally, the mechanisms of immunoglobulin diversity generation tended to be consistent among different breeds and periods of chickens, primarily relying on abundant junctional diversity, somatic hypermutation (SHM), and gene conversion (GCV) to compensate for the limitations of low-level V(D)J recombination. As the age increased, the junctional diversity of IgH and IgL tended to diversify and showed similar expression patterns among different breeds. In the three chicken breeds, the predominant types of mutations observed in IGHV and IGLV SHM were A to G and G to A transitions. Specifically, IGLV exhibited a preference for A to G mutations, whereas IGHV displayed a bias toward G to A mutations. The regions at the junctions between framework regions (FR) and complementarity-determining regions (CDR) and within the CDR regions themselves are typically prone to mutations. The locations of GCV events in IGLV and IGHV do not show significant differences, and replacement segments are concentrated in the central regions of FR1, CDR, and FR2. Importantly, gene conversion events are not random occurrences. Additionally, our investigation revealed that CDRH3 in chickens of diverse breeds and periods the potential for diversification through the incorporation of cysteine. This study demonstrates that the diversity of immunoglobulin expression tends to converge among Hy-line brown hens, Lueyang black-bone chickens, and Beijing-You chickens, indicating that the immunoglobulin gene expression mechanisms in different breeds of chickens do not exhibit significant differences due to selective breeding. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To further improve the quality of antioxidant 6PPD products, differential analysis and comparison are conducted through continuous tracking and comparison of similar domestic products. The effect of reaction temperature, circulating hydrogen content and high ketone content on the quality of antioxidant 6PPD products is investigated, and the production process is optimized. At the same time, the influence of temperature, vacuum degree, material quantity and other factors on the separation effect is studied, and the flash evaporation process is optimized. The production process optimization results have achieved good application effects in the production equipment, achieving the goal of improving the quality of antioxidant 6PPD. [ABSTRACT FROM AUTHOR]

Introduction: Idiopathic pulmonary arterial hypertension (IPAH) is a rare and sporadic form of pulmonary arterial hypertension (PAH), characterized by elevated pulmonary arterial resistance leading to right heart failure. However, molecular mechanisms of PAH development are still not completely understood. Material and methods: In this study, we aimed to uncover key mRNAs and long non-coding RNA (lncRNAs), functional modules and pathways. Moreover, to detect the dysregulated pathway or biological function, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. PPI and co-expression networks were constructed to reveal the potential roles of PAH-related mRNAs and lncRNAs. Results: A total of 3,134 genes, including 945 up-regulated and 2,189 down-regulated genes, were identified to be differentially expressed in IPAH by differential expression analysis. We identified T cell differentiation and the T cell receptor signaling pathway as up-regulated in IPAH by using GO and KEGG analysis. Based on the PPI module analysis, we identified that the pro-inflammatory genes, such as OAS1, CXCL10, STAT1 and TLR4, were the hub genes in the PPI modules. To link the lncRNAs to the PPI modules, we calculated the Spearman correlation coefficient for lncRNA-DE-mRNA pairs to identify the modules with high correlation with each lncRNA. Conclusions: Notably, 6 of these lncRNAs were associated with modules characterized by the NOD-like receptor signaling pathway and chemokine signaling pathway, suggesting that these lncRNAs may promote the occurrence of IPAH via participating in the pro-inflammatory pathways. In conclusion, our systematic analysis not only improved our understanding of the molecular mechanism, but also provided potential lncRNA biomarkers for further research. [ABSTRACT FROM AUTHOR]

The advantage of an increasing amount of bioinformatics data on leukemias intrigued us to explore the hot-spot mutation profiles and investigate the implications of those hot-spot mutations in patient survival. We retrieved somatic mutations and their distribution in protein domains through data analysis of The Cancer Genome Atlas and cBioPortal databases. After determining differentially expressed mutant genes related to leukemia, we further conducted principal component analysis and single-factor Cox regression analyses. Moreover, survival analysis was performed for the obtained candidate genes, followed by a multi-factor Cox proportional hazard model method for the impacts of the candidate genes on the survival and prognosis of patients with leukemia. At last, the signaling pathways involved in leukemia were investigated by gene set enrichment analysis. There were 223 somatic missense mutation hot-spots identified with pertinence to leukemia, which were distributed in 41 genes. Differential expression in leukemia was witnessed in 39 genes. We found a close correlation between seven genes and the prognosis of leukemia patients, among which, three genes could significantly influence the survival rate. In addition, among these three genes, CD74 and P2RY8 were highlighted due to close pertinence with survival conditions of leukemia patients. Finally, data suggested that B cell receptor, Hedgehog, and TGF-beta signaling pathways were enriched in low-hazard patients. In conclusion, these data underline the involvement of hot-spot mutations of CD74 and P2RY8 genes in survival status of leukemia patients, highlighting their as novel therapeutic targets or prognostic indicators for leukemia patients. Summary of Graphical Abstract: We identified 223 leukemia-associated somatic missense mutation hotspots concentrated in 41 different genes from 2297 leukemia patients in the TCGA database. Differential analysis of leukemic and normal samples from the TCGA and GTEx databases revealed that 39 of these 41 genes showed significant differential expression in leukemia. These 39 genes were subjected to PCA analysis, univariate Cox analysis, survival analysis, multivariate Cox regression analysis, GSEA pathway enrichment analysis, and then the association with leukemia survival prognosis and related pathways were investigated. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Cryptologic Research (2095-7025) is the property of Editorial Board of Journal of Cryptologic Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Numerous genes, including SOD1, mutated in familial and sporadic amyotrophic lateral sclerosis (f/sALS) share a role in DNA damage and repair, emphasizing genome disintegration in ALS. One possible outcome of chromosomal instability and repair processes is extrachromosomal circular DNA (eccDNA) formation. Therefore, eccDNA might accumulate in f/sALS with yet unknown function. Methods: We combined rolling circle amplification with linear DNA digestion to purify eccDNA from the cervical spinal cord of 9 co-isogenic symptomatic hSOD1G93A mutants and 10 controls, followed by deep short-read sequencing. We mapped the eccDNAs and performed differential analysis based on the split read signal of the eccDNAs, referred as DifCir, between the ALS and control specimens, to find differentially produced per gene circles (DPpGC) in the two groups. Compared were eccDNA abundances, length distributions and genic profiles. We further assessed proteome alterations in ALS by mass spectrometry, and matched the DPpGCs with differentially expressed proteins (DEPs) in ALS. Additionally, we aligned the ALS-specific DPpGCs to ALS risk gene databases. Results: We found a six-fold enrichment in the number of unique eccDNAs in the genotoxic ALS-model relative to controls. We uncovered a distinct genic circulome profile characterized by 225 up-DPpGCs, i.e., genes that produced more eccDNAs from distinct gene sequences in ALS than under control conditions. The inter-sample recurrence rate was at least 89% for the top 6 up-DPpGCs. ALS proteome analyses revealed 42 corresponding DEPs, of which 19 underlying genes were itemized for an ALS risk in GWAS databases. The up-DPpGCs and their DEP tandems mainly impart neuron-specific functions, and gene set enrichment analyses indicated an overrepresentation of the adenylate cyclase modulating G protein pathway. Conclusions: We prove, for the first time, a significant enrichment of eccDNA in the ALS-affected spinal cord. Our triple circulome, proteome and genome approach provide indication for a potential importance of certain eccDNAs in ALS neurodegeneration and a yet unconsidered role as ALS biomarkers. The related functional pathways might open up new targets for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Electronic commerce(E-commerce) transactions require secure communication to protect sensitive information such as credit card numbers, personal identification, and financial data from unauthorized access and fraud. Encryption using public key cryptography is essential to ensure secure electronic commerce transactions. RSA and Rabin cryptosystem algorithms are widely used public key cryptography techniques, and their security is based on the assumption that it is computationally infeasible to factorize the product of two large prime numbers into its constituent primes. However, existing variants of RSA and Rabin cryptosystems suffer from issues like high computational complexity, low speed, and vulnerability to factorization attacks. To overcome the issue, this article proposes a new method that introduces the concept of fake-modulus during encryption. The proposed method aims to increase the security of the Rabin cryptosystem by introducing a fake-modulus during encryption, which is used to confuse attackers who attempt to factorize the public key. The fake-modulus is added to the original modulus during encryption, and the attacker is unable to distinguish between the two. As a result, the attacker is unable to factorize the public key and cannot access the sensitive information transmitted during electronic commerce transactions. The proposed method's performance is evaluated using qualitative and quantitative measures. Qualitative measures such as visual analysis and histogram analysis are used to evaluate the proposed system's quality. To quantify the performance of the proposed method, the entropy of a number of occurrences for the pixels of cipher text and differential analysis of plaintext and cipher text is used. When the proposed method's complexity is compared to a recent variant of the Rabin cryptosystem, it can be seen that it is more complex to break the proposed method—represented as O (ɲ ×   τ)   which is higher than Rabin-P ( O (ɲ)) algorithms. [ABSTRACT FROM AUTHOR]

Oncidium, an important tropical orchid, has high ornamental value due to its specific color and occupies a significant market position for the worldwide flower. Transcriptome analysis of flower and leaf color formation provides new sources for producing novel Oncidium hybridum cultivars. We sequenced 12 samples of flowers (yellow and white) and leaves (striped and regular) of O. hybridum and assembled 381,136 and 453,566 unigene sequences from RNA-seq data, respectively. Among unigenes, 662 and 1,324 differentially expressed genes were identified in flower and leaf samples, respectively. Gene ontology and pathway enrichment showed that secondary metabolite biosynthetic pathways were responsible for flower and leaf color formation. It was determined that UGT75C1, E2.4.1.115, CCD7, E2.1.1.76, and CCoAOMT are involved in regulating flower color, and UGT75C1, LHCB, UGT, RP-L18Ae, and ABCB1 play crucial roles in regulating leaf color. Kyoto Encyclopedia of Genes and Genomes analysis revealed that UGT75C1 was significantly enriched in the anthocyanin biosynthetic pathway, showing effects on flower and leaf colors. This study was the first detailed analysis of the molecular mechanisms of O. hybridum flower and leaf colors, and the results advanced the understanding of the genetic basis of flower and leaf colors; they also provided additional support for improving commercial value and producing novel cultivars of O. hybridum. [ABSTRACT FROM AUTHOR]

BackgroundMotif enrichment analysis (MEA) identifies over-represented transcription factor binding (TF) motifs in the DNA sequence of regulatory regions, enabling researchers to infer which transcription factors can regulate transcriptional response to a stimulus, or identify sequence features found near a target protein in a ChIP-seq experiment. Score-based MEA determines motifs enriched in regions exhibiting extreme differences in regulatory activity, but existing methods do not control for biases in GC content or dinucleotide composition. This lack of control for sequence bias, such as those often found in CpG islands, can obscure the enrichment of biologically relevant motifs.ResultsWe developed Motif Enrichment In Ranked Lists of Peaks (MEIRLOP), a novel MEA method that determines enrichment of TF binding motifs in a list of scored regulatory regions, while controlling for sequence bias. In this study, we compare MEIRLOP against other MEA methods in identifying binding motifs found enriched in differentially active regulatory regions after interferon-beta stimulus, finding that using logistic regression and covariates improves the ability to call enrichment of ISGF3 binding motifs from differential acetylation ChIP-seq data compared to other methods. Our method achieves similar or better performance compared to other methods when quantifying the enrichment of TF binding motifs from ENCODE TF ChIP-seq datasets. We also demonstrate how MEIRLOP is broadly applicable to the analysis of numerous types of NGS assays and experimental designs.ConclusionsOur results demonstrate the importance of controlling for sequence bias when accurately identifying enriched DNA sequence motifs using score-based MEA. MEIRLOP is available for download from https://github.com/npdeloss/meirlop under the MIT license.

To determine the effects of drying methods on the volatile compounds and explore the key aroma compounds in Chrysanthemum nankingense leaves, head-space solid phase micro-extraction combined with gas chromatography mass spectrometry (HS-SPME-GC-MS) was employed for quantitative and qualitative analysis of the volatile compounds in C. nankingense leaves dried by hot air drying, vacuum-freeze drying or microwave-hot air drying. The result showed that a total of 140 compounds belonging to six classes (terpenes, esters, aldehydes, alcohols, aromatic compounds and other substances) were identified in all samples. Of these, 112, 86, 83 and 85 were detected in fresh and dried C. nankingense obtained by hot air drying, microwave-hot air drying, and vacuum-freeze drying, respectively. Among these compounds, terpenes were the most abundant, with contents of 229 474.33, 64 629.68, 56 469.88 and 70 832.87 μg/kg in fresh, hot air dried, microwave-hot air dried, and vacuum-freeze dried samples, respectively. Compared with the other drying methods, vacuum-freeze drying gave better retention of the abundance of volatile compounds. Vacuum-freeze dried C. nankingense had similar flavor to fresh samples, showing camphor-like, turpentine-like, flowery and grassy aromas. GC-MS combined with odor activity values (OAVs) confirmed that β-ocimene, caryophyllene and trans-β-farnesene were the major aroma components. GC-MS combined with E-nose can represent an efficient nondestructive method for the detection of volatile compounds in C. nankingense leaves and allow the discrimination of dried C. nankingense obtained by different drying methods. These results provide a theoretical basis for choosing drying methods and understanding the difference in volatiles components in dried C. nankingense obtained by different drying methods.

Abstract Background A common task in analyzing metatranscriptomics data is to identify microbial metabolic pathways with differential RNA abundances across multiple sample groups. With information from paired metagenomics data, some differential methods control for either DNA or taxa abundances to address their strong correlation with RNA abundance. However, it remains unknown if both factors need to be controlled for simultaneously. Results We discovered that when either DNA or taxa abundance is controlled for, RNA abundance still has a strong partial correlation with the other factor. In both simulation studies and a real data analysis, we demonstrated that controlling for both DNA and taxa abundances leads to superior performance compared to only controlling for one factor. Conclusions To fully address the confounding effects in analyzing metatranscriptomics data, both DNA and taxa abundances need to be controlled for in the differential analysis.

The differential property of the lightweight cipher algorithm ACE was researched.n-dimension ring AND-gate combination was defined and its differential property was described accurately by only O(n) expressions with the MILP method by analyzing the relationship among AND gates.The nonlinear operation of ACE was transformed to the 32-dimension ring AND-gate combination and the MILP differential model of ACE was proposed.According to the characteristics of Gurobi solver, a model for fast solving the MILP differential model of ACE was given.For ACE permutation with 3 to 6 steps, the optimal differential characteristic was obtained and its probability was improved by multi-difference technique.The differential forge attack on authenticated encryption algorithm ACE- AE-128 and the differential collision attack on hash algorithm ACE- H-256 was given with 3-step ACE permutation, and the success probability was 2-90.52.And it was proved that the 4-steps ACE permutation arrived the differential security bound of 128 bit.Actually, the MILP differential description of ring AND-gate combination can be applied on more cipher algorithms, such as SIMON, Simeck.

In order to evaluate the differences in typical heated tobacco products of different brands, the chemical components in the aerosol particulate matters from 19 heated tobacco product samples were determined by gas chromatography-quadrupole/exactive orbitrap mass spectrometry (GC-Q Exactive Orbitrap MS). Differential statistical analysis of chemical component types and relative mass fractions was performed on the particulate matter. The results showed that: 1) Chemical components in aerosol particulate matters from the heated tobacco product samples of the same brand were similar in type and relative mass fraction. 2) Based on PCA score plots from the selected samples, there was a clear distinction between different brands of heated cigarette samples. Foreign heated cigarette samples had a relatively concentrated spatial distribution and were clustered by brand, while the distribution of domestic heated cigarette samples was relatively discrete. 3) Compared to the selected domestic heated cigarette samples, there were 56 and 9 components in the aerosol particulate matters from the foreign heated cigarette samples that significantly decreased and increased in their mass fractions, respectively. [ABSTRACT FROM AUTHOR]

The Pilsung cipher is part of the North Korean Red Star operating system, which was leaked to the West in 2014. Initial analysis by Kryptos Logic reported a possibility of a class of weak keys due to the use of pseudo-random diffusion. Following this lead, we analyzed the cipher and identified a small class of such weak keys. We developed techniques for searching for a key that belongs to the class. After spending thousands of CPU hours, we found a supposedly weak key for a slightly weaker version of Pilsung, but the key did not behave as we expected. On further investigation we found out a crucial misunderstanding in a critical part of the cipher and that no such class of weak keys exists in Pilsung. Thus, this paper makes two main contributions to the art of cryptanalysis. First, it identifies and shows how to investigate a potential weakness in randomizing diffusion, which although does not exist in Pilsung, may affect future designs. Second, it highlights the need for early verification of results in order to identify errors before expending significant resources. [ABSTRACT FROM AUTHOR]

[Objectives] This study was conducted to explore the X-ray manifestations of pneumoconiosis patients and differentiation from pulmonary tuberculosis. [Methods] Retrospective analysis was conducted on 103 patients who underwent lung exxminations, including47 cases of pneumoconiosis and 56 cases of pulmonary tuberculosis. The differences in nodule characteristics and accompanying cavity sign between pneumoconiosis and pulmonary tuberculosis were compared. [Results] The X-ray manifestations of pneumoconiosis patients mainly included various forms of lung images, which were uneven in density, and had blurry edges, and sometimes thickening of lung markings and reduction of lung volume could be observed. The acinar nodules observed in X-ray films of patients with hematogenous diiseminated pulmonary tuberculosis appeared petal like. The uniformity of nodule appearance such as nodule distribution, nodule density, and nodule size was significantly lower in pneumoconiosis than in hematogenous diiseminated pulmonary tuberculosis, showing a statistical significance (P<0.05). The diameter of cavities in patients with pneumoconiosis accompanied by cavity sign [ (0. (64 ±0. 13 vs 3.37 ± 0. 95) cm] was lower than that in patients with secondary pulmona¬ry tuberculosis accompanied by cavity sign. There was a significant difference in the thickness of the cavity wall between the two diseases, and patients with pneumoconiosis accompanied by cavity sign had a higher rate of thick waH cavities ( >3 mm). The X-ray manifestations of pneumoconiosis and tuberculosis were rela¬tively similar, but the distribution, density and size of nodules in pneumoconiosis were relatively uneven, and the patients accompanied by cavity sign had smaller cavity diameter and higher rate of thick-waHed cavities. [Conclusions] This study provides a reference for the clinical diferential diagnosis of pneumoconiosis and pulmonary tuberculosis. [ABSTRACT FROM AUTHOR]

RNA biology is revolutionized by recent developments of diverse high-throughput technologies for transcriptome-wide profiling of molecular RNA structures. RNA structurome profiling data can be used to identify differentially structured regions between groups of samples. Existing methods are limited in scope to specific technologies and/or do not account for biological variation. Here, we present dStruct which is the first broadly applicable method for differential analysis accounting for biological variation in structurome profiling data. dStruct is compatible with diverse profiling technologies, is validated with experimental data and simulations, and outperforms existing methods.

Introduction: High-grade serous ovarian cancer (HGSOC) is the most common histological subtype of ovarian cancer, and is associated with high mortality rates. Methods: In this study, we analyzed specific cell subpopulations and compared different gene functions between healthy ovarian and ovarian cancer cells using single-cell RNA sequencing (ScRNA-seq). We delved deeper into the differences between healthy ovarian and ovarian cancer cells at different levels, and performed specific analysis on endothelial cells. Results: We obtained scRNA-seq data of 6867 and 17056 cells from healthy ovarian samples and ovarian cancer samples, respectively. The transcriptional profiles of the groups differed at various stages of ovarian cell development. A detailed comparison of the cell cycle, and cell communication of different groups, revealed significant differences between healthy ovarian and ovarian cancer cells. We also found that apoptosis-related genes, URI1, PAK2, PARP1, CLU and TIMP3, were highly expressed, while immune-related genes, UBB, RPL11, CAV1, NUPR1 and Hsp90ab1, were lowly expressed in ovarian cancer cells. The results of the ScRNA-seq were verified using qPCR. Discussion: Our findings revealed differences in function, gene expression and cell interaction patterns between ovarian cancer and healthy ovarian cell populations. These findings provide key insights on further research into the treatment of ovarian cancer. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sarcopenia, characterized by age-related loss of muscle mass, strength, and decreased physical performance, is a growing public health challenge amid the rapidly ageing population. As there are no approved drugs that target sarcopenia, it has become increasingly urgent to identify promising pharmacological interventions. In this study, we conducted an integrative drug repurposing analysis utilizing three distinct approaches. Firstly, we analyzed skeletal muscle transcriptomic sequencing data in humans and mice using gene differential expression analysis, weighted gene co-expression analysis, and gene set enrichment analysis. Subsequently, we employed gene expression profile similarity assessment, hub gene expression reversal, and disease-related pathway enrichment to identify and repurpose candidate drugs, followed by the integration of findings with rank aggregation algorithms. Vorinostat, the top-ranking drug, was also validated in an in vitro study, which demonstrated its efficacy in promoting muscle fiber formation. Although still requiring further validation in animal models and human clinical trials, these results suggest a promising drug repurposing prospect in the treatment and prevention of sarcopenia. [ABSTRACT FROM AUTHOR]

Background: A common task in analyzing metatranscriptomics data is to identify microbial metabolic pathways with differential RNA abundances across multiple sample groups. With information from paired metagenomics data, some differential methods control for either DNA or taxa abundances to address their strong correlation with RNA abundance. However, it remains unknown if both factors need to be controlled for simultaneously. Results: We discovered that when either DNA or taxa abundance is controlled for, RNA abundance still has a strong partial correlation with the other factor. In both simulation studies and a real data analysis, we demonstrated that controlling for both DNA and taxa abundances leads to superior performance compared to only controlling for one factor. Conclusions: To fully address the confounding effects in analyzing metatranscriptomics data, both DNA and taxa abundances need to be controlled for in the differential analysis. [ABSTRACT FROM AUTHOR]