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EDEM-based study on the adjustable feeding parameters of square bale maize straw bale-breaking device
One of the primary challenges faced by small rubbing filament machines is the significant variability in material sizes, particularly in the feeding direction. This variability complicates the processing of locally baled straw with a single device. To address this issue, an adjustable feeding and bale-breaking device was developed and tested to enhance the filamentous performance of baled straw. The machine integrates a series of bale-breaking knives along with a pair of feeding and bale-breaking rollers. This paper presents an overview of the machine’s structure and operating principles, alongside an analysis of the forces acting on the straw within the device, which informed the design of key components and devices. A discrete element simulation model suitable for square baled-straw has been established, providing a research foundation for the subsequent optimization of device design parameters. Effects of motor bale-breaking roller rotating speed (x1), bale-breaking roller height (x2) and bale-breaking knife quantity (x3) on the productivity of bonding bond destruction rate (Y1) and the particle average speed (Y2) were explored. Three-dimensional quadratic regression orthogonal rotation central combination experiment method combined with response surface method was used to conduct experiments and explore the interaction effects of influence factors on indicators. A regression model of influence factors and evaluation indicators was established through the analysis of variance. The significant factors affecting Y1 were ordered of x1, x2, x3, and the significant factors affecting Y2 were ordered of x2, x3, x1. In the interaction of factors, x1x2 and x2x3 had an extremely significant impact, and x1x3 had a significant impact on Y1; x1x2, x1x3 and x2x3 had a significant impact on Y2. The optimal structure and working parameters combination were determined to be 1448 rpm for x1, 268 mm for x2, and 14 pieces for x3. Verification experiments demonstrated that the actual values were 96.95% for the straw rubbing rate and 235.13 kg/(kW·h) for the per unit power productivity. The operation of the adjustable feeding and bale-breaking device developed in this study proved effective in enhancing productivity and breaking performance during the feeding of baled straw. It successfully met the design requirements for the grain size necessary for the comprehensive utilization of straw. Overall, this research establishes a foundational basis for the further development of a small, multipurpose straw rubbing filament machine.
Author Correction: Association between depression and diabetes among American adults using NHANES data from 2005 to 2020
Genetic diversity, population structure in a historical panel of Brazilian soybean cultivars
Soybean [Glycine max (L.) Merrill] is one of the most widely grown legumes in the world, with Brazil being its largest producer and exporter. Breeding programs in Brazil have resulted from multiple cycles of selection and recombination starting from a small number of USA cultivar ancestors in the 1950s and 1960s years. This process has led to the successful adaptation of this crop to tropical conditions, a phenomenon known as tropicalization. Many studies describe a narrow genetic background in Brazilian soybean cultivars. Various factors can affect the genetic diversity in species, especially in cultivated crops, such as the reproduction type, artificial selection, and the number and sources of variability in the breeding programs. In turns, the genetic diversity can affect the linkage disequilibrium blocks (LD) patterns and, consequently, molecular breeding strategies for selection of target loci for agronomic traits. We used high-throughput genotyping with SoySNP50K Illumina SNP markers to assess a collection of 370 Brazilian soybean accessions covering more than 60 years of soybean breeding in Brazil. Our goal was to investigate population structure and genetic diversity in the Brazilian germplasm, detect patterns of LD blocks, and identify regions presenting signals of selective swaps linked with quantitative trait loci (QTLs) of agronomic interest. Population structure analysis revealed two major groups among all genotypes, primarily differentiated by the year of release, separating old and new cultivars (before and after 2000´s years), and by growth habit (stem termination type—SST). The group I comprises about 75% of the panel and includes cultivars release before 2000`s years, including the oldest cultivars released in Brazil, most of which exhibit a determinate growth habit and maturity groups VI and VII. Group II includes only 83 materials, but shows higher levels of diversity than group I, representing most recent introductions in Brazilian germplasm. Further analysis of substructure within Group I, identified seven subgroups with no clear trend for segregation based on maturity group, STT or year of release. Instead, these subgroups were based on the contribution of key donors of disease resistance and adaptability, as soybean cultivation expanded from the South to Central region of Brazil. This finding is consistent with the history of soybean expansion in Brazil. We identified 123 genomic regions under selection among the groups of Brazilian cultivars associated with 440 quantitative trait loci (QTLs), revealing regions fixed across the breeding process associated with yield, disease resistance, water efficiency use, and others.
Noninvasive imaging biomarker reveals invisible microscopic variation in acute ischaemic stroke (≤ 24 h): a multicentre retrospective study
Analysis of glutamate-dependent mechanism and optimization of fermentation conditions for poly-gamma-glutamic acid production by Bacillus subtilis SCP017-03
Poly-gamma-glutamic acid (γ-PGA) is mainly synthesized by glutamate-dependent strains in the manufacturing industry. Therefore, understanding glutamate-dependent mechanisms is imperative. In this study, we first systematically analyzed the response of Bacillus subtilis SCP017-03 to glutamate addition by comparing transcriptomics and proteomics. The introduction of glutamate substantially altered gene expression within the central metabolic pathway of cellular carbon. Most genes in the pentose phosphate pathway (PPP), tricarboxylic acid (TCA) cycle, and energy-consuming phase of the glycolysis pathway (EMP) were down-regulated, whereas those in the energy-producing phase of glycolysis and those responsible for γ-PGA synthesis were up-regulated. Based on these findings, the fermentation conditions were optimized, and γ-PGA production was improved by incorporating oxygen carriers. In a batch-fed fermentor with glucose, the γ-PGA production reached 95.2 g/L, demonstrating its industrial production potential. This study not only elucidated the glutamate dependence mechanism of Bacillus subtilis but also identified a promising metabolic target for further enhancing γ-PGA production.
How and why small volcanic ocean islands collapse and move vertically up and down
Fast and accurate imputation of genotypes from noisy low-coverage sequencing data in bi-parental populations
Motivation Genotyping of bi-parental populations can be performed with low-coverage next-generation sequencing (LC-NGS). This allows the creation of highly saturated genetic maps at reasonable cost, precisely localized recombination breakpoints (i.e., the crossovers), and minimized mapping intervals for quantitative-trait locus analysis. The main issues with these low-coverage genotyping methods are (1) poor performance at heterozygous loci, (2) high percentage of missing data, (3) local errors due to erroneous mapping of sequencing reads and reference genome mistakes, and (4) global, technical errors inherent to NGS itself. Recent methods like Tassel-FSFHap or LB-Impute are excellent at addressing issues 1 and 2, but nonetheless perform poorly when issues 3 and 4 are persistent in a dataset (i.e., “noisy” data). Here, we present a new algorithm for imputation of LC-NGS data that eliminates the need of complex pre-filtering of noisy data, accurately types heterozygous chromosomal regions, precisely estimates crossover positions, corrects erroneous data, and imputes missing data. The imputation of genotypes and recombination breakpoints is based on maximum-likelihood estimation. We compare its performance with Tassel-FSFHap and LB-Impute using simulated data and two real datasets. NOISYmputer is consistently more efficient than the two other software tested and reaches average breakpoint precision of 99.9% and average recall of 99.6% on illumina simulated dataset. NOISYmputer consistently provides precise map size estimations when applied to real datasets while alternative tools may exhibit errors ranging from 3 to 1845 times the real size of the chromosomes in centimorgans. Furthermore, the algorithm is not only highly effective in terms of precision and recall but is also particularly economical in its use of RAM and computation time, being much faster than Hidden Markov Model methods. Availability NOISYmputer and its source code are available as a multiplatform (Linux, macOS, Windows) Java executable at the URL https://gitlab.cirad.fr/noisymputer/noisymputerstandalone/-/tree/1.0.0-RELEASE?reftype=tags.
Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax
Abstract Accurate malaria diagnosis with precise identification of Plasmodium species is crucial for an effective treatment. While microscopy is still the gold standard in malaria diagnosis, it relies heavily on trained personnel. Artificial intelligence (AI) advances, particularly convolutional neural networks (CNNs), have significantly improved diagnostic capabilities and accuracy by enabling the automated analysis of medical images. Previous models efficiently detected malaria parasites in red blood cells but had difficulty differentiating between species. We propose a CNN-based model for classifying cells infected by P. falciparum, P. vivax, and uninfected white blood cells from thick blood smears. Our best-performing model utilizes a seven-channel input and correctly predicted 12,876 out of 12,954 cases. We also generated a cross-validation confusion matrix that showed the results of five iterations, achieving 63,654 out of 64,126 true predictions. The model’s accuracy reached 99.51%, a precision of 99.26%, a recall of 99.26%, a specificity of 99.63%, an F1 score of 99.26%, and a loss of 2.3%. We are now developing a system based on real-world quality images to create a comprehensive detection tool for remote regions where trained microscopists are unavailable.
Carotid artery stenosis and ischemic cerebrovascular events after radiotherapy in patients with head and neck cancer
Radiotherapy is the main treatment for patients with head and neck cancer (HNC) and is associated with an increased risk of ischemic cerebrovascular events (ICVE). The purpose of this cross-sectional study was to determine the incidence of ICVE and carotid artery stenosis (CAS) in patients with HNC who receive radiotherapy and the risk factors for CAS. We enrolled 907 patients with HNC who underwent radiotherapy between February 2011 and June 2022 and obtained information on their clinical and tumor characteristics and their treatment from the clinical records. Data on risk factors for atherosclerosis, medications used, and radiotherapy were also collected. The patients were followed through to the end of 2023 unless they died or were lost to follow-up. The overall incidence of ICVE was 1.98%, with a cumulative incidence of 1.65% over 5 years. In patients who did not have a preexisting carotid artery lesion, the cumulative incidence of significant CAS was 1.3% at 12 months, 2.2% at 24 months, and 2.5% at 36 months post-radiotherapy. The most important risk factors for new CAS were age >65 years (aHR = 2.60, p = 0.008, 95% confidence Interval: 1.28–5.30), laryngeal cancer (aHR = 2.36, p<0.017, 95% confidence Interval: 1.01–5.55), and total plaque score (aHR = 1.38, p<0.001, 95% confidence Interval: 1.23–1.56). There was a significant increase in stenosis, plaque score, and wall thickness in all areas in the carotid artery (p<0.001). The incidence of ICVE and the cumulative incidence of CAS was found to be lower in the Thai population than in other populations. The main risk factors for new CAS were age >65 years, laryngeal cancer, and total plaque score. Changes in the carotid artery were detected early and affected all areas in the artery. Patients with HNC treated by radiotherapy should be assessed for risk factors for CAS and undergo vascular surveillance during follow-up.
Author Correction: High vulnerability of the endemic Southern Ocean snail Neobuccinum eatoni (Buccinidae) to critical projected oceanographic changes
A new computational framework for simulating airway resistance, fraction of exhaled nitric oxide, and diffusing capacity for nitric oxide
In this paper, we present a new computational framework for the simulation of airway resistance, the fraction of exhaled nitric oxide, and the diffusion capacity for nitric oxide in healthy and unhealthy lungs. Our approach is firstly based on a realistic representation of the geometry of healthy lungs as a function of body mass, which compares well with data from the literature, particularly in terms of lung volume and alveolar surface area. The original way in which this geometry is created, including an individual definition of the airways in the first seven generations of the lungs, makes it possible to consider the heterogeneous nature of the lungs in terms of perfusion and ventilation. In addition, a geometry can be easily modified to simulate various abnormalities, local or global (constriction, inflammation, perfusion defect). The natural variability of the lungs at constant body mass is also considered. The computational framework includes the possibility to simulate, on a given (possibly modified) geometry, a test to measure the flow resistance of the lungs (including its component due to the not fully developed flow in the first generations of lungs), a test to measure the concentration of nitric oxide in the exhaled air, and a test to measure the diffusion capacity for nitric oxide. This is implemented in the framework by solving different transport equations (momentum and convection/diffusion) describing these tests. Through numerous simulations, we demonstrate the ability of our model to reproduce results from the literature, both for healthy lungs and lungs of patients with asthma or chronic obstructive pulmonary disease. Such a computational framework, through the possibilities of numerous and rapid tests that it allows, sheds new light on experimental data by providing information on the phenomena that take place in the distal generations of the lungs, which are difficult to access with imaging.
Analysis of the cardiotoxic and myorelaxant effects of camphor on fish of the Nile tilapia species (Oreochromis niloticus) (Linnaeus 1758)
High pulse pressure is associated with an increased risk of prediabetes in hypertensive individuals: A retrospective study based on an adult Chinese population
Objectives The pulse pressure (PP) is an important factor influencing the outcomes of diabetes. However, the relationship between the PP and prediabetes has been rarely studied and how this association might be impacted by hypertension is not clear. Methods In this study, we retrospectively included 184,252 adults from 32 regions in China, spanning from 2010 to 2016. Cox regression and sensitivity analysis were used to examine the relationship between PP and prediabetes. For the hypertensive population, Cox proportional hazards regression and smooth curve fitting were performed to explore the non-linear relationship between PP and prediabetes. A two-stage Cox proportional hazards regression model was used to determine the inflection point of PP in relation to the risk of prediabetes. Results After adjusting for confounding factors, we found a positive association between PP and prediabetes (HR: 1.11, 95% CI: 1.03–1.19, P = 0.0045). However, we observed that this relationship was not significant in the normal blood pressure group (HR: 1.06, 95% CI: 0.94–1.18, P = 0.3529). We also found a non-linear relationship between PP and the risk of prediabetes in hypertensive individuals. The inflection point of PP was 31 mmHg. When PP ≥ 31 mmHg, there was a positive association with the risk of prediabetes (HR: 1.22, 95% CI: 1.04–2.08, P <0.0001). Conversely, when PP < 31 mmHg, this association was not significant (HR: 0.83, 95% CI: 0.59–1.15, P = 0.2646). Conclusions This study suggests a non-linear relationship between PP and the risk of prediabetes in hypertensive individuals. Maintaining PP within 31 mmHg is crucial for preventing the occurrence of prediabetes.
Kinetic and isothermal study of dye absorption using pre-treated natural fabrics using polyamine compounds
Abstract The study examined the use of cationic polymers (Polyethyleneimine and chitosan) in treating fabrics like cotton, wool, and cotton/wool (70/30) to improve their dyeability and printability. The study examined factors such as dye concentration, time, and temperature for the dyeing process. Results showed that all dyed and printed fabrics treated with polyethyleneimine and chitosan increased color strength by significant percentages. Fastness properties, such as washing, rubbing, acidic and alkaline perspiration, and lightness, improved significantly. Fabric roughness, tensile strength, and elongation decreased by about 4-10% for each fabric. Additionally, the dyed and printed fabrics showed high resistance to bacteria and fungi. The study contributed to reducing chemicals used in traditional dyeing processes by a significant percentage, as the dyeing bath contained only the treated sample and dye solution. Furthermore kintic and isothermal study was investigated to explain the behaviour of treated fabrics for dye absorption.
Video-based estimation of blood pressure
In this work, we propose a non-contact video-based approach that estimates an individual’s blood pressure. The estimation of blood pressure is critical for monitoring hypertension and cardiovascular diseases such as coronary artery disease or stroke. Estimation of blood pressure is typically achieved using contact-based devices which apply pressure on the arm through a cuff. Such contact-based devices are cost-prohibitive as well as limited in their scalability due to the requirement of specialized equipment. The ubiquity of mobile phones and video-based capturing devices motivates the development of a non-contact blood pressure estimation method—Video-based Blood Pressure Estimation (V-BPE). We leverage the time difference of the blood pulse arrival at two different locations in the body (Pulse Transit Time) and the inverse relation between the blood pressure and the velocity of blood pressure pulse propagation in the artery to analytically estimate the blood pressure. Through statistical hypothesis testing, we demonstrate that Pulse Transit Time-based approaches to estimate blood pressure require knowledge of subject specific blood vessel parameters, such as the length of the blood vessel. We utilize a combination of computer vision techniques and demographic information (such as the height and the weight of the subject) to capture and incorporate the aforementioned subject specific blood vessel parameters into our estimation of blood pressure. We demonstrate the robustness of V-BPE by evaluating the efficacy of blood pressure estimation in demographically diverse, outside-the-lab conditions. V-BPE is advantageous in three ways; 1) it is non-contact-based, reducing the possibility of infection due to contact 2) it is scalable, given the ubiquity of video recording devices and 3) it is robust to diverse demographic scenarios due to the incorporation of subject specific information.
Mechanistic study of the effect of a high-salt diet on the intestinal barrier
The impact of intermittent preventive treatment in school aged children with dihydroartemisinin piperaquine and artesunate amodiaquine on IgG response against six blood stage Plasmodium falciparum antigens
Several interventional strategies have been implemented in malaria endemic areas where the burden is high, that include among others, intermittent preventive treatment (IPT), a tactic that blocks transmission and can reduce disease morbidity. However, the implementation IPT strategies raises a genuine concern, intervening the development of naturally acquired immunity to malaria which requires continuous contact with parasite antigens. This study investigated whether dihydroartemisinin-piperaquine (DP) or artesunate-amodiaquine (ASAQ) IPT in schoolchildren (IPTsc) impairs IgG reactivity to six malaria antigens. An IPTsc trial in north-eastern Tanzania administered three doses of DP or ASAQ at four-monthly intervals and the schoolchildren were followed up. This study compared IgG reactivity against GLURP-R2, MSP1, MSP3, and CIDR domains (CIDRa1.1, CIDRa1.4, and CIDRa1.5) of Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP-1) in intervention and control groups using enzyme linked immunosorbent assay (ELISA) technique. During the study, 369 schoolchildren were available for analysis, 119, 134 and 116 participants in the control, DP and ASAQ groups, respectively. Breadth of malaria antigen recognition increased significantly during and after the intervention phases and did not differ between the study groups (Trend test: DP, z-score = 5.92, p < 0.001, ASAQ, z-score = 6.64, p < 0.001 and control, z-score = 5.85, p < 0.001). There were no differences between the control and ASAQ group in the recognition of any of the tested antigens at all visits. In the DP group, however, during the intervention period IPTsc did not impair antibody against MSP1, MSP3, CIDRa1.1, CIDRa1.4 and CIDRa1.5, but it did impair against GLURP-R2. The current study has shown that effective IPTsc with DP or ASAQ does not interfere with the development of antibodies against malaria antigens of the blood stages, suggesting that the advancement of naturally acquired immunity to malaria is not impeded by IPTsc interventions.
Chromosome distribution of four LTR retrotransposons and 18 S rDNA in coffea eugenioides
Application of attenuated total reflection–Fourier transform infrared spectroscopy in semi-quantification of blood lipids and characterization of the metabolic syndrome
Background/Purpose Dyslipidemia, a hallmark of metabolic syndrome (MetS), contributes to atherosclerotic and cardiometabolic disorders. Due to days-long analysis, current clinical procedures for cardiotoxic blood lipid monitoring are unmet. This study used AI-assisted attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy to identify MetS and precisely quantify multiple blood lipid levels with a blood sample of 0.5 µl and the assaying time is approximately 10 minutes. Methods ATR-FTIR spectroscopy with 1738 data points in the spectral range of 4000–650 cm−1 was used to analyze the blood samples. An adaptive synthetic technique was used to establish a prevalence-balanced dataset. LDL-C, HDL-C, TG, VLDL-C, and cholesterol levels were defined as the predicted targets of lipid absorption profiles. Linear regression (LR), gradient boosting regression tree (GBT), and histogram-based gradient boosting regression tree (HGBTR) were used to train the models. Lipid profile value prediction was evaluated using R2 and MAE, whereas MetS prediction was evaluated using area under the ROC curve. Results A total of 150 blood samples from 25 individuals without MetS and 25 with MetS yielded 491 spectral measurements. In the regression models, HGBT best predicted the targets of TG, CHOL, HDL-C, LDL-C, and VLDL-C with R2 values of 0.854 (0.12), 0.684 (0.08), 0.758 (0.10), and 0.419 (0.11), respectively. The classification model with the greatest AUC was RF (0.978), followed by HGBT (0.972) and GBT (0.967). Conclusion The results of this study revealed that predicting MetS and determining blood lipid levels with high R2 values and limited errors are feasible for monitoring during therapy and intervention.