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The European Union’s recent decision to renew the authorization for the use of glyphosate until 15 December 2033 has stimulated scientific discussion all around the world regarding its toxicity or otherwise for humans. Glyphosate is a chemical of which millions of tons have
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The European Union’s recent decision to renew the authorization for the use of glyphosate until 15 December 2033 has stimulated scientific discussion all around the world regarding its toxicity or otherwise for humans. Glyphosate is a chemical of which millions of tons have been used in the last 50 years worldwide to dry out weeds in cultivated fields and greenhouses and on roadsides. Concern has been raised in many areas about its possible presence in the food chain and its consequent adverse effects on health. Both aspects that argue in favor of toxicity and those that instead may indicate limited toxicity of glyphosate are discussed here. The widespread debate that has been generated requires further investigations and field measurements to understand glyphosate’s fate once dispersed in the environment and its concentration in the food chain. Hence, there is a need for validated analytical methods that are available to analysts in the field. In the present review, methods for the analytical determination of glyphosate and its main metabolite, AMPA, are discussed, with a specific focus on chromatographic techniques applied to cereal products. The experimental procedures are explained in detail, including the cleanup, derivatization, and instrumental conditions, to give the laboratories involved enough information to proceed with the implementation of this line of analysis. The prevalent chromatographic methods used are LC-MS/MS, GC-MS/SIM, and GC-MS/MS, but sufficient indications are also given to those laboratories that wish to use the better performing high-resolution MS or the simpler HPLC-FLD, HPLC-UV, GC-NPD, and GC-FPD techniques for screening purposes. The concentrations of glyphosate from the literature measured in wheat, corn, barley, rye, oats, soybean, and cereal-based foods are reported, together with its regulatory status in various parts of the world and its accumulation mechanism. As for its accumulation in cereals, the available data show that glyphosate tends to accumulate more in wholemeal flours than in refined ones, that its concentration in the product strictly depends on the treatment period (the closer it is to the time of harvesting, the higher the concentration), and that in cold climates, the herbicide tends to persist in the soil for a long time.
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Soheila Ali Akbari Ghavimi, Trent J. Faulkner, Rama Rao Tata, August J. Hemmerla, Samantha E. Huddleston, Farnoushsadat Rezaei, Ethan S. Lungren, Rui Zhang, Erin E. Bumann and Bret D. Ulery
Pharmaceuticals2024, 17(5), 585; https://doi.org/10.3390/ph17050585 (registering DOI) - 02 May 2024
Though crucial for natural bone healing, local calcium ion (Ca2+) and phosphate ion (Pi) concentrations can exceed the cytotoxic limit leading to mitochondrial overload, oxidative stress, and cell death. For bone tissue engineering applications, H2S can be
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Though crucial for natural bone healing, local calcium ion (Ca2+) and phosphate ion (Pi) concentrations can exceed the cytotoxic limit leading to mitochondrial overload, oxidative stress, and cell death. For bone tissue engineering applications, H2S can be employed as a cytoprotective molecule to enhance mesenchymal stem cell (MSC) tolerance to cytotoxic Ca2+/Pi concentrations. Varied concentrations of sodium hydrogen sulfide (NaSH), a fast-releasing H2S donor, were applied to assess the influence of H2S on MSC proliferation. The results suggested a toxicity limit of 4 mM for NaSH and that 1 mM of NaSH could improve cell proliferation and differentiation in the presence of cytotoxic levels of Ca2+ (32 mM) and/or Pi (16 mM). To controllably deliver H2S over time, a novel donor molecule (thioglutamic acid—GluSH) was synthesized and evaluated for its H2S release profile. Excitingly, GluSH successfully maintained cytoprotective level of H2S over 7 days. Furthermore, MSCs exposed to cytotoxic Ca2+/Pi concentrations in the presence of GluSH were able to thrive and differentiate into osteoblasts. These findings suggest that the incorporation of a sustained H2S donor such as GluSH into CaP-based bone graft substitutes can facilitate considerable cytoprotection, making it an attractive option for complex bone regenerative engineering applications.
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Angelika Zaszczyńska, Arkadiusz Gradys, Anna Ziemiecka, Piotr K. Szewczyk, Ryszard Tymkiewicz, Małgorzata Lewandowska-Szumieł, Urszula Stachewicz and Paweł Ł. Sajkiewicz
Int. J. Mol. Sci.2024, 25(9), 4980; https://doi.org/10.3390/ijms25094980 (registering DOI) - 02 May 2024
Nanofibrous materials generated through electrospinning have gained significant attention in tissue regeneration, particularly in the domain of bone reconstruction. There is high interest in designing a material resembling bone tissue, and many scientists are trying to create materials applicable to bone tissue engineering
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Nanofibrous materials generated through electrospinning have gained significant attention in tissue regeneration, particularly in the domain of bone reconstruction. There is high interest in designing a material resembling bone tissue, and many scientists are trying to create materials applicable to bone tissue engineering with piezoelectricity similar to bone. One of the prospective candidates is highly piezoelectric poly(vinylidene fluoride) (PVDF), which was used for fibrous scaffold formation by electrospinning. In this study, we focused on the effect of PVDF molecular weight (180,000 g/mol and 530,000 g/mol) and process parameters, such as the rotational speed of the collector, applied voltage, and solution flow rate on the properties of the final scaffold. Fourier Transform Infrared Spectroscopy allows for determining the effect of molecular weight and processing parameters on the content of the electroactive phases. It can be concluded that the higher molecular weight of the PVDF and higher collector rotational speed increase nanofibers’ diameter, electroactive phase content, and piezoelectric coefficient. Various electrospinning parameters showed changes in electroactive phase content with the maximum at the applied voltage of 22 kV and flow rate of 0.8 mL/h. Moreover, the cytocompatibility of the scaffolds was confirmed in the culture of human adipose-derived stromal cells with known potential for osteogenic differentiation. Based on the results obtained, it can be concluded that PVDF scaffolds may be taken into account as a tool in bone tissue engineering and are worth further investigation.
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This review focuses on the use of conventional gel or coil and “new” generation hydrogel used as an embolic agent in endovascular applications. In general, embolic agents have deep or multidistrict vascular penetration properties as they ensure complete occlusion of vessels by exploiting
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This review focuses on the use of conventional gel or coil and “new” generation hydrogel used as an embolic agent in endovascular applications. In general, embolic agents have deep or multidistrict vascular penetration properties as they ensure complete occlusion of vessels by exploiting the patient’s coagulation system, which recognises them as substances foreign to the body, thus triggering the coagulation cascade. This is why they are widely used in the treatment of endovascular corrections (EV repair), arteriovenous malformations (AVM), endoleaks (E), visceral aneurysms or pseudo-aneurysms, and embolisation of pre-surgical or post-surgical (iatrogenic) lesions. Conventional gels such as Onyx or coils are now commercially available, both of which are frequently used in endovascular interventional procedures, as they are minimally invasive and have numerous advantages over conventional open repair (OR) surgery. Recently, these agents have been modified and optimised to develop new embolic substances in the form of hydrogels based on alginate, chitosan, fibroin and other polymers to ensure embolisation through phase transition phenomena. The main aim of this work was to expand on the data already known in the literature concerning the application of these devices in the endovascular field, focusing on the advantages, disadvantages and safety profiles of conventional and innovative embolic agents and also through some clinical cases reported. The clinical case series concerns the correction and exclusion of endoleak type I or type II appeared after an endovascular procedure of exclusion of aneurysmal abdominal aortic (EVAR) with a coil (coil penumbra released by a LANTERN microcatheter), the exclusion of renal arterial malformation (MAV) with a coil (penumbra coil released by a LANTERN microcatheter) and the correction of endoleak through the application of Onyx 18 in the arteries where sealing by the endoprosthesis was not guaranteed.
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This study introduces a novel approach for fault classification in bearing components utilizing raw accelerometer data. By employing various neural network models, including deep learning architectures, we bypass the traditional preprocessing and feature-extraction stages, streamlining the classification process. Utilizing the Case Western Reserve
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This study introduces a novel approach for fault classification in bearing components utilizing raw accelerometer data. By employing various neural network models, including deep learning architectures, we bypass the traditional preprocessing and feature-extraction stages, streamlining the classification process. Utilizing the Case Western Reserve University (CWRU) bearing dataset, our methodology demonstrates remarkable accuracy, particularly in deep learning networks such as the three variant convolutional neural networks (CNNs), achieving above 98% accuracy across various loading levels, establishing a new benchmark in fault-detection efficiency. Notably, data exploration through principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) provided valuable insights into feature relationships and patterns, aiding in effective fault detection. This research not only proves the efficacy of neural network classifiers in handling raw data but also opens avenues for more straightforward yet effective diagnostic methods in machinery health monitoring. These findings suggest significant potential for real-world applications, offering a faster yet reliable alternative to conventional fault-classification techniques.
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Language barriers, specifically among refugees, pose significant challenges to delivering quality healthcare in Canada. While the COVID-19 pandemic accelerated the emergence and development of innovative alternatives such as telephone-based and video-conferencing medical interpreting services and AI tools, access remains uneven across Canada. This
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Language barriers, specifically among refugees, pose significant challenges to delivering quality healthcare in Canada. While the COVID-19 pandemic accelerated the emergence and development of innovative alternatives such as telephone-based and video-conferencing medical interpreting services and AI tools, access remains uneven across Canada. This comprehensive analysis highlights the absence of a cohesive national strategy, reflected in diverse funding models employed across provinces and territories, with gaps and disparities in access to medical interpreting services. Advocating for medical interpreting, both as a moral imperative and a prudent investment, this article draws from human rights principles and ethical considerations, justified in national and international guidelines, charters, codes and regulations. Substantiated by a cost-benefit analysis, it emphasizes that medical interpreting enhances healthcare quality and preserves patient autonomy. Additionally, this article illuminates decision-making processes for utilizing interpreting services; recognizing the pivotal roles of clinicians, interpreters, patients and caregivers within the care circle; appreciating intersectional considerations such as gender, culture and age, underscoring the importance of a collaborative approach. Finally, it provides recommendations at provider, organizational and system levels to ensure equitable access to this right and to promote the health and well-being of refugees and other individuals facing language barriers within Canada’s healthcare system.
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This paper presents the development of a novel anti-violence device titled “no pAIn” (an acronym for Never Oppressed Protected by Artificial Intelligence Nonviolence system), which harnesses the power of artificial intelligence (AI). Primarily designed to combat violence against women, the device offers personal
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This paper presents the development of a novel anti-violence device titled “no pAIn” (an acronym for Never Oppressed Protected by Artificial Intelligence Nonviolence system), which harnesses the power of artificial intelligence (AI). Primarily designed to combat violence against women, the device offers personal safety benefits for individuals across diverse demographics. Operating autonomously, it necessitates no user interaction post-activation. The AI engine conducts real-time speech recognition and effectively discerns genuine instances of aggression from non-violent disputes or conversations. Facilitated by its Internet connectivity, in the event of detected aggression, the device promptly issues assistance requests with real-time precise geolocation tracking to predetermined recipients for immediate assistance. Its compact size enables discreet concealment within commonplace items like candy wrappers, purpose-built casings, or wearable accessories. The device is battery-operated. The prototype was developed using a microcontroller board (Arduino Nano RP2040 Connect), incorporating an omnidirectional microphone and Wi-Fi module, all at a remarkably low cost. Subsequent functionality testing, performed in debug mode using the Arduino IDE serial monitor, yielded successful results. The AI engine exhibited exceptional accuracy in word recognition, complemented by a robust logic implementation, rendering the device highly reliable in discerning genuine instances of aggression from non-violent scenarios.
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Shrimp fry counting is an important task for biomass estimation in aquaculture. Accurate counting of the number of shrimp fry in tanks can not only assess the production of mature shrimp but also assess the density of shrimp fry in the tanks, which
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Shrimp fry counting is an important task for biomass estimation in aquaculture. Accurate counting of the number of shrimp fry in tanks can not only assess the production of mature shrimp but also assess the density of shrimp fry in the tanks, which is very helpful for the subsequent growth status, transportation management, and yield assessment. However, traditional manual counting methods are often inefficient and prone to counting errors; a more efficient and accurate method for shrimp fry counting is urgently needed. In this paper, we first collected and labeled the images of shrimp fry in breeding tanks according to the constructed experimental environment and generated corresponding density maps using the Gaussian kernel function. Then, we proposed a multi-scale attention fusion-based shrimp fry counting network called the SFCNet. Experiments showed that our proposed SFCNet model reached the optimal performance in terms of shrimp fry counting compared to CNN-based baseline counting models, with MAEs and RMSEs of 3.96 and 4.682, respectively. This approach was able to effectively calculate the number of shrimp fry and provided a better solution for accurately calculating the number of shrimp fry.
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Accurate feeding management in aquaculture relies on assessing the average weight of aquatic animals during their growth stages. The traditional method involves using a labor-intensive approach and may impact the well-being of fish. The current research focuses on a unique way of estimating
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Accurate feeding management in aquaculture relies on assessing the average weight of aquatic animals during their growth stages. The traditional method involves using a labor-intensive approach and may impact the well-being of fish. The current research focuses on a unique way of estimating red tilapia’s weight in cage culture via a river, which employs unmanned aerial vehicle (UAV) and deep learning techniques. The described approach includes taking pictures by means of a UAV and then applying deep learning and machine learning algorithms to them, such as convolutional neural networks (CNNs), extreme gradient boosting (XGBoost), and a Hybrid CNN-XGBoost model. The results showed that the CNN model achieved its accuracy peak after 60 epochs, showing accuracy, precision, recall, and F1 score values of 0.748 ± 0.019, 0.750 ± 0.019, 0.740 ± 0.014, and 0.740 ± 0.019, respectively. The XGBoost reached its accuracy peak with 45 n_estimators, recording values of approximately 0.560 ± 0.000 for accuracy and 0.550 ± 0.000 for precision, recall, and F1. Regarding the Hybrid CNN-XGBoost model, it demonstrated its prediction accuracy using both 45 epochs and n_estimators. The accuracy value was around 0.760 ± 0.019, precision was 0.762 ± 0.019, recall was 0.754 ± 0.019, and F1 was 0.752 ± 0.019. The Hybrid CNN-XGBoost model demonstrated the highest accuracy compared to using standalone CNN and XGBoost models and could reduce the time required for weight estimation by around 11.81% compared to using the standalone CNN. Although the testing results may be lower than those from previous laboratory studies, this discrepancy is attributed to the real-world testing conditions in aquaculture settings, which involve uncontrollable factors. To enhance accuracy, we recommend increasing the sample size of images and extending the data collection period to cover one year. This approach allows for a comprehensive understanding of the seasonal effects on evaluation outcomes.
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James Kehinde Omifolaji, Sunday Opeyemi Adedoyin, Emmanuel Tersea Ikyaagba, Tauheed Ullah Khan, Victor Abiodun Ojo, Yiming Hu, Abideen Abiodun Alarape, Saka Oladunni Jimoh and Huijian Hu
Animals2024, 14(9), 1374; https://doi.org/10.3390/ani14091374 (registering DOI) - 02 May 2024
Population abundance and density estimates play important roles in biodiversity conservation assessment and can lead to prioritization of conservation efforts, strategies, and management. The Calabar angwantibo (Arctocebus calabarensis) is a poorly studied, Near-Threatened nocturnal, arboreal mammal species occurring only in the
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Population abundance and density estimates play important roles in biodiversity conservation assessment and can lead to prioritization of conservation efforts, strategies, and management. The Calabar angwantibo (Arctocebus calabarensis) is a poorly studied, Near-Threatened nocturnal, arboreal mammal species occurring only in the lowland moist tropical rainforest blocks of southeastern Nigeria and southwestern Cameroon. Like other arboreal nocturnal mammals, there are gaps in knowledge of the distribution and abundance of this species, which may be facing population declines due to habitat loss and hunting. In this study, we investigated the abundance and density of A. calabarensis in the Oban Hills Region of Nigeria. We conducted systematic distance sampling survey along 32 transects in different habitats in a 1227 km of survey efforts. A total of 41 sightings of A. calabarensis were detected, resulting in an abundance of 7345 individuals (95% CI = 1.51–4.37) with an estimated density of 2.57 animals/km2. The estimated population abundance is 6515 individuals in closed-canopy forests and 830 individuals in secondary forests, with encounter rates of 0.52 individual/km2 and 0.60 individuals/km2 in the closed canopy and secondary forest habitats. The global estimates encounter rate of A. calabarensis across the habitat types is 0.33 individuals/km2 and population abundance of 4456 individuals. Our findings indicate that the A. calabarensis populations can adapt to low changes in forest habitat modifications resulting from increasing and widespread forest disturbance by human-dominated activity, which is giving way to forest clearance for agriculture cultivation and infrastructural development. Our findings help to fill a knowledge gap regarding this species and may help establish a baseline for future management, population monitoring, and conservation of the cryptic population of A. calabarensis in Cross-Sanaga Forests.
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Entrepreneurship education largely influences the social and economic dimensions of many countries. In the framework of development, frequent changes seek to discover the most effective way of adopting and integrating educational services to meet the requirements of the labour market. This paper aims
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Entrepreneurship education largely influences the social and economic dimensions of many countries. In the framework of development, frequent changes seek to discover the most effective way of adopting and integrating educational services to meet the requirements of the labour market. This paper aims to analyse entrepreneurial competence in a teaching context from the students’ perspectives. The main objective of the research study aims to measure students’ attitudes towards entrepreneurial intentions, as impacted in an entrepreneurial teaching context. Additionally, it seeks to highlight the significance of the entrepreneurial competence of the lecturing team that goes beyond traditional teaching methods and focuses on fostering an educational environment. As entrepreneurial competence guides opportunity identification by combining skills, knowledge, and attributes and developing them into values, it bridges the gap between teaching and learning, preparing the students to cope with the challenges of the entrepreneurial world. The data were gathered by administering a structured questionnaire that focuses on the perspectives of students in the third cycle of study. The disseminated questionnaire included closed-ended questions related to the entrepreneurial education context, the entrepreneurial competence of the lecturing team, and entrepreneurial intentions. The results of this study demonstrate that the relationship between the entrepreneurial competence of lecturers and entrepreneurial education is crucial for fostering a dynamic and effective learning environment to enhance the entrepreneurial intentions of the students.
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Avian influenza viruses (AIVs) are highly contagious respiratory viruses of birds, leading to significant morbidity and mortality globally and causing substantial economic losses to the poultry industry and agriculture. Since their first isolation in 2013-2014, the Asian-origin H5 highly pathogenic avian influenza viruses
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Avian influenza viruses (AIVs) are highly contagious respiratory viruses of birds, leading to significant morbidity and mortality globally and causing substantial economic losses to the poultry industry and agriculture. Since their first isolation in 2013-2014, the Asian-origin H5 highly pathogenic avian influenza viruses (HPAI) of clade 2.3.4.4b have undergone unprecedented evolution and reassortment of internal gene segments. In just a few years, it supplanted other AIV clades, and now it is widespread in the wild migratory waterfowl, spreading to Asia, Europe, Africa, and the Americas. Wild waterfowl, the natural reservoir of LPAIVs and generally more resistant to the disease, also manifested high morbidity and mortality with HPAIV clade 2.3.4.4b. This clade also caused overt clinical signs and mass mortality in a variety of avian and mammalian species never reported before, such as raptors, seabirds, sealions, foxes, and others. Most notably, the recent outbreaks in dairy cattle were associated with the emergence of a few critical mutations related to mammalian adaptation, raising concerns about the possibility of jumping species and acquisition of sustained human-to-human transmission. The main clinical signs and anatomopathological findings associated with clade 2.3.4.4b virus infection in birds and non-human mammals are hereby summarized.
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Farm crop diversity is often overlooked, predominantly indigenous crops’ role in this diversity. The main concentration has been on the contribution or role of exotic crops to household crop diversification. At the same time, the role played by both types of crops in
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Farm crop diversity is often overlooked, predominantly indigenous crops’ role in this diversity. The main concentration has been on the contribution or role of exotic crops to household crop diversification. At the same time, the role played by both types of crops in household food security has only been aggregated, failing to show how indigenous crops play a key role in household food security. This research paper uses Tanzanian Panel data from waves 4 and 5 to study the factors influencing indigenous and exotic crop diversification and the role of this diversity in household food security. Using a random effect model, the author found that various factors are crucial in determining household crop diversification. Gender, household size, marital status, and expected harvest quantity are among the key factors influencing indigenous crop diversification. On the other hand, age, education, access to markets, access to irrigation services, and soil quality are the primary factors that affect the diversification of exotic crops. Moreover, the findings show that indigenous and exotic crop diversity significantly influences household food consumption. Thus, policies to increase the production of indigenous crops in order to improve household food consumption should be considered.
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To address the shortage of wireless spectrum resources caused by the rapid development of the Internet of Vehicles, spectrum sensing technology in cognitive radio is employed to tackle this issue. In pursuit of superior outcomes, a double-threshold cooperative spectrum sensing algorithm is introduced.
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To address the shortage of wireless spectrum resources caused by the rapid development of the Internet of Vehicles, spectrum sensing technology in cognitive radio is employed to tackle this issue. In pursuit of superior outcomes, a double-threshold cooperative spectrum sensing algorithm is introduced. This algorithm enhances traditional energy detection technology to mitigate the high sensitivity to noise interference in the Internet of Vehicles environment. A double-threshold judgment mechanism can be established based on the uncertainty of noise. Varying fusion rules are implemented in the collaborative spectrum sensing scheme according to the density of vehicles and the spectrum resource demand. Simulation results demonstrate that the performance of the double-threshold cooperative spectrum sensing algorithm surpasses that of the traditional single-threshold energy detection scheme, particularly evident under lower Signal-to-Noise Ratio (SNR) conditions. Moreover, the proposed algorithm exhibits superior sensing performance in environments characterized by higher noise uncertainty.
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Considering that the excitation method of an electric excitation synchronous motor has the disadvantages of the brush and slip ring, this article proposes a new brushless excitation system, which includes two parts: a wireless charging system and a motor. To meet the requirements
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Considering that the excitation method of an electric excitation synchronous motor has the disadvantages of the brush and slip ring, this article proposes a new brushless excitation system, which includes two parts: a wireless charging system and a motor. To meet the requirements of maximum transmission efficiency and constant voltage output of the system, a bilateral cooperation control strategy is proposed. For the strategy, the buck converter in the receiving side of the system can maintain maximum transmission efficiency through impedance matching, while the inverter in the transmitting side can keep the output voltage constant through phase shift modulation. In the control process, considering that the offset of coupling coils will affect the control results, a grey wolf optimization–particle swarm optimization algorithm is proposed to identify mutual inductance. Simulation and experimental results show that this identification algorithm can improve the identification accuracy and maximize the avoidance of falling into local optima. The final experimental result shows that the bilateral cooperation control strategy can maintain the output voltage around 48 V and the transmission efficiency around 84.5%, which meets the expected requirements.
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Fly ash has been utilized as a reinforcing material in the production of aluminum matrix composites, and in this investigation, Al-Si (LM6) fly ash composites were fabricated using the compocasting method. Various compositions of fly ash were incorporated into the samples (4, 5
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Fly ash has been utilized as a reinforcing material in the production of aluminum matrix composites, and in this investigation, Al-Si (LM6) fly ash composites were fabricated using the compocasting method. Various compositions of fly ash were incorporated into the samples (4, 5 and 6 wt%), and the preparation temperature ranged from 560 to 800°C. This study investigated the thermal (CTE and DTA) and chemical properties (XRD) of fly ash reinforcement and the aluminum melt in the composites. The results revealed that composites with 5 wt% of fly ash exhibited the lowest CTE value compared to those with 4 and 6 wt%. This observation was corroborated by XRD analysis, indicating a reaction between the fly ash particles and the aluminum melt. However, the DTA analysis did not find a significant impact of the addition of fly ash on the melting temperature of the prepared composites. In contrast, this study identified and investigated the existence of reaction effects between the fly ash particles and the aluminum melt.
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In this work, we derived a new type model for spatial Hill’s system considering the created perturbation by the parameter effect of the continuation fractional potential. The new model is considered a reduced system from the restricted three-body problem under the same effect
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In this work, we derived a new type model for spatial Hill’s system considering the created perturbation by the parameter effect of the continuation fractional potential. The new model is considered a reduced system from the restricted three-body problem under the same effect for describing Hill’s problem. We identified the associated Lagrangian and Hamiltonian functions of the new system, and used them to verify the existence of the new equations of motion. We also proved that the new model has different six valid solutions under different six symmetries transformations as well as the original solution, where the new model is an invariant under these transformations. The several symmetries of Hill’s model can extremely simplify the calculation and analysis of preparatory studies for the dynamical behavior of the system. Finally, we confirm that these symmetries also authorize us to explore the similarities and differences among many classes of paths that otherwise differ from the obtained trajectories by restricted three-body problem.
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Data variability complicates reproducibility and the interpretation of experimental results. Different animal models have been employed to decrease variability to enhance experimental power. However, variation frequently persists among and within strains/lines. In zebrafish (Danio rerio), inbred lines (e.g., NHGRI-1) derived from
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Data variability complicates reproducibility and the interpretation of experimental results. Different animal models have been employed to decrease variability to enhance experimental power. However, variation frequently persists among and within strains/lines. In zebrafish (Danio rerio), inbred lines (e.g., NHGRI-1) derived from wild-type lines have been produced to greatly decrease genetic variation, with the goal of providing better understanding of genetic backgrounds that may influence the experimental outcome of studies employing such lines. We hypothesized that variations in morphological phenotypes shaped by environmental stressors early in development are correlated with the intrinsic degree of genetic variability of zebrafish lines. We compared morphological variability (yolk–chorion ratio, body mass, embryo mass, total length, condition factor, and specific growth rate) in wild-type AB and NHGRI-1 zebrafish lines as a function of their responses to altered temperature and oxygen availability during the first 7 days post-fertilization. Overall, both lines showed similar developmental trajectories for yolk–chorion ratio, embryo mass, and total length. Additionally, condition factor and specific growth rate showed similar responses within each line, regardless of temperature and hypoxia. Importantly, the coefficient of variation for each variable was significantly lower in NHGRI-1 than AB larvae for 151 of 187 assessed morphological endpoints. Thus, the low-heterozygosity NHGRI-1 zebrafish line can be useful for decreasing inter-individual variation in morphological responses to environmental stressors, thereby aiding in the interpretation of results and enhancing experimental reproducibility.
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Cholera is highly endemic in many sub-Saharan African countries. The bacterium Vibrio cholerae is responsible for this severe dehydrating diarrheal disease that accounts for over 100,000 deaths each year globally. In recent years, the pathogen has been found to invade intestinal layers and
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Cholera is highly endemic in many sub-Saharan African countries. The bacterium Vibrio cholerae is responsible for this severe dehydrating diarrheal disease that accounts for over 100,000 deaths each year globally. In recent years, the pathogen has been found to invade intestinal layers and translocate into the bloodstream of humans. The non-toxigenic strains of V. cholerae (non-O1/O139), also known as NOVC, which do not cause epidemic or pandemic cases of cholera, are the major culprits of V. cholerae bacteremia. In non-cholera-endemic regions, clinical reports on NOVC infection have been noted over the past few decades, particularly in Europe and America. Although low–middle-income countries are most susceptible to cholera infections because of challenges with access to clean water and inappropriate sanitation issues, just a few cases of V. cholerae bloodstream infections have been reported. The lack of evidence-based research and surveillance of V. cholerae bacteremia in Africa may have significant clinical implications. This commentary summarizes the existing knowledge on the host risk factors, pathogenesis, and diagnostics of NOVC bacteremia.
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In this article, we explore a variety of problems within the domain of calculus of variations, specifically in the context of fractional calculus. The fractional derivative we consider incorporates the notion of weighted fractional derivatives along with derivatives with respect to another function.
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In this article, we explore a variety of problems within the domain of calculus of variations, specifically in the context of fractional calculus. The fractional derivative we consider incorporates the notion of weighted fractional derivatives along with derivatives with respect to another function. Besides the fractional operators, the Lagrange function depends on extremal points. We examine the fundamental problem, providing the fractional Euler–Lagrange equation and the associated transversality conditions. Both the isoperimetric and Herglotz problems are also explored. Finally, we conclude with an analysis of the variational problem, incorporating fractional derivatives of any positive real order.
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Molecular biomarkers are central to personalised medicine for human cancer patients. It is gaining traction as part of standard veterinary clinical practice for dogs and cats with cancer. Molecular biomarkers can be somatic or germline genomic alterations and can be ascertained from tissues
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Molecular biomarkers are central to personalised medicine for human cancer patients. It is gaining traction as part of standard veterinary clinical practice for dogs and cats with cancer. Molecular biomarkers can be somatic or germline genomic alterations and can be ascertained from tissues or body fluids using various techniques. This review discusses how these genomic alterations can be determined and the findings used in clinical settings as diagnostic, prognostic, predictive, and screening biomarkers. We showcase the somatic and germline genomic alterations currently available to date for testing dogs and cats in a clinical setting, discussing their utility in each biomarker class. We also look at some emerging molecular biomarkers that are promising for clinical use. Finally, we discuss the hurdles that need to be overcome in going ‘bench to bedside’, i.e., the translation from discovery of genomic alterations to adoption by veterinary clinicians. As we understand more of the genomics underlying canine and feline tumours, molecular biomarkers will undoubtedly become a mainstay in delivering precision veterinary care to dogs and cats with cancer.
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Considering the diversity of battery data under dynamic test conditions, the stability of battery working data is affected due to the diversity of charge and discharge rates, variability of operating temperature, and randomness of the current state of charge, and the data types
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Considering the diversity of battery data under dynamic test conditions, the stability of battery working data is affected due to the diversity of charge and discharge rates, variability of operating temperature, and randomness of the current state of charge, and the data types are multi-sourced, which increases the difficulty of estimating battery SOH based on data-driven methods. In this paper, a lithium-ion battery state of health estimation method with sample transfer learning under dynamic test conditions is proposed. Through the Tradaboost.R2 method, the weight of the source domain sample data is adjusted to complete the update of the sample data distribution. At the same time, considering the division methods of the six auxiliary and the source domain data set, aging features from different state of charge ranges are selected. It is verified that while the aging feature dimension and the demand for target domain label data are reduced, the estimation accuracy of the lithium-ion battery state of health is not affected by the initial value of the state of charge. By considering the mean absolute error, mean square error and root mean square error, the estimated error results do not exceed 1.2% on the experiment battery data, which highlights the advantages of the proposed methods.
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In living cells, some reactions can be conducted by more than one enzyme and sometimes it is difficult to establish which enzyme is responsible. Such is the case with proteins from the TET family, capable of converting 5-methyl-2’-deoxycytidine (5-)
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In living cells, some reactions can be conducted by more than one enzyme and sometimes it is difficult to establish which enzyme is responsible. Such is the case with proteins from the TET family, capable of converting 5-methyl-2’-deoxycytidine (5-) in DNA to 5-(hydroxymethyl)-2’-deoxycytidine (5-) and further to 5-formyl-2’-deoxycytidine (5-) and 5-carboxy-2’-deoxycytidine (5-). The estimation of the efficiency of particular TETs in particular oxidative reactions and different cell types is important but experimentally difficult. Here, we propose an approach with mathematical modeling in which methylation and known deoxycytidine modification pathways are presented by 343 possible model versions with assumed different combinations of TET1, 2, and 3 activities in different pathways. Model parameters were calculated on the basis of 5-, 5-, 5-, 5-, and 5- levels experimentally assessed in five human cultured cell lines and previously published. Selection of the model versions that give in simulations the best average fit to experimental data suggested that not all TET proteins participate in all modification reactions and that TET3 activity may be especially important in the reaction of 5- removal.
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