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A rare manifestation of Choledochal Cyst with Subdural Hematoma in an Infant: a Case...
Santoshi Pokharel Kunwar
Geeta Bashyal

Santoshi Pokharel Kunwar

and 2 more

September 04, 2024
A document by Santoshi Pokharel Kunwar. Click on the document to view its contents.
not-yet-known not-yet-known not-yet-known...
Carlos Ventura-Bort
Manon Giraudier

Carlos Ventura Bort

and 2 more

September 04, 2024
javascript:void(0) Recently, we found that continuous transcutaneous auricular vagus nerve stimulation (taVNS) facilitates the encoding and later recollection of emotionally relevant information, as indicated by enhanced late positive potential (LPP), memory performance, and late ERP Old/New effect. Here, we aimed to conceptually replicate and extend these findings by investigating the effects of different time-dependent taVNS stimulation protocols. In Study 1, an identical paradigm to our previous study was employed with interval stimulation (30-sec on/off). Participants viewed unpleasant and neutral scenes on two consecutive days while receiving taVNS or sham stimulation and completed a recognition test one week later. In line with our previous results, unpleasant images encoded under taVNS, compared to sham stimulation, elicited larger LPP amplitudes and Old/New effects. However, no effects of taVNS on memory performance were found, suggesting that interval stimulation may lower the effects of taVNS on memory. In Study 2, we followed up on these findings by synchronizing the stimulation cycle with image presentation to determine the taVNS effects for images encoded during the on and off cycles. We could replicate the enhancing effects of taVNS on brain potentials (LPP and late Old/New effect) and found that taVNS improved recollection-based memory performance for both unpleasant and neutral images, independently of the stimulation cycle. Overall, our results suggest that taVNS increases electrophysiological correlates of emotional encoding and retrieval in a time-independent manner, substantiating the vagus nerve’s role in emotional processing and memory formation and opening new venues for improving mnemonic processes in both clinical and non-clinical populations.
Effects of Chronological Age and Biological Maturity on Executive Function in Young P...
Luke Gilbert
Ryan Williams

Luke Gilbert

and 7 more

September 04, 2024
javascript:void(0) Executive function is typically considered from a chronological age perspective, despite the influence of biological maturity on executive function development. The purpose of this study was to investigate the influence of chronological age and biological maturity on executive function, separately in boys and girls (due to sex differences in biological maturation). The study employed a cross-sectional design and following familiarisation, 736 (400 female) young people (12.3  1.3 years) completed tests of cognitive function on two separate occasions. Participants completed the Stroop test to measure inhibitory control, and the Sternberg paradigm to measure working memory. Chronological age and biological maturity (Moore et al., 2015) were calculated for each participant. Linear regression models were performed separately for boys and girls. Two models were fit for each test and level of executive function: a chronological age model (executive function x chronological age) and a biological maturity model (executive function x biological maturity). Higher chronological age and biological maturity were associated with superior performance on inhibitory control and working memory tests. In boys, the biological maturity models were a significantly better fit (vs. chronological age), whilst in girls the chronological age models were a better fit (vs. biological maturity). This study provides novel evidence that biological maturity is associated with executive function; and emphasises that future investigations into executive function in young people should consider biological maturity, especially in boys.
Butyrate selectively targets super-enhancers and transcriptional networks associated...
Jelle Folkerts
Marjolein de Bruijn

Jelle Folkerts

and 4 more

September 04, 2024
A document by Jelle Folkerts. Click on the document to view its contents.
not-yet-known not-yet-known not-yet-known...
Callum Bruce
Priyanka Meenamkuzhy-Hariharan

Callum Bruce

and 9 more

September 04, 2024
Background and Aim: Alkaptonuria (AKU) is a rare metabolic disorder characterised by the accumulation of homogentisic acid (HGA). Deposition of HGA in the aortic valve leading to progressive aortic stenosis is a serious complication. Nitisinone has been shown to improve morbidity and slow disease progression in AKU but the effects of this treatment on aortic stenosis progression have not yet been described. This review extrapolated from the data set of SONIA 2, a 4-year multi-centre randomised controlled trial investigating the effect of nitisinone on AKU disease activity, but specifically examined measures of aortic stenosis disease progression. Methods: Data were obtained from echocardiograms performed on 138 patients over 48 months of follow-up. A linear mixed effects regression model was used to ascertain the difference in aortic valve pressure (AVP) at baseline and 48 months between the treatment and control groups. Results: At baseline, 18/138 patients (13.0%) had aortic stenosis of varying degrees of severity and 25/138 (18.1%) had aortic sclerosis. The difference in AVP between the control (N=69) and treatment (N=69) groups at baseline was 0.063mmHg [95% CI: -0.054mmHg to 0.18mmHg) and did not reach statistical significance (p=0.23). At the end of the 4-year treatment period, the difference in AVP was 0.10mmHg [95% CI: -0.0007mmHg to 0.20mmHg] and was statistically significant (p=0.05). Conclusion: Nitisinone slowed progression of aortic stenosis in patients with AKU. This supports the argument for timely initiation of nitisinone to reduce the incidence and severity of aortic valvular disease in AKU patients.
Environmental DNA shedding rates reveal defecation as a major source of terrestrial m...
Gabriele Sauseng
Tamara Schenekar

Gabriele Sauseng

and 1 more

September 04, 2024
not-yet-known not-yet-known not-yet-known unknown The analysis of environmental DNA (eDNA) has become a non-invasive, cost-efficient and universal biomonitoring tool, widely applied across the globe. Most eDNA research focuses on aquatic organisms in freshwater and marine environments. eDNA shedding rates are key to interpretating eDNA-based results, such as for abundance estimations or detection probabilities. Shedding rates have been estimated for several species and life stages, however virtually all of them are aquatic. As eDNA-based biomonitoring expands to terrestrial systems, waterborne eDNA from freshwater is increasingly used to assess species presence of terrestrial mammals. While interacting with the water, terrestrial mammals deposit their DNA into the water body, with the amount deposited presumably heavily depending on the interaction type. Here we quantify eDNA shedding rates from domestic dogs during various interactions with water bodies, including ”passing by”, ”drinking”, ”crossing through”, ”standing still” and ”defecating.” “Crossing through” and “defecating” had the highest DNA shedding rates (both approx. 4x107 pg/h/ind). Since scat largely remains in the water once deposited, and the active movement of terrestrial mammals through the water is brief, we conclude that defecation is the major source of terrestrial mammal DNA in surface waters where direct defecation into the water is possible. This has important implications for interpretations of eDNA-based data from such water bodies. We also highlight the patchiness of eDNA particle distribution in such systems, which needs to be accounted for when designing eDNA sampling schemes.
Option Contracts in the DeFi Ecosystem: Opportunities, Solutions, & Technical Cha...
Srisht Fateh Singh
Vladyslav Nekriach

Srisht Fateh Singh

and 4 more

September 03, 2024
not-yet-known not-yet-known not-yet-known unknown This paper investigates the current landscape of option trading platforms for cryptocurrencies, encompassing both centralized and decentralized exchanges. Option contracts in cryptocurrency markets offer functionalities akin to traditional markets, providing investors with tools to mitigate risks, particularly those arising from price volatility, while also allowing them to capitalize on future volatility trends. The paper discusses these applications of option contracts in the context of decentralized finance (DeFi), emphasizing their utility in managing market uncertainties. Despite a recent surge in the trading volume of option contracts on cryptocurrencies, decentralized platforms account for less than 1% of this total volume. Hence, this paper takes a closer look by examining the design choices of these platforms to understand the challenges hindering their growth and adoption. It identifies technical, financial, and adoption-related challenges that decentralized exchanges face and provides commentary on existing platform responses. Subsequently, it introduces a zero-loss liquidity provision strategy on altcoins that utilizes options with automated market makers. These opportunities result in a positive return with no significant risk. It then investigates opportunities in the past using historical on-chain data to emphasize the number of risk-free opportunities that DeFi is missing due to the lack of a functional options exchange on arbitrary ERC20 token pairs on Ethereum. The experiments show 1015 profitable instances in the past three years on 14 token pairs.
QuantumNetSec: Quantum Machine Learning for Network Security
Diego Abreu
David Moura

Diego Abreu

and 3 more

September 03, 2024
As the digital landscape becomes increasingly complex, traditional cybersecurity measures are struggling to keep pace with the growing sophistication of cyber threats. This escalating challenge calls for new, more robust solutions. In this context, Quantum Computing emerges as a powerful tool that can change our approach to network security. Our research addresses this by introducing QuantumNetSec, a novel Intrusion Detection System (IDS) that combines quantum and classical computing techniques. QuantumNetSec employs Quantum Machine Learning (QML) personalized methodologies to analyze network patterns and detect malicious activities. Through detailed experimentation with publicly shared datasets, QuantumNetSec demonstrated superior performance in both binary and multiclass classification tasks. Our findings highlight the significant potential of quantum-enhanced cybersecurity solutions, showcasing QuantumNetSec’s ability to accurately detect a wide range of cyber threats, paving the way for more resilient and effective intrusion detection systems in the age of quantum utility.
Does counterion matter? Anion and substituents effect on spectral-kinetic and biologi...
Artem Pugachev
Anastasiia Kozlenko

Artem Pugachev

and 17 more

September 03, 2024
Spiropyran salts containing a cationic vinyl-3H-indolium moiety are characterized by NIR absorption and fluorescence of their merocyanine forms. This feature makes them promising fluorescent probes and markers for bioimaging. The article focuses on the synthesis and study of the spectral, kinetic and toxic characteristics of such compounds with respect to various substituents in different moieties and the type of anion. A detailed analysis of the acquired data made it possible to draw some important conclusions regarding the influence of structural factors, which will be very useful for the further rational design of such derivatives. In particular, it was shown that the counterion has minimal effect on the spectral and kinetic characteristics of the dyes but dramatically affects the toxicity of the compounds. Following selection of the most appropriate compounds, bioimaging experiments were carried out to visualize planktonic bacteria and bacterial biofilms of E. coli and A. calcoaceticus. The ability to visualize biofilms is critical for the diagnosis of chronic diseases. By the results of molecular docking a theoretical interaction pattern between spiropyran molecules and DNA was proposed.
not-yet-known not-yet-known not-yet-known...
Ibrahim Khalil Ja’afar

Ibrahim Khalil Ja’afar

September 03, 2024
Type 2 diabetes (T2D) is an escalating public health issue in Nigeria, driven by rapid urbanization, lifestyle changes, and inadequate healthcare infrastructure. The disease affects 5.8% of the adult population, with millions requiring ongoing care. However, significant barriers prevent many from accessing the clinical care they need. These challenges include geographical disparities, with rural areas lacking essential healthcare services, and economic constraints, as many Nigerians cannot afford the high out-of-pocket costs associated with diabetes management. Cultural factors, such as reliance on traditional medicine and low health literacy, further complicate the effective management of T2D. The healthcare system is also hampered by a shortage of trained professionals and inadequate facilities, particularly in rural areas where most of the population resides. This review identifies these critical barriers and offers targeted solutions, including strengthening primary healthcare systems through investment in infrastructure and training, expanding health insurance coverage to reduce the economic burden, and enhancing public health education to improve health literacy and promote early diagnosis. Addressing these multifaceted challenges is crucial for improving access to care, reducing complications, and managing the growing burden of T2D in Nigeria. The findings of this study aim to inform policy and guide future research to develop effective diabetes management strategies in the region.
The Future Capabilities of AI in Visual Effects and Its Economic Impact on Cinema Pro...
Baxodir Murodillayev

Baxodir Murodillayev

September 03, 2024
The integration of artificial intelligence (AI) into the visual effects (VFX) industry represents a profound shift in cinema production, reshaping both the economic landscape and creative processes of filmmaking. This research explores the future capabilities of AI in VFX, analyzing its impact on production costs, timelines, and creative control, while also examining broader economic implications. Through a mixed-methods approach—comprising qualitative interviews with industry professionals and quantitative analysis of budget data from recent films—this study offers a comprehensive understanding of how AI-driven VFX is poised to revolutionize the cinema industry. The findings indicate significant cost reductions, enhanced efficiency, and new creative possibilities, alongside ethical concerns and potential job displacement. The study concludes by outlining future research directions and the necessity for ethical guidelines to navigate AI’s integration into creative industries.
Rare Coexistence: Thyroid hormone resistance Syndrome Unveiled in a Woman with Crohn’...
Ahmad Al-Bitar
Dana Al-Masalma

Ahmad Al-Bitar

and 3 more

September 03, 2024
A document by Ahmad Al-Bitar. Click on the document to view its contents.
Stochastic Sumudu transform and its applications for solving stochastic differential...
Mohsen Alhassoun
Khalil Yahya

Mohsen Alhassoun

and 3 more

September 03, 2024
This manuscript introduces the development of the stochastic Sumudu transform theory of Itô type for stochastic calculus. We employ the stochastic integration by parts method to achieve this. The purpose of the stochastic Sumudu transform is to solve stochastic differential equations and establish a method for solving them using integral transforms. Furthermore, we derive the Sumudu transforms of commonly used functions in stochastic differential equations. These findings will contribute to the enhancement of literature on stochastic differential equations and have practical applications in fields such as applied mathematics and finance. Additionally, we provide several examples to demonstrate the validity of our work.
Competence measurement of software projects in the degree course in Computer Engineer...
Walfredo González Hernández

Walfredo González Hernández

September 17, 2024
Measurement in software projects is one of the activities that define engineering. In this article, it is defined as the competence of the computer engineer and its dimensions and indicators are determined. Subsequently, a pre-experiment is carried out where different empirical methods are applied in three moments to monitor the development of the competence.
Is COVID-19 vaccination beneficial for tumor patients: a cross-sectional investigatio...
Sixiu Wang
Yan Zhu

Sixiu Wang

and 6 more

September 03, 2024
javascript:void(0) Tumor patients take a high risk of SARS-CoV-2 infection, high incidence of serious events, poor prognosis and high mortality in the coronavirus disease 2019 (COVID-19) epidemic, but there is still lack of supporting evidence that the COVID-19 vaccination is beneficial for tumor patients to encourage them to receive the vaccination. A cross-sectional study was conducted in Shantou, China and questionnaires were collected in the hospitals from February 13,2023 to April 23,2023. Using the receiving of COVID-19 vaccination as the primary outcome, descriptive, univariate and multivariate analyses were generated.161 out of 241 patients (66.80%) had received at least one dose of COVID-19 vaccine and 61.00% patients had been infected with SARS-CoV-2. Patients with general symptoms (P = 0.013) and others (P = 0.022) had a higher proportion of non-vaccinated patients than vaccinated ones. In the multivariate analysis, age (aOR = 0.971, 95% CI 0.946-0.997, P = 0.031), the cognition of vaccines’ impact on tumor treatment (aOR = 4.475, 95% CI 1.772-11.299, P = 0.002), time since tumor diagnosis (aOR=4.586, 95% CI 2.122-9.909, P < 0.001) were identified as factors of COVID-19 vaccination uptake. COVID-19 vaccination in China brings many benefits to tumor patients, which could reduce symptoms after infection.
“Current scenario of molecular diagnostics applied to sustainable use of insecticides...
Camila
lizabellard

Camila I. C. V. F. Junqueira

and 3 more

September 05, 2024
AbstractEfforts to prevent losses and counterattack insect dammaging in crops by means of chemical control often contribute to the selection of resistant populations. Resistance to agricultural insecticides have been reported since the early 20th century. In the last decade, some products have been developed with the aim of mitigating the harmful effects of field management on producers and the environment. However, insecticides with different modes of action (MoA) have been reported as prone to generating field resistance and, within a few years, losing their effectiveness. The difficulties in the control management are aggravated due to the occurrence of insect’s resistance to various insecticides. Certain active substances can induce molecular modifications, including point mutations, in the genome of pest insects, are associated to resistance in field populations. The resistance mechanisms categorized by genetic mutations are particularly useful as they enable the analysis of the evolution and spread of the corresponding resistance. Additionally, it serves as a basis for the development of molecular markers that can be used for early detection of the resistance in early infestation phases. Accordingly, it allows diagnosis for preemptive decisions to alternate between products with different MoA and their application methods, contributing to practices that enhance sustainable production management initiatives. Along with the need to reduce pesticides, as ruled by international conventions, diagnostic methods for detecting insecticide resistance are increasingly in demand, especially because of the decreasing effectiveness of insecticides. Some diagnostic methods for this purpose are under development and a few already being offered as services to worldwide cultivated crops. In this review, we will focus on the main diagnostic methodologies using molecular markers, their advancements, and the outlook for the development of resistance diagnostic tools. Furthermore, we discuss the impact of insecticide resistance on coffee, a global market agricultural commodity, towards implementing effective management strategies to maintain the efficacy of chemical products and promote sustainable agricultural and pest control practices.The global view of inseticides in agricultureChemicals were historically the primary method of pest control in global agriculture and remain nowadays at this same status. The use of pesticides allows for less damage of cultivated species and, consequently, increased production. Nonetheless, the use of large quantities of these molecules, estimated at approximately 2 million tons annually [1], implies in economical drawbacks. According to data from the Food and Agriculture Organization of the United Nations (FAO) for 2021-2022, Brazil is the leading country in general pesticide use for agriculture, with 719.51 thousand tons, followed by the United States with 417.39 thousand tons and Indonesia with 283.30 thousand tons [2].Included in this account, insecticides represent a heavy burden to producers, besides having direct consequences for health and the environment. The impacts of insecticides on human health are more severe when workers are directly exposed to the products, considering that the knowledge of health risks is still insufficient for workers to change their handling practices [3]. It is proven that pesticide poisoning can cause effects on the human body such as diarrhea, headaches, dizziness, and in more severe cases, it can contribute to the development of neurological problems and carcinogenic diseases [4], [5]. Beyond human health, the environmental impacts of insecticide application are also severe, as the lack of specificity affects non-target insects that play important roles in ecosystems, such as pollinators [4] and other animals like birds and fish [6], [7]. Additionally, insecticides contaminate water [8], soil [9] and food [10], [11], causing damage to the entire trophic chain. Finally, the excessive use of insecticides can lead to the development of resistant target insect populations.The insecticide resistance problemThe first reports of insecticide resistance appeared around 1914, where resistance to sulfur was observed in scale insects. [12]. Resistance to insecticides remained at low frequency until the introduction and expansion of synthetic organic insecticides such as DDT, cyclodienes and organophosphates, between the 40s and 50s [13]. From the 60s onwards, insecticide resistance began to be considered an impact fator of the use and effectiveness of a wide range of chemical compounds. New chemicals were introduced onto the market in attempt to circumvent the situation, although, in many cases they had the same chemical class as those already existing [14]. In this way, in 1984 the Insecticide Resistance Action Committee (IRAC) was formed together with other organizations in attempt to establish adequate management of resistance. In 1998, IRAC began to develop a classification scheme for agricultural chemicals based on the so-called Modes of Action (MoA), a tool that initially classified acaricides, that is currently extended to cover biologicals and insecticides as the main basis for managing resistance [13].The most recent reports on the global use of insecticides show this ranking is led by Indonesia, the United States, China and Brazil, with 116,405 thousand tons, 72,985 thousand tons, 70,126 thousand tons and 59,587 thousand tons, respectively [2]. Consequently, known resistance in a wide variety of pest insects are closely related to the most cultivated crops in these countries. In Indonesia, the main reports of resistance are in Spodoptera frugiperda , with resistance to insecticides in the chemical groups of organophosphates, avermectins, pyrethroids, spinosyns, and diamides, and in Plutella xylostella , with resistance detected to organophosphate and pyrethroid insecticides [15]. In Brazil, there are insecticide resistance reports for many of the insects figuring on the top of the agricultural pests and diseases government list presenting high phytosanitary risk to production [16]. Among these insects, Bemisia tabaci is noted with reports of resistance to tetranortriterpenoids, diamides, carbamates, phenylthiourea, neonicotinoids, and ketoenol [17];Helicoverpa armigera and Spodoptera frugiperda , with reports of resistance to organophosphates, carbamates, pyrethroids, oxadiazines [18], [19], [20]; Tuta absoluta [21], [22], [23] and Plutella xylostella [24], [25], [26], [27] to organophosphates.The United States government also has a ranking of the pests and diseases that pose a significant threat to the country’s agriculture [28]. Among the listed insects, there are reports of insecticide resistance in Spodoptera litura , to organophosphates, carbamates, pyrethroids, and oxadiazine [29], Thaumatotibia leucotreta, resistant to benzoylureas [30], Helicoverpa armigera , resistant to pyrethroids, cyclodienes, and organophosphates [20],Tecia solanivora, resistant to carbamates and organophosphates [31]  and Tuta absoluta, resistant to organophosphates, carbamates, pyrethroids, avermectins, oxadiazine, benzoylureas, and spinosyns [21].To aggravate the situation, it has been shown that insecticide resistance mechanisms are affected by climate change [32] and that these changes are related to the increased risk of pest invasion areas worldwide [33], [34], [35], [36].Therefore, the challenge of monitoring resistance is greater than just accounting reports of already installed resistance, which would allow a better control of its development and dissemination. Thus, management techniques and technologies that prioritize environmental concerns are essential for ensuring a more sustainable future, and diagnosing resistance can be a crucial action [37], [38], [39], [40].Besides the agricultural problems posed to crop pests, the consequences of the development of insecticide-resistant insect populations are also closely related to human health. Just as it is an environmental concern, resistance in non-target insect populations is also a critical issue for human health, as there are cases of resistance in insect vectors of important human diseases, such as mosquitoes that transmit dengue, zika, chikungunya, yellow fever, and malaria [41], [42], [43]. Finally, other consequences of resistance development are still uncertain, as in non-target insects, such as bees, ants, and termites [44].The main forms of insecticide resistanceIn order to perform diagnosis, the primordial question is to determine the most probable mechanism conferring the resistance to a given insect challenged with a specific insecticide. Resistance development is an evolutionary phenomenon arising from a set of dynamic biochemical actions and reactions that are triggered, for example, by the continuous use of chemical products that result in significant metabolic and genetic changes to organism populations over time as a response to selective pressures. As new MoAs and its associated technologies emerge, the path to discovery is deepened to understand the genetic changes responsible for resistance [47]. At the present, insect resistance mechanisms are categorized into different groups: cuticular resistance, behavioral, metabolic, sequestration and “target-site” mutations.Cuticular resistance occurs due to modifications in the insect’s cuticle that can prevent insecticide penetration. This mechanism involves thickening of the cuticle, which acts as a physical barrier, and changes in cuticle composition, such as increased waxes, which can reduce insecticide absorption [47], [48], [49], [50], [51]. Although this mechanism protects the insect from a wide range of insecticides, it generally confers low levels of resistance when considered in isolation [52].Behavioral resistance, often underestimated due to uncertainty about whether it should be considered a true form of resistance, is defined by the insects’ ability to avoid contact with the toxin [53], [54]. Changes in behavior, such as avoiding treated areas or altering feeding patterns, can reduce exposure to the insecticide. This mechanism of resistance has been reported for a wide range of chemical classes, including organochlorines, organophosphates, carbamates, and pyrethroids [55].Metabolic resistance can be characterized as a detoxification process, meaning the ability to metabolize and/or neutralize chemicals as a defense mechanism, present in insects and plants, through enzymes that degrade or modify toxic compounds, rendering them ineffective [56]. This process involves three main classes of enzymes: 1) Cytochrome P450 Monooxygenases (P450s), which oxidize organic compounds, making them more water-soluble and more easily excreted. 2) Esterases, which hydrolyze esters, often deactivating chemical compounds, and 3) Glutathione S-transferases (GSTs), which conjugate chemical compounds with glutathione, facilitating their excretion [57].  The genes that confer metabolic resistance are generally different between insect species, and the production of detoxification enzymes is usually caused by the amplification of these genes [47]. Because this mechanism involves a succession of reactions, metabolic resistance is influenced by various external factors, such as the type and frequency of chemical use, climatic conditions, biological factors, agricultural and management practices, and environmental residues and contamination, which can accelerate, decelerate, or modify how it develops in populations of organisms, similar to cuticular and sequestration resistance processes.Sequestration resistance is a particular case of metabolic resistance in which insects have the ability to isolate and store insecticide molecules in specific compartments within their bodies without causing harm. This mechanism involves sequestration in vacuoles or organelles and binding to transport or sequestration proteins, which bind and inactivate the insecticides, preventing them from reaching their targets [47], [50].Target-site resistance is relevant for accurately understanding the spread of resistance genes. This mechanism involves changes in the enzymes, receptors, or structural proteins of insects, where chemicals exert their toxic action, preventing the chemical from binding effectively to its target, thereby reducing or eliminating its toxicity [50]. Insect vectors of human diseases and has frequently been studied to understand resistance in agricultural pest insects [18], [57], [58], [59].The main considered mechanisms are: 1) Genetic Mutation, which occurs from mutations that cause changes in the amino acid sequence, potentially altering the structure of the protein involved in binding with insecticide molecules. These can be single nucleotide polymorphisms (SNPs), insertions, or deletions; 2) Alteration in gene expression, either by overexpressing the amount of the target protein, diluting the chemical effect, or by underexpressing the amount of the target protein, minimizing the chemical’s action sites; 3) post-transcriptional regulation of genes involved in resistance processes and its impact on these processes, with research into non-coding RNAs being the main area of development; and 4) Post-Translational Modification, through chemical modifications to the target protein (phosphorylation, methylation, glycosylation) after its synthesis, which can alter its conformation and affinity for the chemical.Genetic mutations of the kdr target-site (knockdown resistance) in the voltage-gated sodium channel (vgsc) are extensively studied and result in resistance to pyrethroids and DDT [60], [61]. Other commonly described mutations occur in the acetylcholinesterase-1 (ace-1) gene, which confer resistance to organophosphates and carbamates [62], [63], [64] and mutations in the GABA receptor, commonly known as rdl mutation (resistance to dieldrin), which are associated with resistance to several insecticide groups [64], [65], [66]. For relatively new insecticide groups, such as diamides, the mutation occurs in ryanodine receptors (RyR) [58], [67], [68] and is frequently described in lepidopterans [18], [67], [69], [70]. A list compiled in 2020 by IRAC presents the relationship between the MoA of each insecticide and the associated target-site resistance, facilitating access to references [71].Post-Translational Modification, gene expression and post-transcriptional regulation are quite puzzling to understanding in the context of the resistance mechanisms [47], [50]. Therefore, a way to shorten this path and allow a greater understanding of the evolution and dissemination of resistance is to seek more direct processes that can be detected, diagnosed, and consequently studied with greater agility.High sensitivity and viability make the target-site resistance driven by genetic mutation of special interest in developing molecular markers [72], as it is primarily characterized by mutations in the coding region of the proteins targeted by an insecticide and, therefore, results in high levels of resistance [73]. Moreover, in many cases, these mutations in the same target gene are responsible for resistance to the same insecticide in different insect species, making molecular markers an excellent monitoring tool [74]. Thus, the identification and localization of genes associated with insecticide resistance are essential for understanding resistance mechanisms and can be effectively achieved with the help of molecular markers, which adds value to resistance management strategies [75]. Therefore, we can conclude that target-site molecular markers are the most suitable for developing products for molecular diagnostics with great market potential, as they can be used to overcome the need for time-consuming bioassays and assist in decision-making in the field, although this second step remains a challenge [72].
Adapting automatic water samplers for the isotopic study of rainfall at high temporal...
Cécile Carton
Florent Barbecot

Cécile Carton

and 4 more

September 03, 2024
Rationale: Stable isotopes of water in precipitation are powerful tracers of atmospheric processes. Automatic rain samplers are valuable for high temporal resolution isotopic studies but building them from scratch requires significant financial and material resources. A commercial water autosampler has been modified to prevent evaporation after sampling and to allow precipitation sampling during an event. Methods: New sampling bottles were created by reducing the original volume and opening area. Evaporation tests were carried out on different volumes of water for 72 hours under laboratory conditions. These were used to determine the minimum amount of rain to collect to minimize the impact of isotopic fractionation by evaporation. The impact of the autosampler’s air moisture saturation was also tested. Samples were analyzed by dual-inlet isotope ratio mass spectrometry and cavity ring-down spectroscopy. Results: For samples larger than 10 mL, evaporative heavy isotope enrichment due to Rayleigh distillation remains negligible compared to the overall analytical uncertainty. Intentional saturation of the autosampler’s atmosphere significantly reduces post-sampling evaporation but leads to equilibration of the samples with the added water. We have investigated the maximum time that samples must be left for this fractionation to remain negligible. Under these conditions, this autosampler is suitable for intra-event rainfall sampling for isotopic analysis. Conclusions: It is now possible to perform low-cost high-resolution precipitation sampling for isotopic analysis. The intentional air saturation of the sampler, which effectively prevents post-sampling evaporation, had never been proposed before. All instructions for modifying this sampler are now available in open access so the scientific community can easily repeat them.
Addressing Behavioral and Psychiatric Symptoms in Dystonia: A C...
Tara Khoeini
Mohammad Javad Sinaeefar

Tara Khoeini

and 1 more

September 03, 2024
Addressing Behavioral and Psychiatric Symptoms in Dystonia: A Case Report of Fahr Disease
Adult-onset Still Disease with Impending Macrophage Activation Syndrome in a 24-year-...
Sagar  Poudel
Sudip Paudel

Sagar Poudel

and 7 more

September 03, 2024
Title : Adult-onset Still Disease with Impending Macrophage Activation Syndrome in a 24-year-old female
javascript:void(0) Targeting cell death: a potential therapeutic strategy...
Tian-gang LI
Ying-li Wu

Tian-gang LI

and 12 more

September 03, 2024
not-yet-known not-yet-known not-yet-known unknown Inflammatory bowel disease (IBD) is a chronic relapsing inflammatory disease of the intestines characterized by a progressive and unpredictable course, and colorectal cancer (CRC), a malignant tumor of the colon or rectum, is a malignant disease that seriously affects human health. The risk of colitis-associated cancer (CAC) is high in patients with IBD, and CRC is one of the most serious consequences for patients with IBD. Cell death is a fundamental physiological process in all living organisms, and it includes apoptosis, necroptosis, pyroptosis, autophagy, ferroptosis, and cuproptosis. Regulatory cell death (RCD), a form of cell death that can be regulated by a variety of biomolecules, plays an important role in maintaining physiological homeostasis in the body, resistance to pathogen attack, and a range of pathological states, such as inflammation and cancers. There is growing evidence that different types of RCD are involved not only in the pathogenesis of IBD, CRC, and CAC but also in the therapeutic process. The present review will provide ideas for further exploration of RCD affecting IBD, CRC, and CAC by summarizing the possible mechanisms of the involvement of different types of RCD in IBD, CRC, and CAC. Additionally, this article will discuss recent advancements in pharmacotherapy.
The role of T cell related genes in COVID-19 and osteoporosis and the screening of bi...
Xining Li
Jianyou Li

Xining Li

and 4 more

September 03, 2024
Background: Studies have revealed that coronavirus disease 2019 (COVID-19) could induce or aggravate osteoporosis (OP) which is the most common metabolic bone disease, and T cells participated in the progression of OP. Methods: OP and COVID-19 related RNA sequencing data (RNA-seq) were downloaded from the bioinformatics database. Firstly, differentially expressed genes between OP and control samples and between COVID-19 and healthy samples were screened out by differential analyses for further intersection to obtain intersected genes. Then, weighted gene co-expression network analysis (WGCNA) was applied based on T cell infiltrating scores (T-scores) calculated by “MCPcounter” package to screen T cell related genes (TRGs). Subsequently, these TRGs were intersected with intersected genes to obtain biomarkers. In addition, to figure out deeper mechanism of them, we conducted enrichment analyses and constructed miRNA-mRNA and TF-miRNA networks of biomarkers. Results: Based on the OP and COVID-19 datasets, totals of 14 intersected genes were obtained via differential analyses, and 459 TRGs were screened out after WGCNA. Then, 3 biomarkers including ITGA7, ZNF302, and LYRM7 were acquired by intersection between TRGs and intersected genes. Results of enrichment analyses demonstrated that biomarkers were mainly commonly enriched in “mitochondrial protein-containing complex”, “Proteasome”, and “Spliceosome” in OP, and “transmitter−gated channel activity”, “Nicotine addiction”, and so on in COVID-19. Otherwise, we predicted 7 micro RNAs (miRNAs) and 46 transcription factors (TFs) regulating the biomarkers, and constructed the miRNA-mRNA and TF-mRNA networks. Conclusion: In this study, we screened out 3 biomarkers associated with OP, COVID-19, and T cells, namely ITGA7, ZNF302, and LYRM7, that had preferable prediction performance of OP. The results could provide references for further studies and treatments of OP.
Periostin induces epithelial-mesenchymal transition via p38-MAPK pathway in human ren...
xiaoling xiong
Xing Feng

xiaoling xiong

and 2 more

September 03, 2024
Background: Periostin mediates inflammation and fibrosis by regulating ECM adhesion, migration, and differentiation in multiple organ diseases. Studies have shown Periostin mainly located in the dilated mesangium, tubulointerstitial and fibrotic regions of the diabetic nephropathy, which is negatively correlated with renal function. However, the underlying mechanisms remain poorly explored. Methods: The expression of periostin in HK-2 cells was investigated under high glucose and high concentration of TGF-β1. The signaling pathway of periostin involved in epithelial-mesenchymal transdifferentiation of HK-2 cells was also validated. The expression of periostin were investigated by RT-PCR with different concentration of glucose and TGF-β1. Periostin expression in HK-2 cells stimulated by high glucose and high TGF-β1 was detected by western blotting and immunofluorescence. The expression of E-Cad, α-SMA and p38 proteins were also detected. The effects of p38 inhibitors on periostin, E-Cad and α-SMA in high glucose environment were also investigated and verified. Results: High concentration of glucose and TGF-β1 increased the fibrosis of HK-2 cells, prompting high expression of periostin. The combined stimulation of high glucose (22 mmol/L) and high TGF-β1(10 ng/mL) upregulated the expression of periostin obviously, stimulating the expression of α-SMA and p38 while inhibiting the secretion of E-Cad. More importantly, p38 inhibitors reduced the expression of periostin and α-SMA protein while promoted E-Cad protein expression in HK-2 cells under high glucose conditions. Furthermore, p38-MAPK signal pathway was involved in the epithelial-mesenchymal transition of human renal tubules in high glucose environment. Conclusion: Periostin, a downstream factor of TGF-β1, is positively regulated by TGF-β1 under high glucose condition, affecting the epithelial-interstitial differentiation of HK-2 cells via the p38-MAPK signaling pathway. Therefore, periostin may serve as a biomarker of renal fibrosis in diabetic kidney disease.
SIB: Sorted-integers-based Index for Compact and Fast Caching in Top-down Logic Rule...
Ruoyu Wang
Raymond Wong

Ruoyu Wang

and 3 more

September 03, 2024
not-yet-known not-yet-known not-yet-known unknown Mining logic rules from structured knowledge bases is the basis of knowledge engineering. Due to the NP-hardness of the rule mining problem, logic rules cannot be efficiently induced from knowledge bases, especially large-scale ones, and most mining techniques employ algorithmic and architectural optimizations to improve efficiency. Data-oriented optimizations have also been explored to some extent, but the data efficiency is relatively low, and the memory consumption is thus becoming a new challenge for state-of-the-art systems. In this article, we propose a compact and efficient index structure for the maintenance of the intermediate data during top-down rule mining. The index is based on a mapping from constant symbols to integers and the sorting of the mapped integers. We evaluate our method on six datasets which contain up to 160K records and are frequently used as benchmarks in knowledge engineering related tasks. The experimental results show that the proposed technique speeds up the rule mining procedure by 5x on average and reduces memory consumption by up to 70%. The space overhead of the data structure is about twice that of the indexed records, which is more than 80% lower than that of the state-of-the-art technique.
Predicting Risk Areas of Cattle, Sheep and Goat Tuberculosis in China Based on Air Po...
Le Xu
Hong Li

Le Xu

and 13 more

September 03, 2024
not-yet-known not-yet-known not-yet-known unknown Tuberculosis is a zoonotic chronic respiratory infectious disease caused by the Mycobacterium tuberculosis complex. Domestic animals such as cattle, sheep, and goats are important but neglected hosts of tuberculosis. The outbreak and epidemic of tuberculosis can seriously threaten human and veterinary health. To investigate the effects of air pollutants and meteorological factors on cattle, sheep, and goat tuberculosis, we obtained the incidence rates of M. tuberculosis infection in cattle, buffaloes, sheep, and goats in China from the published literature. We identified key risk factors among 6 major air pollutants (particulate matter 2.5, particulate matter 10, carbon monoxide, nitrogen dioxide, sulfur dioxide, and ozone) and 19 bioclimatic variables; simulated the risk distribution of cattle, sheep, and goat tuberculosis in China using the maximum entropy niche model; and evaluated the effects of environmental factors. The area under the curve of the model was 0.873 (95% confidence interval, 0.0851–0.0895). The risk factors that most significantly influenced the incidence of tuberculosis included NO2 level, mean temperature of the coldest quarter, cattle distribution density, sheep distribution density, O3 level, and precipitation of the driest month. The predicted risk map indicated that the high-risk regions were Guangxi Province; the northern Taklimakan Desert in Xinjiang, Guangdong Province; Hainan Province; Eastern Qinghai Province; parts of Shandong Province; Gansu Province; Eastern Sichuan Province; Central Shaanxi Province; Central Inner Mongolia; Beijing–Tianjin–Hebei region; Ningxia Hui Autonomous Region; Northern Henan Province; the border area between Jiangsu, Zhejiang, and Shanghai; and Taiwan Island. Improved surveillance is needed in these high-risk areas, and early preventive measures must be implemented based on the risk factors identified to reduce future incidence of cattle, sheep, and goat tuberculosis.
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