Harnessing landrace diversity empowers wheat breeding.

Harnessing genetic diversity in major staple crops through the development of new breeding capabilities is essential to ensure food security1. Here we examined the genetic and phenotypic diversity of the A.E. Watkins landrace collection2 of bread wheat (Triticum aestivum), a major global cereal, through whole-genome re-sequencing (827 Watkins landraces and 208 modern cultivars) and in-depth field evaluation spanning a decade. We discovered that modern cultivars are derived from just two of the seven ancestral groups of wheat and maintain very long-range haplotype integrity. The remaining five groups represent untapped genetic sources, providing access to landrace-specific alleles and haplotypes for breeding. Linkage disequilibrium (LD) based haplotypes and association genetics analyses link Watkins genomes to the thousands of high-resolution quantitative trait loci (QTL), and significant marker-trait associations identified. Using these structured germplasm, genotyping and informatics resources, we revealed many Watkins-unique beneficial haplotypes that can confer superior traits in modern wheat. Furthermore, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritised QTL in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilising genetic diversity in crop improvement to achieve sustainable food security.

Enhancing maize growth through the synergistic impact of potassium enrich biochar and spermidine.

Maize cultivated for dry grain covers approximately 197 million hectares globally, securing its position as the second most widely grown crop worldwide after wheat. Although spermidine and biochar individually showed positive impacts on maize production in existing literature, their combined effects on maize growth, physiology, nutrient uptake remain unclear and require further in-depth investigation. That's why a pot experiment was conducted on maize with spermidine and potassium enriched biochar (KBC) as treatments in Multan, Pakistan, during the year 2022. Four levels of spermidine (0, 0.15, 0.30, and 0.45mM) and two levels of potassium KBC (0 and 0.50%) were applied in completely randomized design (CRD). Results showed that 0.45 mM spermidine under 0.50% KBC caused significant enhancement in maize shoot length (11.30%), shoot fresh weight (25.78%), shoot dry weight (17.45%), root length (27.95%), root fresh weight (26.80%), and root dry weight (20.86%) over control. A significant increase in maize chlorophyll a (50.00%), chlorophyll b (40.40%), total chlorophyll (47.00%), photosynthetic rate (34.91%), transpiration rate (6.51%), and stomatal conductance (15.99%) compared to control under 0.50%KBC validate the potential of 0.45 mM spermidine. An increase in N, P, and K concentration in the root and shoot while decrease in electrolyte leakage and antioxidants also confirmed that the 0.45 mM spermidine performed more effectively with 0.50%KBC. In conclusion, 0.45 mM spermidine with 0.50%KBC is recommended for enhancing maize growth.

The role of strigolactone in alleviating salinity stress in chili pepper.

Salinity stress can significantly delay plant growth. It can disrupt water and nutrient uptake, reducing crop yields and poor plant health. The use of strigolactone can be an effective technique to overcome this issue. Strigolactone enhances plant growth by promoting root development and improvement in physiological attributes. The current pot study used strigolactone to amend chili under no salinity and salinity stress environments. There were four treatments, i.e., 0, 10µM strigolactone, 20µM strigolactone and 30µM strigolactone. All treatments were applied in four replications following a completely randomized design (CRD). Results showed that 20µM strigolactone caused a significant increase in chili plant height (21.07%), dry weight (33.60%), fruit length (19.24%), fruit girth (35.37%), and fruit yield (60.74%) compared to control under salinity stress. Significant enhancement in chili chlorophyll a (18.65%), chlorophyll b (43.52%), and total chlorophyll (25.09%) under salinity stress validated the effectiveness of 20µM strigolactone application as treatment over control. Furthermore, improvement in nitrogen, phosphorus, and potassium concentration in leaves confirmed the efficient functioning of 20µM strigolactone compared to other concentrations under salinity stress. The study concluded that 20µM strigolactone is recommended for mitigating salinity stress in chili plants. Growers are advised to apply 20µM strigolactone to enhance their chili production under salinity stress.

Comparative interactome mapping of Tau-protein in classical and rapidly progressive Alzheimer's disease identifies subtype-specific pathways.

AIMS: Tau is a key player in Alzheimer's disease (AD) and other Tauopathies. Tau pathology in the brain directly correlates with neurodegeneration in AD. The recent identification of a rapid variant of AD demands an urgent need to uncover underlying mechanisms leading to differential progression in AD. Accordingly, we aimed to dissect the underlying differential mechanisms of toxicity associated with the Tau protein in AD subtypes and to find out subtype-dependent biomarkers and therapeutic targets. METHODS: To identify and characterise subtype-specific Tau-associated mechanisms of pathology, we performed comparative interactome mapping of Tau protein in classical AD (cAD) and rapidly progressive AD (rpAD) cases using co-immunoprecipitation coupled with quantitative mass spectrometry. The mass spectrometry data were extensively analysed using several bioinformatics approaches. RESULTS: The comparative interactome mapping of Tau protein revealed distinct and unique interactors (DPYSL4, ARHGEF2, TUBA4A and UQCRC2) in subtypes of AD. Interestingly, an analysis of the Tau-interacting proteins indicated enrichment of mitochondrial organisation processes, including negative regulation of mitochondrion organisation, mitochondrial outer membrane permeabilisation involved in programmed cell death, regulation of autophagy of mitochondrion and necroptotic processes, specifically in the rpAD interactome. While, in cAD, the top enriched processes were related to oxidation-reduction process, transport and monocarboxylic acid metabolism. CONCLUSIONS: Overall, our results provide a comprehensive map of Tau-interacting protein networks in a subtype-dependent manner and shed light on differential functions/pathways in AD subtypes. This comprehensive map of the Tau-interactome has provided subsets of disease-related proteins that can serve as novel biomarkers/biomarker panels and new drug targets.

Exploring non-cytotoxic, antioxidant, and anti-inflammatory properties of selenium nanoparticles synthesized from Gymnema sylvestre and Cinnamon cassia extracts for herbal nanomedicine.

The increasing need for pharmaceutical agents that possess attributes such as safety, cost-effectiveness, environmental sustainability, and absence of side effects has driven the advancement of nanomedicine research, which lies at the convergence of nanotechnology and medicine. AIMS AND OBJECTIVES: The study aimed to synthesize non-toxic selenium nanoparticles (SeNPs) using Gymnema sylvestre (G. sylvestre) and Cinnamon cassia (C. cassia) extracts. It also sought to develop and evaluate versatile nanomedicine formulations i.e. selenium nanoparticles of G. sylvestre and C. cassia (SeNPs), drug (lupeol) loaded SeNPs (DLSeNPs), drug-loaded and coated (PEG) SeNPs (DLCSeNPs) without side effects. METHODS: The SeNPs formulations were hydrothermally synthesized, loaded with lupeol to improve efficacy, coated with polyethylene glycol (PEG) for targeted delivery, and characterized using UV-Vis spectrophotometry, Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), zeta potential analysis, size distribution analysis, and X-ray diffraction (XRD). Hemolytic cytotoxicity, 2,2-Diphenyl-1-picrylhydzayl (DPPH), total Reducing power, and total antioxidant capacity (TAC) antioxidant assays, carrageenan-induced paw edema, and histological studies were used to estimate the acute anti-inflammatory activity of the synthesized SeNPs. RESULTS: The final form of PEGylated and drug (lupeol)-loaded selenium nanoparticles (DLCSeNPs) exhibited an average particle size ranging from 100 to 500 nm as evidenced by SEM, and Zeta potential results. These nanoparticles demonstrated no cytotoxic effects and displayed remarkable antioxidant (IC50 values 19.29) and anti-inflammatory capabilities. These results were fed into Graph-pad Prism 5 software and analyzed by one-way ANOVA, followed by Tukey's post hoc test (p < 0.001). All nano-formulations exhibited significant overall antioxidant activity, with IC50 values ≤ 386 (p < 0.05) as analyzed by ANOVA. The study's results suggest that G. sylvestre outperformed C. cassia in terms of reducing 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) free radical, potassium ferricyanide, and ammonium molybdate in respective antioxidant assays. As far as anti-inflammatory activities are concerned drug (lupeol)-loaded and PEG-coated G. sylvestre SeNPs exhibited the highest anti-inflammatory potential from all other nano-formulations including drug (lupeol)-loaded and PEG-coated C. cassia SeNPs, as exhibited to reduce the release of pro-inflammatory signals i.e. cytokines and NF-kB, making them innovative anti-inflammatory nanomedicine. CONCLUSION: The study synthesized lupeol-loaded and PEG-coated SeNPs, showcasing the potential for biocompatible, cost-effective anti-inflammatory nanomedicines. G. Sylvester's superior antioxidant and anti-inflammatory performance than Cinnamon cassia emphasizes medicinal plant versatility.

Timing of development of osteoradionecrosis post head and neck radiotherapy: does a safe time interval exist for dental extraction?

INTRODUCTION: Risk factors for developing osteoradionecrosis (ORN) are well known, but less is known about factors influencing the interval between radiotherapy and the onset of ORN. Also, it is unknown whether there is any specific period post-radiotherapy with a reduced probability of ORN when irradiated teeth require extraction. PURPOSE: The primary aim of this study was to identify factors influencing the interval in developing ORN in the following subgroups of patients: (1) patients who spontaneously developed ORN, (2) surgical-intervention-related ORN with a particular focus on patients after mandibulectomy. The secondary aim was to attempt to identify a possible time for safer dental intervention after primary treatment. MATERIALS AND METHODS: The authors retrospectively analysed 1608 head and neck cancer (HNC) patients treated in a single centre. Time intervals were measured from the end of radiotherapy to the development of ORN and further analysed in the subgroups listed above. RESULTS: In all, 141 patients (8.8%) developed intra-oral ORN. Median time from radiotherapy to ORN development in the whole cohort was 9 months. Median interval for spontaneous ORN was 8 months, 6.5 months for intervention-related ORN, and 15 months for patients post-mandibulectomy. In patients who required dental extraction preradiotherapy, median interval of ORN onset was 5 months. CONCLUSION: In our study, a slightly higher proportion of patients with intervention developed ORN earlier in comparison with spontaneous ORN. The period from 12-18 months after radiotherapy was identified as having the highest probability of developing ORN in patients after mandibulectomy. A time for safer dental intervention after primary treatment was not identified.

Genomic insights into local adaptation of upland cotton in China and Pakistan.

KEY MESSAGE: Different kinship and resistance to cotton leaf curl disease (CLCuD) and heat were found between upland cotton cultivars from China and Pakistan. 175 SNPs and 82 InDels loci related to yield, fiber quality, CLCuD, and heat resistance were identified. Elite alleles found in Pakistani accessions aided local adaptation to climatic condition of two countries. Adaptation of upland cotton (Gossypium hirsutum) beyond its center of origin is expected to be driven by tailoring of the genome and genes to enhance yield and quality in new ecological niches. Here, resequencing of 456 upland cotton accessions revealed two distinct kinships according to the associated country. Fiber quality and lint percentage were consistent across kinships, but resistance to cotton leaf curl disease (CLCuD) and heat was distinctly exhibited by accessions from Pakistan, illustrating highly local adaption. A total of 175 SNP and 82 InDel loci related to yield, fiber quality, CLCuD and heat resistance were identified; among them, only two overlapped between Pakistani and Chinese accessions underscoring the divergent domestication and improvement targets in each country. Loci associated with resistance alleles to leaf curl disease and high temperature were largely found in Pakistani accessions to counter these stresses prevalent in Pakistan. These results revealed that breeding activities led to the accumulation of unique alleles and helped upland cotton become adapted to the respective climatic conditions, which will contribute to elucidating the genetic mechanisms that underlie resilience traits and help develop climate-resilient cotton cultivars for use worldwide.

Genome dosage alteration caused by chromosome pyramiding and shuffling effects on karyotypic heterogeneity, reproductive diversity, and phenotypic variation in Zea-Tripsacum allopolyploids.

KEY MESSAGE: We developed an array of Zea-Tripsacum tri-hybrid allopolyploids with multiple ploidies. We unveiled that changes in genome dosage due to the chromosomes pyramiding and shuffling of three species effects karyotypic heterogeneity, reproductive diversity, and phenotypic variation in Zea-Tripsacum allopolyploids. Polyploidy, or whole genome duplication, has played a major role in evolution and speciation. The genomic consequences of polyploidy have been extensively studied in many plants; however, the extent of chromosomal variation, genome dosage, phenotypic diversity, and heterosis in allopolyploids derived from multiple species remains largely unknown. To address this question, we synthesized an allohexaploid involving Zea mays, Tripsacum dactyloides, and Z. perennis by chromosomal pyramiding. Subsequently, an allooctoploid and an allopentaploid were obtained by hybridization of the allohexaploid with Z. perennis. Moreover, we constructed three populations with different ploidy by chromosomal shuffling (allopentaploid × Z. perennis, allohexaploid × Z. perennis, and allooctoploid × Z. perennis). We have observed 3 types of sexual reproductive modes and 2 types of asexual reproduction modes in the tri-species hybrids, including 2n gamete fusion (2n + n), haploid gamete fusion (n + n), polyspermy fertilization (n + n + n) or 2n gamete fusion (n + 2n), haploid gametophyte apomixis, and asexual reproduction. The tri-hybrids library presents extremely rich karyotype heterogeneity. Chromosomal compensation appears to exist between maize and Z. perennis. A rise in the ploidy of the trihybrids was linked to a higher frequency of chromosomal translocation. Variation in the degree of phenotypic diversity observed in different segregating populations suggested that genome dosage effects phenotypic manifestation. These findings not only broaden our understanding of the mechanisms of polyploid formation and reproductive diversity but also provide a novel insight into genome pyramiding and shuffling driven genome dosage effects and phenotypic diversity.

Interplay of oxidative stress, cellular communication and signaling pathways in cancer.

Cancer remains a significant global public health concern, with increasing incidence and mortality rates worldwide. Oxidative stress, characterized by the production of reactive oxygen species (ROS) within cells, plays a critical role in the development of cancer by affecting genomic stability and signaling pathways within the cellular microenvironment. Elevated levels of ROS disrupt cellular homeostasis and contribute to the loss of normal cellular functions, which are associated with the initiation and progression of various types of cancer. In this review, we have focused on elucidating the downstream signaling pathways that are influenced by oxidative stress and contribute to carcinogenesis. These pathways include p53, Keap1-NRF2, RB1, p21, APC, tumor suppressor genes, and cell type transitions. Dysregulation of these pathways can lead to uncontrolled cell growth, impaired DNA repair mechanisms, and evasion of cell death, all of which are hallmark features of cancer development. Therapeutic strategies aimed at targeting oxidative stress have emerged as a critical area of investigation for molecular biologists. The objective is to limit the response time of various types of cancer, including liver, breast, prostate, ovarian, and lung cancers. By modulating the redox balance and restoring cellular homeostasis, it may be possible to mitigate the damaging effects of oxidative stress and enhance the efficacy of cancer treatments. The development of targeted therapies and interventions that specifically address the impact of oxidative stress on cancer initiation and progression holds great promise in improving patient outcomes. These approaches may include antioxidant-based treatments, redox-modulating agents, and interventions that restore normal cellular function and signaling pathways affected by oxidative stress. In summary, understanding the role of oxidative stress in carcinogenesis and targeting this process through therapeutic interventions are of utmost importance in combating various types of cancer. Further research is needed to unravel the complex mechanisms underlying oxidative stress-related pathways and to develop effective strategies that can be translated into clinical applications for the management and treatment of cancer. Video Abstract.

Exploiting the biocatalytic potential of co-expressed l-fucose isomerase and d-tagatose 3-epimerase for the biosynthesis of 6-deoxy-l-sorbose.

6-Deoxy-l-sorbose (6-DLS) is an imperative rare sugar employed in food, agriculture, pharmaceutical and cosmetic industeries. However, it is a synthetic and very expensive rare sugars, previously synthesized by chemo-enzymatic methods through a long chain of chemical processes. Recently, enzymatic synthesis of rare sugars has attracted a lot of attention due to its advantages over synthetic methods. In this work, a promising approach for the synthesis of 6-DLS from an inexpensive sugar l-fucose was identified. The genes for l-fucose isomerase from Paenibacillus rhizosphaerae (Pr-LFI) and genes for d-tagatose-3-epimerase from Caballeronia fortuita (Cf-DTE) have been used for cloning and co-expression in Escherichia coli, developed a recombinant plasmid harboring pANY1-Pr-LFI/Cf-DTE vector. The recombinant co-expression system exhibited an optimum activity at 50 °C of temperature and pH 6.5 in the presence of Co2+ metal ion which inflated the catalytic activity by 6.8 folds as compared to control group with no metal ions. The recombinant co-expressed system was stable up to more than 50 % relative activity after 12 h and revealed a melting temperature (Tm) of 63.38 °C exhibiting half-life of 13.17 h at 50 °C. The co-expression system exhibited, 4.93, 11.41 and 16.21 g/L of 6-DLS production from initial l-fucose concentration of 30, 70 and 100 g/L, which equates to conversion yield of 16.44 %, 16.30 % and 16.21 % respectively. Generally, this study offers a promising strategy for the biological production of 6-DLS from an inexpensive substrate l-fucose in slightly acidic conditions with the aid of co-expression system harboring Pr-LFI and CF-DTE genes.

Advanced photocatalysis as a viable and sustainable wastewater treatment process: A comprehensive review.

In our era, water pollution not only poses a serious threat to human, animal, and biotic life but also causes serious damage to infrastructure and the ecosystem. A set of physical, chemical, and biological technologies have been exploited to decontaminate and/or disinfect water pollutants, toxins, microbes, and contaminants, but none of these could be ranked as sustainable and scalable wastewater technology. The photocatalytic process can harmonize the sunlight to degrade certain toxins, chemicals, microbes, and antibiotics, present in water. For example, transition metal oxides (ZnO, SnO2, TiO2, etc.), when integrated into an organic framework of graphene or nitrides, can bring about more than 90% removal of dyes, microbial load, pesticides, and antibiotics. Similarly, a modified network of graphitic carbon nitride can completely decontaminate petrochemicals. The present review will primarily highlight the mechanistic aspects for the removal and/or degradation of highly concerned contaminants, factors affecting photocatalysis, engineering designs of photoreactors, and pros and cons of various wastewater treatment technologies already in practice. The photocatalytic reactor can be a more viable and sustainable wastewater treatment opportunity. We hope the researcher will find a handful of information regarding the advanced oxidation process accomplished via photocatalysis and the benefits associated with the photocatalytic-type degradation of water pollutants and contaminants.

Spatial distribution of heavy metal abundance at distance gradients of roadside agricultural soil from the busiest highway in Bangladesh: A multi-index integration approach.

Bangladesh is currently experiencing significant infrastructural development in road networking system through the construction or reconstruction of multiple roads and highways. Consequently, there is a rise in traffic intensity on roads and highways, along with a significant contamination of adjacent agricultural soils with heavy metals. The purpose of this study was to evaluate the ecological risk, health risk and the abundance of seven heavy metals (Cu, Mn, Pb, Cd, Cr, As, and Ni) in three distance gradients (0, 300, and 500 m) of agricultural soil along the Dhaka-Chattogram highway. The concentration of heavy metals was measured with an Atomic Absorption Spectrophotometer (AAS) on a total of 36 soil samples that were taken from 12 different sampling sites. Based on the findings, Cd had a high contamination factor for all distance gradients, whereas Cr had a moderate contamination factor in 67% of the study areas. According to the Pollution Load Index (PLI), Cd, Cr, and Pb were the predominant pollutants. Principal component analysis (PCA) result shows these metals mainly came from anthropogenic sources. The considerable positive correlations between Cu-Pb, Cu-Cd, Pb-Cd, and Cr-Ni all pointed to shared anthropogenic origins. As per Potential Ecological Risk Assessment (PERI) analysis, Pb, Cd, Cr, and Ni each contribute significantly and pose a moderate threat. The Target Hazard Quotient (THQ) values for all pathways of exposure to Pb and Cr in soils were more than 1, which would pose a significant risk to human health in the following order: THQadult female > THQadult male > THQchildren. This study will help to evaluate the human health risk and develop a better understanding of the heavy metal abundance scenario in the agricultural fields adjacent to this highway.

Distribution and antimicrobial resistance patterns of urinary pathogens in preoperative midstream urine cultures from Chinese patients with urinary calculi: a meta-analysis.

BACKGROUND AND OBJECTIVE: This study comprehensively evaluates the distribution patterns and antimicrobial resistance profiles of urinary pathogens in Preoperative midstream urine cultures collected from patients with urinary calculi in China over the last two decades. METHODS: A cross-sectional analysis of 41 studies was conducted. A systematic search across various databases, including Wanfang Data, CNKI, SinoMed, Embase, PubMed, and Web of Science, was carried out, covering the time period from 2002 to 2022. Using R 4.2.1 software, a meta-analysis was performed to assess heterogeneity using Cochran's Q test and the I2 statistic. RESULTS: In the analysis of preoperative midstream urine cultures from Chinese patients with urinary calculi, gram-negative bacteria dominated at 69%, with Escherichia coli (43%), Klebsiella pneumoniae (8%), Proteus mirabilis (6%), Pseudomonas aeruginosa (5%), Acinetobacter baumannii (3%), and Enterobacter cloacae (4%) being prominent. Gram-positive organisms included Enterococcus faecalis (9%), Enterococcus faecium (5%), and Staphylococcus aureus (4%). Over time, proportions of Proteus mirabilis, Enterococcus faecalis, and Staphylococcus aureus decreased, while Klebsiella pneumoniae and Pseudomonas aeruginosa increased. Notably, Escherichia coli proportion reduced from 37 to 33% within the last two decades. Antimicrobial resistance analysis indicated declining resistance in E. coli (e.g., co-trimoxazole from 73 to 55%, gentamicin from 64 to 40%), but rising resistance in piperacillin and cefotaxime (34-60%). Enterococcus faecalis exhibited increasing resistance to ampicillin (5-69%), gentamicin (59-94%), and tetracycline (77-89%) over time, while resistance to levofloxacin and ciprofloxacin notably decreased (72-16% and 49-8%, respectively). CONCLUSION: Over the past two decades, the proportion of gram-negative bacteria was declined, while the proportion of gram-positive bacteria increased. Escherichia coli remained the most common pathogen in the urine culture of patients with urinary calculi in China and the resistance of Escherichia coli to commonly used antibiotics increased. Clinicians should select appropriate antibiotics according to the results of urine culture and drug sensitivity test to reduce the occurrence of antibiotic resistance.

Exploring determinants of sex and family history-based disparity in type 2 diabetes mellitus prevalence among clinical patients.

BACKGROUND: Type 2 diabetes mellitus represents a multifaceted disorder characterized by intricate pathophysiological mechanisms, encompassing diminished insulin secretion, augmented hepatic glucose production, and heightened insulin resistance. This study aims to assess the sex (Male and Female only) and family history-based differences in the prevalence of T2DM and explore the determinants contributing to this disparity among clinical patients. SUBJECTS AND METHODS: The study encompassed a diverse pool of clinical patients, encompassing both individuals with diabetes and those without the condition, who had previously sought medical attention for clinical checkups at healthcare centers. The collected data included essential parameters such as blood pressure, weight, height, smoking habits, educational background, and physical activity levels. To ensure methodological rigor and data accuracy, blood pressure measurements adhered to the stringent guidelines set forth by the World Health Organization. RESULTS: Participants of the present study reported diabetes, among which notable findings emerged regarding health indicators. It was observed that the prevalence of high blood pressure, obesity, and high blood cholesterol exhibited a statistically significant increase among the female participants, underscoring the sex-based disparities in these health parameters. The male population aged 60 or older, the presence of a family history of DM accentuated this risk, resulting in a striking 3.1 times higher prevalence compared to females, who exhibited a 2.4 times higher risk (OR = 2.4, p = 0.0008). This intriguing relationship between diabetes and cholesterol levels was not limited to sex. Both male (OR = 2.47) and female (OR = 2.1) diabetes patients displayed highly significant associations with cholesterol levels. The risk of T2DM was significantly associated with triglycerides in both sexes (1.58 times higher in males, and 1.71 times higher in females). CONCLUSIONS: The significance of hypertension as a comorbidity in T2DM, highlighting sex-specific associations and the potential impact of a family history of diabetes on blood pressure. Our findings emphasize the importance of considering lipid profiles, obesity, and their sex-specific associations when assessing and managing diabetes risk. Comprehensive diabetes care should include strategies for lipid control, weight management, and cardiovascular risk reduction, tailored to the individual's sex and specific risk profile.

Twelve tips to virtually operationalize co-creation of educational design.

Co-creation is the active involvement of all stakeholders, including students, in educational design processes to improve the quality of education by embodying inclusivity, transparency and empowerment. Virtual co-creation has the potential to expand the utility of co-creation as an inclusive approach by overcoming challenges regarding the practicality and availability of stakeholders, typically experienced in face-to-face co-creation. Drawing from the literature and our experiences of virtual co-creation activities in different educational contexts, this twelve tips paper provides guidelines on how to effectively operationalize co-creation in a virtual setting. Our proposed three-phased approach (preparation, conduction, follow-up) might help those aiming to virtually co-create courses and programs by involving stakeholders beyond institutes and across borders.

Uncovering the history of recombination and population structure in western Canadian stripe rust populations through mating type alleles.

BACKGROUND: The population structure of crop pathogens such as Puccinia striiformis f. sp. tritici (Pst), the cause of wheat stripe rust, is of interest to researchers looking to understand these pathogens on a molecular level as well as those with an applied focus such as disease epidemiology. Cereal rusts can reproduce sexually or asexually, and the emergence of novel lineages has the potential to cause serious epidemics such as the one caused by the 'Warrior' lineage in Europe. In a global context, Pst lineages in Canada were not well-characterized and the origin of foreign incursions was not known. Additionally, while some Pst mating type genes have been identified in published genomes, there has been no rigorous assessment of mating type diversity and distribution across the species. RESULTS: We used a whole-genome/transcriptome sequencing approach for the Canadian Pst population to identify lineages in their global context and evidence tracing foreign incursions. More importantly: for the first time ever, we identified nine alleles of the homeodomain mating type locus in the worldwide Pst population and show that previously identified lineages exhibit a single pair of these alleles. Consistently with the literature, we find only two pheromone receptor mating type alleles. We show that the recent population shift from the 'PstS1' lineage to the 'PstS1-related' lineage is also associated with the introduction of a novel mating type allele (Pst-b3-HD) to the Canadian population. We also show evidence for high levels of mating type diversity in samples associated with the Himalayan center of diversity for Pst, including a single Canadian race previously identified as 'PstPr' (probable recombinant) which we identify as a foreign incursion, most closely related to isolates sampled from China circa 2015. CONCLUSIONS: These data describe a recent shift in the population of Canadian Pst field isolates and characterize homeodomain-locus mating type alleles in the global Pst population which can now be utilized in testing several research questions and hypotheses around sexuality and hybridization in rust fungi.

Smart Resource Allocation in Mobile Cloud Next-Generation Network (NGN) Orchestration with Context-Aware Data and Machine Learning for the Cost Optimization of Microservice Applications.

Mobile cloud computing (MCC) provides resources to users to handle smart mobile applications. In MCC, task scheduling is the solution for mobile users' context-aware computation resource-rich applications. Most existing approaches have achieved a moderate service reliability rate due to a lack of instance-centric resource estimations and task offloading, a statistical NP-hard problem. The current intelligent scheduling process cannot address NP-hard problems due to traditional task offloading approaches. To address this problem, the authors design an efficient context-aware service offloading approach based on instance-centric measurements. The revised machine learning model/algorithm employs task adaptation to make decisions regarding task offloading. The proposed MCVS scheduling algorithm predicts the usage rates of individual microservices for a practical task scheduling scheme, considering mobile device time, cost, network, location, and central processing unit (CPU) power to train data. One notable feature of the microservice software architecture is its capacity to facilitate the scalability, flexibility, and independent deployment of individual components. A series of simulation results show the efficiency of the proposed technique based on offloading, CPU usage, and execution time metrics. The experimental results efficiently show the learning rate in training and testing in comparison with existing approaches, showing efficient training and task offloading phases. The proposed system has lower costs and uses less energy to offload microservices in MCC. Graphical results are presented to define the effectiveness of the proposed model. For a service arrival rate of 80%, the proposed model achieves an average 4.5% service offloading rate and 0.18% CPU usage rate compared with state-of-the-art approaches. The proposed method demonstrates efficiency in terms of cost and energy savings for microservice offloading in mobile cloud computing (MCC).

ANN-Based Intelligent Secure Routing Protocol in Vehicular Ad Hoc Networks (VANETs) Using Enhanced AODV.

A vehicular ad hoc network (VANET) is a sophisticated wireless communication infrastructure incorporating centralized and decentralized control mechanisms, orchestrating seamless data exchange among vehicles. This intricate communication system relies on the advanced capabilities of 5G connectivity, employing specialized topological arrangements to enhance data packet transmission. These vehicles communicate amongst themselves and establish connections with roadside units (RSUs). In the dynamic landscape of vehicular communication, disruptions, especially in scenarios involving high-speed vehicles, pose challenges. A notable concern is the emergence of black hole attacks, where a vehicle acts maliciously, obstructing the forwarding of data packets to subsequent vehicles, thereby compromising the secure dissemination of content within the VANET. We present an intelligent cluster-based routing protocol to mitigate these challenges in VANET routing. The system operates through two pivotal phases: first, utilizing an artificial neural network (ANN) model to detect malicious nodes, and second, establishing clusters via enhanced clustering algorithms with appointed cluster heads (CH) for each cluster. Subsequently, an optimal path for data transmission is predicted, aiming to minimize packet transmission delays. Our approach integrates a modified ad hoc on-demand distance vector (AODV) protocol for on-demand route discovery and optimal path selection, enhancing request and reply (RREQ and RREP) protocols. Evaluation of routing performance involves the BHT dataset, leveraging the ANN classifier to compute accuracy, precision, recall, F1 score, and loss. The NS-2.33 simulator facilitates the assessment of end-to-end delay, network throughput, and hop count during the path prediction phase. Remarkably, our methodology achieves 98.97% accuracy in detecting black hole attacks through the ANN classification model, outperforming existing techniques across various network routing parameters.

Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence.

Driving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enable effective detection of driver drowsiness, helping to prevent accidents and enhance driver performance. This research aims to address the crucial need for real-time and accurate drowsiness detection to mitigate the impact of fatigue-related accidents. Leveraging ultra-wideband radar data collected over five minutes, the dataset was segmented into one-minute chunks and transformed into grayscale images. Spatial features are retrieved from the images using a two-dimensional Convolutional Neural Network. Following that, these features were used to train and test multiple machine learning classifiers. The ensemble classifier RF-XGB-SVM, which combines Random Forest, XGBoost, and Support Vector Machine using a hard voting criterion, performed admirably with an accuracy of 96.6%. Additionally, the proposed approach was validated with a robust k-fold score of 97% and a standard deviation of 0.018, demonstrating significant results. The dataset is augmented using Generative Adversarial Networks, resulting in improved accuracies for all models. Among them, the RF-XGB-SVM model outperformed the rest with an accuracy score of 99.58%.

Towards Industrially Important Applications of Enhanced Organic Reactions by Microfluidic Systems.

This review presents a comprehensive evaluation for the manufacture of organic molecules via efficient microfluidic synthesis. Microfluidic systems provide considerably higher control over the growth, nucleation, and reaction conditions compared with traditional large-scale synthetic methods. Microfluidic synthesis has become a crucial technique for the quick, affordable, and efficient manufacture of organic and organometallic compounds with complicated characteristics and functions. Therefore, a unique, straightforward flow synthetic methodology can be developed to conduct organic syntheses and improve their efficiency.