Improving prediction of blood cancer using leukemia microarray gene data and Chi2 features with weighted convolutional neural network.

Blood cancer has emerged as a growing concern over the past decade, necessitating early diagnosis for timely and effective treatment. The present diagnostic method, which involves a battery of tests and medical experts, is costly and time-consuming. For this reason, it is crucial to establish an automated diagnostic system for accurate predictions. A particular field of focus in medical research is the use of machine learning and leukemia microarray gene data for blood cancer diagnosis. Even with a great deal of research, more improvements are needed to reach the appropriate levels of accuracy and efficacy. This work presents a supervised machine-learning algorithm for blood cancer prediction. This work makes use of the 22,283-gene leukemia microarray gene data. Chi-squared (Chi2) feature selection methods and the synthetic minority oversampling technique (SMOTE)-Tomek resampling is used to overcome issues with imbalanced and high-dimensional datasets. To balance the dataset for each target class, SMOTE-Tomek creates synthetic data, and Chi2 chooses the most important features to train the learning models from 22,283 genes. A novel weighted convolutional neural network (CNN) model is proposed for classification, utilizing the support of three separate CNN models. To determine the importance of the proposed approach, extensive experiments are carried out on the datasets, including a performance comparison with the most advanced techniques. Weighted CNN demonstrates superior performance over other models when coupled with SMOTE-Tomek and Chi2 techniques, achieving a remarkable 99.9% accuracy. Results from k-fold cross-validation further affirm the supremacy of the proposed model.

Translation and psychometric properties of the Arabic version of the ageism scale for dental students (ASDS-Ar): A multi-institutional validation.

BACKGROUND AND OBJECTIVE: Ageism represents an important barrier to high-quality healthcare for older adults. The present study sought to translate and validate the Arabic version of the Ageism Scale for Dental Students (ASDS-Arabic). MATERIALS AND METHODS: The 27-item ASDS tool was translated from English into Arabic following recommended cross-sectional forward and backward translation guidelines. The translated version was subjected to the content validity ratio (CVR) and sent to dental students in 21 institutes from 10 different Arab countries. Principal components analysis (PCA) was used to assess the dimensionality of the scale, and Cronbach's alpha was used to determine internal consistency reliability. The discriminant validity of the scale was assessed using the independent t-test. Confirmatory factor analysis (CFA) was also undertaken. RESULTS: Based on CVR, three items were removed. The 24-item Arabic version was completed by 3284 dental students. PCA and CFA retained 17 items in six components, explaining 50.3% of the total variance, with acceptable reliability, validity and discrimination. The first component "Adherence of older patients with dental treatment and instructions," included four items with a Cronbach α of 0.64 and scored 4.3 ± 0.8. The second component "Feasibility of the treatment plan," included three items with a Cronbach α of 0.66 and scored from 2.6 ± 1.2 to 2.9 ± 1.1. The third component "Cost of and responsibility for the dental treatment" included four items with a Cronbach α of 0.47 and scored 4.4 ± 0.8 to 4.5 ± 0.8. The fourth component "Medical history of older patients" included two items with a Cronbach α of 0.70 and scored 4.0 ± 1.0 to 4.1 ± 1.0. The fifth Component "Feeling towards older patients" included two items with a Cronbach α of 0.672 and scored 2.6 ± 1.2 to 2.0 ± 1.4. The sixth Component "Confidence and experience in treating older patients" included two items with a Cronbach α of 0.33 and scored 4.4 ± 1 to 4.6 ± 1. CONCLUSION: This preliminary validation of the ASDS-Ar resulted in a new 17-item scale with six components with acceptable validity, reliability and discrimination.

Specialized nutritious foods and behavior change communication interventions during the first 1,000 days of life to prevent stunting: A quasi-experimental study in Afghanistan.

BACKGROUND: Considerable evidence supports the effectiveness of nutritional supplementation with or without nutrition education in preventing stunting in developing countries, but evidence from Afghanistan is scarce. OBJECTIVE: This project aimed to assess the effectiveness of specialized nutritious food (SNF), social and behavior change communication (SBCC) intervention to prevent stunting among children under 2 years during the first 1,000 days of life in Badakhshan, Afghanistan. METHODS: We used a community-based quasi-experimental pre-post study design with a control group. Pregnant and lactating women received a monthly ration of 7.5 kg of Super Cereal (250g/day) during pregnancy and the first 6 months of breastfeeding. Children aged 6-23 months received 30 sachets of medium-quantity lipid-based nutrient supplement (50g/sachet/day) monthly. We compared pre- and post-intervention assessments of the intervention and control groups to isolate the effect of the intervention on key study outcomes at the endline by difference-in-differences (DID) estimates. RESULTS: A total of 2,928 and 3,205 households were surveyed at baseline and endline. DID estimates adjusted for child, maternal, and household characteristics indicated a significant reduction in stunting (DID: -5% (95% CI: -9.9, -0.2) and underweight (DID: -4.6% (95% CI: -8.6, -0.5) among children <2 years of age. However, DID estimates for wasting among children in the intervention and control groups were not significantly different (DID: -1.7 (95% CI: -5.1,1.6). Furthermore, exposure to the SBCC messages was associated with improvements in the early initiation of breastfeeding (DID: 19.6% (95% CI: 15.6,23.6), exclusive breastfeeding under 6-months (DID: 11.0% (95% CI: 2.3,19.7), minimum meal frequency (MMF) (DID: 23% (95% CI: 17.7,28.2), minimum acceptable diet (MAD) (DID: 13% (95% CI: 9.8,16.3). CONCLUSIONS: The provision of SNF in combination with SBCC during the first 1,000 days of life was associated with reduction in stunting and underweight and improvements in IYCF practices among children under 2 years of age. CLINICAL TRIAL REGISTRY NUMBER: Clinicaltrials.gov, NCT04581993.

Materials Containing Single-, Di-, Tri-, and Multi-Metal Atoms Bonded to C, N, S, P, B, and O Species as Advanced Catalysts for Energy, Sensor, and Biomedical Applications.

Modifying the coordination or local environments of single-, di-, tri-, and multi-metal atom (SMA/DMA/TMA/MMA)-based materials is one of the best strategies for increasing the catalytic activities, selectivity, and long-term durability of these materials. Advanced sheet materials supported by metal atom-based materials have become a critical topic in the fields of renewable energy conversion systems, storage devices, sensors, and biomedicine owing to the maximum atom utilization efficiency, precisely located metal centers, specific electron configurations, unique reactivity, and precise chemical tunability. Several sheet materials offer excellent support for metal atom-based materials and are attractive for applications in energy, sensors, and medical research, such as in oxygen reduction, oxygen production, hydrogen generation, fuel production, selective chemical detection, and enzymatic reactions. The strong metal-metal and metal-carbon with metal-heteroatom (i.e., N, S, P, B, and O) bonds stabilize and optimize the electronic structures of the metal atoms due to strong interfacial interactions, yielding excellent catalytic activities. These materials provide excellent models for understanding the fundamental problems with multistep chemical reactions. This review summarizes the substrate structure-activity relationship of metal atom-based materials with different active sites based on experimental and theoretical data. Additionally, the new synthesis procedures, physicochemical characterizations, and energy and biomedical applications are discussed. Finally, the remaining challenges in developing efficient SMA/DMA/TMA/MMA-based materials are presented.

The Effectiveness of Nutritional Interventions Implemented through Lady Health Workers on the Reduction of Stunting in Children under 5 in Pakistan: The Difference-in-Difference Analysis.

In Pakistan, the 2018 National Nutrition Survey reported that 40% of children under five years old were stunted. This study assessed the effectiveness of nutritional supplementation in reducing stunting among children under five years old in two rural districts in Sindh, Pakistan. This was a mixed-method quasi-experimental study comprising intervention and control populations, with 3397 and 3277 children under five years old participating in the baseline and end-line surveys, respectively. The study areas were similar in terms of demographic and economic circumstances. In the intervention group, pregnant and lactating women (first six months post-partum) received wheat soy blend, children 6-23 months old received Wawamum (lipid-based supplement), and children 24-59 months old received micronutrient powders, all through lady health workers. This was underpinned by nutrition behaviour change communication for appropriate complementary feeding practices and hygiene promotion targeted at primary caregivers. The control group received no intervention. The impact was assessed using the difference-in-difference analysis with kernel propensity score matching to adjust the differences among the control and intervention populations. The overall DID analysis indicated that the intervention did not significantly reduce the prevalence of stunting (under 5 years) [DID = -5.1, p = 0.079]. The adjusted DID indicated a significant decrease of 13% [DID = -13.0, p = 0.001] in the number of stunted children 24-59 months of age at the endline survey. A significant reduction in underweight among children 24-59 months old was also observed (DID = -9.4%, p = 0.014). In conclusion, this evidence further establishes that nutrient uptake through an intervention for a short duration cannot effectively reduce stunting. It requires continuous nutritional supplementation for mothers during the pregnancy and an initial six months of lactation and then nutritional supplementation for children 6-59 months of age underpinned by effective behaviour change communication targeting mothers and other caregivers for improving complementary feeding practices and hygiene promotion.

Genetic Analysis of Cotton Fiber Traits in Gossypium Hybrid Lines.

Cotton plays a crucial role in the progress of the textile industry and the betterment of human life by providing natural fibers. In our study, we explored the genetic determinants of cotton architecture and fiber yield and quality by crossbreeding Gossypium hirsutum and Gossypium barbadense, creating a recombinant inbred line (RIL) population. Utilizing SNP markers, we constructed an extensive genetic map encompassing 7,730 markers over 2,784.2 cM. We appraised two architectural and seven fiber traits within six environments, identifying 58 QTLs, of which 49 demonstrated stability across these environments. These encompassed QTLs for traits such as lint percentage (LP), boll weight (BW), fiber strength (STRENGTH), seed index (SI), and micronaire (MIC), primarily located on chromosomes chr-A07, chr-D06, and chr-D07. Notably, chr-D07 houses a QTL region affecting SI, corroborated by multiple studies. Within this region, the genes BZIP043 and SEP2 were identified as pivotal, with SEP2 particularly showing augmented expression in developing ovules. These discoveries contribute significantly to marker-assisted selection, potentially elevating both the yield and quality of cotton fiber production. These findings provide valuable insights into marker-assisted breeding strategies, offering crucial information to enhance fiber yield and quality in cotton production.

Assessment of Digital Dentistry Knowledge and Practices Among Dental Students at King Faisal University, Saudi Arabia.

BACKGROUND Digital dental (DD) technologies need to be developed for dental use because of the prominent position that these technologies have recently acquired. This 21-item online questionnaire-based study aimed to assess the understanding of DD methods in 120 undergraduate dental students at King Faisal University, Saudi Arabia (SA). MATERIAL AND METHODS Electronic surveys were sent to 123 dental students at different study phases (basic, preclinical, and clinical). Dental students were requested to answer the questionnaires in accordance with their knowledge, observations, particular experiences, and DD practice. Data were analyzed using descriptive statistics, which involved numerical values and ratios. Then, the associations among study level, knowledge, practice, and study phases were analyzed using chi-square and Fisher's exact tests. RESULTS Completed questionnaires were returned by 120 students. The chi-square test showed significant differences in relation to questions "Do you have any previous knowledge of DD?", "The field that uses DD the most is…", "Does DD provide more precise results than conventional dentistry?", and "Do you know about CAD/CAM?", with P values of 0.006, 0.000, 0.018, and 0.002, respectively. Students at clinical phase exhibited significantly higher levels of knowledge than those at the preclinical phase (P<0.01). With regard to DD practice, 73.3% of students expressed a negative viewpoint, 82.5% stated that DD is essential for the future, and half said that practicing DD will result in improvements in patient satisfaction, time consumed, and level of predictability. CONCLUSIONS Students at basic, preclinical, and clinical phases had good knowledge on DD and were motivated to practice it in future in their workplaces.

Characterization of biotinylated human ACE2 and SARS-CoV-2 Omicron BA.4/5 spike protein reference materials.

Accurate diagnostic and serology assays are required for the continued management of the COVID-19 pandemic yet spike protein mutations and intellectual property concerns with antigens and antibodies used in various test kits render comparability assessments difficult. As the use of common, well-characterized reagents can help address this lack of standardization, the National Research Council Canada has produced two protein reference materials (RMs) for use in SARS-CoV-2 serology assays: biotinylated human angiotensin-converting enzyme 2 RM, ACE2-1, and SARS-CoV-2 Omicron BA.4/5 spike protein RM, OMIC-1. Reference values were assigned through a combination of amino acid analysis via isotope dilution liquid chromatography tandem mass spectrometry following acid hydrolysis, and ultraviolet-visible (UV-Vis) spectrophotometry at 280 nm. Vial-to-vial homogeneity was established using UV-Vis measurements, and protein oligomeric status, monitored by size exclusion liquid chromatography (LC-SEC), was used to evaluate transportation, storage, and freeze-thaw stabilities. The molar protein concentration in ACE2-1 was 25.3 ± 1.7 µmol L-1 (k = 2, 95% CI) and consisted almost exclusively (98%) of monomeric ACE2, while OMIC-1 contained 5.4 ± 0.5 µmol L-1 (k = 2) spike protein in a mostly (82%) trimeric form. Glycoprotein molar mass determination by LC-SEC with multi-angle light scattering detection facilitated calculation of corresponding mass concentrations. To confirm protein functionality, the binding of OMIC-1 to immobilized ACE2-1 was investigated with surface plasmon resonance and the resulting dissociation constant, KD ~ 4.4 nM, was consistent with literature values.

Multistage temporal transcriptomic atlas unveils major contributor to reproductive phase in upland cotton.

Flowering is a major developmental transition in plants, but asynchronous flowering hinders the utilization of wild cotton relatives in breeding programs. We performed comparative transcriptomic profiling of early- and late-flowering Gossypium hirsutum genotypes to elucidate genetic factors influencing reproductive timing. Shoot apices were sampled from the photoperiod-sensitive landrace G. hirsutum purpurascens (GhP) and early-maturing variety ZhongMianSuo (ZMS) at five time points following the emergence of sympodial nodes. RNA-sequencing revealed extensive transcriptional differences during floral transition. Numerous flowering-associated genes exhibited genotype-specific expression, including FLOWERING LOCUS T (FT) homologs upregulated in ZMS. FT-interacting factors like SOC1 and CO-like also showed higher expression in ZMS, implicating florigen pathways in early flowering. Additionally, circadian clock and light signalling components were misregulated between varieties, suggesting altered photoperiod responses in GhP. Weighted co-expression network analysis specifically linked a module enriched for circadian-related genes to GhP's late flowering. Through an integrated transcriptome analysis, we defined a regulatory landscape of reproductive phase change in cotton. Differentially expressed genes related to photoperiod, circadian clock, and light signalling likely contribute to delayed flowering in wild cottons. Characterization of upstream flowering regulators will enable modifying photoperiod sensitivity and expand germplasm use for cotton improvement. This study provides candidate targets for elucidating interactive mechanisms that control cotton flowering time across diverse genotypes.

Integration of transcriptomics, metabolomics, and hormone analysis revealed the formation of lesion spots inhibited by GA and CTK was related to cell death and disease resistance in bread wheat (Triticum aestivum L.).

BACKGROUND: Wheat is one of the important grain crops in the world. The formation of lesion spots related to cell death is involved in disease resistance, whereas the regulatory pathway of lesion spot production and resistance mechanism to pathogens in wheat is largely unknown. RESULTS: In this study, a pair of NILs (NIL-Lm5W and NIL-Lm5M) was constructed from the BC1F4 population by the wheat lesion mimic mutant MC21 and its wild genotype Chuannong 16. The formation of lesion spots in NIL-Lm5M significantly increased its resistance to stripe rust, and NIL-Lm5M showed superiour agronomic traits than NIL-Lm5W under stripe rust infection.Whereafter, the NILs were subjected to transcriptomic (stage N: no spots; stage S, only a few spots; and stage M, numerous spots), metabolomic (stage N and S), and hormone analysis (stage S), with samples taken from normal plants in the field. Transcriptomic analysis showed that the differentially expressed genes were enriched in plant-pathogen interaction, and defense-related genes were significantly upregulated following the formation of lesion spots. Metabolomic analysis showed that the differentially accumulated metabolites were enriched in energy metabolism, including amino acid metabolism, carbohydrate metabolism, and lipid metabolism. Correlation network diagrams of transcriptomic and metabolomic showed that they were both enriched in energy metabolism. Additionally, the contents of gibberellin A7, cis-Zeatin, and abscisic acid were decreased in leaves upon lesion spot formation, whereas the lesion spots in NIL-Lm5M leaves were restrained by spaying GA and cytokinin (CTK, trans-zeatin) in the field. CONCLUSION: The formation of lesion spots can result in cell death and enhance strip rust resistance by protein degradation pathway and defense-related genes overexpression in wheat. Besides, the formation of lesion spots was significantly affected by GA and CTK. Altogether, these results may contribute to the understanding of lesion spot formation in wheat and laid a foundation for regulating the resistance mechanism to stripe rust.

Effect of pharmaceutical promotion and incentives offered by pharmaceutical companies on the prescribing pattern of medical students: a cross-sectional study from a developing nation Pakistan.

Background: Pharmaceutical companies continuously pursue healthcare professionals, starting from the medical college level, which can ultimately lead to irrational prescribing of drugs and antibiotics. Therefore, our main aim was to evaluate the opinions and attitudes of medical students toward pharmaceutical promotion. Methods: This study utilized a cross-sectional online survey that applied the snowball sampling technique. Data were collected from three public and three private sector medical colleges in Punjab, Pakistan using snowball sampling. A modified version of a pre-structured questionnaire was used to collect data between October 2020 and January 2021. Medical students from the third year onward were captivated. The tool was made available on Google Forms and students could access it by clicking the link shared. The effect of promotion on prescribing pattern and future prescribing of antibiotics were measured. Descriptive statistics, chi-square, and t-test were used to analyze the data. Results: A total of 1,301 students filled out the survey, but only 1,227 responses were acceptable. The average age was found to be 23.4 ± 1.59 years. Slightly more than half of the respondents were male participants (57.7%), and a significant proportion (84.1%) reported being aware of pharmaceutical promotion. A smaller number (27.7%) felt that physicians who meet medical representatives more frequently tend to prescribe more antibiotics and 46.3% indicated they would be willing to prescribe antibiotics under the promotional influence. Medical students who were male, in senior college years, attended government institutions, and had lower parental income showed significantly higher perception and attitude scores (p < 0.05) which, in turn, may show their inclination to promotional activities. Many students agreed with the view that pharmaceutical promotion (PP) activities may alter prescribing practices and also believed that they contribute to the increased irrational prescribing of drugs and antibiotics. Conclusion: The study revealed that only a small number of students are willing to engage in promotional activities and accept rewards, which influences their choice toward selection of drugs and antibiotics. This study highlighted the necessity of giving proper educational instructions regarding the promotion of drugs to medical students. This study also focused on the educational prerequisites of the students.

Hydropneumopericardium Due to a Traumatic Esophageal-Pericardial Fistula.

Esophago-pericardial fistula is a rare, life-threatening condition, usually arising as a complication of benign esophageal disorders or iatrogenic causes. Prompt diagnosis via multimodality imaging is crucial, with computed tomography being the most sensitive. Management varies based on severity, with a growing trend toward early endoscopic interventions, which result in improved outcomes.

Attention 3D central difference convolutional dense network for hyperspectral image classification.

Hyperspectral Images (HSI) classification is a challenging task due to a large number of spatial-spectral bands of images with high inter-similarity, extra variability classes, and complex region relationships, including overlapping and nested regions. Classification becomes a complex problem in remote sensing images like HSIs. Convolutional Neural Networks (CNNs) have gained popularity in addressing this challenge by focusing on HSI data classification. However, the performance of 2D-CNN methods heavily relies on spatial information, while 3D-CNN methods offer an alternative approach by considering both spectral and spatial information. Nonetheless, the computational complexity of 3D-CNN methods increases significantly due to the large capacity size and spectral dimensions. These methods also face difficulties in manipulating information from local intrinsic detailed patterns of feature maps and low-rank frequency feature tuning. To overcome these challenges and improve HSI classification performance, we propose an innovative approach called the Attention 3D Central Difference Convolutional Dense Network (3D-CDC Attention DenseNet). Our 3D-CDC method leverages the manipulation of local intrinsic detailed patterns in the spatial-spectral features maps, utilizing pixel-wise concatenation and spatial attention mechanism within a dense strategy to incorporate low-rank frequency features and guide the feature tuning. Experimental results on benchmark datasets such as Pavia University, Houston 2018, and Indian Pines demonstrate the superiority of our method compared to other HSI classification methods, including state-of-the-art techniques. The proposed method achieved 97.93% overall accuracy on the Houston-2018, 99.89% on Pavia University, and 99.38% on the Indian Pines dataset with the 25 × 25 window size.

Improving prediction of maternal health risks using PCA features and TreeNet model.

Maternal healthcare is a critical aspect of public health that focuses on the well-being of pregnant women before, during, and after childbirth. It encompasses a range of services aimed at ensuring the optimal health of both the mother and the developing fetus. During pregnancy and in the postpartum period, the mother's health is susceptible to several complications and risks, and timely detection of such risks can play a vital role in women's safety. This study proposes an approach to predict risks associated with maternal health. The first step of the approach involves utilizing principal component analysis (PCA) to extract significant features from the dataset. Following that, this study employs a stacked ensemble voting classifier which combines one machine learning and one deep learning model to achieve high performance. The performance of the proposed approach is compared to six machine learning algorithms and one deep learning algorithm. Two scenarios are considered for the experiments: one utilizing all features and the other using PCA features. By utilizing PCA-based features, the proposed model achieves an accuracy of 98.25%, precision of 99.17%, recall of 99.16%, and an F1 score of 99.16%. The effectiveness of the proposed model is further confirmed by comparing it to existing state of-the-art approaches.

Comparative Effect of Seed Coating and Biopriming of Bacillus aryabhattai Z-48 on Seedling Growth, Growth Promotion, and Suppression of Fusarium Wilt Disease of Tomato Plants.

Beneficial plant microbes can enhance the growth and quality of field crops. However, the benefits of microbes using cheap and efficient inoculation methods are still uncommon. Seed coating with biocontrol agents can reduce the amount of inocula along with having the potential for large-scale application. Hence, in this research work, the comparative potential of tomato seed coating and biopriming with Bacillus aryabhattai Z-48, harboring multiple plant-beneficial traits, to suppress Fusarium wilt disease along with its beneficial effect on seedling and plant growth promotion was analyzed. Among two bacterial strains, B. aryabhattai Z-48 was able to antagonize the mycelial growth of Fusarium oxysporum f.sp. lycopersici in vitro and its application as a seed coating superiorly benefited seedling traits like the germination percentage, vigor index, and seedling growth index along with a reduced germination time. The seed coating with B. aryabhattai Z-48 resulted in significant increases in the shoot length, root length, dry biomass, and total chlorophyll contents when compared with the bioprimed seeds with the same bacterial strain and non-inoculated control plants. The seed coating with B. aryabhattai Z-48 significantly reduced the disease index (>60%) compared with the pathogen control during pot trials. Additionally, the seed coating with B. aryabhattai Z-48 resulted in a significantly higher production of total phenolics, peroxidase, polyphenol oxidase, and phenylalanine ammonia lyase enzyme in tomato plants. The GC/MS-based non-targeted metabolic profiling indicated that the seed coating with B. aryabhattai Z-48 could cause large-scale metabolite perturbations in sugars, sugar alcohols, amino acids, and organic acids to increase the fitness of tomato plants against biotic stress. Our study indicates that a tomato seed coating with B. aryabhattai Z-48 can improve tomato growth and suppress Fusarium wilt disease effectively under conventional agricultural systems.

Exploring the path to polio eradication: insights from consecutive seroprevalence surveys among Pakistani children.

Introduction: After trivalent oral poliovirus vaccine (tOPV) cessation, Pakistan has maintained immunity to type 2 poliovirus by administering inactivated polio vaccine (IPV) in routine immunization, alongside monovalent OPV type 2 (mOPV2) and IPV in supplementary immunization activities (SIAs). This study assesses the change in poliovirus type 2 immunity after tOPV withdrawal and due to SIAs with mOPV2 and IPV among children aged 6-11 months. Methods: Three cross-sectional sequential serological surveys were conducted in 12 polio high-risk areas of Pakistan. 25 clusters from each geographical stratum were selected utilizing probability proportional to size. Results: Seroprevalence of type 2 poliovirus was 49%, with significant variation observed among surveyed areas; <30% in Pishin, >80% in Killa Abdullah, Mardan & Swabi, and Rawalpindi. SIAs with IPV improved immunity from 38 to 57% in Karachi and 60 to 88% in Khyber. SIAs with IPV following mOPV2 improved immunity from 62 to 65% in Killa Abdullah, and combined mOPV2 and IPV SIAs in Pishin improved immunity from 28 to 89%. Results also reflected that immunity rates for serotypes 1 and 3 were consistently above 90% during all three phases and across all geographical areas. Conclusion: The study findings highlight the importance of implementing effective vaccination strategies to prevent the re-emergence of poliovirus. Moreover, the results provide crucial information for policymakers working toward achieving global polio eradication.

Endophytic Fungi-Mediated Defense Signaling in Maize: Unraveling the Role of WRKY36 in Regulating Immunity against Spodoptera frugiperda.

Seed priming with beneficial endophytic fungi is an emerging sustainable strategy for enhancing plant resistance against insect pests. This study examined the effects of Beauvaria bassiana Bb20091317 and Metarhizium rileyi MrCDTLJ1 fungal colonization on maize growth, defence signalling, benzoxazinoid levels and gene expression. The colonization did not adversely affect plant growth but reduced larval weights of Spodoptera frugiperda. Maize leaves treated with M. rileyi exhibited higher levels of jasmonic acid, jasmonoyl-Isoleucine, salicylic acid, and indole acetic acid compared to control. B. bassiana and M. rileyi accelerated phytohormone increase upon S. frugiperda herbivory. Gene expression analysis revealed modulation of benzoxazinoid biosynthesis genes. We further elucidated the immune regulatory role of the transcription factor zmWRKY36 using virus-induced gene silencing (VIGS) in maize. zmWRKY36 positively regulates maize immunity against S. frugiperda, likely by interacting with defense-related proteins. Transient overexpression of zmWRKY36 in tobacco-induced cell death, while silencing in maize reduced chitin-triggered reactive oxygen species burst, confirming its immune function. Overall, B. bassiana and M. rileyi successfully colonized maize, impacting larval growth, defense signalling, and zmWRKY36-mediated resistance. This sheds light on maize-endophyte-insect interactions for sustainable plant protection.

Quantification of quercetin from red onion (Allium cepa L.) powder via high-performance liquid chromatography-ultraviolet (HPLC-UV) and its effect on hyperuricemia in male healthy Wistar albino rats.

Onions (Allium cepa L.) contain various flavonols, including quercetin, kaempferol, anthocyanin, luteolin, and myricetin. Quercetin in onions is considered the primary bioactive component. To assess the impact of quercetin on hyperuricemia in healthy Wistar albino rats, this study used high-performance liquid chromatography with ultraviolet (HPLC-UV) to identify and measure quercetin in onion powder. Twenty-four 160 ± 10 g, six wistar albino male rats in each group were kept: NC (control sample, no onion powder), OT1, OT2, and OT3, which contained 11.13, 14.84, and 18.61 g/100 g onion powder, respectively. The treatment lasted 28 days, during which the last 7 days were for urine, feces, and blood collection. The results showed a trend of decreasing levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase, total bilirubin, total cholesterol, and low-density lipoprotein in rats fed OT1, OT2, and OT3 diets. Improvements were observed in feed, water, and nutrient intake, feed conversion ratio, feed efficiency ratio, nutrient digestibility, nitrogen balance, body weight, blood urea nitrogen, creatinine, and uric acid levels (p ≤ .05). In contrast, high-density lipoprotein, triglycerides, serum total protein, neutrophils, and lymphocytes did not change (p ≥ .05). White blood cells, red blood cell count, platelet count, hemoglobin, and monocytes showed an upward trend. Based on our calculations, we determined the optimal human dosage from the most effective amount of onion powder. By taking into account the ratio of human-to-rat surface area, we estimate that the equivalent human dose of onion is 181.04 grams with 204 mg of quercetin. Additionally, when factoring in the dry matter content, the recommended dose of onion is 29.19 grams with 220 mg of quercetin.

White blood cells classification using multi-fold pre-processing and optimized CNN model.

White blood cells (WBCs) play a vital role in immune responses against infections and foreign agents. Different WBC types exist, and anomalies within them can indicate diseases like leukemia. Previous research suffers from limited accuracy and inflated performance due to the usage of less important features. Moreover, these studies often focus on fewer WBC types, exaggerating accuracy. This study addresses the crucial task of classifying WBC types using microscopic images. This study introduces a novel approach using extensive pre-processing with data augmentation techniques to produce a more significant feature set to achieve more promising results. The study conducts experiments employing both conventional deep learning and transfer learning models, comparing performance with state-of-the-art machine and deep learning models. Results reveal that a pre-processed feature set and convolutional neural network classifier achieves a significantly better accuracy of 0.99. The proposed method demonstrates superior accuracy and computational efficiency compared to existing state-of-the-art works.

Noval soliton solution, sensitivity and stability analysis to the fractional gKdV-ZK equation.

This work examines the fractional generalized Korteweg-de-Vries-Zakharov-Kuznetsov equation (gKdV-ZKe) by utilizing three well-known analytical methods, the modified [Formula: see text]-expansion method, [Formula: see text]-expansion method and the Kudryashov method. The gKdV-ZK equation is a nonlinear model describing the influence of magnetic field on weak ion-acoustic waves in plasma made up of cool and hot electrons. The kink, singular, anti-kink, periodic, and bright soliton solutions are observed. The effect of the fractional parameter on wave shapes have been analyzed by displaying various graphs for fractional-order values of [Formula: see text]. In addition, we utilize the Hamiltonian property to observe the stability of the attained solution and Galilean transformation for sensitivity analysis. The suggested methods can also be utilized to evaluate the nonlinear models that are being developed in a variety of scientific and technological fields, such as plasma physics. Findings show the effectiveness simplicity, and generalizability of the chosen computational approach, even when applied to complex models.