Harmful Diseases Research Articles

Research progress on V delta 1+ T cells and their effect on pathogen infection.

The ongoing high occurrence of harmful infectious diseases significantly threatens human health. Existing methods used to control such diseases primarily involve targeting the pathogens, usually neglecting the vital role of host factors in disease advancement. Gamma delta (γδ) T cells act as a bridge between innate and adaptive immunity, playing a crucial role in combating pathogen invasion. Among these γδT cell subsets, which are categorized based on T cell receptor delta variable expression patterns, V delta (δ) 1+ T cells possess unique recognition abilities and regulatory characteristics and actively engage in various immune responses. The differentiation, development, and immune reactivity of Vδ1+ T cells are closely associated with the initial and progressive stages of infectious diseases. This article provides an overview of the classification, distribution, differentiation, and development of Vδ1+ T cells and their mechanisms in combating pathogenic infections, offering new insights for disease diagnosis and treatment.

Resistance of barley cultivars and accessions to pathotypes of the spot blotch causative agent

Background. The spot blotch disease caused by the hemibiotrophic fungus Bipolaris sorokiniana has become a serious problem for barley. Utilization of resistant or tolerant barley cultivars ensures sustainable diversity conservation and environmentfriendly crop production. Thus, supplying barley breeders with sources of resistance to harmful diseases is an urgent task. Materials and methods. A set of 100 barley accessions, earlier selected for different levels of resistance to B. sorokiniana, served as the material for this study. Eleven isolates of B. sorokiniana of various geographic origin, belonging to 4 pathotypes, were used for testing. The resistance of barley seedlings was assessed under controlled laboratory conditions, and that of adult plants under artificial infection pressure in the field. Responses to B. sorokiniana were scored using the 0–9 rating scale.Results and conclusions. Barley genotypes with race-specific resistance to the spot blotch causative agent were identified. The percentage of barley genotypes resistant to five isolates of B. sorokiniana pathotype 1 averaged 24.2%; two isolates of pathotype 3, 29.5%; three isolates of pathotype 7, 18.3%; and one isolate of pathotype 0, 37%. Barley accessions manifesting resistance in their seedlings, but susceptible in the phase of milk-wax ripeness, and vice versa, with seedling susceptibility and adult resistance, were identified. Six (6) barley genotypes showed seedling and adult resistance to pathotype 1, nine (9) to pathotype 3, and two (2) to pathotype 7. No barley accessions resistant to all isolates of the pathogen were found.

Multifractal Analysis in Age-Based Classification for COVID-19 Patients’ CT-Scan Images with Different Noise Levels

Recently, many number of people various countries contracted the COVID-19 (C-19) disease. The identification of this harmful disease and other pneumonia diseases is an important process in the medical world. CT-Scan is mainly prescribed to predict the severity of lung diseases affected by C-19 and other pneumonia diseases. Generally, a CT-Scan image is represented as a grayscale image (GI). Biomedical-oriented GIs are more complex and they are too difficult to recognize the status of lung diseases directly from the experimental images. To address this type of medical problem, a multifractal approach can be applied to analyze and illustrate the GIs in detail. Therefore, the multifractal dimensional analysis is used to diagnose and explore the vehemence of the contamination levels in the lungs. In this study, the complexity of CT-Scan images of C-19 patients is analyzed in order to perform a comparison in terms of age and noise levels. It was also discovered that the intricate of CT-Scan images is considerably varied for patients aged 50 and above when compared to younger subjects. This comparative study indicates that the deadly virus affects elderly persons compared to youngsters. The proposed age-based classification is supported by image processing techniques, qualitative measures, and statistical tools. The obtained results are demonstrated graphically by Generalized Fractal Dimensions (GFD) spectrum, 3D visualization, ANOVA table, and box plots to expose the rate of discrimination of complexity in CT-Scan lung images.

Multi-functional PGPR Serratia liquefaciens confers enhanced resistance to lead stress and bacterial blight in soybean (Glycine max L.)

Lead toxicity and bacterial blight disease caused by Pseudomonas savastanoi pv. glycinea have destructive impacts on soybean growth and productivity. Plant growth-promoting rhizobacteria have been used as an eco-friendly approach for augmenting crop growth and stress resistance. The current study investigated the efficacy of Serratia liquefaciens ZM6 strain in enhancing soybean resistance to lead (Pb) stress and bacterial blight. Two pot experiments were performed. In the first pot experiment, soybean plants were inoculated with S. liquefaciens ZM6 and grown under variable Pb stress levels (0, 200 and 400µM of Pb(NO3)2). In the second experiment, S. liquefaciens-inoculated soybean plants were infected with P. savastanoi pv. glycinea, and disease severity was assessed two weeks post infection. The results revealed that S. liquefaciens strain resisted Pb stress up to 400µM Pb(NO3)2 and exhibited the highest levels of solubilized phosphate, solubilized zinc, siderophore, indole acetic acid, exopolysaccharide, trehalose and antioxidant enzymes at 400µM Pb compared to the other treatments. Moreover, Pb stress (200 and 400µM) significantly decreased the growth, yield, nutrient uptake, gas exchange, and contents of chlorophyll, soluble proteins, sugars, and phenolics of soybean plants. Pb stress also induced the levels of proline, glycine betaine, Pb, oxidative stress markers, antioxidant enzymes, ascorbate, glutathione and expression of stress-responsive genes (CAT, APX, POD, Fe-SOD, CHS7, CHI1A, PAL, IFS2, P5CS and WRKY54) in soybean plants. On the other hand, S. liquefaciens application markedly boosted the growth, yield and levels of nutrients, gas-exchange, chlorophyll, osmolytes, antioxidant enzymes and expression of stress-tolerant genes of Pb-stressed soybean plants. The bacterial inoculation significantly diminished oxidative stress indicators and Pb content in stressed plants. Inoculation of soybean plants with S. liquefaciens also caused significant reductions in blight disease symptoms in P. savastanoi pv. glycinea-infected plants, indicating the efficiency of this strain in controlling harmful blight disease. Overall, this study demonstrated S. liquefaciens ZM6 effectiveness in enhancing soybean resistance to Pb stress and bacterial blight.

Identification of Potent CHK2 Inhibitors‐Modulators for Therapeutic Application in Cancer: A Machine Learning Integrated Fragment‐Based Drug Design Approach

AbstractThe CHK2 protein regulates the cell division cycle and responds to DNA damage. Additionally, it facilitates the repair of DNA damage and maintains the integrity of its biological processes. Dysregulation of the CHK2 protein is associated with a predisposition to harmful diseases. The current research protocol was designed to identify novel hit molecules as CHK2 inhibitors and disrupt the normal biological function of the CHK2 protein via a fragment‐based drug discovery approach. The protocol involved generating fragments using the MacFrag tool, followed by a chemical similarity search utilizing RDKit to identify fragment molecules analogous to previously established CHK2 inhibitor scaffolds. The bioactive molecules were constructed using the Fragmenstein tool, followed by molecular docking simulations to investigate their binding affinity. In addition, pharmacokinetic properties were analyzed, and a molecular dynamics simulation study was conducted to assess the stability of selected compounds with CHK2 protein. Finally, five novel compounds were identified as excellent CHK2 inhibitors through the FBDD and show good binding interactions at active sites of CHK2 with beneficial ADMET properties. This research work presents novel CHK2 inhibitor molecules that have the potential to be utilized in drug discovery, serving as key leads for future advancements in healthcare industries and sectors.

Air Quality Prediction using Ensemble Classifiers and Single Decision Tree

Air pollution is a major concern nowadays that needs immediate action. Various acts have already been initiated by the government in controlling it. The harmful gases present in the air are Nitrogen dioxide, Sulphur dioxide, Ozone, and Carbon monoxide that is causing air pollution and are becoming the major cause of harmful diseases. It does not affect human beings only but the entire environment. According to World Health Organization, air pollution is killing seven million people around the world. Planting trees and avoiding using plastics is the possible solution to control air pollution. The air quality index is the measure through which we categorize the air pollution of various cities. In this paper, we will discuss the bagging and boosting method, the extra trees method of machine learning in predicting air quality index, and its comparison with Decision trees. The dataset is collected from the Open Weather Application Program Interface. In this, the prediction of the Air Quality Index is done based on previous data. Time i.e., hourly prediction and space series prediction are done on the dataset. After implementing each algorithm confusion matrix is obtained and from this precision and recall are calculated for each category of the Air quality index ranging from one to five with one being good and five being very unhealthy. It has been observed that Gradient Boosting achieves the highest accuracy with 98.89%.

Genetic diversity of naked barley accessions from the VIR collection for resistance to powdery mildew in the North-West Region of the Russian Federation

BACKGROUND: Barley is an important grain crop characterized by adaptability to various growing conditions. In recent years close attention has been paid to groups of naked barley which compared to covered barley is more susceptible to the influence of pathogens, that decreases the yield and quality of grain. Powdery mildew is the most harmful diseases of barley (caused by the biotrophic fungus Blumeria graminis (DC.) Golovin ex Speer f. sp. hordei Marchal). The search for new promising sources of resistance to powdery mildew is necessary for barley breeding. AIM: The aim is studying the powdery mildew resistance of naked spring barley accessions from the world collection of VIR and identifying promising sources for economically valuable traits. MATERIALS AND METHODS: In field and laboratory conditions 271 of naked barley accessions of different ecological and geographical origin were studied for powdery mildew resistance and other economically valuable traits (lodging resistance, duration of the vegetative period, yield). The pathogen inoculum for laboratory work was represented by the north-western population of the pathogen. The resistance of barley samples was assessed in the field using the VIR point scale, in the laboratory using the E.B. Mains, S.M. Dietz point scale. The highly effective to powdery mildew resistance allele mlo11 was identified using PCR. RESULTS: The diversity of barley of different origins in resistance to powdery mildew is shown. 16 samples mainly from Europe, local forms from Ethiopia, Japan and India, were found to be resistant in field condition. According to the results of the assessment at the juvenile stage, 1 highly resistant sample k-31058 and 5 moderately resistant (k-20923, k-25801, k-27165, k-29911, k-30231) were identified. The naked forms k-20923 from Germany and k-29911 from Poland were resistant at all stages of plant development. The mlo11 allele was detected in the Arabische variety (k-20923) and heterogeneous pathogen resistance accessions k-20921, k-25793, k-27080, k-29440, k-29820. CONCLUSIONS: As a result of the work the sources of resistance to powdery mildew with a complex of economically valuable traits were identified, which can be involve in the breeding.

Guanidine Derivatives Leverage the Antibacterial Performance of Bio-Based Polyamide PA56 Fibres

Bacterial damage has significantly impacted humanity, prompting the control of harmful microorganisms and infectious diseases. In this study, antibacterial bio-based PA56 fibres were prepared with high-speed spinning using ethylene-methyl acrylate-glycidyl methacrylate terpolymer (EMA) as the compatibiliser and polypentamethylene guanidine sulphate (PPGS) as the antibacterial agent. The effects of PPGS content on the properties of PA56 draw-textured yarns (DTYs) were investigated. The compatibility between PPGS and PA greatly improved with EMA incorporation. Compared with PA56 fibres, the elongation at break of the sample containing 2.0 wt% EMA and PPGS increased by 25.93%. The inhibition rates of the fibres with 1.0 wt% PPGS against Escherichia coli and Staphylococcus aureus reached over 99.99%. Samples were easily coloured with dyes, exhibiting good colour fastness, regardless of the EMA content. However, the antibacterial performances of dyed DTYs decreased to varying degrees. the inhibition rates of samples of 0.5wt% addition of PPGS against E. coli were reduced from 99.99% to 28.50% and 25.36% after dyeing with Acid Blue 80 and Dispersible Blue 2BLN, respectively. The EMA-modified fibres exhibited the best antibacterial activity after dyeing with neutral gray 2BL. These findings are expected to promote the wider use of biobased PA56 in practical applications that require antibacterial performance and to guide the dyeing process of antimicrobial fibres.

In vitro and in vivo antifungal activity of different bacterial isolates against Botrytis gray mold of tomato

Gray mold rot, caused by Botrytis cinerea, is considered as one of the most harmful fungal diseases affecting postharvest tomato fruits. In the current work, we explore the biocontrol potential of 174 bacterial strains isolated from tomato rhizosphere, argan rhizosphere and a vermicompost to control this fungal pathogen. The in vitro dual culture study of isolated bacterial strains and the fungus-causing pathogen revealed that 31 isolates exhibited a substantial antifungal activity against B. cinerea mycelial growth. The inhibition rates ranged from 55.36 to 85.07%. Twelve bacterial strains which showed the highest antifungal properties (more than 79.6%) were subsequently investigated for their ability to produce compounds with antifungal activity, including diffusible substances, volatile compounds and hydrocyanic acid. These strains were then evaluated in vivo for their ability to reduce fruit decay caused by the fungus. Indeed, isolates VC-B1 (from vermicompost), RS-TB3, and RS-T6 (from the rhizosphere of tomato root), and RH-TB11 (from the tomato rhizoplane) released the most active diffusible substances, which totally inhibited the mycelial growth of B. cinerea. In addition, bacterial strains RS-TB1 and RS-T6 isolated both from the tomato rhizospheric soil were among the isolates that produced the most effective volatile compounds. They reduced the mycelial growth of the fungal pathogen by 75.36% ± 7.24% and 72.94 ± 4.129% respectively. Moreover, RS-TB3, RS-TB4, RH-TB1, and VC-B1 exhibited the highest production of hydrocyanic acid, followed by RS-TB1, VC-3, and VC-13. In vivo bioassays showed disease reduction ranging from 37.92% to 93.14%, with VC-1, VC-5, and RS-T4 showing the highest efficacy. This study identifies several bacterial strains with high potential for biocontrol of B. cinerea in postharvest tomatoes, presenting a promising alternative to chemical fungicides for managing gray mold rot.

Pseudomonas protegens ML15 and Trichoderma koningiopsis Tr21 co-culture: A potent strategy for suppressing Fusarium cerealis infections in wheat through augmented antifungal metabolite production

Wheat (Triticum aestivum L.), a staple grain consumed worldwide, is heavily affected by Fusarium species, which cause harmful diseases that threaten its production. The present study was conducted to investigate the biocontrol activity of monocultures of Pseudomonas protegens ML15 and Trichoderma koningiopsis Tr21 as well as their co-culture, as a sustainable strategy to combat Fusarium cerealis. The cell-free supernatant and cell-free extract of co-culture demonstrated increased inhibitory effects against F. cerealis, compared to the monocultures. GC-MS analysis revealed that cell-free extract of P. protegens ML15, T. koningiopsis Tr21, and co-culture contained different bioactive metabolites. Pyrrolo[1,2-a]pyrazine-1,4-dione derivatives were major compounds in the cell-free extract of co-culture. Further analysis using NMR and HPLC, revealed that co-culture produced higher concentrations of pyoluteorin, 2,4-diacetylphloroglucinol, and 2,4-di-tert-butylphenol, compared to their respective monocultures. In vivo plant experiments indicated that co-culture treatment reduced F. cerealis infection and improved wheat development. Our findings highlight the exciting potential of co-culturing P. protegens ML15 and T. koningiopsis Tr21 as a formidable biocontrol duo, particularly effective against notorious fungal plant pathogens like Fusarium. This innovative approach holds promise for revolutionizing agricultural practices, offering sustainable solutions to combat crop diseases, and ensuring global food security.

Classification of infection grade for anthracnose in mango leaves under complex background based on CBAM-DBIRNet

Anthracnose is one of the most harmful fungal diseases in mango orchards. Accurate and rapid detection of anthracnose infection grade for mango leaves in complex natural environments is a prerequisite of precise variable pesticide spraying by robots in intelligent orchards. In this paper, A lightweight double branch inverted residual attention network (CBAM-DBIRNet) model was proposed by combining the inverted residual network and the attention mechanism, which was used to detect the infection grade of anthracnose for mango leaves in natural environment. The model designed two parallel residual branch structures to extract multi-scale features of mango leaves with different infection grades through different dilation coefficients. The inverted residual structure and depthwise separable convolution were used to reduce the complexity of the model. The CBAM attention module was integrated into the model to suppress the interference of complex background information. The mango leaves collected in the natural orchard were used for experiments. The results showed that the accuracy, recall and F1 of the CBAM-DBIRNet model for the classification of anthracnose infection grade were 98.42 %, 97.80 % and 97.89 %, respectively. The model size and parameter were 0.64 MB and 0.15 M, respectively. This study provides technical support for smart orchard management and robotic precision variable application operations.

An efficient zero-labeling segmentation approach for pest monitoring on smartphone-based images

Timely and precise farm inspection, which involves the identification and recognition of harmful insects and diseases, is crucial for safeguarding crop production. Traditional vision-based pest recognition methods typically require extensive annotated data for each pest species and a lengthy training process. This approach is time-consuming, labor-intensive, and prone to human error. Zero-shot learning offers a potential solution by enabling pest segmentation and control without requiring explicit training data. This study supports farmers in automatically identifying ten common pests and their precise locations in real-world outdoor environments. The zero-shot pest segmentation is based on a hybrid approach combining Explainable Contrastive Language-Image Pre-training (ECLIP) and Segment-Anything (SAM). Moreover, an optimized super-resolution model and various data augmentation methods are implemented to improve the quality of the dataset. Lastly, a mask post-processing step is applied to remove highly overlapping segmented masks and noise blobs caused by the complex background. The mean Intersection over Union (mIoU) of 66.5 % on the validation set demonstrates the potential of zero-shot methods for automated pest segmentation during farm inspections. This research lays the foundation for accurate pest monitoring systems capable of adapting to new pests, ultimately improving agricultural productivity.

Корневая гниль яровой пшеницы в условиях Зауралья, варианты оперативной защиты

Abstract. Root rot is a harmful and widespread disease of cereal crops. In the conditions of the Urals, Siberia, and Northern Kazakhstan, its causative agents are various species of fungi of the genus Fusarium and the fungus Bipolaris sorokiniana. The purpose of this study was to comparatively determine the effectiveness of microbiological, chemical and combined protection of spring wheat seeds. Field experiments were carried out on the experimental field of the Kurgan Scientific Research Institute of Agriculture – branch of the Ural Federal Agrarian Scientific Research Centre of the Ural Branch of the Russian Academy of Sciences (Kurgan SRIA – branch of FSBSI UrFASRC, UrB of RAS) in 2019, 2021, 2022. Scientific novelty lies in the determining the competitiveness of various methods of protecting spring wheat seeds in the conditions of the Trans-Urals within the framework of modern cultivation technology. The methods used are generally accepted in the Russian Federation. Results. In conditions of almost annual occurrence of negative natural phenomena for the growth and development of plants (droughts, frosts, sudden changes in temperature, dry winds, etc.), the use of seed treaters can be an additional stress for plants; the presence of the effect of shortening the underground internode can negatively affect field germination culture. To reduce these risks, as well as the pesticide load, we recommend using a combined method of seed protection. It involves the use of a mixture of a bacterial fungicide based on Bacillus subtilis with a chemical disinfectant at half the consumption rate. At the same time, the level of control of phytopathogens is maintained, there is no retardant effect, and economic efficiency is not inferior to the level of using a two-component chemical seed protectant (113–114 %). Chemical protection of seeds reduced the development of root rot pathogens by 63–72 %. The use of combined protection provided good control of phytopathogens, including the dominant fungi Fusarium. The predominant species from the genus Fusarium were the highly dangerous F. oxysporum, F. graminearum, F. sporotrichioides.

Innovating Airport Luggage Disinfection Systems with Advanced Technologies and Automation

In this article, we point out that luggage disinfection is a key step in stopping the spread of infectious diseases that can be contracted at airports due to viruses and bacteria, which can spread through passenger luggage at airports. To prevent the spread of respiratory infections at airports, in this research study, we compare two types of baggage disinfection system. The first method uses UV light to disinfect luggage while selectively checking it for the presence of bacteria and viruses. The second system uses non-selective disinfection, taking into account the possibility of the spread of disease from the aircraft’s home country. An analysis and simulation of a specific airport security procedure was carried out on the model under study, which is an automated system for disinfecting baggage at airports in two variants. The aim is to reduce the transmission of harmful diseases and, at the same time, to ensure the accuracy of passenger security screening by efficiently exhausting each of the proposed models. This research shows that the suggested measures to stop the spread of infectious diseases that travelers’ luggage can bring in will enhance screening procedures and, in particular, boost overall security while lowering the risk of infection transmission at airports.

Evaluation of effectiveness resistance genes in wheat genotypes using marker-assisted selection for stripe rust resistance breeding”

Stripe rust, induced by Puccinia striiformis f. sp. tritici, is the most harmful and prevalent disease in temperate regions worldwide, affecting wheat production areas globally. An effective strategy for controlling the disease involves enhancing genetic resistance against stripe rust, achieved through Egyptian breeding efforts not previously conducted on wheat genotypes. The resistance level to stripe rust in thirty-eight wheat genotypes was assessed using marker-assisted selection methods. The investigation suggests that wheat breeding programs can utilize slow-rusting Yr genes, which are effective resistance genes, to develop novel genotypes with stripe rust resistance through marker-assisted breeding. Based on the four disease responses of the wheat genotypes under investigation, the results categorized the genotypes into three groups. The first group included resistant genotypes, the second group exhibited a slow-rusting character with the lowest disease symptom rates, and the last group displayed the highest disease characteristics rates throughout the three seasons, comprising fast-rusting genotypes. The rust-resistant genes identified were Yr5, Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr29, Yr30, and Yr36. Genes Yr26, Yr30, and Yr36 were present in all genotypes. Genotypes Misr3, Misr4, Giza168, Giza167, Giza170, Giza171, Gemmeiza9, and Gemmeiza10 carried the Yr9 gene. Only one genotype, Sids13, was found to have the Yr17 gene. Genes Yr18 and Yr29 were identified in Sids14, Giza168, Giza170, Gemmeiza9, and Gemmeiza10. However, none of the wheat genotypes showed the presence of Yr5, Yr10, or Yr15. Several backcrossing generations were conducted to introduce the Yr5 and Yr10 genes into susceptible genotypes (Misr1, Misr2, and Gemmeiza11). These genotypes are cultivated globally and are known for producing high-quality flour, making them of great importance to farmers. The study demonstrates significant potential for enhancing wheat genotypes for stripe rust resistance and increased production.

High-performance simulation of disease outbreaks in growing-finishing pig herds raised by the precision feeding method

Perturbations always affect livestock during the breeding process, including harmful diseases. Researching the impact of disease outbreaks on pig herds is extremely important so that disease control measures can be applied early. However, conducting practical experiments on disease outbreaks is extremely expensive. Precision feeding systems (PFS) for pigs use data on the animal’s own feed intake to calculate the appropriate amount of feed for each individual. This helps increase productivity and product quality while contributing to reducing waste generation in the environment. Daily feed intake (DFI) and cumulative feed intake (CFI) data can be automatically collected and estimated from the PFS, which can help detect or predict disease outbreaks. In this article, we introduce an advanced simulation model of the PFS for pigs and the integration of disease outbreak models into this system. A disease outbreak simulation application within the pig herd raised by the precision feeding method is also developed for running high-performance experimental simulations. The results of the simulation scenarios are analyzed and compared with data from a real-world experiment to assess the accuracy of the application. The correlation coefficient values of DFI in all scenarios fall within the range of 0.25 to 0.5, suggesting almost no correlation between simulated DFI and actual DFI. The overall average correlation coefficient of CFI for all scenarios is 0.764, falling within the strong correlation range. It can be concluded that the simulation accurately represents CFI values compared to reality.

RNA interference-based strategies to control Botrytis cinerea infection in cultivated strawberry

Key messageGene silencing of BcDCL genes improves gray mold disease control in the cultivated strawberry.Gene silencing technology offers new opportunities to develop new formulations or new pathogen-resistant plants for reducing impacts of agricultural systems. Recent studies offered the proof of concept that the symptoms of gray mold can be reduced by downregulating Dicer-like 1 (DCL1) and 2 (DCL2) genes of Botrytis cinerea. In this study, we demonstrate that both solutions based on dsRNA topical treatment and in planta expression targeting BcDCL1 and BcDCL2 genes can be used to control the strawberry gray mold, the most harmful disease for different fruit crops. 50, 70 and 100 ng μL−1 of naked BcDCL1/2 dsRNA, sprayed on plants of Fragaria x ananassa cultivar Romina in the greenhouse, displayed significant reduction of susceptibility, compared to the negative controls, but to a lesser extent than the chemical fungicide. Three independent lines of Romina cultivar were confirmed for their stable expression of the hairpin gene construct that targets the Bc-DCL1 and 2 sequences (hp-Bc-DCL1/2), and for the production of hp construct-derived siRNAs, by qRT-PCR and Northern blot analyses. In vitro and in vivo detached leaves, and fruits from the hp-Bc-DCL1/2 lines showed significantly enhanced tolerance to this fungal pathogen compared to the control. This decreased susceptibility was correlated to the reduced fungal biomass and the downregulation of the Bc-DCL1 and 2 genes in B. cinerea. These results confirm the potential of both RNAi-based products and plants for protecting the cultivated strawberry from B. cinerea infection, reducing the impact of chemical pesticides on the environment and the health of consumers.

6-shogaol against 3-Nitropropionic acid-induced Huntington's disease in rodents: Based on molecular docking/targeting pro-inflammatory cytokines/NF-κB-BDNF-Nrf2 pathway.

Huntington's disease (HD) is an extremely harmful autosomal inherited neurodegenerative disease. Motor dysfunction, mental disorder, and cognitive deficits are the characteristic features of this disease. The current study examined whether 6-shogaol has a protective effect against 3-Nitropropionic Acid (3-NPA)-induced HD in rats. A total of thirty male Wistar rats received 6-shogaol (10 and 20 mg/kg, per oral) an hour before injection of 3-NPA (10 mg/kg i.p.) for 15 days. Behavioral tests were performed, including narrow beam walk, rotarod test, and grip strength test. Biochemical tests promoting oxidative stress were evaluated [superoxide dismutase (SOD), reduced glutathione (GSH), catalase (CAT) and malondialdehyde (MDA)], including changes to neurotransmitters serotonin (5-HT), dopamine (DA), norepinephrine (NE), homovanillic acid (HVA), (3,4-dihydroxyphenylacetic acid (DOPAC), γ-aminobutyric acid (GABA), and 5-hydroxy indole acetic acid (5-HIAA), nuclear factor kappa-B (NF-κB), tumor necrosis factor-α (TNF-α), interleukins-1β (IL-1β), IL-6, brain-derived neurotrophic factor (BDNF), and nuclear factor erythroid 2-related factor 2 (Nrf2). The 6-shogaol was docked to the active site of TNF-α (2AZ5), NF-κB (1SVC), BDNF) [1B8M], and Nrf2 [5FZN] proteins using AutoDock tools. The 6-shogaol group significantly improved behavioral activity over the 3-NPA-injected control rats. Moreover, 3-NPA-induced significantly altered neurotransmitters, biochemical and neuroinflammatory indices, which could efficiently be reversed by 6-shogaol. The 6-shogaol showed favorable negative binding energies at -9.271 (BDNF) kcal/mol. The present investigation demonstrated the neuroprotective effects of 6-shogaol in an experimental animal paradigm against 3-NPA-induced HD in rats. The suggested mechanism is supported by immunohistochemical analysis and western blots, although more research is necessary for definite confirmation.

Identification and Antimicrobial Susceptibility Testing of Staphylococcus Aureus from Clinical Samples of Tertiary Care Centre, North India

Staphylococci are contributors of the Micrococcaceae family. Staphylococcus aureus is the most common type of bacteria which causes infections in the humans. They are classically taken into consideration extracellular, pyogenic pathogens due to their capacity to set off abscess formation. The microorganisms are non-motile and generally tend to develop in clusters. They are extraordinarily hardy and may continue to exist for extended durations of time on environmental surfaces. Staphylococci are identified in medical samples with the aid of using Gram stain and their function morphology – Gram positive cocci in grape-like clusters. They shape spherical frequently beta-hemolytic colonies on agar. It is characterized by the presence of the bacteria in different samples collected from different departments and the use of different antibiotic drugs and other medicines have increased the rate of infections. Some of the other risk factors includes the advanced ages and hospitalization. Staphylococcus aureus can be of different types like MRSA, MSSA, VRSA etc. Staphylococcus can cause infections in different ages it can infect child also or adult also. Different types of samples of Staphylococcus aureus can be identified using MALDI-TOF, MICROSCAN and BD PHOENIX and their interpretation of the antimicrobial susceptibility test can be given. Staphylococcus aureus is a major bacterial human pathogen that causes a wide variety of harmful diseases to the clinical manifestations. Infections caused by this bacterium are commonboth in community as well as hospital settings and treatment of the diseases caused by this remains challenging to manage. Because due to the emergence of its multi-drug resistant strainssuch as MRSA. Different drugs were used like Amp/Sulbactam, Ampicilin, Ceftriaxone, Ciprofloxacin, Clindamycin, Daptomycin, Erythomycin, Linezolid, Oxacillin, Rifampin, Synercid, Tetracycline, Teicoplanin, Vancomycin, Penicillin. The antimicrobial susceptibility test was done and their resistance percentage is calculated.

Enhancing cowpea wilt resistance: insights from gene coexpression network analysis with exogenous melatonin treatment

BackgroundCowpea wilt is a harmful disease caused by Fusarium oxysporum, leading to substantial losses in cowpea production. Melatonin reportedly regulates plant immunity to pathogens; however the specific regulatory mechanism underlying the protective effect of melatonin pretreated of cowpea against Fusarium oxysporum remains known. Accordingly, the study sought to evaluate changes in the physiological and biochemical indices of cowpea following melatonin treated to facilitate Fusarium oxysporum resistance and elucidate the associated molecular mechanism using a weighted gene coexpression network.ResultsTreatment with 100 µM melatonin was effective in increasing cowpea resistance to Fusarium oxysporum. Glutathione peroxidase (GSH-PX), catalase (CAT), and salicylic acid (SA) levels were significantly upregulated, and hydrogen peroxide (H2O2) levels were significantly downregulated in melatonin treated samples in roots. Weighted gene coexpression network analysis of melatonin- and Fusarium oxysporum-treated samples identified six expression modules comprising 2266 genes; the number of genes per module ranged from 9 to 895. In particular, 17 redox genes and 32 transcription factors within the blue module formed a complex interconnected expression network. KEGG analysis revealed that the associated pathways were enriched in secondary metabolism, peroxisomes, phenylalanine metabolism, flavonoids, and flavonol biosynthesis. More specifically, genes involved in lignin synthesis, catalase, superoxide dismutase, and peroxidase were upregulated. Additionally, exogenous melatonin induced activation of transcription factors, such as WRKY and MYB.ConclusionsThe study elucidated changes in the expression of genes associated with the response of cowpea to Fusarium oxysporum under melatonin treated. Specifically, multiple defence mechanisms were initiated to improve cowpea resistance to Fusarium oxysporum.