Identification of novel and safe fungicidal molecules against fusarium oxysporum from plant essential oils: in vitro and computational approaches.

Phytopathogenic fungi are serious threats in the agriculture sector especially in fruit and vegetable production. The use of plant essential oil as antifungal agents has been in practice from many years. Plant essential oils (PEOs) of Cuminum cyminum, Trachyspermum ammi, Azadirachta indica, Syzygium aromaticum, Moringa oleifera, Mentha spicata, Eucalyptus grandis, Allium sativum, and Citrus sinensis were tested against Fusarium oxysporum. Three phase trials consist of lab testing (MIC and MFC), field testing (seed treatment and foliar spray), and computer-aided fungicide design (CAFD). Two concentrations (25 and 50 μl/ml) have been used to asses MIC while MFC was assessed at four concentrations (25, 50, 75, and 100 μl/ml). C. sinensis showed the largest inhibition zone (47.5 and 46.3 m2) for both concentrations. The lowest disease incidence and disease severity were recorded in treatments with C. sinensis PEO. Citrus sinensis that qualified in laboratory and field trials was selected for CAFD. The chemical compounds of C. sinensis PEO were docked with polyketide synthase beta-ketoacyl synthase domain of F. oxysporum by AutoDock Vina. The best docked complex was formed by nootkatone with -6.0 kcal/mol binding affinity. Pharmacophore of the top seven C. sinensis PEO compounds was used for merged pharmacophore generation. The best pharmacophore model with 0.8492 score was screened against the CMNP database. Top hit compounds from screening were selected and docked with polyketide synthase beta-ketoacyl synthase domain. Four compounds with the highest binding affinity and hydrogen bonding were selected for confirmation of lead molecule by doing MD simulation. The polyketide synthase-CMNPD24498 showed the highest stability throughout 80 ns run of MD simulation. CMNPD24498 (FW054-1) from Verrucosispora was selected as the lead compound against F. oxysporum

Factors associated with COVID-19 pandemic induced post-traumatic stress symptoms among adults living with and without HIV in Nigeria: a cross-sectional study

Background: Nigeria is a country with high risk for traumatic incidences, now aggravated by the COVID-19 pandemic. This study aimed to identify differences in COVID-19 related post-traumatic stress symptoms (PTSS) among people living and not living with HIV; to assess whether PTSS were associated with COVID-19 pandemic-related anger, loneliness, social isolation, and social support; and to determine the association between PTSS and use of COVID-19 prevention strategies.Methods: The data of the 3761 respondents for this analysis was extracted from a cross-sectional online survey that collected information about mental health and wellness from a convenience sample of adults, 18 years and above, in Nigeria from July to December 2020. Information was collected on the study's dependent variable (PTSS), independent variables (self-reported COVID-19, HIV status, use of COVID-19 prevention strategies, perception of social isolation, access to emotional support, feelings of anger and loneliness), and potential confounder (age, sex at birth, employment status). A binary logistic regression model tested the associations between independent and dependent variables.Results: Nearly half (47.5%) of the respondents had PTSS. People who had symptoms but were not tested (AOR = 2.20), felt socially isolated (AOR = 1.16), angry (AOR = 2.64), or lonely (AOR = 2.19) had significantly greater odds of reporting PTSS (p p Conclusion: The present study identified some multifaceted relationships between post-traumatic stress, HIV status, facemask use, anger, loneliness, social isolation, and access to emotional support during this protracted COVID-19 pandemic. These findings have implications for the future health of those affected, particularly for individuals living in Nigeria. Public health education should be incorporated in programs targeting prevention and prompt diagnosis and treatment for post-traumatic stress disorder at the community level.</p

Design of Multi-Epitope Vaccine for Staphylococcus saprophyticus: Pan-Genome and Reverse Vaccinology Approach

Staphylococcus saprophyticus is a Gram-positive coccus responsible for the occurrence of cystitis in sexually active, young females. While effective antibiotics against this organism exist, resistant strains are on the rise. Therefore, prevention via vaccines appears to be a viable solution to address this problem. In comparison to traditional techniques of vaccine design, computationally aided vaccine development demonstrates marked specificity, efficiency, stability, and safety. In the present study, a novel, multi-epitope vaccine construct was developed against S. saprophyticus by targeting fully sequenced proteomes of its five different strains, which were examined using a pangenome and subtractive proteomic strategy to characterize prospective vaccination targets. The three immunogenic vaccine targets which were utilized to map the probable immune epitopes were verified by annotating the entire proteome. The predicted epitopes were further screened on the basis of antigenicity, allergenicity, water solubility, toxicity, virulence, and binding affinity towards the DRB*0101 allele, resulting in 11 potential epitopes, i.e., DLKKQKEKL, NKDLKKQKE, QDKLKDKSD, NVMDNKDLE, TSGTPDSQA, NANSDGSSS, GSDSSSSNN, DSSSSNNDS, DSSSSDRNN, SSSDRNNGD, and SSDDKSKDS. All these epitopes have the efficacy to cover 99.74% of populations globally. Finally, shortlisted epitopes were joined together with linkers and three different adjuvants to find the most stable and immunogenic vaccine construct. The top-ranked vaccine construct was further scrutinized on the basis of its physicochemical characterization and immunological profile. The non-allergenic and antigenic features of modeled vaccine constructs were initially validated and then subjected to docking with immune receptor major histocompatibility complex I and II (MHC-I and II), resulting in strong contact. In silico cloning validations yielded a codon adaptation index (CAI) value of 1 and an ideal percentage of GC contents (46.717%), indicating a putative expression of the vaccine in E. coli. Furthermore, immune simulation demonstrated that, after injecting the proposed MEVC, powerful antibodies were produced, resulting in the sharpest peaks of IgM + IgG formation (&gt;11,500) within 5 to 15 days. Experimental testing against S. saprophyticus can evaluate the safety and efficacy of these prophylactic vaccination designs

Design of a Multi-Epitopes Vaccine against Hantaviruses: An Immunoinformatics and Molecular Modelling Approach

Hantaviruses are negative-sense, enveloped, single-stranded RNA viruses of the family Hantaviridae. In recent years, rodent-borne hantaviruses have emerged as novel zoonotic viruses posing a substantial health issue and socioeconomic burden. In the current research, a reverse vaccinology approach was applied to design a multi-epitope-based vaccine against hantavirus. A set of 340 experimentally reported epitopes were retrieved from Virus Pathogen Database and Analysis Resource (ViPR) and subjected to different analyses such as antigenicity, allergenicity, solubility, IFN gamma, toxicity, and virulent checks. Finally, 10 epitopes which cleared all the filters used were linked with each other through specific GPGPG linkers to construct a multi-antigenic epitope vaccine. The designed vaccine was then joined to three different adjuvants—TLR4-agonist adjuvant, β-defensin, and 50S ribosomal protein L7/L12—using an EAAAK linker to boost up immune-stimulating responses and check the potency of vaccine with each adjuvant. The designed vaccine structures were modelled and subjected to error refinement and disulphide engineering to enhance their stability. To understand the vaccine binding affinity with immune cell receptors, molecular docking was performed between the designed vaccines and TLR4; the docked complex with a low level of global energy was then subjected to molecular dynamics simulations to validate the docking results and dynamic behaviour. The docking binding energy of vaccines with TLR4 is −29.63 kcal/mol (TLR4-agonist), −3.41 kcal/mol (β-defensin), and −11.03 kcal/mol (50S ribosomal protein L7/L12). The systems dynamics revealed all three systems to be highly stable with a root-mean-square deviation (RMSD) value within 3 Å. To test docking predictions and determine dominant interaction energies, binding free energies of vaccine(s)–TLR4 complexes were calculated. The net binding energy of the systems was as follows: TLR4-agonist vaccine with TLR4 (MM–GBSA, −1628.47 kcal/mol and MM–PBSA, −37.75 kcal/mol); 50S ribosomal protein L7/L12 vaccine with TLR4 complex (MM–GBSA, −194.62 kcal/mol and MM–PBSA, −150.67 kcal/mol); β-defensin vaccine with TLR4 complex (MM–GBSA, −9.80 kcal/mol and MM–PBSA, −42.34 kcal/mol). Finally, these findings may aid experimental vaccinologists in developing a very potent hantavirus vaccine

Drone and Controller Detection and Localization: Trends and Challenges

Unmanned aerial vehicles (UAVs) have emerged as a rapidly growing technology seeing unprecedented adoption in various application sectors due to their viability and low cost. However, UAVs have also been used to perform illegal and malicious actions, which have recently increased. This creates a need for technologies capable of detecting, classifying, and deactivating malicious and unauthorized drones. This paper reviews the trends and challenges of the most recent UAV detection methods, i.e., radio frequency-based (RF), radar, acoustic, and electro-optical, and localization methods. Our research covers different kinds of drones with a major focus on multirotors. The paper also highlights the features and limitations of the UAV detection systems and briefly surveys the UAV remote controller detection methods

Drone and Controller Detection and Localization: Trends and Challenges

Unmanned aerial vehicles (UAVs) have emerged as a rapidly growing technology seeing unprecedented adoption in various application sectors due to their viability and low cost. However, UAVs have also been used to perform illegal and malicious actions, which have recently increased. This creates a need for technologies capable of detecting, classifying, and deactivating malicious and unauthorized drones. This paper reviews the trends and challenges of the most recent UAV detection methods, i.e., radio frequency-based (RF), radar, acoustic, and electro-optical, and localization methods. Our research covers different kinds of drones with a major focus on multirotors. The paper also highlights the features and limitations of the UAV detection systems and briefly surveys the UAV remote controller detection methods

Performance Analysis of Mars-Powered Descent-Based Landing in a Constrained Optimization Control Framework

It is imperative to find new places other than Earth for the survival of human beings. Mars could be the alternative to Earth in the future for us to live. In this context, many missions have been performed to examine the planet Mars. For such missions, planetary precision landing is a major challenge for the precise landing on Mars. Mars landing consists of different phases (hypersonic entry, parachute descent, terminal descent comprising gravity turn, and powered descent). However, the focus of this work is the powered descent phase of landing. Firstly, the main objective of this study is to minimize the landing error during the powered descend landing phase. The second objective involves constrained optimization in a predictive control framework for landing at non-cooperative sites. Different control algorithms like PID and LQR have been developed for the stated problem; however, the predictive control algorithm with constraint handling&rsquo;s ability has not been explored much. This research discusses the Model Predictive Control algorithm for the powered descent phase of landing. Model Predictive Control (MPC) considers input/output constraints in the calculation of the control law and thus it is very useful for the stated problem as shown in the results. The main novelty of this work is the implementation of Explicit MPC, which gives comparatively less computational time than MPC. A comparison is done among MPC variants in terms of feasibility, constraints handling, and computational time. Moreover, other conventional control algorithms like PID and LQR are compared with the proposed predictive algorithm. These control algorithms are implemented on quadrotor UAV (which emulates the dynamics of a planetary lander) to verify the feasibility through simulations in MATLAB

Performance Analysis of Mars-Powered Descent-Based Landing in a Constrained Optimization Control Framework

It is imperative to find new places other than Earth for the survival of human beings. Mars could be the alternative to Earth in the future for us to live. In this context, many missions have been performed to examine the planet Mars. For such missions, planetary precision landing is a major challenge for the precise landing on Mars. Mars landing consists of different phases (hypersonic entry, parachute descent, terminal descent comprising gravity turn, and powered descent). However, the focus of this work is the powered descent phase of landing. Firstly, the main objective of this study is to minimize the landing error during the powered descend landing phase. The second objective involves constrained optimization in a predictive control framework for landing at non-cooperative sites. Different control algorithms like PID and LQR have been developed for the stated problem; however, the predictive control algorithm with constraint handling’s ability has not been explored much. This research discusses the Model Predictive Control algorithm for the powered descent phase of landing. Model Predictive Control (MPC) considers input/output constraints in the calculation of the control law and thus it is very useful for the stated problem as shown in the results. The main novelty of this work is the implementation of Explicit MPC, which gives comparatively less computational time than MPC. A comparison is done among MPC variants in terms of feasibility, constraints handling, and computational time. Moreover, other conventional control algorithms like PID and LQR are compared with the proposed predictive algorithm. These control algorithms are implemented on quadrotor UAV (which emulates the dynamics of a planetary lander) to verify the feasibility through simulations in MATLAB

Exposure to, understanding of and interest in interventional radiology among Pakistani medical students: a cross-sectional study.

BACKGROUND: Medical students need more awareness regarding minimally invasive image-guided procedures carried out by interventional radiological approach. This study analyzed the knowledge and attitudes of medical students regarding interventional radiology (IR) and the factors influencing their decision to choose IR as a specialty in the future. METHODS: A cross-sectional, web-based study was conducted among medical students across Pakistan. The data were collected from October 14, 2021, to November 14, 2021. The questionnaire included demographic variables, exposure, interest, and self-reported knowledge of IR, interventions, instruments utilized in IR, and the responsibilities of the interventional radiologist. Variables affecting the possible choice of IR as a future career were analyzed using logistic regression analysis. RESULTS: The median age was 22 years, with a male predominance. 65.5% exhibited an interest in radiology, and 20.2% in IR. The majority, 83.5%, perceived IR. As having good to adequate prospects. Male participants preferred IR more as compared to females. Participants willing to attend IR rotation and had an excellent view of IR as a specialty had higher propensity towards IR as a future career than their counterparts. The majority opted for IR as a better-paying job with lots of intellectual stimulation and career flexibility. CONCLUSION: IR is a demanding specialty with rigorous routines but reasonable monetary compensation. Lack of infrastructure and low numbers of trained specialists limit medical students\u27 exposure to IR in developing health economies like Pakistan. Clinical rotations in IR departments would help raise awareness about the field and bridging this gap

A multi-country survey on access to healthcare and treatment services among individuals with critical medical care needs during the first wave of the pandemic

Background Healthcare services were significantly interrupted during the early phase of the COVID-19 pandemic. The aim of the present study was to determine the associations between sociodemographic factors and healthcare access during the first wave of the COVID-19 pandemic among individuals with critical care needs.MethodsThis was a secondary analysis of the data of 5,156 participants recruited from 152 countries during the first wave of the COVID-19 pandemic. The dependent variables were self-reported difficulty of access to health care, challenges with obtaining medication, and the use of alternative medical services. The independent variables were age at last birthday; sex at birth, level of education, employment status and the macro-social vulnerability status. The confounding variable was the country income level. Three multivariable logistic regression analyses were conducted to determine the associations between the dependent variables and the independent variables after adjusting for the confounder.ResultsDifficulty accessing health care services and obtaining medications was experienced by 1922 (37.3%) and 3746 (72.7%) participants respectively. Also, 1433 (27.8%) used alternative medical care. Retirees (AOR:1.59), unemployed (AOR:1.198), people living with HIV (AOR:2.36) and at increased risk of COVID-19 (AOR:2.10), people who used drugs (AOR:1.83) and transacted sex (AOR:1.971) had significantly higher odds for reporting difficulty with access to health care. Males (AOR:1.23), respondents with secondary level of education (AOR:1.39), retirees (AOR:2.19), unemployed (AOR:1.47), people living with HIV (AOR:2.46), people who used drugs (AOR:1.79), transacted sex (AOR:2.71) and those who might be (AOR: 1.66) and were at (AOR: 2.3) increased risk of severe COVID-19 had significantly higher odds for reporting difficulty with access to medications. People who used drugs (AOR:2.093) transacted sex (AOR:1.639), who might be (AOR: 1.211) and were at (AOR: 1.511) increased risk of severe COVID-19, and who had difficulty accessing usual healthcare (AOR: 9.047) and obtaining medications (AOR:2.16) had significantly higher odds of reporting alternative medical care use. People living with HIV (AOR:0.562) had significantly lower odds of using alternative medical care.ConclusionWe identified populations who had challenges with access to healthcare and obtaining medications used alternative medical care except for people living with HIV. Priority attention should be given to alternative medical care use during future health pandemics.Peer reviewe