Search

Aluminium alloys are used for the fabrication of the fuel clad of research-grade nuclear reactors as well as for several types of core components of high-flux research reactors. In order to carry out design and safety analysis of these components, their mechanical and fracture properties are required by the designer. In this work, experiments have been conducted on tensile specimens machined from an aluminium alloy block to evaluate the material stress-strain curve. Experiments have also been conducted on disc-shaped compact tension specimens in order to determine the fracture toughness of aluminium alloy. Numerical simulations of both tensile and fracture specimens have been carried out using the crystal plasticity model. Initially, the slip system level parameters of the crystal plasticity material model have been calibrated using experimental stress-strain data for single as well as polycrystalline aluminium. For the prediction of crack initiation toughness, Rice and Tracey’s damage model has been used. The critical damage parameter has been evaluated for a fractured specimen with a crack length-to-width (a/W) ratio of 0.6. The attainment of the critical damage parameter in the analysis corresponds to the instance of experimentally observed ductile crack initiation in the specimen. Later, this model was applied to other fracture specimens with different a/W ratios with values ranging from 0.39 to 0.59. It was observed that the critical damage parameter corresponding to crack initiation in the material has a very small variation, even if the specimens have different crack lengths. It is well-known in the literature that Rice and Tracey’s critical damage parameter is a material constant. Hence, we have applied the same model to predict crack initiation for single crystal fracture specimens with two different orientations of the crack plane. It was observed that the orientation is more susceptible to crack initiation and propagation compared with the orientation, as the damage parameter is high in the ligament of the specimen ahead of the crack tip for the same level of applied loading. As the [111] crack plane is more closely packed compared with the [100] plane, the distance between atomic planes is greater for the former, and hence, it is more susceptible to ductile damage. The results of the experiments and the material damage parameter are helpful for the integrity analysis of the fuel clad of research reactors as well as components of high-flux research reactors.

A Heating, Ventilation, and Air Conditioning (HVAC) system is often utilized in passenger vehicles to enhance the comfort of both the driver and the passengers. The reliability of an HVAC system refers to the probability that a component within the system will fulfil its intended function during a specified timeframe while operating according to the predefined operational and environmental conditions. Conducting a reliability analysis for the HVAC system of a passenger vehicle is crucial to ensure safety, comfort, cost-effectiveness, and a positive standing. A methodology for analyzing the reliability analysis of a HVAC system using field failure data were developed to identify the critical failure modes, components, and subsystems. A detailed Pareto analysis was applied at subsystem and failure mode levels in order to prioritize them accordingly to their failure frequency. The analysis showed that the A/C evaporator and blower front sides were observed to be the most critical subsystems, contributing to approximately 50% of all failures. Furthermore, the leakages at the joints and vibrations are the primary failure modes of the HVAC system. The Weibull++ software package (version 2021) was used to estimate the best-fit probability distributions for each subsystem and system reliability modelling using a Reliability Block Diagram. The results show that the exponential distribution fits well for several subsystem’s Time-To-Failure (TTF) data and show that the failures were random and due to external reasons.

The most prevalent reason for vision impairment in aging inhabitants is age-related macular degeneration (AMD), a posterior ocular disease with a poor understanding of the anatomic, genetic, and pathophysiological progression of the disease. Recently, new insights exploring the role of atrophic changes in the retinal pigment epithelium, extracellular drusen deposits, lysosomal lipofuscin, and various genes have been investigated in the progression of AMD. Hence, this review explores the incidence and risk factors for AMD, such as oxidative stress, inflammation, the complement system, and the involvement of bioactive lipids and their role in angiogenesis. In addition to intravitreal anti-vascular endothelial growth factor (VEGF) therapy and other therapeutic interventions such as oral kinase inhibitors, photodynamic, gene, and antioxidant therapy, as well as their benefits and drawbacks as AMD treatment options, strategic drug delivery methods, including drug delivery routes with a focus on intravitreal pharmacokinetics, are investigated. Further, the recent advancements in nanoformulations such as polymeric and lipid nanocarriers, liposomes, etc., intended for ocular drug delivery with pros and cons are too summarized. Therefore, the purpose of this review is to give new researchers an understanding of AMD pathophysiology, with an emphasis on angiogenesis, inflammation, the function of bioactive lipids, and therapy options. Additionally, drug delivery options that focus on the development of drug delivery system(s) via several routes of delivery can aid in the advancement of therapeutic choices.

Since the first reported case of COVID-19 in December 2019, several SARS-CoV-2 variants have evolved, and some of them have shown higher transmissibility, becoming the prevalent strains. Genomic epidemiological investigations into strains from different time points, including the early stages of the pandemic, are very crucial for understanding the evolution and transmission patterns. Using whole-genome sequences, our study describes the early landscape of SARS-CoV-2 variants in central India retrospectively (including the first known occurrence of SARS-CoV-2 in Madhya Pradesh). We performed amplicon-based whole-genome sequencing of randomly selected SARS-CoV-2 isolates (n = 38) collected between 2020 and 2022 at state level VRDL, ICMR-NIRTH, Jabalpur, from 11899 RT-qPCR-positive samples. We observed the presence of five lineages, namely B.1, B.1.1, B.1.36.8, B.1.195, and B.6, in 19 genomes from the first wave cases and variants of concern (VOCs) lineages, i.e., B.1.617.2 (Delta) and BA.2.10 (Omicron) in the second wave cases. There was a shift in mutational pattern in the spike protein coding region of SRAS-CoV-2 strains from the second wave in contrast to the first wave. In the first wave of infections, we observed variations in the ORF1Ab region, and with the emergence of Delta lineages, the D614G mutation associated with an increase in infectivity became a prominent change. We have identified five immune escape variants in the S gene, P681R, P681H, L452R, Q57H, and N501Y, in the isolates collected during the second wave. Furthermore, these genomes were compared with 2160 complete genome sequences reported from central India that encompass 109 different SARS-CoV-2 lineages. Among them, VOC lineages Delta (28.93%) and Omicron (56.11%) were circulating predominantly in this region. This study provides useful insights into the genetic diversity of SARS-CoV-2 strains over the initial course of the COVID-19 pandemic in central India.

The trajectory estimation of a highly maneuvering target is a challenging problem and has practical applications. The interacting multiple model (IMM) filter is a well-established filtering algorithm for the trajectory estimation of maneuvering targets. In this study, we present an overview of IMM filtering algorithms for tracking a highly-maneuverable fighter aircraft using an air moving target indicator (AMTI) radar on another aircraft. This problem is a nonlinear filtering problem due to nonlinearities in the dynamic and measurement models. We first describe single-model nonlinear filtering algorithms: the extended Kalman filter (EKF), unscented Kalman filter (UKF), and cubature Kalman filter (CKF). Then, we summarize the IMM-based EKF (IMM-EKF), IMM-based UKF (IMM-UKF), and IMM-based CKF (CKF). In order to compare the state estimation accuracies of the IMM-based filters, we present a derivation of the posterior Cramér-Rao lower bound (PCRLB). We consider fighter aircraft traveling with accelerations 3g, 4g, 5g, and 6g and present numerical results for state estimation accuracy and computational cost under various operating conditions. Our results show that under normal operating conditions, the three IMM-based filters have nearly the same accuracy. This is due to the accuracy of the measurements of the AMTI radar and the high data rate.

In this paper, we introduce an environmentally friendly approach to recycle used batteries and recover highly valuable manganese-based cathode materials. This study demonstrates the feasibility of fast plasma pyrolysis to recover LiMn2O4 electrode materials (e.g., lithium manganese oxide, LMO) and demonstrate their reuse in newly assembled Li-ion cells. The electrochemical performance of as-recycled cathodes shows an initial discharge capacity of 72 mAh/g and is stable for 100 cycles at 0.1 C. After adding 20 mole % of excess LiOH, the recycled LMO after relithiation at 660 °C can deliver an initial discharge capacity of 96 mAh/g and retain a decent discharge capacity of 88 mAh/g after 50 cycles at a 0.2 C rate. Without relithiation, the as-recycled LMO cathode after heating at 1000 °C delivers the best electrochemical cycling performance, including an initial discharge capacity of 94 mAh/g and 50th cycle capacity of 91 mAh/g at a 0.2 C rate. This study highlights a feasible approach for recycling electrode materials in spent LIBs. Recycling of lithium-ion batteries and especially electrode materials is crucial for the sustained growth of the lithium-ion battery industry and reduced environmental issues.

The intensive applications of nanomaterials in the agroecosystem led to the creation of several environmental problems. More efforts are needed to discover new insights in the nanomaterial–microbe–plant nexus. This relationship has several dimensions, which may include the transport of nanomaterials to different plant organs, the nanotoxicity to soil microbes and plants, and different possible regulations. This review focuses on the challenges and prospects of the nanomaterial–microbe–plant nexus under agroecosystem conditions. The previous nano-forms were selected in this study because of the rare, published articles on such nanomaterials. Under the study’s nexus, more insights on the carbon nanodot–microbe–plant nexus were discussed along with the role of the new frontier in nano-tellurium–microbe nexus. Transport of nanomaterials to different plant organs under possible applications, and translocation of these nanoparticles besides their expected nanotoxicity to soil microbes will be also reported in the current study. Nanotoxicity to soil microbes and plants was investigated by taking account of morpho-physiological, molecular, and biochemical concerns. This study highlights the regulations of nanotoxicity with a focus on risk and challenges at the ecological level and their risks to human health, along with the scientific and organizational levels. This study opens many windows in such studies nexus which are needed in the near future.

Baked pretzels are a popular choice for a quick snack, easily identifiable by their classic twisted shape, glossy exterior, and small salt crystals sprinkled on top, making them a standout snack. However, it is not commonly known that compounds with fluorescent properties can be formed during their production. Carbon nanodots (CNDs) with an average size of 3.5 nm were isolated and identified in bakery products. This study delved into the formation of CNDs in pretzel production using a fractional factorial experimental design. The research revealed that the baking temperature had the most significant impact on the concentration of CNDs, followed by the concentration of NaOH in the immersion solution, and then the baking time. This study highlights the unique role of the NaOH immersion step, which is not typically present in bread-making processes, in facilitating the formation of CNDs. This discovery highlights the strong correlation between the formation of CNDs and the heat treatment process. Monitoring and controlling these factors is crucial for regulating the concentration of CNDs in pretzel production and understanding nanoparticle formation in processed foods for food safety.

In the present research, the open-source WRF-SFIRE model has been used to carry out surface forest fire spread forecasting in the North Sikkim region of the Indian Himalayas. Global forecast system (GFS)-based hourly forecasted weather model data obtained through the National Centers for Environmental Prediction (NCEP) at 0.25 degree resolution were used to provide the initial conditions for running WRF-SFIRE. A landuse–landcover map at 1:10,000 scale was used to define fuel parameters for different vegetation types. The fuel parameters, i.e., fuel depth and fuel load, were collected from 23 sample plots (0.1 ha each) laid down in the study area. Samples of different categories of forest fuels were measured for their wet and dry weights to obtain the fuel load. The vegetation specific surface area-to-volume ratio was referenced from the literature. The atmospheric data were downscaled using nested domains in the WRF model to capture fire–atmosphere interactions at a finer resolution (40 m). VIIRS satellite sensor-based fire alert (375 m spatial resolution) was used as ignition initiation point for the fire spread forecasting, whereas the forecasted hourly weather data (time synchronized with the fire alert) were used for dynamic forest-fire spread forecasting. The forecasted burnt area (1.72 km2) was validated against the satellite-based burnt area (1.07 km2) obtained through Sentinel 2 satellite data. The shapes of the original and forecasted burnt areas matched well. Based on the various simulation studies conducted, an operational fire spread forecasting system, i.e., Sikkim Wildfire Forecasting and Monitoring System (SWFMS), has been developed to facilitate firefighting agencies to issue early warnings and carry out strategic firefighting.

The microflora of the soil is adversely affected by chemical fertilizers. Excessive use of chemical fertilizers has increased crop yield dramatically at the cost of soil vigor. The pH of the soil is temporarily changed by chemical fertilizers, which kill the beneficial soil microflora and can cause absorption stress on crop plants. This leads to higher dosages during the application, causing groundwater leaching and environmental toxicity. Nanofertilizers (NFs) reduce the quantity of fertilizer needed in agriculture, enhance nutrient uptake efficiency, and decrease fertilizer loss due to runoff and leaching. Moreover, NFs can be used for soil or foliar applications and have shown promising results in a variety of plant species. The main constituents of nanomaterials are micro- and macronutrient precursors and their properties at the nanoscale. Innovative approaches to their application as a growth promoter for crops, their modes of application, and the mechanism of absorption in plant tissues are reviewed in this article. In addition, the review analyzes potential shortcomings and future considerations for the commercial agricultural application of NFs.

Acquired bacterial resistance against several antibiotics has severely impaired the drug treatment regime. Multidrug-resistant Staphylococcus aureus (MDRSA) causes several life-threatening human pathologies. The introduction of novel antibiotics is a tedious process. Therefore, we have introduced glycyrrhizin (Gly) as a bioenhancer of norfloxacin (Nor), which showed synergistic interactions and a robust drug response. The drug resistance reversal potential of Gly against MDRSA was monitored. Gly and GlyNor (glycyrrhizin + norfloxacin) were used for spectrofluorometer and flow cytometry analysis for the measurement of free radicals and its effect upon cell membranes and macromolecules. Morphological analysis was carried out with the help of SEM. qRT-PCR analysis was conducted for gene regulation. Gly was observed to lower the MIC (minimum inhibitory concentration) of different groups of antibiotics up to 64-fold against MDRSA. GlyNor exerted oxidative stress, as evidenced by the measurement of reactive oxygen species (ROS) and their effect upon cell components. Gly and GlyNor showed membrane damage potential. The expression analysis of oxidative-related and MDR genes showed the up- and downregulation of these genes, respectively. GlyNor significantly lengthened post-antibiotic effects (PAE) and showed reduced mutation frequency rate (MFR). The synergistic bioenhancer properties of Gly with Nor and their enhanced ROS generation against MDRSA are reported for the first time in this study. Severe oxidative stress caused membrane damage, DNA fragmentation, transcriptional changes, and bacterial cell death. We strongly believe this could be a potential measure against rapidly evolving MDRSA.

The research focuses on the impact of transformational leadership on the decision to stay mediated by commitment after a court refusal regarding illegal extraordinary congress involving the outsiders of a political party in Indonesia (in this case, it is the Democratic Party currently led by Agus Harimurti Yudhoyono), where this phenomenon is classified as a crisis. Theories and the previous literature pointed out that transformational leadership would significantly affect an individual’s decision to stay with the institution through commitment. Therefore, this research empirically analyzes the hypotheses using quantitative methods on 349 respondents who are central (DPP) and local (DPD and DPC) active committees of the Democratic Party. Respondents are collected using cluster random sampling. Referring to theories and the previous literature, the latent variables of this research are constructed using dimensions. Transformational leadership (TL) has four dimensions which are charisma (idealized influence), inspirational motivation, intellectual stimulation, and individual considerations. Commitment has three dimensions which are affective, normative, and sustainable commitments. The decision to stay has two dimensions, which are intrinsic and extrinsic motivations. By using Structural Equation Modeling–Partial Least Square (SEM–PLS), the research revealed that the direct effect shows that transformational leadership and commitment significantly influence the decision to stay. On the other hand, the indirect effect indicates that commitment significantly mediates the relationship between transformational leadership and the decision to stay. The result indicates strong transformational leadership performed by Agus Harimurti Yudhoyono as the chief of the Democratic Party in Indonesia.

Massive use of antibiotics in veterinary medicine has led to their accumulation in meat and dairy products. Consumption of antibiotic-contaminated food can trigger the development of antibiotic-resistant bacteria, endangering human lives. Among antibiotics, the oxytetracycline (OTC) family of antibiotics is most widely used in veterinary medicine. Strict control of the antibiotics in food necessitates the development of fast and effective methods for OTC detection, for instance, in milk. One of the most promising approaches to OTC detection is based on the use of specially designed DNA aptamers. These DNA aptamers are relatively short, 15–60 bases, nucleotides folded in the solution in a 3D structure, forming a binding site for the target antibiotic. Aptamers can be chemically modified for attachment to sensor electrodes. In this work, we investigated the electrochemical detection of OTC using DNA aptamers specific to OTC that have been covalently immobilized onto the nanocomposite surface of a glassy carbon electrode with electrodeposited reduced graphene oxide and multiwalled carbon nanotubes. Differential pulse voltammetry, DPV, in the presentence of a ferri/ferrocyanide redox couple was used as an internal standard and to monitor the redox current. In the presence of OTC, the amplitude of DPV decreased, evidencing the blocking of charge transfer. After system optimization, we reached the limit of detection of 0.45 ng OTC/mL, which is 200 times lower than the maximum residue limit established by the European Commission of 100 ng OTC/mg.

Cotton (Gossypium spp.), a crucial cash crop in the United States, requires the constant monitoring of growth parameters for informed decision-making. Recently, forecasting models have gained prominence for predicting canopy indicators, aiding in-season planning and management decisions to optimize cotton production. This study employed unmanned aerial system (UAS) technology to collect canopy cover (CC) data from a 40-hectare cotton field in Driscoll, Texas, in 2020 and 2021. Long short-term memory (LSTM) models, trained using 2020 data, were subsequently applied to forecast the CC values for 2021. These models were compared with real-time auto-regressive integrated moving average (ARIMA) models to assess their effectiveness in predicting the CC values up to 14 days in advance, starting from the 28th day after crop emergence. The results showed that multiple-input multi-step output LSTM models achieved higher accuracy in predicting the in-season CC values during the early growth stages (up to the 56th day), with an average testing RMSE of 3.86, significantly lower than other single-input LSTM models. Conversely, when sufficient testing data are available, single-input stacked-LSTM models demonstrated precision in CC predictions for later stages, achieving an average RMSE of 3.06. These findings highlight the potential of LSTM models for in-season CC forecasting, facilitating effective management strategies in cotton production.

The preparation of raw images for subsequent analysis, known as image preprocessing, is a crucial step that can boost the performance of an image classification model. Although deep learning has succeeded in image classification without handcrafted features, certain studies underscore the continued significance of image preprocessing for enhanced performance during the training process. Nonetheless, this task is often demanding and requires high-quality images to effectively train a classification model. The quality of training images, along with other factors, impacts the classification model’s performance and insufficient image quality can lead to suboptimal classification performance. On the other hand, achieving high-quality training images requires effective image preprocessing techniques. In this study, we perform exploratory experiments aimed at improving a classification model of unexposed potsherd cavities images via image preprocessing pipelines. These pipelines are evaluated on two distinct image sets: a laboratory-made, experimental image set that contains archaeological images with controlled lighting and background conditions, and a Jōmon–Yayoi image set that contains images of real-world potteries from the Jōmon period through the Yayoi period with varying conditions. The best accuracy performances obtained on the experimental images and the more challenging Jōmon–Yayoi images are 90.48% and 78.13%, respectively. The comprehensive analysis and experimentation conducted in this study demonstrate a noteworthy enhancement in performance metrics compared to the established baseline benchmark.

Pleurotus ostreatus (Jacq. ex Fr.) P. Kumm mushrooms are cultivated on diverse by-products based on substrates that hold promise for mitigating antibiotic usage in the poultry industry and reducing environmental pollution. By incorporating agricultural by-products into mushroom cultivation, the functionality of the mushroom products can be increased, then the final product can be a more effective feed supplement. After mushroom cultivation, spent mushroom substrate (SMS) can be valorized, due to the presence of huge amounts of bioactive compounds like β-glucan, chitin, polyphenols, and flavonoids related to mycelia. As a prebiotic and antimicrobial feed supplement, these mushrooms positively influence gut microbiota, intestinal morphology, and thus overall poultry well-being. This article underscores the potential of solid-state fermentation (SSF) to enhance the bioactivity of oyster mushrooms and their derivatives, offering a cost-effective and efficient strategy for transforming unconventional feeding materials. Moreover, it emphasizes broader implications, including the reduction of antibiotic dependence in poultry farming, highlighting the promising integration of oyster mushrooms and their derivatives for sustainable and environmentally conscious poultry production.

Microplastics and nanoplastics are abundant in the environment. Further research is necessary to examine the consequences of microplastic contamination on living species, given its widespread presence. In our research, we determined the toxic effects of PET microplastics on Drosophila melanogaster at the cellular and genetic levels. Our study revealed severe cytotoxicity in the midgut of larvae and the induction of oxidative stress after 24 and 48 h of treatment, as indicated by the total protein, Cu-Zn SOD, CAT, and MDA contents. For the first time, cell damage in the reproductive parts of the ovaries of female flies, as well as in the accessory glands and testes of male flies, has been observed. Furthermore, a decline in reproductive health was noted, resulting in decreased fertility among the flies. By analyzing stress-related genes such as hsp83, hsp70, hsp60, and hsp26, we detected elevated expression of hsp83 and hsp70. Our study identified hsp83 as a specific biomarker for detecting early redox changes in cells caused by PET microplastics in all the treated groups, helping to elucidate the primary defense mechanism against PET microplastic toxicity. This study offers foundational insights into the emerging environmental threats posed by microplastics, revealing discernible alterations at the genetic level.

Sugarcane breeding for drought tolerance is a sustainable strategy to cope with drought. In addition to biotechnology, high-throughput phenotyping has become an emerging tool for plant breeders. The objectives of the present study were to (1) identify drought-tolerant cultivars using vegetation indices (VIs), compared to the traditional method and (2) assess the accuracy of VIs-based prediction model estimating stomatal conductance (Gs) and chlorophyll content (Chl). A field trial was arranged in a randomized complete block design, consisting of seven cultivars of sugarcane. At the tillering and elongation stages, irrigation was withheld, and then furrow irrigation was applied to relieve sugarcane from stress. The physiological assessment measuring Gs and Chl using a handheld device and VIs were recorded under stress and recovery periods. The results showed that the same cultivars were identified as drought-tolerant cultivars when VIs and traditional methods were used for identification. Likewise, the results derived from genotype by trait biplot and heatmap were comparable, in which TCP93-4245 and CP72-1210 cultivars were classified as tolerant cultivars, while sensitive cultivars were CP06-2400 and CP89-2143 for both physiological parameters and VIs-based identification. In the prediction model, the random forest outperformed linear models in predicting the performance of cultivars in untested crops/environments for both Gs and Chl. In contrast, it underperformed linear models in the tested crops/environments. The identification of tolerant cultivars through prediction models revealed that at least two out of three cultivars had consistent rankings in both measured and predicted outcomes for both traits. This study shows the possibility of using UAS mounted with sensors to assist plant breeders in their decision-making.

In the pursuit of sustainable agriculture, efficient water management remains crucial, with growers relying on advanced techniques for informed decision-making. Cotton yield prediction, a critical aspect of agricultural planning, benefits from cutting-edge technologies. However, traditional methods often struggle to capture the nuanced complexities of crop health and growth. This study introduces a novel approach to cotton yield prediction, leveraging the synergy between Unmanned Aerial Vehicles (UAVs) and scale-aware convolutional neural networks (CNNs). The proposed model seeks to harness the spatiotemporal dynamics inherent in high-resolution UAV imagery to improve the accuracy of the cotton yield prediction. The CNN component adeptly extracts spatial features from UAV-derived imagery, capturing intricate details related to crop health and growth, modeling temporal dependencies, and facilitating the recognition of trends and patterns over time. Research experiments were carried out in a cotton field at the USDA-ARS Cropping Systems Research Laboratory (CSRL) in Lubbock, Texas, with three replications evaluating four irrigation treatments (rainfed, full irrigation, percent deficit of full irrigation, and time delay of full irrigation) on cotton yield. The prediction revealed that the proposed CNN regression models outperformed conventional CNN models, such as AlexNet, CNN-3D, CNN-LSTM, ResNet. The proposed CNN model showed state-of-art performance at different image scales, with the R2 exceeding 0.9. At the cotton row level, the mean absolute error (MAE) and mean absolute percentage error (MAPE) were 3.08 pounds per row and 7.76%, respectively. At the cotton grid level, the MAE and MAPE were 0.05 pounds and 10%, respectively. This shows the proposed model’s adaptability to the dynamic interplay between spatial and temporal factors that affect cotton yield. The authors conclude that integrating UAV-derived imagery and CNN regression models is a potent strategy for advancing precision agriculture, providing growers with a powerful tool to optimize cultivation practices and enhance overall cotton productivity.

Benign and low-grade malignant bone tumours are often treated with curettage and filling of the resultant defect using any of a number of materials, including autologous bone grafts, allografts, or synthetic materials. The objective of this study was to report our experience using a synthetic bone graft substitute in these patients. Ten consecutive cases (four males, six females; mean age, 36 years) of benign bone tumours were treated surgically at a tertiary musculoskeletal oncology centre, between 2019 and 2021. Following curettage, the contained defects were managed with injectable beta-tricalcium phosphate/calcium sulfate (GeneX; Biocomposites Ltd., Keele, UK). The desired outcomes were early restoration of function and radiographic evidence of healing. No other graft materials were used in any of the patients. The mean follow-up was 24 months (range, 20–30 months). All patients in this series (100%) demonstrated radiographic evidence of healing and resumed their daily living activities. There were no tumour recurrences and no complications were encountered with the use of GeneX. In patients with contained defects following curettage of benign bone tumours, we found GeneX to be a safe and effective filling agent. These findings contrast with some existing studies that have reported local complications with the use of injectable beta-tricalcium phosphate/calcium sulfate.

Cell therapies derived from induced pluripotent stem cells (iPSCs) offer a promising avenue in the field of regenerative medicine due to iPSCs’ expandability, immune compatibility, and pluripotent potential. An increasing number of preclinical and clinical trials have been carried out, exploring the application of iPSC-based therapies for challenging diseases, such as muscular dystrophies. The unique syncytial nature of skeletal muscle allows stem/progenitor cells to integrate, forming new myonuclei and restoring the expression of genes affected by myopathies. This characteristic makes genome-editing techniques especially attractive in these therapies. With genetic modification and iPSC lineage specification methodologies, immune-compatible healthy iPSC-derived muscle cells can be manufactured to reverse the progression of muscle diseases or facilitate tissue regeneration. Despite this exciting advancement, much of the development of iPSC-based therapies for muscle diseases and tissue regeneration is limited to academic settings, with no successful clinical translation reported. The unknown differentiation process in vivo, potential tumorigenicity, and epigenetic abnormality of transplanted cells are preventing their clinical application. In this review, we give an overview on preclinical development of iPSC-derived myogenic cell transplantation therapies including processes related to iPSC-derived myogenic cells such as differentiation, scaling-up, delivery, and cGMP compliance. And we discuss the potential challenges of each step of clinical translation. Additionally, preclinical model systems for testing myogenic cells intended for clinical applications are described.

In the present study, we sought to develop materials applicable to personal and collective protection equipment to mitigate SARS-CoV-2. For this purpose, AgNPs were synthesized and stabilized into electrospinning nanofiber matrices (NMs) consisting of poly(vinyl alcohol) (PVA), chitosan (CHT), and poly-ε-caprolactone (PCL). Uniaxial nanofibers of PVA and PVA/CHT were developed, as well as coaxial nanofibers of PCL[PVA/CHT], in which the PCL works as a shell and the blend as a core. A crucial aspect of the present study is the in situ synthesis of AgNPs using PVA as a reducing and stabilizing agent. This process presents few steps, no additional toxic reducing agents, and avoids the postloading of drugs or the posttreatment of NM use. In general, the in situ synthesized AgNPs had an average size of 11.6 nm, and the incorporated nanofibers had a diameter in the range of 300 nm, with high uniformity and low polydispersity. The NM’s spectroscopic, thermal, and mechanical properties were appropriate for the intended application. Uniaxial (PVA/AgNPs and PVA/CHT/AgNPs) and coaxial (PCL[PVA/CHT/AgNPs]) NMs presented virucidal activity (log’s reduction ≥ 5) against mouse hepatitis virus (MHV-3) genus Betacoronavirus strains. In addition to that, the NMs did not present cytotoxicity against fibroblast cells (L929 ATCC® CCL-1TM lineage).

Second-generation biorefinery refers to the production of different types of biofuels, biomaterials, and biochemicals by using agri-based and other lignocellulosic biomasses as substrates, which do not compete with arable lands, water for irrigation, and food supply. From the perspective of transportation fuels, second-generation bioethanol plays a crucial role in minimizing the dependency on fossil-based fuels, especially gasoline. Significant efforts have been invested in the research and development of second-generation bioethanol for commercialization in both developing and developed countries. However, in different developing countries like India, commercialization of second-generation bioethanol has been obstructed despite the abundance and variety of agricultural feedstocks. This commercial obstruction was majorly attributed to the recalcitrance of the feedstock, by-product management, and marginal subsidies compared to other nations. This article reviews the major roadblocks to the viability and commercialization of second-generation biofuels, especially bioethanol in India and a few other leading developed and developing nations. This article also reviews the biomass availability, technological advancements, investments, policies, and scale-up potential for biorefineries. A thorough discussion is made on the prospects and barriers to research, development, and demonstration as well as strengths, weaknesses, opportunities, and threats for the commercialization of second-generation bioethanol.

Layer-by-layer (LbL) immobilization of DNA aptamers in the realm of electrochemical detection of heavy metal ions (HMIs) offers an enhancement in specificity, sensitivity, and low detection limits by leveraging the cross-reactivity obtained from multiple interactions between immobilized aptamers and developed material surfaces. In this research, we present a LbL approach for the immobilization of thiol- and amino-modified DNA aptamers on a Ag-incorporated cobalt-succinate metal–organic framework (MOF) (Ag@Co-Succinate) to achieve a cross-reactive effect on the electrochemical behavior of the sensor. The solvothermal method was utilized to synthesize Ag@Co-Succinate, which was also characterized through various techniques to elucidate its structure, morphology, and presence of functional groups, confirming its suitability as a host matrix for immobilizing both aptamers. The Ag@Co-Succinate aptasensor exhibited extraordinary sensitivity and selectivity towards Hg(II) ions in electrochemical detection, attributed to the unique binding properties of the immobilized aptamers. The exceptional limit of detection of 0.3 nM ensures the sensor’s suitability for trace-level Hg(II) detection in various environmental and analytical applications. Furthermore, the developed sensor demonstrated outstanding repeatability, highlighting its potential for long-term and reliable monitoring of Hg(II).

This study aims to develop a novel retention method combining the retrievability of the screw retention method with the ideal occlusal table and the aesthetic capability of cement retention. Coping was developed to have lateral screw access, allowing the screw to lock the coping using lateral forces from screw tightening and friction between the tip of the screw and the sandblasted surface of an abutment. Sandblasting parameters varied based on particle size. The results show a positive correlation to surface roughness and indicate a positive correlation to retention force. The highest surface roughness and retention force result was shown by groups that were sandblasted using 686 μm of aluminum oxide. Experiments on the tightening strength of 48 subjects measured in simulated conditions similar to the assembly conditions of lateral screw retention implants resulted in a mean of 69.75 Nmm with the highest and lowest values of 120.67 Nmm and 34.67 Nmm. This result became the basis of tightening torque variation. Each group’s retention capability is measured and compared to cement-retained dental implants. The results show that the tightening torque correlates positively with retention force, with the highest average retention score showed by lateral screws retained under a tightening torque of 200 Nmm—317.87 N higher than cement-retained screws.

Individualized survival prognostic models for symptomatic patients with appendicular metastatic bone disease are key to guiding clinical decision-making for the orthopedic surgeon. Several prognostic models have been developed in recent years; however, most orthopedic surgeons have not incorporated these models into routine practice. This is possibly due to uncertainty concerning their accuracy and the lack of comparison publications and recommendations. Our aim was to conduct a review and quality assessment of these models. A computerized literature search in MEDLINE, EMBASE and PubMed up to February 2022 was done, using keywords: “Bone metastasis”, “survival”, “extremity” and “prognosis”. We evaluated each model’s performance, assessing the estimated discriminative power and calibration accuracy for the analyzed patients. We included 11 studies out of the 1779 citations initially retrieved. The 11 studies included seven different models for estimating survival. Among externally validated survival prediction scores, PATHFx 3.0, 2013-SPRING and potentially Optimodel were found to be the best models in terms of performance. Currently, it is still a challenge to recommend any of the models as the standard for predicting survival for these patients. However, some models show better performance status and other quality characteristics. We recommend future, large, multicenter, prospective studies to compare between PATHfx 3.0, SPRING 2013 and OptiModel using the same external validation dataset.

Previous studies assessed the involvement and impact of periodontal bacteria in preeclamptic women with chronic periodontitis. To explore further, the current study aimed to associate periodontal viruses and bacteria with mir155 levels in placental tissues of preeclamptic women with generalized chronic periodontitis. Four-hundred 45 pregnant women, 18–35 years of age, were selected and divided into four groups (controls, A, B, and C) where the Controls included 145 systemically and periodontally healthy pregnant women Group A-100 systemically healthy pregnant women with chronic periodontitis, Group B- 100 preeclamptic women with chronic periodontitis, Group C- 100 preeclamptic women without chronic periodontitis. Age, BMI, SES, and periodontal parameters such as PI, BOP, PPD, and CAL were noted. Periodontal pathogens such as Tf, Td, Pg, Pi, Fn, HSV, EBV, and HCMV were tested in subgingival plaque, placental tissues, and mir155. We observed that PI, BOP, PPD, CAL, Tf, and EBV were highly significant in Group B. We found a higher number of periodontal bacteria, viruses, and mir 155 in Group B showing a higher risk of preeclampsia. More genetic studies in this field are advised to ascertain the role of periodontopathogens and mir 155 in preeclampsia and periodontal inflammation. What is already known on this subject? Periodontal diseases pose an increased risk of developing preeclampsia and delivering preterm and/or low-birth-weight babies. What do the results of this study add? Periodontal variables such as PI, pocket depth, BOP, and clinical attachment levels, were found to be increased in the preeclamptic women with chronic periodontitis. The significant difference was seen in the relative fold expression of mir155 with higher gene expression of mir155 in groups B and A as compared to group C and controls. What are the implications of these findings for clinical practice and/or further research? In our study, mir155 correlation with the periodontal parameters and periodontal pathogens further strengthen the evidence of periodontal inflammation as a risk of preeclampsia in pregnant women especially when associated with chronic periodontitis. mir155 can be considered to be one of the genetic biomarkers and can be used as a diagnostic tool for the early detection of PE.

Lignin, a naturally occurring aromatic polymer, possesses a range of biological functions [...]

Heavy metal ions (HMIs) in drinking water result from industrialization and can cause a nuisance to the environment. Due to their toxicity and carcinogenic tendencies toward humans, determining HMIs remains challenging. This study focuses on creating a cutting-edge electrochemical sensor with unprecedented sensitivity to lead (Pb(II)). In the present investigation, we have hydrothermally produced lanthanum porous coordination polymer (La-TMA), which was further modified with chromium (Cr) nanoparticles, characterized with structural, morphological, electrochemical, and spectroscopic techniques, and used as a sensing material. The differential pulse voltammogram pattern of the chromium-modified lanthanum porous coordination polymer (Cr@La-TMA) sensor indicates an affinity for Pb(II). Sensing parameters such as sensitivity, selectivity, and linearity have been investigated. The Cr@La-TMA sensor shows selectivity towards Pb(II), which is also validated by the interference study for various analytes such as Cd(II), Hg(II), Cu(II), Cr(II), and Fe(II). The sensor exhibited excellent linearity for the concentration range of 1 nM to 10 nM with a limit of detection of 1 nM, which is below the maximum contamination level (MCL) suggested by the United States Environmental Protection Agency (US-EPA) and World Health Organization (WHO). The proposed sensor would be incredibly useful for the real-time monitoring of heavy metal ions.

Analysing and understanding donor behaviour in nonprofit organisations (NPOs) is challenging due to the lack of human and technical resources. Machine learning (ML) techniques can analyse and understand donor behaviour at a certain level; however, it remains to be seen how to build and design an artificial-intelligence-enabled decision-support system (AI-enabled DSS) to analyse donor behaviour. Thus, this paper proposes an AI-enabled DSS conceptual design to analyse donor behaviour in NPOs. A conceptual design is created following a design science research approach to evaluate an AI-enabled DSS’s initial DPs and features to analyse donor behaviour in NPOs. The evaluation process of the conceptual design applied formative assessment by conducting interviews with stakeholders from NPOs. The interviews were conducted using the Appreciative Inquiry framework to facilitate the process of interviews. The evaluation of the conceptual design results led to the recommendation for efficiency, effectiveness, flexibility, and usability in the requirements of the AI-enabled DSS. This research contributes to the design knowledge base of AI-enabled DSSs for analysing donor behaviour in NPOs. Future research will combine theoretical components to introduce a practical AI-enabled DSS for analysing donor behaviour in NPOs. This research is limited to such an analysis of donors who donate money or volunteer time for NPOs.

The detection of ammonia is very crucial for the welfare of modern society because of its hazardous effect on the environment and human beings. High response time is one of the serious concerns of most of the ammonia detectors reported so far in the literature. This issue has been comprehensively addressed in the present investigation. Herein, the solvothermally synthesized Cu-BTC was combined with the 5 wt%, 10 wt% and 20 wt% of partially reduced graphene oxide (rGO). The structural, spectroscopic, morphological and electrical studies of as-synthesized CuBTC@rGO-5wt%, CuBTC@rGO-10wt% and CuBTC@rGO-20wt% were done by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, atomic force microscopy, and current-voltage (I-V) characterization. The chemiresistive sensor based on Cu-BTC@rGO was developed on a copper-coated glass electrode via the shadow mask technique. It shows excellent sensing properties for CuBTC@rGO-10wt% in a range of 10 ppm to 80 ppm with a high stability of up to 30 days, good linearity, and excellent response/recovery time, i.e., 84 s and 125 s, respectively. The limit of detection has been established as 10 ppm, which is below the maximum residue limit established by the OSHA (Occupational Safety and Health Administration).

Lipschitz mapping appears inevitably in many branches of mathematics, especially in functional analysis, and leads to the study of new results in metric fixed point theory. Goebel and Sims (resp. Goebel and Japon-Pineda) introduced a class of the Lipschitz mappings termed as (α,p)-Liptschitz mappings and studied not only the modified form of the Lipschitz condition, but also the behavior of a finite number of their iterates. The purpose of this paper is to discuss the various types of (α,p)-contractions with cyclic representation that extend the results due to Banach, Kannan, and Chatterjea. Moreover, based on such types of contractions and the property of symmetry, we obtain some related fixed-point results in the setting of metric spaces. Some examples are studied to illustrate the validity of our obtained results. As an application of our results, we establish the existence of the solution to a class of Fredholm integral equations.

Propolis has numerous biological properties and technological potential, but its low solubility in water makes its use quite difficult. With the advent of nanotechnology, better formulations with propolis, such as nanopropolis, can be achieved to improve its properties. Nanopropolis is a natural nanomaterial with several applications, including in the maintenance of food quality. Food safety is a global public health concern since food matrices are highly susceptible to contamination of various natures, leading to food loss and transmission of harmful foodborne illness. Due to their smaller size, propolis nanoparticles are more readily absorbed by the body and have higher antibacterial and antifungal activities than common propolis. This review aims to understand whether using propolis with nanotechnology can help preserve food and prevent foodborne illness. Nanotechnology applied to propolis formulations proved to be effective against pathogenic microorganisms of industrial interest, making it possible to solve problems of outbreaks that can occur through food.

Microplastics are readily available in the natural environment. Due to the pervasiveness of microplastic pollution, its effects on living organisms necessitate further investigation. The size, time of exposure, and amount of microplastic particles appear to be the most essential factor in determining their toxicological effects, either organismal or sub-organismal. For our research work, we preferred to work on a terrestrial model organism Drosophila melanogaster (Oregon R+). Therefore, in the present study, we characterized 2–100 µm size PET microplastic and confirmed its accumulation in Drosophila, which allowed us to proceed further in our research work. At larger dosages, research on locomotory activities such as climbing, jumping, and crawling indicated a decline in physiological and neuromuscular functions. Our studies also determined retarded development in flies and decreased survival rate in female flies after exposure to the highest concentration of microplastics. These experimental findings provide insight into the possible potential neurotoxic effects of microplastics and their detrimental effects on the development and growth of flies.

Nanotechnology holds significant ameliorative potential against neurodegenerative diseases, as it can protect the therapeutic substance and allow for its sustained release. In this study, the reducing and capping agents of Urtica dioica (UD), Matricaria chamomilla (MC), and Murraya koenigii (MK) extracts were used to synthesize bio-mediated zinc oxide nanoparticles (ZnO-NPs) against bacteria (Staphylococcus aureus and Escherichia coli) and against rotenone-induced toxicities in D. melanogaster for the first time. Their optical and structural properties were analyzed via FT-IR, DLS, XRD, EDS, SEM, UV–Vis, and zeta potential. The antioxidant and antimicrobial properties of the fabricated ZnO-NPs were evaluated employing cell-free models (DPPH and ABTS) and the well diffusion method, respectively. Rotenone (500 µM) was administered to Drosophila third instar larvae and freshly emerged flies for 24–120 h, either alone or in combination with plant extracts (UD, MC, an MK) and their biogenic ZnO-NPs. A comparative study on the protective effects of synthesized NPs was undertaken against rotenone-induced neurotoxic, cytotoxic, and behavioral alterations using an acetylcholinesterase inhibition assay, dye exclusion test, and locomotor parameters. The findings revealed that among the plant-derived ZnO-NPs, MK-ZnO NPs exhibit strong antimicrobial and antioxidant activities, followed by UD-ZnO NPs and MC-ZnO NPs. In this regard, ethno-nano medicinal therapeutic uses mimic similar effects in D. melanogaster by suppressing oxidative stress by restoring biochemical parameters (AchE and proteotoxicity activity) and lower cellular toxicity. These findings suggest that green-engineered ZnO-NPs have the potential to significantly enhance outcomes, with the promise of effective therapies for neurodegeneration, and could be used as a great alternative for clinical development.

Bronchial asthma is a widely prevalent illness that substantially impacts an individual’s health standard worldwide and has a significant financial impact on society. Global guidelines for managing asthma do not recommend the routine use of antimicrobial agents because most episodes of the condition are linked to viral respiratory tract infections (RTI), and bacterial infection appears to have an insignificant impact. However, antibiotics are recommended when there is a high-grade fever, a consolidation on the chest radiograph, and purulent sputum that contains polymorphs rather than eosinophils. Managing acute bronchial asthma with sepsis, specifically the choice of whether or not to initiate antimicrobial treatment, remains difficult since there are currently no practical clinical or radiological markers that allow for a simple distinction between viral and bacterial infections. Researchers found that serum procalcitonin (PCT) values can efficiently and safely minimize antibiotic usage in individuals with severe acute asthma. Again, the clinical manifestations of acute asthma and bacterial RTI are similar, as are frequently used test values, like C-reactive protein (CRP) and white blood cell (WBC) count, making it harder for doctors to differentiate between viral and bacterial infections in asthma patients. The role and scope of each biomarker have not been precisely defined yet, although they have all been established to aid healthcare professionals in their diagnostics and treatment strategies.

The human commensal yeast Candida albicans is pathogenic and results in a variety of mucosal and deep tissue problems when the host is immunocompromised. Candida exhibits enormous metabolic flexibility and dynamic morphogenetic transition to survive under host niche environmental conditions and to cause virulence. The amino sugar N-acetylglucosamine (GlcNAc) available at the host infection sites, apart from acting as an extremely good carbon and nitrogen source, also induces cellular signalling in this pathogen. In C. albicans, GlcNAc performs multifaceted roles, including GlcNAc scavenging, GlcNAc import and metabolism, morphogenetic transition (yeast—hyphae and white—opaque switch), GlcNAc-induced cell death (GICD), and virulence. Understanding the molecular mechanism(s) involved in GlcNAc-induced cellular processes has become the main focus of many studies. In the current study, we focused on GlcNAc-induced metabolic changes associated with phenotypic changes. Here, we employed gas chromatography–mass spectrometry (GC–MS), which is a high-throughput and sensitive technology, to unveil global metabolomic changes that occur in GlcNAc vs. glucose grown conditions in Candida cells. The morphogenetic transition associated with metabolic changes was analysed by high-resolution field emission scanning electron microscopy (FE-SEM). Metabolite analysis revealed the upregulation of metabolites involved in the glyoxylate pathway, oxidative metabolism, and fatty acid catabolism to probably augment the synthesis of GlcNAc-induced hypha-specific materials. Furthermore, GlcNAc-grown cells showed slightly more sensitivity to amphotericin B treatment. These results all together provide new insights into the development of antifungal therapeutics for the control of candidiasis in humans.

Background: Diabetic ketoacidosis (DKA) is a life-threatening acute complication of diabetes mellitus and can lead to patient demise if not immediately treated. From the recent literature, the diabetic ketoacidosis mortality rate, depending on age, is 2–5%. Insulin discontinuation and infection remain the two most common triggers for diabetic ketoacidosis. About 50% of cases of ketoacidosis result from bacterial infections like urinary tract infections and pneumonia. It is also important to diagnose the presence of infection in diabetic ketoacidosis patients to prevent the excessive use of antibiotics, which may lead to antibiotic resistance. Although performing bacterial culture is confirmatory for the presence or absence of bacterial infection, the time required to obtain the result is long. At the same time, emergency treatment needs to be started as early as possible. Methods: This narrative review examines various septic markers to identify the appropriate tools for diagnosis and to distinguish between diabetic ketoacidosis with and without infection. Electronic databases were searched using the Google engine with the keywords “Diabetes Mellitus”, “Diabetic Ketoacidosis”, “Infection with Diabetic Ketoacidosis”, “biomarkers for infection in Diabetic Ketoacidosis”, “Procalcitonin”, “Inflammatory cytokines in DKA”, “Lactic acidosis in DKA”, and “White blood cell in infection in DKA”. Results: This narrative review article presents the options for diagnosis and also aims to create awareness regarding the gravity of diabetic ketoacidosis with infection and emphasizes the importance of early diagnosis for appropriate management. Diabetes mellitus is a clinical condition that may lead to several acute and chronic complications. Acute diabetic ketoacidosis is a life-threatening condition in which an excess production of ketone bodies results in acidosis and hypovolemia. Infection is one of the most common triggers of diabetic ketoacidosis. When bacterial infection is present along with diabetic ketoacidosis, the mortality rate is even higher than for patients with diabetic ketoacidosis without infection. The symptoms and biomarkers of diabetic ketoacidosis are similar to that of infection, like fever, C reactive protein, and white blood cell count, since both create an environment of systemic inflammation. It is also essential to distinguish between the presence and absence of bacterial infection to ensure the appropriate use of antibiotics and prevent antimicrobial resistance. A bacterial culture report is confirmatory for the existence of bacterial infection, but this may take up to 24 h. Diagnosis needs to be performed approximately in the emergency room upon admission since there is a need for immediate management. Therefore, researching the possible diagnostic tools for the presence of infection in diabetic ketoacidosis patients is of great importance. Several of such biomarkers have been discussed in this research work.

An integrated forage-legume cropping system has immense potential to address the issue of land degradability. It provides a critical understanding of the capacity of diversified species mixes vs. monocultures to boost forage production and the dynamics of soil organic carbon (SOC) and phosphorus (P). In this study, we assessed the performance of Napier Bajra Hybrid (NBH) (Pennisetum glaucum × P. purpureum) + cowpea (Vigna unguiculata) and tri-specific hybrid (TSH) (P. glaucum × P. purpureum × P. squamulatum) + cluster bean (Cyamopsis tetragonoloba) as compared to monocultures of NBH and TSH. The legume equivalent yield of NBH + cowpea and TSH + cluster bean intercropping systems were found −31% and −23% higher than monoculture systems. The SOC increased by −5% in the NBH + cowpea system as compared to NBH monoculture. The carbon mineralization rates under NBH + cowpea and TSH + cluster bean were −32% and −38% lower than the NBH and TSH monoculture cropping systems, respectively. It was found that the legume intensification with the forage significantly improved the soil’s P status. The research suggested that coalescing diverse crops (e.g., grass and legume) poses enormous potential for sustaining soil health and productivity in semi-arid regions of India. This study advances the research on characterizing the crucial factors of grass-legume-based cropping systems and helps in assessing the impact of these factors on long-term sustainability.

Nuclear factor kappa beta (NF-κB) is a transcriptional factor that plays a crucial role in regulating cancer cell proliferation. Therefore, the inhibition of NF-κB activity by small molecules may be beneficial in cancer therapy. In this report, methyl-thiol-bridged oxadiazole and triazole heterocycles were synthesized via click chemistry and it was observed that the lead structure, 2-(((1-(3,4-dichlorophenyl)-1H-1,2,3-triazol-4-yl)methyl)thio)-5-(4-methoxybenzyl)-1,3,4-oxadiazole (4c), reduced the viability of MCF-7 cells with an IC50 value of 7.4 µM. Compound 4c also caused concentration-dependent loss of cell viability in chronic myelogenous leukemia (CML) cells. Furthermore, compound 4c inhibited the activation of NF-κB in human CML cells as observed by nuclear translocation and DNA binding assays. Functionally, compound 4c produced PARP cleavage and also suppressed expression of Bcl-2/xl, MMP-9, COX-2, survivin, as well as VEGF, resulting in apoptosis of CML cells. Moreover, ChIP assay showed that compound 4c decreased the binding of COX-2 to the p65 gene promoter. Detailed in silico analysis also indicated that compound 4c targeted NF-κB in CML cells. In conclusion, a novel structure bearing both triazole and oxadiazole moieties has been identified that can target NF-κB in CML cells and may constitute a potential novel drug candidate.

Pulses are a key source of dietary proteins in human nutrition. Despite several efforts to increase the production, various constraints, such as biotic and abiotic factors, threaten pulse production by various means. Bruchids (Callosobruchus spp.) are the serious issue of concern, particularly in storage conditions. Understanding host–plant resistance at morphological, biochemical and molecular levels is the best way to minimize yield losses. The 117 mungbean (Vigna radiata L. Wilczek) genotypes, including endemic wild relatives, were screened for resistance against Callosobruchus chinensis; among them, two genotypes, PRR 2008-2 and PRR 2008-2-sel, which belong to V. umbellata (Thumb.), were identified as highly resistant. The expression of antioxidants in susceptible and resistant genotypes revealed that the activity of phenylalanine ammonia lyase (PAL) was upregulated in the highly resistant wild Vigna species and lower in the cultivated susceptible genotypes, along with other biomarkers. Further, the SCoT-based genotyping revealed SCoT-30 (200 bp), SCoT-31 (1200 bp) and SCoT-32 (300 bp) as unique amplicons, which might be useful for developing the novel ricebean-based SCAR markers to accelerate the molecular breeding programme.

Metabolic syndrome is a multifaceted pathophysiologic condition that is largely caused by an imbalance between caloric intake and energy expenditure. The pathogenesis of metabolic syndrome is determined by an individual’s genetic/epigenetics and acquired factors. Natural compounds, notably plant extracts, have antioxidant, anti-inflammatory, and insulin-sensitizing properties and are considered to be a viable option for metabolic disorder treatment due to their low risk of side effects. However, the limited solubility, low bioavailability, and instability of these botanicals hinder their performance. These specific limitations have prompted the need for an efficient system that reduces drug degradation and loss, eliminates unwanted side effects, and boosts drug bioavailability, as well as the percentage of the drug deposited in the target areas. The quest for an enhanced (effective) drug delivery system has led to the formation of green-engineered nanoparticles, which has increased the bioavailability, biodistribution, solubility, and stability of plant-based products. The unification of plant extracts and metallic nanoparticles has helped in the development of new therapeutics against metabolic disorders such as obesity, diabetes mellitus, neurodegenerative disorders, non-alcoholic fatty liver, and cancer. The present review outlines the pathophysiology of metabolic diseases and their cures with plant-based nanomedicine.

In the present paper, we introduce the notion of C*-algebra-valued partial modular metric space satisfying the symmetry property that generalizes partial modular metric space, C*-algebra-valued partial metric space, and C*-algebra-valued modular metric space and discuss it with examples. Some fixed point results using (ϕ,MF)-contraction mapping are discussed in such space. In addition, we study the stability of obtained results in the spirit of Ulam and Hyers. As an application, we also provide the existence and uniqueness of the solution for a system of Fredholm integral equations.

A program’s bug, fault, or mistake that results in unintended results is known as a software defect or fault. Software flaws are programming errors due to mistakes in the requirements, architecture, or source code. Finding and fixing bugs as soon as they arise is a crucial goal of software development that can be achieved in various ways. So, selecting a handful of optimal subsets of features from any dataset is a prime approach. Indirectly, the classification performance can be improved through the selection of features. A novel approach to feature selection (FS) has been developed, which incorporates the Golden Jackal Optimization (GJO) algorithm, a meta-heuristic optimization technique that draws on the hunting tactics of golden jackals. Combining this algorithm with four classifiers, namely K-Nearest Neighbor, Decision Tree, Quadrative Discriminant Analysis, and Naive Bayes, will aid in selecting a subset of relevant features from software fault prediction datasets. To evaluate the accuracy of this algorithm, we will compare its performance with other feature selection methods such as FSDE (Differential Evolution), FSPSO (Particle Swarm Optimization), FSGA (Genetic Algorithm), and FSACO (Ant Colony Optimization). The result that we got from FSGJO is great for almost all the cases. For many of the results, FSGJO has given higher classification accuracy. By utilizing the Friedman and Holm tests, to determine statistical significance, the suggested strategy has been verified and found to be superior to prior methods in selecting an optimal set of attributes.

The investigation aimed at assessing a comparative study on the production and characterization of ACE inhibitory, anti-diabetic, and anti-inflammatory activities, along with the production of ACE inhibitory and anti-diabetic peptides through the fermentation of buffalo and camel milk by Limosilactobacillus fermentum (KGL4) and Saccharomyces cerevisiae (WBS2A). The angiotensin-converting enzyme (ACE) inhibitory and anti-diabetic properties were evaluated at particular time intervals (12, 24, 36, and 48 h) at 37 °C, and we discovered maximum activity at 37 °C after 48 h of incubation. The maximum ACE inhibitory, lipase inhibitory activities, alpha-glucosidase inhibitory, and alpha-amylase inhibitory activities were found in the fermented camel milk (77.96 ± 2.61, 73.85 ± 1.19, 85.37 ± 2.15, and 70.86 ± 1.02), as compared to the fermented buffalo milk (FBM) (75.25 ± 1.72, 61.79 ± 2.14, 80.09 ± 0.51, and 67.29 ± 1.75). Proteolytic activity was measured with different inoculation rates (1.5%, 2.0%, and 2.5%) and incubation times (12, 24, 36, and 48 h) to optimize the growth conditions. Maximum proteolysis was found at a 2.5% inoculation rate and at a 48 h incubation period in both fermented buffalo (9.14 ± 0.06) and camel milk (9.10 ± 0.17). SDS-PAGE and 2D gel electrophoresis were conducted for protein purification. The camel and buffalo milk that had not been fermented revealed protein bands ranging from 10 to 100 kDa and 10 to 75 kDa, respectively, whereas all the fermented samples showed bands ranging from 10 to 75 kDa. There were no visible protein bands in the permeates on SDS-PAGE. When fermented buffalo and camel milk were electrophoresed in 2D gel, 15 and 20 protein spots were detected, respectively. The protein spots in the 2D gel electrophoresis ranged in size from 20 to 75 kDa. To distinguish between different peptide fractions, water-soluble extract (WSE) fractions of ultrafiltration (3 and 10 kDa retentate and permeate) of fermented camel and buffalo milk were employed in RP-HPLC (reversed-phase high-performance liquid chromatography). The impact of fermented buffalo and camel milk on inflammation induced by LPS (lipopolysaccharide) was also investigated in the RAW 264.7 cell line. Novel peptide sequences with ACE inhibitory and anti-diabetic properties were also analyzed on the anti-hypertensive database (AHTDB) and bioactive peptide (BIOPEP) database. We found the sequences SCQAQPTTMTR, EMPFPK, TTMPLW, HPHPHLSFMAIPPK, FFNDKIAK, ALPMHIR, IPAVFK, LDQWLCEK, and AVPYPQR from the fermented buffalo milk and the sequences TDVMPQWW, EKTFLLYSCPHR, SSHPYLEQLY, IDSGLYLGSNYITAIR, and FDEFLSQSCAPGSDPR from the fermented camel milk.

Magnetic sensors are key elements in many industrial, security, military, and biomedical applications. Heusler alloys are promising materials for magnetic sensor applications due to their high spin polarization and tunable magnetic properties. The dynamic field range of magnetic sensors is strongly related to the perpendicular magnetic anisotropy (PMA). By tuning the PMA, it is possible to modify the sensing direction, sensitivity and even the accuracy of the magnetic sensors. Here, we report the tuning of PMA in a Co2MnGa Heusler alloy film via argon (Ar) ion irradiation. MgO/Co2MnGa/Pd films with an initial PMA were irradiated with 30 keV 40Ar+ ions with fluences (ions·cm−2) between 1 × 1013 and 1 × 1015 Ar·cm−2, which corresponds to displacement per atom values between 0.17 and 17, estimated from Monte-Carlo-based simulations. The magneto optical and magnetization results showed that the effective anisotropy energy (Keff) decreased from ~153 kJ·m−3 for the un-irradiated film to ~14 kJ·m−3 for the 1 × 1014 Ar·cm−2 irradiated film. The reduced Keff and PMA are attributed to ion-irradiation-induced interface intermixing that decreased the interfacial anisotropy. These results demonstrate that ion irradiation is a promising technique for shaping the PMA of Co2MnGa Heusler alloy for magnetic sensor applications.

Human epidermal growth factor receptor 2 (HER2)-positive breast cancer exhibits early relapses, poor prognoses, and high recurrence rates. Herein, a JNK-targeting compound has been developed that may be of utility in HER2-positive mammary carcinoma. The design of a pyrimidine-and coumarin-linked structure targeting JNK was explored and the lead structure PC-12 [4-(3-((2-((4-chlorobenzyl)thio) pyrimidin-4-yl)oxy)propoxy)-6-fluoro-2H-chromen-2-one (5d)] was observed to selectively inhibit the proliferation of HER2-positive BC cells. The compound PC-12 exerted DNA damage and induced apoptosis in HER-2 positive BC cells more significantly compared to HER-2 negative BC cells. PC-12 induced PARP cleavage and down-regulated the expression of IAP-1, BCL-2, SURVIVIN, and CYCLIN D1 in BC cells. In silico and theoretical calculations showed that PC-12 could interact with JNK, and in vitro studies demonstrated that it enhanced JNK phosphorylation through ROS generation. Overall, these findings will assist the discovery of new compounds targeting JNK for use in HER2-positive BC cells.

Reliable regional-scale permeability data and minimum sustained injectivity rate estimates are key parameters required to mitigate economic risk in the site selection, design, and development of commercial-scale carbon sequestration projects, but are seldom available. We used extensive publicly available disposal well data from over 4000 disposal wells to assess and history-match regional permeability estimates and provide the frequency distribution for disposal well injection rates in each of 66 disposal formations in the Alberta Basin. We then used core data and laboratory analyses from over 3000 cores to construct 3D geological, geomechanical and petrophysical models for 22 of these disposal formations. We subsequently used these models and the history-matched regional permeability estimates to conduct coupled geomechanical and reservoir simulation modeling (using the ResFrac™, Palo Alto, CA, USA, numerical simulator) to assess: (i) well performance in each formation when injecting carbon dioxide for a 20-year period; (ii) carbon dioxide saturation and reservoir response at the end of the 20-year injection period; (iii) reliability of our simulated rates compared to an actual commercial sequestration project. We found that: (i) the injection rate from our simulations closely matched actual performance of the commercial case; (ii) only 7 of the 22 disposal formations analyzed appeared capable of supporting carbon dioxide injectors operating at greater than 200,000 tons per year/well; (iii) three of these formations could support injectors operating at rates comparable to the successful commercial-scale case; (iv) carbon dioxide presence and a formation pressure increase of at least 25% above pre-injection pressure can be expected at the boundaries of the (12 km × 12 km) model domain at the end of 20 years of injection.

Acetaminophen (APAP) is the most commonly used nonprescription antipyretic-analgesic drug. This medication is thought to be safe at the suggested dosage (4 g/24 h), but its overdose (up to 2.5 g/kg) can cause severe injuries to the human body, including renal injury. APAP has various toxic effects on nephrons, as it leads to an excessive free radical generation that, in turn, results in a disturbance in the redox homeostasis of cells, causing oxidative stress. To replenish this oxidative stress, there is an ultimate urge for natural therapies that can retain the cellular homeostasis of nephrons by diminishing the overdose impression of acetaminophen. The principle objective of this work is to appraise nephrotoxicity due to APAP and its amelioration through the antioxidant properties of aqueous extracts of selected medicinal plants: Urtica dioica, Capsella bursa-pastoris, and Inula racemosa (UD, CBP, and IR, respectively). The pH stability of the nutraceuticals used was examined by determining the impact of pH 4, pH 7 and pH 9 on the DPPH radical scavenging activity of aqueous plant extracts. Gas chromatography-Mass spectroscopy (GC–MS) analytical technique was performed to determine the volatile organic phytochemical profiles of all three medicinal plants. Male Swiss albino mice were used for the present investigation. The animals were distributed into five groups of (n = 6), a total of 30 mice, for in vivo analysis. Group 1 served as the control group; group 2 received a single IP dose of APAP (600 mg/kg); group 3 received APAP pretreated with UD (300 mg/kg); group 4 received APAP pretreated with CBP (300 mg/kg); and group 5 received APAP pretreated with IR (300 mg/kg). Overdose of the APAP- induced a significant (p < 0.05) alterations in the total protein concentration, weight and the nephrological architecture in renal tissue, as observed through biochemical assays and histopathological examinations. Due to nephrotoxicity, there was a substantial (p < 0.05) drop in body weight and total protein contents in the APAP alone group when compared to the treatment groups. There was remarkable protection against APAP-induced alterations in the total protein of renal homogenate in the treatment groups. Histopathological analysis (H&E staining) of the mice kidneys indicated severe deterioration in the APAP alone group, whereas the therapy groups showed considerable nephroprotection towards APAP-induced abnormalities. The biochemical findings and histopathological study of the kidneys revealed that the herbal extracts (UD, CBP, and IR) have a nephroprotective potential against APAP-induced nephropathy. The trend of efficacy was observed as UD > CBP > IR. However, extensive study is needed to determine the likely ameliorative mechanism of these nutraceuticals.

In breast cancer (BC), STAT3 is hyperactivated. This study explored the design of imidazopyridine-tethered pyrazolines as a de novo drug strategy for inhibiting STAT3 phosphorylation in human BC cells. This involved the synthesis and characterization of two series of compounds namely, 1-(3-(2,6-dimethylimidazo [1,2-a]pyridin-3-yl)-5-(3-nitrophenyl)-4,5-dihydro-1H-pyrazol-1-yl)-2-(4-(substituted)piperazin-1-yl)ethanone and N-substituted-3-(2,6-dimethylimidazo[1,2-a]pyridin-3-yl)-5-(3-nitrophenyl)-4,5-dihydro-1H-pyrazoline-1-carbothioamides. Compound 3f with 2,3-dichlorophenyl substitution was recognized among the tested series as a lead structure that inhibited the viability of MCF-7 cells with an IC50 value of 9.2 μM. A dose- and time-dependent inhibition of STAT3 phosphorylation at Tyr705 and Ser727 was observed in MCF-7 and T47D cells when compound 3f was added in vitro. Calculations using density functional theory showed that the title compounds HOMOs and LUMOs are situated on imidazopyridine-pyrazoline and nitrophenyl rings, respectively. Hence, compound 3f effectively inhibited STAT3 phosphorylation in MCF-7 and T47D cells, indicating that these structures may be an alternative synthon to target STAT3 signaling in BC.