Search Results (15)

Background: Gout is a chronic inflammatory condition characterized by elevated uric acid levels in the blood, which can precipitate acute gout attacks in individuals with genetic susceptibility, existing medical conditions, and dietary influences. Genetic predispositions, comorbid medical conditions, nutritional choices, and environmental factors increasingly recognize the multifactorial etiology of the disease. Methods: Recent research has highlighted the potential of phytochemicals, particularly flavonoids, saponins, and alkaloids, to manage hyperuricemia (HUA) and its associated complications. Results: Plant’s natural compounds have garnered attention for their anti-inflammatory, antioxidant, and uric acid-lowering properties, suggesting their role in alternative and complementary medicine. Phytochemicals have demonstrated promise in mitigating gout symptoms and potentially modifying the disease course by addressing different aspects of hyperuricemia and inflammation. Herbal remedies, with their complex phytochemical profiles, offer a unique advantage by potentially complementing conventional pharmacological treatments. The integration of herbal therapies with standard medications could lead to enhanced therapeutic outcomes through synergistic effects, optimizing disease management, and improving patient quality of life. Conclusions: This review examines the current understanding of the multifaceted etiology of gout, explores the role of phytochemicals in managing hyperuricemia, and discusses the potential benefits of combining herbal remedies with conventional treatments to improve patient care and therapeutic efficacy. Full article

Puumala orthohantavirus (PUUV) is an emerging zoonotic virus endemic to Europe and Russia that causes nephropathia epidemica, a mild form of hemorrhagic fever with renal syndrome (HFRS). There are limited options for treatment and diagnosis of orthohantavirus infection, making the search for potential immunogenic candidates crucial. In the present work, various bioinformatics tools were employed to design conserved immunogenic peptides containing multiple epitopes of PUUV nucleocapsid protein. Eleven conserved peptides (90% conservancy) of the PUUV nucleocapsid protein were identified. Three conserved peptides containing multiple T and B cell epitopes were selected using a consensus epitope prediction algorithm. Molecular docking using the HPEP dock server demonstrated strong binding interactions between the epitopes and HLA molecules (ten alleles for each class I and II HLA). Moreover, an analysis of population coverage using the IEDB database revealed that the identified peptides have over 90% average population coverage across six continents. Molecular docking and simulation analysis reveal a stable interaction with peptide constructs of chosen immunogenic peptides and Toll-like receptor-4. These computational analyses demonstrate selected peptides’ immunogenic potential, which needs to be validated in different experimental systems. Full article

Potato biofortification is a comprehensive approach aimed at enhancing the nutritional content of potatoes, addressing widespread nutrient deficiencies and contributing to global food security. This systematic review examines the existing literature on various aspects of potato biofortification, encompassing genetic, agronomic, and biotechnological strategies. The review highlights the nutritional significance of potatoes, emphasizing their role as a staple food in many regions. Genetic approaches to biofortification involve the identification and use of natural variations in potato germplasm to develop varieties with elevated levels of essential nutrients. This includes targeting key micronutrients, such as iron, zinc, and vitamins, through traditional breeding methods. The review explores the genetic diversity within potato germplasm and the potential for breeding programs to develop nutrient-rich varieties. Agronomic practices play a crucial role in potato biofortification, with studies demonstrating the impact of tuber priming and the application of mineral fertilizers on nutrient concentrations in potatoes. The review delves into the intricacies of agronomic biofortification, emphasizing the importance of precise dosages and timing for optimal results. Biotechnological tools, including transgenic and non-transgenic approaches, are discussed in the context of potato biofortification. The review evaluates the efficiency and ethical considerations associated with the development of biofortified transgenic potatoes and emphasizes the significance of non-transgenic approaches in addressing consumer concerns and regulatory barriers. Overall, this systematic review provides a comprehensive overview of the current state of potato biofortification research. It synthesizes findings from diverse studies, offering insights into the potential of biofortified potatoes to address hidden hunger and contribute to improved nutritional outcomes. This review also identifies knowledge gaps and areas for future research, guiding the direction of efforts to harness the full potential of potato biofortification for global food and nutrition security. Full article

Medulloblastoma (MB) comprises four broad molecular subgroups, namely wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4, respectively, with subgroup-specific developmental origins, unique genetic profiles, distinct clinico-demographic characteristics, and diverse clinical outcomes. This is a retrospective audit of clinical outcomes in molecularly confirmed WNT-MB patients treated with maximal safe resection followed by postoperative standard-of-care risk-stratified adjuvant radio(chemo)therapy at a tertiary-care comprehensive cancer centre. Of the 74 WNT-MB patients registered in a neuro-oncology unit between 2004 to 2020, 7 patients accrued on a prospective clinical trial of treatment deintensification were excluded, leaving 67 patients that constitute the present study cohort. The median age at presentation was 12 years, with a male preponderance (2:1). The survival analysis was restricted to 61 patients and excluded 6 patients (1 postoperative mortality plus 5 without adequate details of treatment or outcomes). At a median follow-up of 72 months, Kaplan–Meier estimates of 5-year progression-free survival and overall survival were 87.7% and 91.2%, respectively. Traditional high-risk features, large residual tumour (≥1.5 cm²), and leptomeningeal metastases (M+) did not significantly impact upon survival in this molecularly characterized WNT-MB cohort treated with risk-stratified contemporary multimodality therapy. The lack of a prognostic impact of conventional high-risk features suggests the need for refined risk stratification and potential deintensification of therapy. Full article

Steelmaking is a water-intensive process. The mean water intake against each ton of steel manufactured is ascertained as between 2 and 20 m³. Primarily, the stated requirement is in the form of make-up water to compensate for evaporation and mechanical losses and does not contribute to wastewater generation. Conversely, unit operations, such as rolling, continuous casting, pickling, etc., generate highly complex wastewater rich in polycyclic aromatic hydrocarbons (PAH), cyanide, ammonia, non-consumed acids, benzene, toluene, xylene, oil, grease, etc. Further, the conjugative wastewater contains a high concentration of metallic oxides, toxic elements, oil, nitrogen, and heavy metals such as zinc, nickel, chromium, etc. These contaminants are generally treated and neutralized using physicochemical and membrane-based systems. This also yields hazardous sludge, which is landfilled, thereby incurring an ancillary financial burden. However, sludge can be a frugal source of extracting multi-dimensional benefits. The present review investigated and identified the most water-intensive and wastewater/sludge-contributing unit operations and proposed a preferential combination of treatments to balance efficacy and economy. Further, the various global practices for sludge recycling and management documented in the existing literature are summarized and ranked with the help of the analytic hierarchy process (AHP). The findings revealed concrete making and nutrient recovery as the most- and least-preferred recycling alternatives. Full article

Grading of gliomas is a piece of critical information related to prognosis and survival. Classifying glioma grade by semantic radiological features is subjective, requires multiple MRI sequences, is quite complex and clinically demanding, and can very often result in erroneous radiological diagnosis. We used a radiomics approach with machine learning classifiers to determine the grade of gliomas. Eighty-three patients with histopathologically proven gliomas underwent MRI of the brain. Whenever available, immunohistochemistry was additionally used to augment the histopathological diagnosis. Segmentation was performed manually on the T2W MR sequence using the TexRad texture analysis softwareTM, Version 3.10. Forty-two radiomics features, which included first-order features and shape features, were derived and compared between high-grade and low-grade gliomas. Features were selected by recursive feature elimination using a random forest algorithm method. The classification performance of the models was measured using accuracy, precision, recall, f1 score, and area under the curve (AUC) of the receiver operating characteristic curve. A 10-fold cross-validation was adopted to separate the training and the test data. The selected features were used to build five classifier models: support vector machine, random forest, gradient boost, naive Bayes, and AdaBoost classifiers. The random forest model performed the best, achieving an AUC of 0.81, an accuracy of 0.83, f1 score of 0.88, a recall of 0.93, and a precision of 0.85 for the test cohort. The results suggest that machine-learning-based radiomics features extracted from multiparametric MRI images can provide a non-invasive method for predicting glioma grades preoperatively. In the present study, we extracted the radiomics features from a single cross-sectional image of the T2W MRI sequence and utilized these features to build a fairly robust model to classify low-grade gliomas from high-grade gliomas (grade 4 gliomas). Full article

Background: Re-irradiation (ReRT) is an effective treatment modality in appropriately selected patients with recurrent/progressive high-grade glioma (HGG). The literature is limited regarding recurrence patterns following ReRT, which was investigated in the current study. Methods: Patients with available radiation (RT) contours, dosimetry, and imaging-based evidence of recurrence were included in the retrospective study. All patients were treated with fractionated focal conformal RT. Recurrence was detected on imaging with magnetic resonance imaging (MRI) and/ or amino-acid positron emission tomography (PET), which was co-registered with the RT planning dataset. Failure patterns were classified as central, marginal, and distant if >80%, 20–80%, or <20% of the recurrence volumes were within 95% isodose lines, respectively. Results: Thirty-seven patients were included in the current analysis. A total of 92% of patients had undergone surgery before ReRT, and 84% received chemotherapy. The median time to recurrence was 9 months. Central, marginal, and distant failures were seen in 27 (73%), 4 (11%), and 6 (16%) patients, respectively. None of the patient-, disease-, or treatment-related factors were significantly different across different recurrence patterns. Conclusion: Failures are seen predominantly within the high-dose region following ReRT in recurrent/ progressive HGG. Full article

Rice is the major staple food crop for more than 50% of the world’s total population, and its production is of immense importance for global food security. As a photophilic plant, its yield is governed by the quality and duration of light. Like all photosynthesizing plants, rice perceives the changes in the intensity of environmental light using phytochromes as photoreceptors, and it initiates a morphological response that is termed as the shade-avoidance response (SAR). Phytochromes (PHYs) are the most important photoreceptor family, and they are primarily responsible for the absorption of the red (R) and far-red (FR) spectra of light. In our endeavor, we identified the morphological differences between two contrasting cultivars of rice: IR-64 (low-light susceptible) and Swarnaprabha (low-light tolerant), and we observed the phenological differences in their growth in response to the reduced light conditions. In order to create genomic resources for low-light tolerant rice, we constructed a subgenomic library of Swarnaprabha that expedited our efforts to isolate light-responsive photoreceptors. The titer of the library was found to be 3.22 × 10⁵ cfu/mL, and the constructed library comprised clones of 4–9 kb in length. The library was found to be highly efficient as per the number of recombinant clones. The subgenomic library will serve as a genomic resource for the Gramineae community to isolate photoreceptors and other genes from rice. Full article

Potassium (K) is a critical nutrient for crops, as it is a major constituent in fertilizer formulations. With increasing concentrations of K in agricultural soil, it is necessary to understand its movement and retention in the soil. Sub-surface modeling is an alternative method to overcome the exhausting and uneconomical methods to study and determine the actual concentration of K in soil. HYDRUS-1D is considered an effective finite-element model which is suitable for sub-surface modeling. This model requires the input of ground-station meteorological (GM) data taken at a daily timestep for the simulation period. It can be a limiting factor in the absence of ground stations. The study compares K predictions in surface and sub-surface soil layers under Boro rice cultivation obtained with the usage of different meteorological datasets. Thus, the main hypothesis of the study was to validate that, in the absence of GM data, satellite-based meteorological data could be utilized for simulating the K concentration in soil. The two meteorological datasets that are considered in the study included the GM and satellite-derived NASA-Power (NP) meteorological datasets. The usage of a satellite meteorological product at a field scale may help in applying the method to other regions where GM data is not available. The numerical model results were validated with field experiments from four experimental fields which included varied K doses. The concentration in soil was assessed at the regular depths (0–5, 5–10, 10–15, 15–30, 30–45 and 45–60 cm), and at various stages of crop growth, from bare soil and sowing, to the tillering stages. The concentration of K was measured in the laboratory and also simulated through the optimized model. The modeled values were compared with measured values statistically using relative root mean square error (RMSER) and Nash–Sutcliffe modeling efficiency (E) for simulating K concentration in the soil for the Boro rice cropping pattern with both GM data and NP data. The model was found most suitable for the 0–30 cm depth on all days and for all treatment variations. Full article

Purpose and background: Isocitrate dehydrogenase (IDH) mutation and O-6 methyl guanine methyl transferase (MGMT) methylation are surrogate biomarkers of improved survival in gliomas. This study aims at studying the ability of semantic magnetic resonance imaging (MRI) features to predict the IDH mutation status confirmed by the gold standard molecular tests. Methods: The MRI of 148 patients were reviewed for various imaging parameters based on the Visually AcceSAble Rembrandt Images (VASARI) study. Their IDH status was determined using immunohistochemistry (IHC). Fisher’s exact or chi-square tests for univariate and logistic regression for multivariate analysis were used. Results: Parameters such as mild and patchy enhancement, minimal edema, necrosis < 25%, presence of cysts, and less rCBV (relative cerebral blood volume) correlated with IDH mutation. The median age of IDH-mutant and IDH-wild patients were 34 years (IQR: 29–43) and 52 years (IQR: 45–59), respectively. Mild to moderate enhancement was observed in 15/19 IDH-mutant patients (79%), while 99/129 IDH-wildtype (77%) had severe enhancement (p-value <0.001). The volume of edema with respect to tumor volume distinguished IDH-mutants from wild phenotypes (peritumoral edema volume < tumor volume was associated with higher IDH-mutant phenotypes; p-value < 0.025). IDH-mutant patients had a median rCBV value of 1.8 (IQR: 1.4–2.0), while for IDH-wild phenotypes, it was 2.6 (IQR: 1.9–3.5) {p-value = 0.001}. On multivariate analysis, a cut-off of 25% necrosis was able to differentiate IDH-mutant from IDH-wildtype (p-value < 0.001), and a cut-off rCBV of 2.0 could differentiate IDH-mutant from IDH-wild phenotypes (p-value < 0.007). Conclusion: Semantic imaging features could reliably predict the IDH mutation status in high-grade gliomas. Presurgical prediction of IDH mutation status could help the treating oncologist to tailor the adjuvant therapy or use novel IDH inhibitors. Full article

DNA methylation in insects is integral to cellular differentiation, development, gene regulation, genome integrity, and phenotypic plasticity. However, its evolutionary potential and involvement in facilitating rapid adaptations in insects are enigmatic. Moreover, our understanding of these mechanisms is limited to a few insect species, of which none are pests of crops. Hence, we studied methylation patterns in the brown planthopper (BPH), a major rice pest, under pesticide and nutritional stress, across its life stages. Moreover, as the inheritance of epigenetic changes is fundamentally essential for acclimation, adaptability, and evolution, we determined the heritability and persistence of stress-induced methylation marks in BPH across generations. Our results revealed that DNA methylation pattern(s) in BPH varies/vary with environmental cues and is/are insect life-stage specific. Further, our findings provide novel insights into the heritability of stress-induced methylation marks in BPH. However, it was observed that, though heritable, these marks eventually fade in the absence of the stressors, thereby suggesting the existence of fitness cost(s) associated with the maintenance of the stressed epigenotype. Furthermore, we demonstrate how 5-azacytidine-mediated disruption of BPH methylome influences expression levels of stress-responsive genes and, thereby, highlight demethylation/methylation as a phenomenon underlying stress resilience of BPH. Full article

Taxol drugs can be extracted from various species of the taxaceae family. It is an alkaloid (metabolic product) used for the treatment of various types of cancer. Since taxol is a metabolic product, multiple aspects such as edaphic, biochemical, topographic factors need to be assessed in determining the variation in Taxol Content (TC). In this study, both sensor-based hyperspectral reflectance data and absorption-based indices were tested together for the development of an advanced statistical unfolding approach to understand the influencing factors for TC in high altitude Himalayan region. Seriation analysis based on permutation matrix was applied with complete linkage and a multi-fragment heuristic scaling rule along with the common techniques such as Principal Component Analysis (PCA) and correlation to understand the relationship of TC with various factors. This study also tested the newly developed taxol indices to rule out the possibility of overlapping of TC determining bands with the foliar pigment’s wavelengths in the visible region. The result implies that T. wallichiana with a high TC is found more in its natural habitat of deep forest, relating it indirectly to elevation in the case of the montane ecosystem. Taxol is the most varying parameter among the measured variables, followed by hyperspectral Taxol content (TC) indices such as TC 2, TC 5, and carotenoids, which suggests that the indices are well versed to capture variations in TC with elevation. Full article

The integration of ecological and atmospheric characteristics for biodiversity management is fundamental for long-term ecosystem conservation and drafting forest management strategies, especially in the current era of climate change. The explicit modelling of regional ecological responses and their impact on individual species is a significant prerequisite for any adaptation strategy. The present study focuses on predicting the regional distribution of Rhododendron arboreum, a medicinal plant species found in the Himalayan region. Advanced Species Distribution Models (SDM) based on the principle of predefined hypothesis, namely BIOCLIM, was used to model the potential distribution of Rhododendron arboreum. This hypothesis tends to vary with the change in locations, and thus, robust models are required to establish nonlinear complex relations between the input parameters. To address this nonlinear relation, a class of deep neural networks, Convolutional Neural Network (CNN) architecture is proposed, designed, and tested, which eventually gave much better accuracy than the BIOCLIM model. Both of the models were given 16 input parameters, including ecological and atmospheric variables, which were statistically resampled and were then utilized in establishing the linear and nonlinear relationship to better fit the occurrence scenarios of the species. The input parameters were mostly acquired from the recent satellite missions, including MODIS, Sentinel-2, Sentinel-5p, the Shuttle Radar Topography Mission (SRTM), and ECOSTRESS. The performance across all the thresholds was evaluated using the value of the Area Under Curve (AUC) evaluation metrics. The AUC value was found to be 0.917 with CNN, whereas it was 0.68 with BIOCLIM, respectively. The performance evaluation metrics indicate the superiority of CNN for species distribution over BIOCLIM. Full article

Objectives: To explore the potential of Radiomics alone and in combination with a diffusion-weighted derived quantitative parameter, namely the apparent diffusion co-efficient (ADC), using supervised classification algorithms in the prediction of outcomes and prognosis. Materials and Methods: Retrospective evaluation of the imaging was conducted for a study cohort of uterine cervical cancer, candidates for radical treatment with chemo radiation. ADC values were calculated from the darkest part of the tumor, both before (labeled preADC) and post treatment (labeled postADC) with chemo radiation. Post extraction of 851 Radiomics features and feature selection analysis—by taking the union of the features that had Pearson correlation >0.35 for recurrence, >0.49 for lymph node and >0.40 for metastasis—was performed to predict clinical outcomes. Results: The study enrolled 52 patients who presented with variable FIGO stages in the age range of 28–79 (Median = 53 years) with a median follow-up of 26.5 months (range: 7–76 months). Disease recurrence occurred in 12 patients (23%). Metastasis occurred in 15 patients (28%). A model generated with 24 radiomics features and preADC using a monotone multi-layer perceptron neural network to predict the recurrence yields an AUC of 0.80 and a Kappa value of 0.55 and shows that the addition of radiomics features to ADC values improves the statistical metrics by approximately 40% for AUC and approximately 223% for Kappa. Similarly, the neural network model for prediction of metastasis returns an AUC value of 0.84 and a Kappa value of 0.65, thus exceeding performance expectations by approximately 25% for AUC and approximately 140% for Kappa. There was a significant input of GLSZM features (SALGLE and LGLZE) and GLDM features (SDLGLE and DE) in correlation with clinical outcomes of recurrence and metastasis. Conclusions: The study is an effort to bridge the unmet need of translational predictive biomarkers in the stratification of uterine cervical cancer patients based on prognosis. Full article

Apicomplexan parasites, through their motor machinery, produce the required propulsive force critical for host cell-entry. The conserved components of this so-called glideosome machinery are myosin A and myosin A Tail Interacting Protein (MTIP). MTIP tethers myosin A to the inner membrane complex of the parasite through 20 amino acid-long C-terminal end of myosin A that makes direct contacts with MTIP, allowing the invasion of Plasmodium falciparum in erythrocytes. Here, we discovered through screening a peptide library, a de-novo peptide ZA1 that binds the myosin A tail domain. We demonstrated that ZA1 bound strongly to myosin A tail and was able to disrupt the native myosin A tail MTIP complex both in vitro and in vivo. We then showed that a shortened peptide derived from ZA1, named ZA1S, was able to bind myosin A and block parasite invasion. Overall, our study identified a novel anti-malarial peptide that could be used in combination with other antimalarials for blocking the invasion of Plasmodium falciparum. Full article