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Amplification of the epidermal growth factor receptor gene (EGFR) represents one of the most commonly observed genetic lesions in glioblastoma (GBM); however, therapies targeting this signaling pathway have failed clinically. Here, using human tumors, primary patient-derived xenografts (PDX), and a murine model for GBM, we demonstrate that EGFR inhibition leads to increased invasion of tumor cells. Further, EGFR inhibitor-treated GBM demonstrates altered oxidative stress, with increased lipid peroxidation, and generation of toxic lipid peroxidation products. A tumor cell subpopulation with elevated aldehyde dehydrogenase (ALDH) levels was determined to comprise a significant proportion of the invasive cells observed in EGFR inhibitor-treated GBM. Our analysis of the ALDH1A1 protein in newly diagnosed GBM revealed detectable ALDH1A1 expression in 69% (35/51) of the cases, but in relatively low percentages of tumor cells. Analysis of paired human GBM before and after EGFR inhibitor therapy showed an increase in ALDH1A1 expression in EGFR-amplified tumors (P < 0.05, n = 13 tumor pairs), and in murine GBM ALDH1A1-high clones were more resistant to EGFR inhibition than ALDH1A1-low clones. Our data identify ALDH levels as a biomarker of GBM cells with high invasive potential, altered oxidative stress, and resistance to EGFR inhibition, and reveal a therapeutic target whose inhibition should limit GBM invasion.

A critical review of lab and field measurement methodologies, harmonization in measuring techniques, and modelling of skid resistance of asphalt concrete pavement have been provided. Although several past studies have provided literature review on general topics of skid resistance, to the best of the author’s knowledge, none of them have compressively covered the topic considering the status & requirements of developing nations. There has been significant development in speed with the improvement in computational facilities. In modern times, with the improvement in infrastructure quality in developing nations, permitted speeds have also drastically increased. To avoid skid-related accidents, it is important to develop good practices in maintaining sufficient skid resistance. The requirements and the availability of technology might be significantly different in developing nations. The suitability and limitations of various methods used for capturing the skid characteristics of the surface have been outlined. The harmonization in skid resistance measurement using laboratory and field-testing methods has been summarized. Correlation analysis of various in-situ and laboratory test data has been made to maintain a better harmony of measurement either in the field or in the laboratory. In the subsequent sections, progress in the modelling approach (analytical to numerical) has been discussed in brief. Computational capabilities of an analytical and numerical modelling approach for predicting pavement skid resistance characteristics have been reviewed. These models have been developed to consider complex attributes of tire pavement interactions like hydroplaning, temperature rise in the tire, mix morphology, tire inflation, and vehicle acceleration and deceleration for predicting skid resistance. These attributes of skid resistance have been discussed in detail and presented a basic overview of the model development process which is missing in past review studies. Few recent studies on skid resistance measurement and modelling to highlight the use of new technology and improvements over conventional techniques have been presented in the manuscript which has not been reviewed earlier. Critical factors affecting the skid resistance model like hydroplaning, tire-related parameters, temperature, and surface texture have been highlighted in this manuscript. Few key research directions have been suggested as the scope of future study to predict a more reliable skid resistance model.

ABSTRACT Bio‐inspired computer‐aided diagnosis (CAD) has garnered significant attention in recent years due to the inherent advantages of bio‐inspired evolutionary algorithms (EAs) in handling small datasets with elevated precision and reduced computational complexity. Traditional CAD models face limitations as they can only be developed post‐outbreak, relying on datasets that become available during such events such as the COVID‐19 pandemic. The scarcity of data for emerging diseases poses a substantial challenge to achieving elevated precision with conventional deep‐learning algorithms. Furthermore, even when datasets are available, employing deep learning for class‐based classification is arduous, necessitating model retraining, in this paper, we propose a novel hybrid algorithm that leverages the strengths of the crow search algorithm (CSA) and the spider monkey optimization (SMO) algorithm to create an optimised spider monkey crow search (OSM‐CS) algorithm. We developed a CAD tool that maps each input CT image to a high‐dimensional vector by extracting four categories of features: high contrast, polynomial decomposition, textural, and pixel statistics. The proposed OSM‐CS algorithm is employed as a feature selection method. Our experimental results demonstrate the effectiveness of the OSM‐CS algorithm, achieving an impressive accuracy of 98.2% when coupled with an AdaBoost classifier for multi‐class classification and 99.93% for binary classification. This performance surpasses that of state‐of‐the‐art (SOTA) deep learning models and recently published hybrid algorithms, underscoring the potential of the OSM‐CS algorithm as a powerful tool in the realm of CAD. [ABSTRACT FROM AUTHOR]

Acute Respiratory Distress Syndrome (ARDS) is a condition of varied etiology characterized by the acute onset (within 1 week of the inciting event) of hypoxemia, reduced lung compliance, diffuse lung inflammation and bilateral opacities on chest imaging attributable to noncardiogenic (increased permeability) pulmonary edema. Although multi-organ failure is the most common cause of death in ARDS, an estimated 10-15% of the deaths in ARDS are caused due to refractory hypoxemia, i.e.- hypoxemia despite lung protective conventional ventilator modes. In these cases, clinicians may resort to other measures with less robust evidence -referred to as "salvage therapies". These include proning, 48 h of paralysis early in the course of ARDS, various recruitment maneuvers, unconventional ventilator modes, inhaled pulmonary vasodilators, and Extracorporeal membrane oxygenation (ECMO). All the salvage therapies described have been associated with improved oxygenation, but with the exception of proning and 48 h of paralysis early in the course of ARDS, none of them have a proven mortality benefit. Based on the current evidence, no salvage therapy has been shown to be superior to the others and each of them is associated with its own risks and benefits. Hence, the order of application of these therapies varies in different institutions and should be applied following a risk-benefit analysis specific to the patient and local experience. This review explores the rationale, evidence, advantages and risks behind each of these strategies.

Panchatikta is an Ayurvedic multiherbal combination containing five bitter‐tasting drugs—Azadirachta indica, Tinospora cordifolia, Justicia adhatoda, Solanum virginianum, and Trichosanthes dioica. The objective of this study is to develop standards for Panchatikta ingredients using pharmacognostic parameters and to analyze the chemical composition. The plant materials were collected from different natural habitats, authenticated, dried, ground, and the combination was prepared by mixing the ingredients in equal amounts followed by macroscopic, organoleptic, microscopic, histochemical, and physicochemical characterization according to the standard protocol of the Ayurvedic Pharmacopoeia of India. Special morphological characteristics of the A. indica (stem bark), T. cordifolia (stem), J. adhatoda (roots), S. virginainum (roots), and T. dioica (aerial parts) were identified. The anatomical structure of each drug was observed, and microscopic markers were developed for identification. Histochemical deposits such as starch, oil, lignin, and tannin were located in each plant material. Powder characters such as fibers from phloem with pointed ends and narrow lumen, parenchyma cells containing starch grains, crystal fibers, fragments of bordered pitted vessels, fragments of pitted vessels, cells containing black powdery masses, and epidermal cells from leaves in surface view with an anomocytic stomata were identified as the key features for the Panchatikta combination. The organoleptic characterization of component drugs and combinations was performed. The physicochemical evaluation of parameters such as ash content (5.53 ± 0.29), water‐insoluble ash (4.57 ± 0.32), acid‐insoluble ash (1.55 ± 0.31), alcohol‐soluble extract (5.9 ± 1.21), water‐soluble extract (9.19 ± 0.21), fiber content (33.27 ± 1.37), total sugar (1.83 ± 0.65), and reducing sugar (1.73 ± 0.40) were evaluated for the Panchatikta combination. Preliminary phytochemical tests were carried out to verify the presence of alkaloids, flavonoids, saponins, tannins, phenols, glycosides, and steroids. The HPTLC profile comparison of ethanolic, hydroalcoholic, and aqueous extracts of Panchatikta and single drugs showed some type of synergy and antagonistic activities among the chemical principles present. Marker‐based screening of azadirachtin, betulinic acid, and lupeol was done in Panchatikta ethanol using HPTLC. As Panchatikta is prescribed for various life‐threatening diseases including cancer, the standards developed here ensure the authenticity of the ingredients, which in turn ensures the quality of the prepared medicines. [ABSTRACT FROM AUTHOR]

The pea, or Pisum sativum, is the third most popular grain crop grown worldwide and a member of the Leguminaceae family. With an area of 294 million hectares, a production of million tons and an average productivity of 1460 q/ha, Uttar Pradesh leads India in this regard. Numerous biotic and abiotic elements include accountable for the crop's poor production. Powdery mildew is one of the fungus foliar diseases that is most prevalent in the Himachal Pradesh and causes significant losses, both in terms of quantity and quality. The powdery mildew investigation, "management of powdery mildew (Erysiphe pisi) of pea," was carried out at Agriculture research farm in 2023-2024 at Abhilashi University. The data indicated that all the fungicides used were found effective to reducing the disease severity index of powdery mildew as compare to control. The minimum (22.22%) severity index was recorded in T6 (Karathane) followed by T1 (24.44%). The maximum disease severity was recorded in T4 Tridemorph (33.33%) whereas, 57.77% was recorded in case of control. Maximum PDC was recorded T6 Karathane (61.33%) followed by T1 Hexaconazole (57.69%), T5 Wettable sulphur (53.85%). While, minimum PDC was recorded in T4 Tridemorph (42.30%). [ABSTRACT FROM AUTHOR]

Pea is third most important pulse crop of the world, which is being cultivated all over the globe over the land area of two million hectares. Despite of its being grown in large area, this crop is infected by numerous pathogens including rust disease. Rust disease of pea is caused by Uromyces viciaefabae affect the pea crop all over the mid-hill conditions of Himachal Pradesh. The data revealed that all the bioagents decreases the % disease severity over control. The minimum PDI was recorded in T6 - Soil application of Trichoderma viride @ 20g/m² (38.27%) followed by T5-Soil application of Trichoderma harzianum @ 20g/m² (40.74%) and T3- Seed treatment with Pseudomonas fluorescens @10g/kg of seed (43.20%). Whereas, maximum PDI T1- Seed treatment with Trichoderma harzianum @ 10g/kg of seed (53.08%) followed by T4- Seed treatment with Bacillus sp @ 10g/kg of seed (50.61%) and T2- Seed treatment with Tricoderma viride @ 10g/kg of seed (48.14%), respectively. In case of control 71.60% PDI was recorded. The maximum PDC was recorded in T6- Soil application of Trichoderma viride @ 20g/m² (46.55%) and minimum PDC was recorded under the treatment T1- Seed treatment with Trichoderma harzianum @ 10g/kg of seed (25.86%). [ABSTRACT FROM AUTHOR]