Current stage of preclinical and clinical development of guggulsterone in cancers: Challenges and promises.

Throughout human history, the utilization of medicinal herbs has been recognized as a crucial defense against various ailments, including cancer. Natural products with potential anticancer properties, capable of inducing apoptosis in cancer cells, have garnered substantial attention. One such agent under investigation is guggulsterone (GS), a phytosterol derived from the gum resin of the Commiphora mukul tree. This review aims to provide a comprehensive summary of recent studies elucidating the anticancer molecular mechanisms and molecular targets of GS, guiding future research and potential applications as an adjuvant drug in cancer therapy. Recent in vivo and in vitro studies have explored the biological activities of the active ingredients in Commiphora mukul. Specifically, GS emerges as a potential cancer chemopreventive and therapeutic agent. The investigations delve into the impact of GS on constitutively activated survival pathways, including Janus kinase/signal transducer and activator of transcription (JAK/STAT), nuclear factor-kappa B (NF-kB), and PI3-kinase/AKT signaling pathways. These pathways regulate antiapoptotic and proinflammatory genes, exerting control over growth and inflammatory responses. The findings highlight the potential of GS in disrupting survival pathways crucial for cancer cell viability. The inhibition of JAK/STAT, NF-kB, and PI3-kinase/AKT signaling pathways positions GS as a promising candidate for cancer therapy. The review synthesizes evidence from diverse studies, underscoring the multifaceted biological activities of GS in cancer prevention and treatment. To advance our understanding, future clinical and translational studies are imperative to determine effective doses in humans. Additionally, there is a need for the development of new pharmaceutical forms of GS to optimize therapeutic effects. This comprehensive review provides a foundation for ongoing research, offering insights into the potential of GS as a valuable addition to the armamentarium against cancer.

Single-trial extraction of event-related potentials (ERPs) and classification of visual stimuli by ensemble use of discrete wavelet transform with Huffman coding and machine learning techniques.

BACKGROUND: Presentation of visual stimuli can induce changes in EEG signals that are typically detectable by averaging together data from multiple trials for individual participant analysis as well as for groups or conditions analysis of multiple participants. This study proposes a new method based on the discrete wavelet transform with Huffman coding and machine learning for single-trial analysis of evenal (ERPs) and classification of different visual events in the visual object detection task. METHODS: EEG single trials are decomposed with discrete wavelet transform (DWT) up to the [Formula: see text] level of decomposition using a biorthogonal B-spline wavelet. The coefficients of DWT in each trial are thresholded to discard sparse wavelet coefficients, while the quality of the signal is well maintained. The remaining optimum coefficients in each trial are encoded into bitstreams using Huffman coding, and the codewords are represented as a feature of the ERP signal. The performance of this method is tested with real visual ERPs of sixty-eight subjects. RESULTS: The proposed method significantly discards the spontaneous EEG activity, extracts the single-trial visual ERPs, represents the ERP waveform into a compact bitstream as a feature, and achieves promising results in classifying the visual objects with classification performance metrics: accuracies 93.60[Formula: see text], sensitivities 93.55[Formula: see text], specificities 94.85[Formula: see text], precisions 92.50[Formula: see text], and area under the curve (AUC) 0.93[Formula: see text] using SVM and k-NN machine learning classifiers. CONCLUSION: The proposed method suggests that the joint use of discrete wavelet transform (DWT) with Huffman coding has the potential to efficiently extract ERPs from background EEG for studying evoked responses in single-trial ERPs and classifying visual stimuli. The proposed approach has O(N) time complexity and could be implemented in real-time systems, such as the brain-computer interface (BCI), where fast detection of mental events is desired to smoothly operate a machine with minds.

Metal transportation mechanism by rainfall runoff as a contribution to the bioaccumulation in seafood.

Trace metal transport mechanism via rainfall runoff from soil to the water body in the context of the bioaccumulation in seafood was unprecedentedly investigated. Instead of a conventional simulation experiment at a laboratory, the twelve soil sampling sites were selected in the region (Windar Valley, Balochistan-Pakistan) reported with high trace metal content, and Threadfin Sea Catfish and Belanger's Croaker were caught from the adjacent coastal water body. The Pb, Cd, Ni, and Zn in soil samples were high in proportion; the average concentrations were 2793.8, 622.44, 331.33, and 440 in mg kg-1, respectively, as per expectations. Using ArcGIS, the soil sample results were extensively illustrated by the spatial distribution in the sampling regions. The Zn > Pb > Ni > Cd was found in pre- and post-rainfall fish flesh samples. Trace metals were higher in post-rain fish flesh samples than pre-rainfall samples, indicating that rainwater runoff could be the significant source for trace metal transport except for Zn. The Pb, Cd, Ni, and Zn elevated results were 0.80828 ± 0.17752, 0.12102 ± 0.03027, 0.71064 ± 0.24188, and 6.49223 ± 3.65094 in mg kg-1, respectively, in post-rainfall fish flesh samples. Appling chemometric tools revealed that Zn content depends on Zn-protein interaction, and Pb, Cd, and Ni contents significantly pertain to the rainwater runoff. Other probable transport routes for trace metals to the water body could be less responsible. The soil sampling region's NOAA HYSPLIT backward air trajectory showed that the air direction was mostly from ocean to land.

Trends in per-operative parameters and postoperative complications associated with coronary artery bypass graft surgery (CABG); A four-year retrospective study.

OBJECTIVE: To determine the patterns of per-operative parameters and early outcomes of patients that underwent CABG surgery during a four-year period. METHODS: This is a cross-sectional descriptive study conducted in a tertiary care of hospital from November 2020 to January 2021. All the patients that underwent the isolated coronary artery bypass grafting (CABG) procedure were included in the study from June 2017 till June 2020. Data was collected on a data extraction form and stored in SPSS format which was analyzed for qualitative statistics keeping p<0.05 as significant. All the results were represented in the form of tables. RESULTS: A total of 1,613 patients were operated upon for Coronary Artery Bypass Grafting (CABG) procedure during the study period with 1,222 (75.8%) males and 391 (24.2%) females. Dyslipidemia (71.8%) was the most common risk factor. The average perfusion time decreased only slightly (~1 minute) from 96.01 minutes to 95.07 minutes (2017 to 2020). This change however was not significant (p=0.301). The rate of Left Internal Mammary Artery (LIMA) use stayed relatively stable over the 4-year period fluctuating between 88.7% and 92.9% (p=0.360). The average initial ICU stay (in hours), drain at 12 hours and 24 hours stays almost the same. The rate of mortality peaked in 2018 (4.76%) and subsequently fell to 3.57% by 2020. CONCLUSION: More males underwent CABG surgery at this tertiary care hospital and the overall complication rate and per-operative parameters improved over the years. The non-risk stratified mortality in this study was found to be higher than developed nations.

Siesta: Recent developments and applications.

A review of the present status, recent enhancements, and applicability of the Siesta program is presented. Since its debut in the mid-1990s, Siesta's flexibility, efficiency, and free distribution have given advanced materials simulation capabilities to many groups worldwide. The core methodological scheme of Siesta combines finite-support pseudo-atomic orbitals as basis sets, norm-conserving pseudopotentials, and a real-space grid for the representation of charge density and potentials and the computation of their associated matrix elements. Here, we describe the more recent implementations on top of that core scheme, which include full spin-orbit interaction, non-repeated and multiple-contact ballistic electron transport, density functional theory (DFT)+U and hybrid functionals, time-dependent DFT, novel reduced-scaling solvers, density-functional perturbation theory, efficient van der Waals non-local density functionals, and enhanced molecular-dynamics options. In addition, a substantial effort has been made in enhancing interoperability and interfacing with other codes and utilities, such as wannier90 and the second-principles modeling it can be used for, an AiiDA plugin for workflow automatization, interface to Lua for steering Siesta runs, and various post-processing utilities. Siesta has also been engaged in the Electronic Structure Library effort from its inception, which has allowed the sharing of various low-level libraries, as well as data standards and support for them, particularly the PSeudopotential Markup Language definition and library for transferable pseudopotentials, and the interface to the ELectronic Structure Infrastructure library of solvers. Code sharing is made easier by the new open-source licensing model of the program. This review also presents examples of application of the capabilities of the code, as well as a view of on-going and future developments.

GC-MS analysis of bioactive compounds present in medicinally important Periploca hydaspidis.

The present study investigates the pharmaceutically bioactive compounds in Methanol, n-hexane and ethyl acetate extracted samples from the root of Periploca hydaspidis through Gas Chromatography and Mass Spectroscopy analysis. The mass spectrum obtained was compared with the data base of National Institute of Standards and Technology (NIST) which contains more than 62000 patterns of the mass spectrum. During matching with NIST library the match factor greater than 700 was considered only for better and pure results. The GC-MS analysis revealed the presence of various important compounds in the extracts like Lupeol, Furanol, Decanal, Decanoic acid, Dioxane and Oxirane. Besides these compounds the analysis also revealed the presence of antibiotics, fatty acids and protein.

Bioinspired synthesis and characterization of gold nano-particles from medicinally important Periploca hydaspidis and their in vitro antioxidant and antimicrobial activity.

This research investigates the synthesis and characterization of gold nanoparticles from Periploca hydaspidis and their antimicrobial and anti oxidant activity. The synthesis of AuNPs was confirmed by UV-Vis spectrophotometer and structure by a high resolution atomic force microscope. X-ray diffraction and Fourier transformed infrared spectroscopy was used to study the crystallite size and different functional groups. DPPH radical scavenging activity and disc diffusion protocol was applied for the determination of antioxidant and antimicrobial activity. A ratio of 1:8 of 1mM AuCl3 solutions with plant boiled extract used for synthesis of gold nano-particles. The formation of the gold nano-particles was determined by the color change from yellow to dark purple which were confirmed by UV-Vis spectrophotometer. Gold nano-particles were stable between 24°C and 39°C, mM concentration of the salt and neutral pH. The groups responsible for the synthesis of gold nano-paricles were Alkenes and aliphatic amines. The AuNP were cubic in nature and the nanocrystallite size was 6.99nm. Gold nano-particles revealed good antioxidant activity and controlled the growth of K. pnemoniae, E. coli, X. compestris, C. albicans and P. chrysogenum.

Core Electrons in the Electronic Stopping of Heavy Ions.

Electronic stopping power in the keV/Å range is accurately calculated from first principles for high atomic-number projectiles and the effect of core states is carefully assessed. The energy loss to electrons in self-irradiated nickel is studied using real-time time-dependent density functional theory. Different core states are explicitly included in the simulations to understand their involvement in the dissipation mechanism. The core electrons of the projectile are found to open additional dissipation channels as the projectile velocity increases. Almost all of the energy loss is accounted for, even for high projectile velocities, when core electrons as deep as 2s^{2}2p^{6} are explicitly treated. In addition to their expected excitation at high velocities, a flapping dynamical response of the projectile core electrons is observed at intermediate velocities. The empirical reference data are well reproduced in the projectile velocity range of 1.0-12.0 a.u. (1.5-210 MeV).

Green synthesis and characterization of silver nano-particles from pharmaceutically important Periploca hydaspidis and their biological activity.

The present study describes the synthesis, characterization of nano-particles from Periploca hyaspidis and their in vitro biological activity. The synthesis of AgNPs was confirmed by UV-Vis spectrophotometer and structure by atomic force microscope. The crystallite size and different functional groups was determined by X-ray diffraction and Fourier transformed infrared spectroscopy. Anti-microbial and anti-oxidant activity was carried out by disc diffusion and DPPH radical scavenging protocol respectively. Silver nano-particles (AgNPs) were synthesized by mixing 1mM AgNO3 solutions with plant boiled extract in 1:9. The color change from yellow to dark brown indicated the synthesis of the nano-particles. The AgNPs were more stable at 25°C to 45°C, 1mM concentration of the salt and neutral to slightly basic pH. The results revealed that aromatic amines were responsible for the synthesis of AgNPs. The crystallite size was 7.50 nm, cubic and in nanorgime. AgNPs showed good anti-oxidant activity and was effective against K. pnemoniae, E. coli, X. compestris, C. albicans and P. chrysogenum.

Phytochemical analysis, phytotoxic and insecticidal activities of medicinally important Periploca hydaspidis.

The present study investigates the phyto-chemical analysis, phytotoxic activity and insecticidal activity of the stem and root tissues of medicinally important Periploca hydaspidis. All the extracted samples exhibited the phytotoxic activity. The data confirmed that water was the best solvent to extract the phytotoxic compounds from stem and root tissues. Roots extracted with different solvents exhibited better phytotoxic potential than samples obtained from the stem tissues. Samples extracted in methanol and water from both stems and roots tissues were active against the subject insects while hexane, ethyl acetate and butanol extracted samples in both parts exhibited no insecticidal activity. Water extracted samples of the stem and root exhibited better insecticidal activity compared with methanol extracted samples. Tribolium castaneum and Rhizopertha dominica were more sensitive in both the cases than Callosobruchus maculates. The plant contained alkaloids, flavonoids, carbohydrate, proteins and saponins.

GC-MS profile of bioactive compounds from medicinally important Periploca hydaspidis.

The aim of the present study was to investigate bioactive compounds in different solvent extracted samples from the stem tissues of P. hydaspidis using Gas Chromatography and Mass Spectroscopy techniques. GC-mass spectrum was compared with the data base of National Institute of Standards and Technology (NIST) containing more than 62000 patterns of the mass spectrum. During matching with NIST library the match factor greater than 700 was considered only for better and pure results. The results revealed that different solvent extracted samples analyzed through GC-MS contained appreciable quantities of different bioactive molecules including antibiotics, fatty acids and protein which have important pharmacological significance.

Tracking of EEG activity using motion estimation to understand brain wiring.

The fundamental step in brain research deals with recording electroencephalogram (EEG) signals and then investigating the recorded signals quantitatively. Topographic EEG (visual spatial representation of EEG signal) is commonly referred to as brain topomaps or brain EEG maps. In this chapter, full search full search block motion estimation algorithm has been employed to track the brain activity in brain topomaps to understand the mechanism of brain wiring. The behavior of EEG topomaps is examined throughout a particular brain activation with respect to time. Motion vectors are used to track the brain activation over the scalp during the activation period. Using motion estimation it is possible to track the path from the starting point of activation to the final point of activation. Thus it is possible to track the path of a signal across various lobes.

Multi-century (635-year) spring season precipitation reconstruction from northern Pakistan revealed increasing extremes.

The Hindu Kush Himalaya region is experiencing rapid climate change with adverse impacts in multiple sectors. To put recent climatic changes into a long-term context, here we reconstructed the region's climate history using tree-ring width chronologies of climate-sensitive Cedrus deodara and Pinus gerardiana. Growth-climate analysis reveals that the species tree-growth is primarily limited by moisture stress during or preceding the growing season, as indicated by a positive relationship between the chronology and precipitation and scPDSI, and a negative one with temperature. We have reconstructed 635 years (1384-2018 CE) of February-June precipitation using a robust climate reconstruction model that explains about 53% variance of the measured precipitation data. Our reconstruction shows several dry and wet episodes over the reconstruction period along with an increase in extreme precipitation events during recent centuries or years. Long, very wet periods were observed during the following years: 1392-1393, 1430-1433, 1456-1461, 1523-1526, 1685-1690, 1715-1719, 1744-1748, 1763-1767, 1803-1806, 1843-1846, 1850-1855, 1874-1876, 1885-1887, 1907-1909, 1921-1925, 1939-1944, and 1990-1992, while long dry periods were observed during the following years: 1398-1399, 1464-1472, 1480-1484, 1645-1649, 1724-1727, 1782-1786, 1810-1814, 1831-1835, 1879-1881, 1912-1918, 1981-1986, 1998-2003, and 2016-2018 CE. We found predominantly short-term periodicity cycles of 2.0, 2.2, 2.3, 2.4, 2.6-2.7, 2.9, 3.3, 4.8, 8.1-8.3, and 9.4-9.6 years in our reconstruction. Spatial correlation analyses reveal that our reconstruction is an effective representation of the precipitation variability in the westerly climate-dominated areas of Pakistan and adjacent regions. In addition to the influence of regional circulation systems like western disturbances, we found possible teleconnections between the precipitation variability in northern Pakistan and broader-scale climate modes or phases like AMO and ENSO. The study also highlights the prospects of tree-ring application to explore linkages between western disturbance, increasing intensity and frequency of extreme climate events, and analysis of long-term atmospheric circulation over the western Himalayan region.

Cellulose nanocrystals boosted hydrophobically associated self-healable conductive hydrogels for the application of strain sensors and electronic devices.

Currently, hydrogel-based flexible devices become hot areas for scientists in the field of electronic devices, artificial intelligence, human motion detection, and electronic skin. These devices show responses to external stimuli (mechanical signals) and convert them into electrical signals (resistance, current, and voltage). However, the applications of the hydrogel-based sensor are hampered due to low mechanical properties, high time response, low fatigue resistance, low self-healing nature, and low sensing range. Herein, a strain sensing conductive hydrogel constructed from the CNCs (cellulose nanocrystal) reinforced, in which acrylamide and butyl acrylate work as hydrophilic and hydrophobic monomers respectively. The incorporation of CNCs in the polymeric system has a direct effect on their mechanical properties. The hydrogel having a high amount of CNCs (C4), its fracture stress and fracture strain reached 371.2 kPa and 2108 % respectively as well as self-healing of C4 hydrogel Broke at 499 % strain and bore 197 kPa stress. The elastic behavior of the hydrogels was confirmed by the rheological parameter frequency sweep and strain amplitude. Besides this our designed hydrogel shows an excellent response to deformation with conductivity 420 mS m-1, shows response to small strain (10 %) and large (400 %) strain, and has excellent anti-fatigue resistance with continuous stretching for 700 s at 300 % strain, with 140 msec response time, and gauge factor 7.4 at 750 % strain. The C4 hydrogel can also work as electronic skin when it is applied to different joints like the finger, elbow, neck, etc. The prepared hydrogel can also work as an electronic pen when it is worn to a plastic pen cover.

Phytotherapeutic options for the treatment of epilepsy: pharmacology, targets, and mechanism of action.

Epilepsy is one of the most common, severe, chronic, potentially life-shortening neurological disorders, characterized by a persisting predisposition to generate seizures. It affects more than 60 million individuals globally, which is one of the major burdens in seizure-related mortality, comorbidities, disabilities, and cost. Different treatment options have been used for the management of epilepsy. More than 30 drugs have been approved by the US FDA against epilepsy. However, one-quarter of epileptic individuals still show resistance to the current medications. About 90% of individuals in low and middle-income countries do not have access to the current medication. In these countries, plant extracts have been used to treat various diseases, including epilepsy. These medicinal plants have high therapeutic value and contain valuable phytochemicals with diverse biomedical applications. Epilepsy is a multifactorial disease, and therefore, multitarget approaches such as plant extracts or extracted phytochemicals are needed, which can target multiple pathways. Numerous plant extracts and phytochemicals have been shown to treat epilepsy in various animal models by targeting various receptors, enzymes, and metabolic pathways. These extracts and phytochemicals could be used for the treatment of epilepsy in humans in the future; however, further research is needed to study the exact mechanism of action, toxicity, and dosage to reduce their side effects. In this narrative review, we comprehensively summarized the extracts of various plant species and purified phytochemicals isolated from plants, their targets and mechanism of action, and dosage used in various animal models against epilepsy.

Climate and soil factors co-derive the functional traits variations in naturalized downy thorn apple (Datura innoxia Mill.) along the altitudinal gradient in the semi-arid environment.

Plant functional traits are consistently linked with certain ecological factors (i.e., abiotic and biotic), determining which components of a plant species pool are assembled into local communities. In this sense, non-native naturalized plants show more plasticity of morphological traits by adopting new habitat (an ecological niche) of the invaded habitats. This study focuses on the biomass allocation pattern and consistent traits-environment linkages of a naturalized Datura innoxia plant population along the elevation gradient in NW, Pakistan. We sampled 120 plots of the downy thorn apple distributed in 12 vegetation stands with 18 morphological and functional biomass traits during the flowering season and were analyzed along the three elevation zones having altitude ranges from 634.85 m to 1405.3 m from sear level designated as Group I to III identified by Ward's agglomerative clustering strategy (WACS). Our results show that many morphological traits and biomass allocation in different parts varied significantly (p < 0.05) in the pair-wise comparisons along the elevation. Likewise, all plant traits decreased from lower (drought stress) to high elevation zones (moist zones), suggesting progressive adaptation of Datura innoxia with the natural vegetation in NW Pakistan. Similarly, the soil variable also corresponds with the trait's variation e.g., significant variations (P < 0.05) of soil organic matter, organic carbon, Nitrogen and Phosphorus was recorded. The trait-environment linkages were exposed by redundancy analysis (RDA) that was co-drive by topographic (elevation, r = -0.4897), edaphic (sand, r = -0.4565 and silt, r = 0.5855) and climatic factors. Nevertheless, the influences of climatic factors were stronger than soil variables that were strongly linked with elevation gradient. The study concludes that D. innoxia has adopted the prevailing environmental and climatic conditions, and further investigation is required to evaluate the effects of these factors on their phytochemical and medicinal value.

Ecological factors affecting minerals and nutritional quality of "Dryopteris filix-mas (L.) Schott": an underutilized wild leafy vegetable in rural communities.

Dryopteris filix-mas (hereafter D. filix-mas), a wild leafy vegetable, has gained popularity among high mountain residents in the Hindukush-Himalaya region due to its exceptional nutritional profile, and their commercial cultivation also offers viable income alternatives. Nevertheless, besides phytochemicals with medicinal applications, ecological factors strongly affect their mineral contents and nutritional composition. Despite this, little has been known about how this wild fern, growing in heterogeneous ecological habitats with varying soil physiochemical properties and coexisting species, produces fronds with optimal mineral and nutritional properties. Given its nutritional and commercial significance, we investigated how geospatial, topographic, soil physiochemical characteristics and coexisting plants influence this widely consumed fern's mineral and nutrient content. We collected soil, unripe fern fronds, and associated vegetation from 27 D. filix-mas populations in Swat, NW Pakistan, and were analyzed conjointly with cluster analysis and ordination. We found that the fronds from sandy-loam soils at middle elevation zones exhibited higher nitrogen contents (9.17%), followed by crude fibers (8.62%) and fats (8.09%). In contrast, juvenile fronds from the lower and high elevation zones had lower moisture (1.26%) and ash (1.59%) contents, along with fewer micronutrients such as calcium (0.14-0.16%), magnesium (0.18-0.21%), potassium (0.72-0.81%), and zinc (12% mg/kg). Our findings indicated the fern preference for middle elevation zones with high organic matter and acidic to neutral soil (pH ≥ 6.99) for retaining higher nutritional contents. Key environmental factors emerged from RDA analysis, including elevation (r = -0.42), aspect (r = 0.52), P-3 (r = 0.38), K+ (r = 0.41), EC (r = 0.42), available water (r = -0.42), and field capacity (r = -0.36), significantly impacting fern frond's mineral accumulation and nutrient quality enhancement. Furthermore, coexisting plant species (r = 0.36) alongside D. filix-mas played a pivotal role in improving its mineral and nutritional quality. These findings shed light on the nutritional potential of D. filix-mas, which could help address malnutrition amidst future scarcity induced by changing climates. However, the prevalent environmental factors highlighted must be considered if the goal is to cultivate this fern on marginal lands for commercial exploitation with high mineral and nutrient yields in Hindukush-Himalaya.

Guar gum reinforced conductive hydrogel for strain sensing and electronic devices.

Hydrophobically associated conductive hydrogels got great attention due to their excellent properties like stretchability, energy dissipation mechanism, and strain sensor. But hydrophobically associated hydrogels have poor mechanical properties and time response to external stimuli. To enhance the mechanical properties and response to stimuli, Acrylamide- co-Butyl acrylate/Gum based conductive hydrogels were prepared. SDS works as a cross-linker and micelle-forming agent while NaCl makes hydrogel as conductive. The results show that our % strain sensing reached up to 400 %, and fracture stress and fracture strain reached to 0.5 MPa and 401 % respectively. Besides this, it's having an excellent response to continuous stretching and unstretching multiple cycles without any fracture up to 180 s and an excellent time response of 190 s. The conductivity of the hydrogel was 0.20 Sm-1. The hydrophobic hydrogels showed a clear and quick response to human motions like finger, wresting, writing, speaking, etc. Interestingly, our prepared hydrogels can detect the mood of the human face. Similarly, the hydrogels were found efficient in bridging the surface of electronic devices with human skin. This indicates that our prepared hydrogels can monitor human body motion and will replace the existing materials used in strain sensors in the near future.

Deep learning for plant bioinformatics: an explainable gradient-based approach for disease detection.

Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a combination of these omics data to learn crucial plant disease detection characteristics. We trained our model with multiple hyperparameters, such as the learning rate, number of hidden layers, and dropout rate, and attained a test set accuracy of 95.5%. We also conducted a sensitivity analysis to determine the model's resistance to hyperparameter variations. Our analysis revealed that our model exhibited a notable degree of resilience in the face of these variations, resulting in only marginal changes in performance. Furthermore, we conducted a comparative examination of the time efficiency of our EG-CNN model in relation to baseline models, including SVM, Random Forest, and Logistic Regression. Although our model necessitates additional time for training and validation due to its intricate architecture, it demonstrates a faster testing time per sample, offering potential advantages in real-world scenarios where speed is paramount. To gain insights into the internal representations of our EG-CNN model, we employed saliency maps for a qualitative analysis. This visualization approach allowed us to ascertain that our model effectively captures crucial aspects of plant disease, encompassing alterations in gene expression, metabolite levels, and spectral discrepancies within plant tissues. Leveraging omics data and hyperspectral images, this study underscores the potential of deep learning methods in the realm of plant disease detection. The proposed EG-CNN model exhibited impressive accuracy and displayed a remarkable degree of insensitivity to hyperparameter variations, which holds promise for future plant bioinformatics applications.

Risk Assessment, Interdependencies, and Source Appraisal of Bioaccumulated Heavy and Essential Metals in Seafood as Pollutants.

Fish as seafood is a bioindicator for chemical substances like trace metals in the water systems that accumulate in fish bodies. Fe and Zn as essential and Pb, Ni, and Cd as heavy metals were quantitatively analyzed in fish muscle samples by an atomic absorption spectrophotometer (Perkin Elmer, Model AAnalyst-700). Fe and Zn's results agreed with the food quality guidelines. Fe was the highest in the range of 2.6-9.4 in mg kg-1. The Zn content indicates the contribution of anthropogenic agents through the food chain. Ni > Pb > Cd was found in marine fish species and Pb > Ni > Cd in freshwater fish. The results have been explored for source appraisal of bioaccumulated trace metals and categorized selected marine and freshwater species based on characteristics (like life cycle and habitats) by applying multivariate principal component analysis to risk assessment parameters. The Pearson correlation coefficients were applied to the risk assessment parameters for interdependencies of metals. Interestingly, synchronized outcomes were obtained with trace metal data. The study results were interpreted in the context of the fish type, habitat, surroundings, feed, life cycle, etc. The living habitats strongly affect trace metal accumulation, target hazard quotient (THQ), and target cancer risk (TR) attributes. The fishermen's community was at higher risk for carcinogenic effects than other seafood consumers. Overall, determinations for fish species were under safe limits as described by international regulatory bodies (FAO, WHO, ANHMRC, WAA).