Metalloid transporters in plants: bridging the gap in molecular structure and physiological exaptation.

The rhizosphere contains both essential nutrients and potentially harmful substances for plant growth. Plants, as sessile organisms, must efficiently absorb the necessary nutrients while actively avoiding the uptake of toxic compounds. Metalloids, which are elements that exhibit properties of both metals and nonmetals, can have different effects on plant growth, ranging from being essential and beneficial to being toxic. The toxicity of metalloids in plants arises due to either the dosage of exposure or the specific elemental type. To utilize or detoxify these elements, plants have developed various transporters that regulate their uptake and distribution in plants. Arguably, genomic sequence analysis suggests the presence of such transporter families throughout the plant kingdom, from chlorophytes to higher plants. These transporters form defined families with related transport preferences. The isoforms within these families have evolved with specialized functions regulated by defined selectivity. Hence, understanding transporters' chemistry to atomic detail is important to achieve desired genetic modifications for crop improvement. Here, we outline various adaptations in plant transport systems to deal with metalloids, including their uptake, distribution, detoxification, and homeostasis in plant tissues. Structural parallels are drawn to other nutrient transporter systems to support emerging themes of functional diversity of active sites of transporters, elucidating adaptations of plants to utilize and extrude metalloid concentrations. Considering the observed physiological importance of metalloids, this review intends to highlight the shared and disparate features in metalloid transport systems and their corresponding nutrient transporters.

Efficacy and safety of vitamin C supplementation in the treatment of community-acquired pneumonia: a systematic review and meta-analysis with trial sequential analysis.

Community-acquired pneumonia (CAP) poses a significant global health challenge, prompting exploration of innovative treatments. This systematic review and meta-analysis aimed to evaluate the efficacy and safety of vitamin C supplementation in adults undergoing treatment for CAP. A comprehensive search of the MEDLINE, Embase, CINAHL, the Cochrane Central Register of Controlled Trials, and Clinical Trials.gov databases from inception to 17 November 2023 identified six randomized-controlled-trials (RCTs) meeting inclusion criteria. The primary outcome analysis revealed a non-significant trend towards reduced overall mortality in the vitamin C group compared to controls (RR 0.51; 95% CI 0.24 to 1.09; p = 0.052; I2 = 0; p = 0.65). Sensitivity analysis, excluding corona-virus-disease 2019 (COVID-19) studies and considering the route of vitamin C administration, confirmed this trend. Secondary outcomes, including hospital length-of-stay (LOS), intensive-care-unit (ICU) LOS, and mechanical ventilation, exhibited mixed results. Notably, heterogeneity and publication bias were observed in hospital LOS analysis, necessitating cautious interpretation. Adverse effects were minimal, with isolated incidents of nausea, vomiting, hypotension, and tachycardia reported. This meta-analysis suggests potential benefits of vitamin C supplementation in CAP treatment. However, inconclusive findings and methodological limitations warrants cautious interpretation, emphasising the urgency for high-quality trials to elucidate the true impact of vitamin C supplementation in CAP management.

Green route to fabrication of Semal-ZnO nanoparticles for efficient solar-driven catalysis of noxious dyes in diverse aquatic environments.

This work successfully demonstrates a sustainable and environmentally friendly approach for synthesizing Semal-ZnO nanoparticles (NPs) using the aqueous leaf extract of Bombax ceiba L. These NPs exhibit an absorption peak at approximately 390 nm in the UV-visible spectrum and an energy gap (Eg) of 3.11 eV. Detailed analyses of the morphology and particle size using various spectroscopic and microscopic techniques, XRD, FE-SEM with EDS, and HR-TEM reveal crystallographic peaks attributable to the hexagonal phase, with an average crystal size of 17 nm. The Semal-ZnO NPs also exhibit a notable photocatalytic efficiency for degrading methylene blue (MB) and methyl orange (MO) under sunlight in different water samples collected from diverse natural sources, indicating that they are promising photocatalysts for environmental remediation. The photocatalytic efficiency of the biofabricated Semal-ZnO NPs is impressive, exhibiting a photodegradation rate of up to 99% for MB and 79% for MO in different water samples under exposure to sunlight. The novel phytofabricated Semal-ZnO NPs are thus a beacon of hope for the environment, with their desirable photocatalytic efficiency, pseudo-first-order kinetics, and ability to break down noxious dye pollutants in various aquatic environments.

Comparing Outcomes of Community-Acquired Pneumonia Patients Discharged from General Medicine and Respiratory Units in Australia: A Propensity Score-Matched Analysis.

Background/Objectives: Community-acquired pneumonia (CAP) is a common emergency presentation in Australia, with the choice of admitting specialty unit often influenced by pneumonia severity and comorbidities. However, it remains unclear whether there are between-specialty differences in patient characteristics and outcomes. We sought to address this issue by investigating the characteristics and outcomes of CAP patients admitted to General Medicine (GM) versus Respiratory units. Methods: This retrospective observational study utilised data from the two largest metropolitan hospitals in South Australia, encompassing all non-COVID-19-related CAP admissions throughout 2021 to 2023. The hospital length of stay (LOS), in-patient and 30-day mortality, and 30-day readmission rates were assessed by propensity score matching (PSM) using 17 variables. Results: Of the 3004 cases of non-COVID-19 CAP admitted across the two hospitals during the study period, 2673 (71.8%) were admitted under GM units and 331 (9.1%) under Respiratory units. GM patients were, on average, a decade older, presented with a significantly higher burden of comorbidities, exhibited a greater prevalence of frailty, and had higher pneumonia severity compared to those admitted under a Respiratory unit (p < 0.05). Unadjusted analysis revealed a shorter median LOS among GM-admitted patients (5.9 vs. 4.1 days, p < 0.001). After PSM adjustment, patients admitted under the Respiratory units had an 8-fold higher odds of a longer LOS compared to GM (adjusted odds ratio [aOR] 8.53, 95% CI 1.96-37.25, p = 0.004). Other clinical outcomes were comparable between the two groups. Conclusions: Our findings indicate that GM units compared to Respiratory units provide efficient and safe care for patients requiring hospitalisation for CAP.

Role of vitamin C in treatment of community-acquired pneumonia in adult patients requiring hospitalisation: a systematic review protocol.

INTRODUCTION: Community-acquired pneumonia (CAP) is a leading cause of hospitalisation and is associated with a high mortality. Vitamin C is a powerful antioxidant and has been used in treatment of infections; however, its role as an adjunctive treatment in CAP is unclear. This review aims to assess the efficacy and safety of vitamin C in adults who require hospitalisation for CAP. METHODS AND ANALYSES: Searches will be conducted from inception to November 2023 on Ovid MEDLINE Daily and MEDLINE, Embase CINAHL, the Cochrane Central Register of Controlled Trials, Scopus, Web of Science and ClinicalTrials.gov databases with the aid of a medical librarian. We will include data from randomised controlled trials reporting vitamin C supplementation in patients with CAP requiring hospitalisation. Two independent reviewers will select studies, extract data and will assess the risk of bias by use of the Risk of Bias tool. The overall certainty of evidence will be assessed by use of the Grading of Recommendations Assessment, Development and Evaluation framework. Random-effects meta-analyses will be conducted, and effect measures will be reported as relative risks with 95% CIs. ETHICS AND DISSEMINATION: No previous ethical approval is required for this review. The findings of this review will be submitted to a scientific journal and presented at an international medical conference. PROSPERO REGISTRATION NUMBER: 483860.

In Situ Electrophoretic Decorated Cactus-Type Metallic-Phase MoS2 on CaMn2O4 Nanofibers for Binder-Free Next-Generation LIBs.

Ternary manganese-based oxides, such as CaMn2O4 (CMO) nanofibers fabricated via the electrospinning technique, have the potential to offer higher reversible capacity through conversion reactions in comparison to that of carbon-based anodes. However, its poor electrical conductivity hinders its usage in lithium-ion batteries (LIBs). Hence, to mitigate this issue, controlled single-step in situ decoration of highly conducting metallic-phase MoS2@CMO nanofibers has been achieved for the first time via the electrophoretic deposition (EPD) technique and utilized as a binder-free nanocomposite anode for LIBs. Further, the composition of MoS2@CMO nanofibers has also been optimized to attain better electronic and ionic conductivity. The morphological investigation revealed that the flakes of MoS2 nanoflowers are successfully and uniformly decorated over the CMO nanofibers' surface, forming a cactus-type morphology. As a binder-free nanocomposite LIB anode, CMOMS-7 (7 wt % MoS2@CMO) demonstrates a specific capacity of 674 mA h g-1 after 60 cycles at 50 mA g-1 and maintains a capacity of 454 mA h g-1 even after 300 cycles at 1000 mA g-1. Further, the good rate performance (102 mA h g-1 at 5000 mA g-1) of CMOMS-7 can be ascribed to the enhanced electrical conductivity provided by the metallic-phase MoS2. Moreover, the feasibility of CMOMS-7 is thoroughly investigated by using a full Li-ion cell incorporating a binder-free cathode of LiNi0.3Mn0.3Co0.3O2 (NMC). This configuration showcases an impressive energy density of 154 Wh kg-1. Thus, the hierarchical and aligned structure of CMO nanofibers combined with highly conductive MoS2 nanoflowers facilitates charge transportation within the composite electrodes. This synergistic effect significantly enhances the energy density of the conversion-based nanocomposites, making them highly promising anodes for advanced LIBs.

Barriers and Enablers to a Hospital-to-Home, Combined Exercise and Nutrition, Self-Managed Program for Pre-Frail and Frail Hospitalised Older Adults.

INTRODUCTION: Self-managed exercise and nutrition interventions can alleviate pre-frailty and frailty but understanding of adherence to them is lacking. This study aimed to explore the experiences of, and barriers and enablers to, a hospital-to-home self-managed combined exercise and nutrition program for hospitalised older adults living with pre-frailty and frailty. METHODS: A hybrid approach to data- and theory-driven descriptive thematic analysis identified experiences, barriers, and enablers to participation in a 3-month, self-managed, exercise-nutrition, hospital-to-home frailty-support program. Pre-frail and frail older adult patients ≥ 65 years admitted to the acute medical unit at a South Australian tertiary hospital were recruited. Individual semi-structured interviews were audio-recorded, transcribed verbatim, and analysed descriptively, using the Theoretical Domains Framework. RESULTS: The nutrition component of the program found 11 common barriers and 18 common enablers. The exercise component included 14 barriers and 24 enablers. Intentions, Social influences, Environmental context/resource and Emotions served as primary barriers towards adherence to both components. Common enablers for both components included Knowledge, Social identity, Environmental context/resource, Social influences, and Emotions. CONCLUSIONS: This research revealed important factors affecting adherence to a self-managed exercise-nutrition program in pre-frail and frail older adults within the environment, resources, and emotion domains that should be considered when designing other intervention programs in this population group.

Microalgae derived honeycomb structured mesoporous diatom biosilica for adsorption of malachite green: Process optimization and modeling.

The present study investigated the removal of malachite green dye from aquifers by means of microalgae-derived mesoporous diatom biosilica. The various process variables (dye concentration, pH, and adsorbent dose) influencing the removal of the dye were optimized and their interactive effects on the removal efficiency were explored by response surface methodology. The pH of the solution (pH = 5.26) was found to be the most dominating among other tested variables. The Langmuir isotherm (R2 = 0.995) best fitted the equilibrium adsorption data with an adsorption capacity of 40.7 mg/g at 323 K and pseudo-second-order model (R2 = 0.983) best elucidated the rate of dye removal (10.6 mg/g). The underlying mechanism of adsorption was investigated by Weber-Morris and Boyd models and results revealed that the film diffusion governed the overall adsorption process. The theoretical investigations on the dye structure using DFT-based chemical reactivity descriptors indicated that malachite green cations are electrophilic, reactive and possess the ability to accept electrons, and are strongly adsorbed on the surface of diatom biosilica. Also, the Fukui function analysis proposed the favorable adsorption sites available on the adsorbent surface.

Silicon, a quasi-essential element: Availability in soil, fertilizer regime, optimum dosage, and uptake in plants.

The essentiality of silicon (Si) has always been a matter of debate as it is not considered crucial for the lifecycles of most plants. But beneficial effects of endogenous Si and its supplementation have been observed in many plants. Silicon plays a pivotal role in alleviating the biotic and abiotic stress in plants by acting as a physical barrier as well as affecting molecular pathways involved in stress tolerance, thus widely considered as "quasi-essential". In soil, most of Si is found in complex forms as mineral silicates which is not available for plant uptake. Monosilicic acid [Si(OH)4] is the only plant-available form of silicon (PAS) present in the soil. The ability of a plant to uptake Si is positively correlated with the PAS concentration of the soil. Since many cultivated soils often lack a sufficient amount of PAS, it has become common practice to supplement Si through the use of Si-based fertilizers in various crop cultivation systems. This review outlines the use of natural and chemical sources of Si as fertilizer, different regimes of Si fertilization, and conclude by identifying the optimum concentration of Si required to observe the beneficial effects in plants. Also, the different mathematical models defining the mineral dynamics for Si uptake at whole plant scale considering various natural factors like plant morphology, mineral distribution, and transporter expression have been discussed. Information provided here will further help in increasing understanding of Si role and thereby facilitate efficient exploration of the element as a fertilizer in crop production.

A precise model for skin cancer diagnosis using hybrid U-Net and improved MobileNet-V3 with hyperparameters optimization.

Skin cancer is a frequently occurring and possibly deadly disease that necessitates prompt and precise diagnosis in order to ensure efficacious treatment. This paper introduces an innovative approach for accurately identifying skin cancer by utilizing Convolution Neural Network architecture and optimizing hyperparameters. The proposed approach aims to increase the precision and efficacy of skin cancer recognition and consequently enhance patients' experiences. This investigation aims to tackle various significant challenges in skin cancer recognition, encompassing feature extraction, model architecture design, and optimizing hyperparameters. The proposed model utilizes advanced deep-learning methodologies to extract complex features and patterns from skin cancer images. We enhance the learning procedure of deep learning by integrating Standard U-Net and Improved MobileNet-V3 with optimization techniques, allowing the model to differentiate malignant and benign skin cancers. Also substituted the crossed-entropy loss function of the Mobilenet-v3 mathematical framework with a bias loss function to enhance the accuracy. The model's squeeze and excitation component was replaced with the practical channel attention component to achieve parameter reduction. Integrating cross-layer connections among Mobile modules has been proposed to leverage synthetic features effectively. The dilated convolutions were incorporated into the model to enhance the receptive field. The optimization of hyperparameters is of utmost importance in improving the efficiency of deep learning models. To fine-tune the model's hyperparameter, we employ sophisticated optimization methods such as the Bayesian optimization method using pre-trained CNN architecture MobileNet-V3. The proposed model is compared with existing models, i.e., MobileNet, VGG-16, MobileNet-V2, Resnet-152v2 and VGG-19 on the "HAM-10000 Melanoma Skin Cancer dataset". The empirical findings illustrate that the proposed optimized hybrid MobileNet-V3 model outperforms existing skin cancer detection and segmentation techniques based on high precision of 97.84%, sensitivity of 96.35%, accuracy of 98.86% and specificity of 97.32%. The enhanced performance of this research resulted in timelier and more precise diagnoses, potentially contributing to life-saving outcomes and mitigating healthcare expenditures.

Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model.

Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and results in severe depression and suicide attempts in the social community. Prompt actions are crucial in tackling PPDD, which requires a quick recognition and accurate analysis of the probability factors associated with this condition. This concern requires attention. The primary aim of our research is to investigate the feasibility of anticipating an individual's mental state by categorizing individuals with depression from those without depression using a dataset consisting of text along with audio recordings from patients diagnosed with PPDD. This research proposes a hybrid PPDD framework that combines Improved Bi-directional Long Short-Term Memory (IBi-LSTM) with Transfer Learning (TL) based on two Convolutional Neural Network (CNN) architectures, respectively CNN-text and CNN audio. In the proposed model, the CNN section efficiently utilizes TL to obtain crucial knowledge from text and audio characteristics, whereas the improved Bi-LSTM module combines written material and sound data to obtain intricate chronological interpersonal relationships. The proposed model incorporates an attention technique to augment the effectiveness of the Bi-LSTM scheme. An experimental analysis is conducted on the PPDD online textual and speech audio dataset collected from UCI. It includes textual features such as age, women's health tracks, medical histories, demographic information, daily life metrics, psychological evaluations, and 'speech records' of PPDD patients. Data pre-processing is applied to maintain the data integrity and achieve reliable model performance. The proposed model demonstrates a great performance in better precision, recall, accuracy, and F1-score over existing deep learning models, including VGG-16, Base-CNN, and CNN-LSTM. These metrics indicate the model's ability to differentiate among women at risk of PPDD vs. non-PPDD. In addition, the feature importance analysis demonstrates that specific risk factors substantially impact the prediction of PPDD. The findings of this research establish a basis for improved precision and promptness in assessing the risk of PPDD, which may ultimately result in earlier implementation of interventions and the establishment of support networks for women who are susceptible to PPDD.

A hybrid cloud load balancing and host utilization prediction method using deep learning and optimization techniques.

Virtual machine (VM) integration methods have effectively proven an optimized load balancing in cloud data centers. The main challenge with VM integration methods is the trade-off among cost effectiveness, quality of service, performance, optimal resource utilization and compliance with service level agreement violations. Deep Learning methods are widely used in existing research on cloud load balancing. However, there is still a problem with acquiring noisy multilayered fluctuations in workload due to the limited resource-level provisioning. The long short-term memory (LSTM) model plays a vital role in the prediction of server load and workload provisioning. This research presents a hybrid model using deep learning with Particle Swarm Intelligence and Genetic Algorithm ("DPSO-GA") for dynamic workload provisioning in cloud computing. The proposed model works in two phases. The first phase utilizes a hybrid PSO-GA approach to address the prediction challenge by combining the benefits of these two methods in fine-tuning the Hyperparameters. In the second phase, CNN-LSTM is utilized. Before using the CNN-LSTM approach to forecast the consumption of resources, a hybrid approach, PSO-GA, is used for training it. In the proposed framework, a one-dimensional CNN and LSTM are used to forecast the cloud resource utilization at various subsequent time steps. The LSTM module simulates temporal information that predicts the upcoming VM workload, while a CNN module extracts complicated distinguishing features gathered from VM workload statistics. The proposed model simultaneously integrates the resource utilization in a multi-resource utilization, which helps overcome the load balancing and over-provisioning issues. Comprehensive simulations are carried out utilizing the Google cluster traces benchmarks dataset to verify the efficiency of the proposed DPSO-GA technique in enhancing the distribution of resources and load balancing for the cloud. The proposed model achieves outstanding results in terms of better precision, accuracy and load allocation.

Fluorescence Study of Pr3+ Doped CdS Nanoparticles and its Applications in Sensors and Detectors.

Fluorescence spectra of Pr3+ doped CdS nanoparticles, synthesized by chemical precipitation method, have been recorded at room temperature. The synthesized particles are nearly spherical shaped and the grain size is decreased with the increase in Pr3+ concentration. The chemical identity of the nanoparticles was confirmed by EDAX spectrum, the absorption peaks was confirmed by FTIR spectrum and then the recorded values were compared with the CIE diagram. The oscillator strengths of the 4f ↔ 4I transitions are parameterized in terms of three phenomenological Judd-Ofelt intensity parameters Ωλ (λ = 2, 4 and 6). Using the fluorescence data and these Ωλ parameters, theoretical and experimental study of various radiative properties viz., spontaneous emission probability (A), radiative life time , fluorescence branching ratio and stimulated emission cross-section were evaluated. The values of these parameters indicate that 3P0→ 3H4 transition can be considered to be good laser transition in the visible colour region. Also, excitation with 493 nm, leads to similar blue regions. The synthesized Pr3+ doped CdS nanomaterials could be useful for sensing and detecting devices, particularly for temperature sensing measurement and bio-sensing detection.

Structural assessment of OsNIP2;1 highlighted critical residues defining solute specificity and functionality of NIP class aquaporins.

INTRODUCTION: Nodulin-26-like intrinsic proteins (NIPs) are integral membrane proteins belonging to the aquaporin family, that facilitate the transport of neutral solutes across the bilayer. The OsNIP2;1 a member of NIP-III class of aquaporins is permeable to beneficial elements like silicon and hazardous arsenic. However, the atomistic cross-talk of these molecules traversing the OsNIP2;1 channel is not well understood. OBJECTIVE: Due to the lack of genomic variation but the availability of high confidence crystal structure, this study aims to highlight structural determinants of metalloid permeation through OsNIP2;1. METHODS: The molecular simulations, combined with site-directed mutagenesis were used to probe the role of specific residues in the metalloid transport activity of OsNIP2;1. RESULTS: We drew energetic landscape of OsNIP2;1, for silicic and arsenous acid transport. Potential Mean Force (PMF) construction illuminate three prominent energetic barriers for metalloid passage through the pore. One corresponds to the extracellular molecular entry in the channel, the second located on ar/R filter, and the third size constriction in the cytoplasmic half. Comparative PMF for silicic acid and arsenous acid elucidate a higher barrier for silicic acid at the cytoplasmic constrict resulting in longer residence time for silicon. Furthermore, our simulation studies explained the importance of conserved residues in loop-C and loop-D with a direct effect on pore dynamics and metalloid transport. Next we assessed contribution of predicted key residues for arsenic uptake, by functional complementation in yeast. With the aim of reducing arsenic uptake while maintaining beneficial elements uptake, we identified novel OsNIP2;1 mutants with substantial reduction in arsenic uptake in yeast. CONCLUSION: We provide a comprehensive assessment of pore lining residues of OsNIP2;1 with respect to metalloid uptake. The findings will expand mechanistic understanding of aquaporin's metalloid selectivity and facilitate variant interpretation to develop novel alleles with preference for beneficial metalloid species and reducing hazardous ones.

Facile preparation, characterization and application of novel sugarcane bagasse-derived nanoceria-biochar for defluoridation of drinking water: kinetics, thermodynamics, reusability and mechanism.

Although expensive, rare-earth oxides are well known for being powerful defluoridation agents. Being costlier, cerium is used as a hybrid adsorbent in conjunction with a prudent and environmentally benign substance like biochar. The novel CeO2/BC (surface area 260.05 m2/g) composite was shaped using the facile chemical precipitation technique without any cross-linkers. Surface properties of synthesised CeO2/BC were investigated using powder XRD, FTIR, BET, pH point of zero charge and SEM. According to XRD analysis, immobilized Ce is primarily in form of CeO2, while pristine biochar is in an amorphous state. Batch mode adsorption tests were carried out with different solution pH, F- initial concentration, adsorbent dosage and contact time and counter anions. CeO2/BC can be used in a varied pH range (2-10) but shows maximum removal at pH 4. The Langmuir adsorption isotherm and a pseudo-second-order kinetic model are best fitted to support the adsorption process with a maximum Langmuir adsorption capacity of 16.14 mg/g (F- concentration 5 to 40 mg/L). The removal phenomenon is non-spontaneous in nature. The plausible mechanism of fluoride uptake was explained using XPS and pHPZC, and it was demonstrated that the fluoride was mainly removed by ion exchange and electrostatic attraction. The adsorbent could be successfully used up to fourth cycle after regenerating.

Spatial distribution of heavy metals in the sediments of River Ganges, India: Occurrence, contamination, source identification, seasonal variations, mapping, and ecological risk evaluation.

Present study analyzed the seasonal and spatial distribution patterns, sources, and ecological risks of seven heavy metals (Cr, Fe, Ni, Cu, Zn, Cd and Pb) in the sediments of River Ganges, finding that the majority of concentrations were lithologic, except for Cd, which was significantly higher than background standards. Elevated values of geochemical indices viz. Igeo, CF, RI, Cd, mCd, HQ, mHQ, and PN suggest moderate to high ecological risk in the benthic environment and its organisms due to the synergistic effect of heavy metals. The PEC-Qmetals revealed 8-10 % toxicity in the upstream and downstream sites, due to the influence of agricultural activities. Multivariate statistical techniques (PCM and PCA) indicated that Cd and Pb predominantly originated from anthropogenic sources, while other metals primarily derived from geological background. These geochemical findings may help to understand the potential risks and recommend strategies to mitigate the effects of metallic contamination in river sediments.

Cu(II)-Catalyzed Aminocyclization of N-Propargyl Hydrazones to Substituted Pyrazolines.

An efficient route for the copper(II)-catalyzed synthesis of substituted pyrazolines from readily accessible N-propargyl hydrazones has been reported under open flask conditions via intramolecular C-N bond formation. N-acyl and N-tosyl-substituted pyrazolines have been prepared in moderate to excellent yields. Mechanistic investigations using NMR, high-resolution mass spectrometry (HRMS), and Hammett analyses suggest that the Cu(II) catalyst generally acts as a Lewis acid to form an iminium-ion intermediate via cyclization, which afforded the desired pyrazolines upon hydrolysis. One progesterone receptor antagonist has also been synthesized utilizing this reaction methodology.

Semisynthesis of Novel Dispiro-pyrrolizidino/thiopyrrolizidino-oxindolo/indanedione Natural Product Hybrids of Parthenin Followed by Their Cytotoxicity Evaluation.

Natural products possess unique and broader intricacies in the chemical space and have been essential for drug discovery. The crucial factor for drug discovery success is not the size of the library but rather its structural diversity. Although reports on the number of new structurally diverse natural products (NPs) have declined recently, researchers follow the next logical step: synthesizing natural product hybrids and their analogues using the most potent tool, diversity-oriented synthesis (DOS). Here, we use weed Parthenium hysterophorus as a source of parthenin for synthesis of novel dispiro-pyrrolizidino/thiopyrrolizidino-oxindolo/indanedione natural product hybrids of parthenin via chemo-, regio-, and stereoselective azomethine ylide cycloaddition. All synthesized compounds were characterized through a detailed analysis of one-dimensional (1D) and two-dimensional (2D) NMR and HRMS data, and the stereochemistries of the compounds were confirmed by X-ray diffraction analysis. All compounds were evaluated for their cytotoxicity against four cell lines (HCT-116, A549, Mia-Paca-2, and MCF-7), and compound 6 inhibited the HCT-116 cells with an IC50 of 5.0 ± 0.08 µM.

Identification of VrNIP2-1 aquaporin with novel selective filter regulating the transport of beneficial as well as hazardous metalloids in mungbean (Vigna radiata L.).

Nodulin 26-like intrinsic protein (NIP) subfamily of aquaporins (AQPs) in plants, is known to be involved in the uptake of metalloids including boron, germanium (Ge), arsenic (As), and silicon (Si). In the present study, a thorough evaluation of 55 AQPs found in the mungbean genome, including phylogenetic distribution, sequence homology, expression profiling, and structural characterization, contributed to the identification of VrNIP2-1 as a metalloid transporter. The pore-morphology of VrNIP2-1 was studied using molecular dynamics simulation. Interestingly, VrNIP2-1 was found to harbor an aromatic/arginine (ar/R) selectivity filter formed with ASGR amino acids instead of GSGR systematically reported in metalloid transporters (NIP2s) in higher plants. Evaluation of diverse cultivars showed a high level of Si accumulation in leaves indicating functional Si transport in mungbean. In addition, heterologous expression of VrNIP2-1 in yeast revealed As(III) and GeO2 transport activity. Similarly, VrNIP2-1 expression in Xenopus oocytes confirmed its Si transport ability. The metalloid transport activity with unique structural features will be helpful to better understand the solute specificity of NIP2s in mungbean and related pulses. The information provided here will also serve as a basis to improve Si uptake while restricting hazardous metalloids like As in plants.

Fluoride release by restorative materials after applying surface coating agents.

The prompt use of an enamel surface covering reagent is advised to safeguard the dental restorative substance from mishaps. Therefore, it is of interest to assess the fluoride emitting capabilities of standard GIC, and Zirconomer cement together with surface coverings and without surface coverings. The conventional GIC cement was part of experimental category A while Zirconomer cement was part of category B. For every experimental categories, a set of sixty brass mould prototypes in the form of disc with dimensions: diameter (6±0.1mm) and thickness (2±0.1 mm) were created and subsequently covered with Teflon strip in accordance with the package recommendations. Also, for both experimental categories, such pellets were randomly allocated to three sub-categories of 20 each. For one category petroleum jelly was administered with a cotton bud and then delicately dried under airflow (A3 subcategory and B3 subcategory); for another sub-category G-Coat was laced through a micro-tip dispenser and light treated for twenty seconds (A2 subcategory and B2 subcategory); the rest 20 specimens were left without any coating (A1 subcategory and B1 subcategory). It was observed that in subcategory A1 and A3 there was continuous decline in emission of fluoride ion as the days progressed. However there was an increase in emission of fluoride in A2 subcategory on moving to day 5 from day 1. However, from day 5 onwards decline in fluoride emission was observed in A2 subcategory. It was concluded that both materials studied (GIC and Zirconomer) exhibited fluoride emission whether or not they were surface-coated for protection.