Machine learning powered CN-coordinated cobalt nanoparticles embedded cellulosic nanofibers to assess meat quality via clenbuterol monitoring.

The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat quality because, athletes might have positive test for CLN even after consuming very low quantity of CLN contaminated meat. Numerous materials applied for CLN monitoring faced potential challenges like sluggish ion transport, non-uniform ion/molecule movement, and inadequate electrode surface binding. To overcome these shortcomings, herein we engineered bimetallic zeolitic imidazole framework (BM-ZIF) derived N-doped porous carbon embedded Co nanoparticles (CN-CoNPs), dispersed on conductive cellulose acetate-polyaniline (CP) electrospun nanofibers for sensitive electrochemical monitoring of CLN. Interestingly, the smartly designed CN-CoNPs wrapped CP (CN-CoNPs-CP) electrospun nanofibers offers rapid diffusion of CLN molecules to the sensing interface through amine and imine groups of CP, thus minimizing the inhomogeneous ion transportation and inadequate electrode surface binding. Additionally, to synchronize experiments, machine learning (ML) algorithms were applied to optimize, predict, and validate voltametric current responses. The ML-trained sensor demonstrated high selectivity, even amidst interfering substances, with notable sensitivity (4.7527 µA/µM/cm2), a broad linear range (0.002-8 µM), and a low limit of detection (1.14 nM). Furthermore, the electrode exhibited robust stability, retaining 98.07% of its initial current over a 12-h period. This ML-powered sensing approach was successfully employed to evaluate meat quality in terms of CLN level. To the best of our knowledge, this is the first study of using ML powered system for electrochemical sensing of CLN.

Correction: Shakir et al. Exorbitant Drug Loading of Metformin and Sitagliptin in Mucoadhesive Buccal Tablet: In Vitro and In Vivo Characterization in Healthy Volunteers. Pharmaceuticals 2022, 15, 686.

In the original publication, a mistake was observed in Figure 5 as published [...].

Clinical characteristics, outcome, and factors associated with mortality of pulmonary mucormycosis: a retrospective single-center study from Pakistan.

Introduction and objective: Pulmonary mucormycosis is a rare but rapidly progressive fatal disease. Limited data exist on the outcomes and factors associated with poor prognosis of pulmonary mucormycosis. The objective of this study was to evaluate clinical characteristics, factors associated with mortality, and outcomes of pulmonary mucormycosis at a tertiary care hospital in Pakistan. Methods: This was a retrospective observational study conducted at a tertiary care hospital in Karachi, Pakistan. Medical records of hospitalized patients diagnosed with proven or probable pulmonary mucormycosis between January 2018 and December 2022 were reviewed. Univariate and regression analyses were performed to identify factors associated with mortality. Results: Fifty-three pulmonary mucormycosis patients (69.8% male) were included, with mean age of 51.19 ± 21.65 years. Diabetes mellitus was the most common comorbidity [n = 26 (49.1%)]. Chronic lung diseases were present in [n = 5 (9.4%)], and [n = 16 (30.2%)] had concurrent coronavirus disease 2019 (COVID-19) pneumonia. The predominant isolated Mucorales were Rhizopus [n = 32 (60.3%)] and Mucor species [n = 9 (17%)]. Main radiological findings included consolidation [n = 39 (73.6%)] and nodules [n = 14 (26.4%)]. Amphotericin B deoxycholate was prescribed in [n = 38 (71.7%)], and [n = 14 (26.4%)] of patients received combined medical and surgical treatment. The median [interquartile range (IQR)] hospital stay was 15.0 (10.0-21.5) days. Intensive care unit (ICU) care was required in [n = 30 (56.6%)] patients, with 26 (49.1%) needing mechanical ventilation. Overall mortality was seen in 29 (54.7%) patients. Significantly higher mortality was found among patients requiring mechanical ventilation 20/29 (69%, p = 0.002). Immunosuppression (p = 0.042), thrombocytopenia (p = 0.004), and mechanical ventilation (p = 0.018) were identified as risk factors for mortality on multivariable analysis. Conclusion: This study provides essential insights into the clinical characteristics, outcomes, and mortality factors associated with pulmonary mucormycosis. The mortality rate was high (54.7%), particularly in patients with immunosuppression, thrombocytopenia, and those who required mechanical ventilation.

Emerging trends to replace pesticides with nanomaterials: Recent experiences and future perspectives for ecofriendly environment.

Despite the widespread usage to safeguard crops and manage pests, pesticides have detrimental effects on the environment and human health. The necessity to find sustainable agricultural techniques and meet the growing demand for food production has spurred the quest for pesticide substitutes other than traditional ones. The unique qualities of nanotechnology, including its high surface area-to-volume ratio, controlled release, and better stability, have made it a promising choice for pest management. Over the past ten years, there has been a noticeable growth in the usage of nanomaterials for pest management; however, concerns about their possible effects on the environment and human health have also surfaced. The purpose of this review paper is to give a broad overview of the worldwide trends and environmental effects of using nanomaterials in place of pesticides. The various types of nanomaterials, their characteristics, and their possible application in crop protection are covered. The limits of the current regulatory frameworks for nanomaterials in agriculture are further highlighted in this review. Additionally, it describes how standard testing procedures must be followed to assess the effects of nanomaterials on the environment and human health before their commercialization. In order to establish sustainable and secure nanotechnology-based pest control techniques, the review concludes by highlighting the significance of taking into account the possible hazards and benefits of nanomaterials for pest management and the necessity of an integrated approach. It also emphasizes the importance of more investigation into the behavior and environmental fate of nanomaterials to guarantee their safe and efficient application in agriculture.

Moxifloxacin-loaded nanoparticles of thiolated xyloglucan for ocular drug delivery: Permeation, mucoadhesion and pharmacokinetic evaluation.

The current study goal was to improve mucoadhesive potential and ocular pharmacokinetics of nanoparticles of thiolated xyloglucan (TXGN) containing moxifloxacin (MXF). Thiolation of xyloglucan (XGN) was achieved with esterification with 3-mercaptopropionic acid. TXGN was characterized by NMR and FTIR analysis. The nanoparticles of TXGN were prepared using ionic-gelation method and evaluate the antibacterial properties. TXGN and nanoparticles were determined to possess 0.06 and 0.08 mmol of thiol groups/mg of polymer by Ellman's method. The ex-vivo bioadhesion time of TXGN and nanoparticles was higher than XGN in a comparative assessment of their mucoadhesive properties. The creation of a disulfide link between mucus and TXGN is responsible for the enhanced mucoadhesive properties of TXGN (1-fold) and nanoparticles (2-fold) over XGN. Improved MXF penetration in nanoparticulate formulation (80 %) based on TXGN was demonstrated in an ex-vivo permeation research utilizing rabbit cornea. Dissolution study showed 95 % release of MXF from nanoparticles. SEM images of nanoparticles showed spherical shape and cell viability assay showed nontoxic behavior when tested on RPE cell line. Antibacterial analysis revealed a zone of inhibition of 31.5 ± 0.5 mm for MXF, while NXM3 exhibited an expanded zone of 35.5 ± 0.4 mm (p < 0.001). In conclusion, thiolation of XGN improves its bioadhesion, permeation, ocular-retention and pharmacokinetics of MXF.

Utilization of microalgae for agricultural runoff remediation and sustainable biofuel production through an integrated biorefinery approach.

Generally wastewater such agricultural runoff is considered a nuisance; however, it could be harnessed as a potential source of nutrients like nitrates and phosphates in integrated biorefinery context. In the current study, microalgae Chlorella sp. S5 was used for bioremediation of agricultural runoff and the leftover algal biomass was used as a potential source for production of biofuels in an integrated biorefinery context. The microalgae Chlorella sp. S5 was cultivated on Blue Green (BG 11) medium and a comprehensive optimization of different parameters including phosphates, nitrates, and pH was carried out to acquire maximum algal biomass enriched with high lipids content. Dry biomass was quantified using the solvent extraction technique, while the identification of nitrates and phosphates in agricultural runoff was carried out using commercial kits. The algal extracted lipids (oils) were employed in enzymatic trans-esterification for biodiesel production using whole-cell biomass of Bacillus subtilis Q4 MZ841642. The resultant fatty acid methyl esters (FAMEs) were analyzed using Fourier transform infrared (FTIR) spectroscopy and gas chromatography coupled with mass spectrometry (GC-MS). Subsequently, both the intact algal biomass and its lipid-depleted algal biomass were used for biogas production within a batch anaerobic digestion setup. Interestingly, Chlorella sp. S5 demonstrated a substantial reduction of 95% in nitrate and 91% in phosphate from agricultural runoff. The biodiesel derived from algal biomass exhibited a noteworthy total FAME content of 98.2%, meeting the quality standards set by American Society for Testing and Materials (ASTM) and European union (EU) standards. Furthermore, the biomethane yields obtained from whole biomass and lipid-depleted biomass were 330.34 NmL/g VSadded and 364.34 NmL/g VSadded, respectively. In conclusion, the findings underscore the potent utility of Chlorella sp. S5 as a multi-faceted resource, proficiently employed in a sequential cascade for treating agricultural runoff, producing biodiesel, and generating biogas within the integrated biorefinery concept.

Significance of Estrogen/Progesterone Receptor Expression in Metaplastic Breast Carcinoma.

Introduction: Metaplastic breast carcinoma (MBC) is a rare subgroup of breast neoplasms associated with adverse outcomes because of its aggressive nature. Typically, MBCs show triple-negative hormone receptor (HR) status. Determining the HR status of breast cancer is an integral part because it is an important prognostic factor and helps in the treatment course of the disease. This study aimed to determine the HR status of MBC, its significance, and its association with various clinicopathological parameters. Methods: This was a retrospective study conducted at the Department of Histopathology, Liaquat National Hospital. A total of 140 biopsy-proven cases of MBC were enrolled in the study. Clinical and pathological data were retrieved from the institutes' archives. Immunohistochemical studies were conducted to determine the estrogen receptor (ER) and progesterone receptor (PR) status. Results: The mean age of MBC in our population was found to be 52.18 ± 12.19 years. The HR positivity rate in our population was found to be 32.9%. A significant association was found between HR status and tumor laterality, tumor size, tumor grade, tumor stage, and recurrence. ER/PR-negative MBCs were most probably associated with higher grade and higher tumor stage and were larger in size (6.62 ± 3.43 cm) than ER/PR-positive MBCs (4.20 ± 1.88 cm). Moreover, ER/PR-positive MBCs showed a higher recurrence rate than ER/PR-negative MBCs (43.5% vs. 25.5%, respectively). No statistically significant relationship was found between HR status and patient age, histological subtype, or survival rate. Conclusion: MBC is a rare breast neoplasm. MBC was found to be triple negative in most cases, but a significant percentage were HR (ER/PR) positive. Moreover, we found an association between HR status and various clinicopathological features, indicating that HR status is a significant predictor of MBC prognosis.

Estimation of population median using bivariate auxiliary information in simple random sampling.

To estimate the unknown population median, several researchers have developed efficient estimators but these estimators are unable to provide efficient results in the existence of outliers. Keeping this point in view, the present work suggests enhanced class of robust estimators to estimate population median under simple random sampling in case of outliers/extreme observations. The suggested estimators are a mixture of bivariate auxiliary information and robust measures with the linear combination of deciles mean, tri-mean and Hodges Lehmann estimator. Mathematical properties associated with the improved class of robust estimators are evaluated in terms of bias and mean squared error. Moreover, the potentiality of our suggested estimators as compared to already available estimators is checked by considering two real-life data sets with outlier(s). In addition, a simulation study is also added in this regard. From theoretical and numerical findings, it is observed that our newly suggested estimators outperforms as compared to its competitors.

Enhancing brain tumor diagnosis: an optimized CNN hyperparameter model for improved accuracy and reliability.

Hyperparameter tuning plays a pivotal role in the accuracy and reliability of convolutional neural network (CNN) models used in brain tumor diagnosis. These hyperparameters exert control over various aspects of the neural network, encompassing feature extraction, spatial resolution, non-linear mapping, convergence speed, and model complexity. We propose a meticulously refined CNN hyperparameter model designed to optimize critical parameters, including filter number and size, stride padding, pooling techniques, activation functions, learning rate, batch size, and the number of layers. Our approach leverages two publicly available brain tumor MRI datasets for research purposes. The first dataset comprises a total of 7,023 human brain images, categorized into four classes: glioma, meningioma, no tumor, and pituitary. The second dataset contains 253 images classified as "yes" and "no." Our approach delivers exceptional results, demonstrating an average 94.25% precision, recall, and F1-score with 96% accuracy for dataset 1, while an average 87.5% precision, recall, and F1-score, with accuracy of 88% for dataset 2. To affirm the robustness of our findings, we perform a comprehensive comparison with existing techniques, revealing that our method consistently outperforms these approaches. By systematically fine-tuning these critical hyperparameters, our model not only enhances its performance but also bolsters its generalization capabilities. This optimized CNN model provides medical experts with a more precise and efficient tool for supporting their decision-making processes in brain tumor diagnosis.

Transcriptomic analysis provides an insight into the function of CmGH9B3, a key gene of ß-1, 4-glucanase, during the graft union healing of oriental melon scion grafted onto squash rootstock.

The melon (Cucumis melo L.) is a globally cherished and economically significant crop. The grafting technique has been widely used in the vegetative propagation of melon to promote environmental tolerance and disease resistance. However, mechanisms governing graft healing and potential incompatibilities in melons following the grafting process remain unknown. To uncover the molecular mechanism of healing of grafted melon seedlings, melon wild type (Control) and TRV-CmGH9B3 lines were obtained and grafted onto the squash rootstocks (C. moschata). Anatomical differences indicated that the healing process of the TRV-CmGH9B3 plants was slower than that of the control. A total of 335 significantly differentially expressed genes (DEGs) were detected between two transcriptomes. Most of these DEGs were down-regulated in TRV-CmGH9B3 grafted seedlings. GO and KEGG analysis showed that many metabolic, physiological, and hormonal responses were involved in graft healing, including metabolic processes, plant hormone signaling, plant MAPK pathway, and sucrose starch pathway. During the healing process of TRV-CmGH9B3 grafted seedlings, gene synthesis related to hormone signal transduction (auxin, cytokinin, gibberellin, brassinolide) was delayed. At the same time, it was found that most of the DEGs related to the sucrose pathway were down-regulated in TRV-CmGH9B3 grafted seedlings. The results showed that sugar was also involved in the healing process of melon grafted onto squash. These results deepened our understanding of the molecular mechanism of GH9B3, a key gene of ß-1, 4-glucanase. It also provided a reference for elucidating the gene mechanism and function analysis of CmGH9B3 in the process of graft union healing.

Unraveling the impact of wildfires on permafrost ecosystems: Vulnerability, implications, and management strategies.

Permafrost regions play an important role in global carbon and nitrogen cycling, storing enormous amounts of organic carbon and preserving a delicate balance of nutrient dynamics. However, the increasing frequency and severity of wildfires in these regions pose significant challenges to the stability of these ecosystems. This review examines the effects of fire on chemical, biological, and physical properties of permafrost regions. The physical, chemical, and pedological properties of frozen soil are impacted by fires, leading to changes in soil structure, porosity, and hydrological functioning. The combustion of organic matter during fires releases carbon and nitrogen, contributing to greenhouse gas emissions and nutrient loss. Understanding the interactions between fire severity, ecosystem processes, and the implications for permafrost regions is crucial for predicting the impacts of wildfires and developing effective strategies for ecosystem protection and agricultural productivity in frozen soils. By synthesizing available knowledge and research findings, this review enhances our understanding of fire severity's implications for permafrost ecosystems and offers insights into effective fire management strategies.

Tragacanth gum-based copper oxide nanoparticles: Comprehensive characterization, antibiofilm, antimicrobial and photocatalytic potentials.

Hereunder, we pioneered the synthesis of Copper Oxide nanoparticles (CuO NPs) utilizing Tragacanth gum (TG). The NPs were characterized using advanced techniques and assessed for different pharmaceutical and environmental perspectives. The successful formation of a colloidal NPs solution was confirmed by the appearance of a distinct black color and a distinct peak at 260 nm in UV-Visible spectrophotometry. The FTIR analysis unveiled a spectrum of functional groups responsible for the reduction and stabilization of CuO NPs. Dynamic Light Scattering (DLS) and Transmission Electron Microscopy (TEM) revealed size of NPs as 36.24 nm and 28 ± 04 nm respectively. Energy Dispersive X-ray (EDX) Analysis indicated weight percentages of 70.38 % for Cu and 18.88 % for O, with corresponding atomic percentages. The X-ray Diffraction (XRD) analysis revealed the orthorhombic crystal structure of the prepared CuO NPs. Antimicrobial assessments through disc-diffusion assays demonstrated significant zones of inhibition (ZOI) against gram-positive bacterial strains (Bacillus Halodurans and Micrococcus leutus) and a gram-negative bacterial strain (E. coli). Against the fungal strain Aspergillus niger, a ZOI of 18.5 ± 0.31 mm was observed. The NPs exhibited remarkable antioxidant potential determined through 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and H2O2 scavenging assays. At a concentration of 3 mg/mL, the NPs demonstrated biofilm inhibition rates of 96 %, 90 %, 89.60 %, and 72.10 % against Micrococcus luteus, Bacillus halodurans, MRSA and E.coli respectively. Furthermore, the CuO NPs showed a high photocatalytic potential towards the degradation of safranin dye under sunlight irradiation. In conclusion, the findings underline the promising multifunctional properties of TG-based CuO NPs for different practical applications.

Approach towards sustainable leather: Characterization and effective industrial application of proteases from Bacillus sps. for ecofriendly dehairing of leather hide.

Tanneries are one of the most polluted industries known for production of massive amount of solid and liquid wastes without proper management and disposal. In this project we demonstrated the ecofriendly single step dehairing of leather hides with minimum pollution load. In this study, Bacillus species (Bacillus paralicheniformis strain BL.HK, Bacillus cereus strain BS.P) capable of producing proteases was successfully isolated by employing the new optimized selective media named M9-PEA as confirmed by 16sRNA genes sequencing. Sequence of 1493 bp long 16S rRNA genes of Bacillus paralicheniformis strain BL.HK and Bacillus cereus strain BS. P was submitted to GenBank under the accession number OP612692.1, OP612721.1 respectively The Bacillus paralicheniformis strain BL.HK, Bacillus cereus strain BS.P produced extracellur proteases of 28 and 37 KDa as resolved by SDS-PAGE respectively. The enzymes showed temperature optima at 50 °C and 55 °C and pH optima at 8.5, 9.5 respectively. The Proteases of Bacillus paralicheniformis strain BL.HK, Bacillus cereus strain BS.P were employed for dehairing of animal hides. The process resulted in significant removal of interfibriller substances without damage to collagen layer after one hour treatment, which was confirmed by histology, scanning electron microscopy. The quantification of various skin constituents (collagen, uronic acid, hexosamines, and GAGs) and pollution load parameters revealed that enzymatic treatment are more reliable. The results of skin application trials at industrial level with complete elimination of chemicals remark the biotechnological potential of these proteases for ecofriendly dehairing of animal hides without affecting the quality of the leathers produced.

Advancing brain tumor detection: harnessing the Swin Transformer's power for accurate classification and performance analysis.

The accurate detection of brain tumors through medical imaging is paramount for precise diagnoses and effective treatment strategies. In this study, we introduce an innovative and robust methodology that capitalizes on the transformative potential of the Swin Transformer architecture for meticulous brain tumor image classification. Our approach handles the classification of brain tumors across four distinct categories: glioma, meningioma, non-tumor, and pituitary, leveraging a dataset comprising 2,870 images. Employing the Swin Transformer architecture, our method intricately integrates a multifaceted pipeline encompassing sophisticated preprocessing, intricate feature extraction mechanisms, and a highly nuanced classification framework. Utilizing 21 matrices for performance evaluation across all four classes, these matrices provide a detailed insight into the model's behavior throughout the learning process, furthermore showcasing a graphical representation of confusion matrix, training and validation loss and accuracy. The standout performance parameter, accuracy, stands at an impressive 97%. This achievement outperforms established models like CNN, DCNN, ViT, and their variants in brain tumor classification. Our methodology's robustness and exceptional accuracy showcase its potential as a pioneering model in this domain, promising substantial advancements in accurate tumor identification and classification, thereby contributing significantly to the landscape of medical image analysis.

Bridging drug discovery through hierarchical subtractive genomics against asd, trpG, and secY of pneumonia causing MDR Staphylococcus aureus.

Staphylococcus aureus (S. aureus) is an opportunistic gram-positive, non-motile, and non-sporulating bacteria that induces pneumonia, a provocative lung infection affecting mainly the terminal bronchioles and the small air sacs known as alveoli. Recently, it has developed antibiotic resistance to the available consortium as per the WHO reports; thereby, novel remedial targets and resilient medications to forestall and cure this illness are desperately needed. Here, using pan-genomics, a total of 1,387 core proteins were identified. Subtractive proteome analyses further identified 12 proteins that are vital for bacteria. One membrane protein (secY) and two cytoplasmic proteins (asd and trpG) were chosen as possible therapeutic targets concerning minimum % host identity, essentiality, and other cutoff values, such as high resistance in the MDR S. aureus. The UniProt AA sequences of the selected targets were modelled and docked against 3 drug-like chemical libraries. The top-ranked compounds i.e., ZINC82049692, ZINC85492658 and 3a of Isosteviol derivative for Aspartate-semialdehyde dehydrogenase (asd); ZINC38222743, ZINC70455378, and 5 m Isosteviol derivative for Anthranilate synthase component II (trpG); and finally, ZINC72292296, ZINC85632684, and 7 m Isosteviol derivative for Protein translocase subunit secY (secY), were further subjected to molecular dynamics studies for thermodynamic stability and energy calculation. Our study proposes new therapeutic targets in S. aureus, some of which have previously been reported in other pathogenic microorganisms. Owing to further experimental validation, we anticipate that the adapted methodology and the predicted results in this work could make major contributions towards novel drug discovery and their targets in S. aureus caused pneumonia.

Nonparametric mixed exponentially weighted moving average-moving average control chart.

This research designed a distribution-free mixed exponentially weighted moving average-moving average (EWMA-MA) control chart based on signed-rank statistic to effectively identify changes in the process location. The EWMA-MA charting statistic assigns more weight to information obtained from the recent w samples and exponentially decreasing weights to information accumulated from all other past samples. The run-length profile of the proposed chart is obtained by employing Monte Carlo simulation techniques. The effectiveness of the proposed chart is evaluated under symmetrical distributions using a variety of individual and overall performance measures. The analysis of the run-length profile indicates that the proposed chart performs better than the existing control charts discussed in the literature. Additionally, an application from a gas turbine is provided to demonstrate how the proposed chart can be used in practice.

Effect of biochar, zeolite and bentonite on physiological and biochemical parameters and lead and zinc uptake by maize (Zea mays L.) plants grown in contaminated soil.

Heavy metals (HMs) are common contaminants with major concern of severe environmental and health problems. This study evaluated the effects of organo-mineral amendments (mesquite biochar (MB), zeolite (ZL) and bentonite (BN) alone and in combination) applied at different rates to promote the maize (Zea mays L.) growth by providing essential nutrient and improving the soil physio-chemical properties under zinc (Zn) and lead (Pb) contamination. Result revealed that the incorporation of organo-mineral amendments had significantly alleviated Pb and Zn contamination by maize plants and improved the physiological and biochemical attributes of plants. Combined application of organo-mineral amendments including BMA-1, BMA-2 and BMA-3 performed excellently in terms of reducing Pb and Zn concentrations in both leaves (19-60%, 43-75%, respectively) and roots (24-59%, 42-68%, respectively) of maize. The amendments decreased the extractable, reducible, oxidisable and residual fractions of metals in soil and significantly reduced the soil DTPA-extractable Pb and Zn. BMA-1 substantially improved antioxidant enzyme activities in metal-stressed plants. This study indicated that combined use of organo-mineral amendments can effectively reduce the bioavailability and mobility of Pb and Zn in co-contaminated soils. Combined application of organo-mineral amendments could be viable remediation technology for immobilization and metal uptake by plants in polluted soils.