Investigating lactic acid bacteria genus Lactococcus lactis properties: Antioxidant activity, antibiotic resistance, and antibacterial activity against multidrug-resistant bacteria Staphylococcus aureus.

Background: Lactic acid bacteria (LAB) are utilized as a starter culture in the manufacturing of fermented dairy items, as a preservative for various food products, and as a probiotic. In our country, some research has been carried out, even if LAB plays a principal role in food preservation and improves the texture and taste of fermented foods, that is why we tried to evaluate their probiotic effect. The objective of this research was to determine the antibacterial activity of Lactococcus lactis (L. lactis) against Staphylococcus aureus (S. aureus) ATCC 29213, investigate their antioxidant activity, and characterize their sensitivity against 18 antibiotics. Methods: A total of 23 LAB (L. lactis subsp. cremoris, L. lactis subsp. Lactis diacetylactis, L. lactis subsp. lactis) were isolated from cow's raw milk. The antibacterial activity was performed using two techniques, competition for nutrients and a technique utilizing components nature, using the disk diffusion method. The sensitivity of the studied LAB to different antibiotics was tested on Man rogosa sharp (MRS) agar using commercial antibiotic disks. All strains of LAB were examined for their antioxidant activity. The antioxidant activity of L. lactis was tested by 2,2-diphenyl-1 picrylhydrazyl (DPPH). Results: The results showed that the MRS medium was more adapted than Muller Hinton Agar (MHA) to investigate the antibacterial activity of L. lactis against S. aureus ATCC 29213. Also, L. lactis exhibited a notable degree of antibacterial activity against S. aureus ATCC 29213. L. Lactis subsp. Lactis displayed higher antibacterial activities, followed by L. lactis ssp. lactis biovar. diacetylactis, and lastly, L. lactis ssp. cremoris against S. aureus ATCC 29213. Lc 26 among all strains of L. lactis showed a high potential antibacterial activity reaching 40 ± 3 mm against S. aureus ATCC 29213. All strains of L. lactis showed a slightly moderate antioxidant activity (10.56 ± 1.28%-26.29 ± 0.05 %). The results of the antibiotic resistance test indicate that all strains of L. lactis were resistant to cefotaxime, sulfamethoxazole-trimethoprim, and streptomycin and were sensitive to Ampicillin, Amoxicillin, Penicillin G, Teicoplanin, Vancomycin, Gentamicin 500, Tetracycline, and Chloramphenicol. These test results indicate that this strain falls within the criteria of not posing any harmful effects on human health. The important antibacterial properties recorded for all L. Lactis strains were derived from the production of antibacterial active metabolites, such as protein, diacetyl, hydrogen peroxide, and lactic acid, together with the fight for nutrients. Conclusion: This study suggests that the strains of L. lactis could be added as an antibacterial agent against S. aureus ATCC 29213 and can provide an important nutritional property for their antioxidant potential.

Liquid phase selective oxidation of veratryl alcohol to veratraldehyde using pure and Mg-doped copper chromite catalysts.

Mg-doped copper chromite (CuCr2O4) nanocomposites were synthesised through conventional technique. The pure and doped CuCr2-xMgx O4 (x = 0.00-0.1, 0.2 and 0.3%) nanocomposites were characterized in terms of their morphology, crystal structure, surface area and catalytic performance. The chemical composition of CuCr2-xMgx O4 was confirmed via FT-IR. The formation of pure and doped catalysts was validated by XRD results. TEM/SEM confirmed the formation of CuCr2-xMgxO4 nanoparticles. Mg-doped samples possess a high specific surface area compared to pure CuCr2O4. Thus, the effects of temperature, solvent, time, oxidant and the amount of catalyst on the oxidation of veratryl alcohol were reported. Furthermore, detailed mechanisms of the catalytic oxidation of veratryl alcohol as well as the reusability and stability of the nanomaterial were investigated. The resulting composites were shown to be effective heterogeneous catalysts for the oxidation of veratryl alcohol.

Variety-dependent responses of common tobacco with differential cadmium resistance: Cadmium uptake and distribution, antioxidative activity, and gene expression.

Cadmium (Cd), which accumulates in tobacco leaves, enters the human body through inhalation of smoke, causing harmful effects on health. Therefore, identifying the pivotal factors that govern the absorption and resistance of Cd in tobacco is crucial for mitigating the harmful impact of Cd. In the present study, four different Cd-sensitive varieties, namely, ZhongChuan208 (ZC) with resistance, ZhongYan100 (ZY), K326 with moderate resistance, and YunYan87 (YY) with sensitivity, were cultivated in hydroponic with different Cd concentrations (20 µM, 40 µM, 60 µM and 80 µM). The results indicated that plant growth was significantly decreased by Cd. Irrespective of the Cd concentration, ZC exhibited the highest biomass, while YY had the lowest biomass; ZY and K326 showed intermediate levels. Enzymatic (APX, CAT, POD) and nonenzymatic antioxidant (Pro, GSH) systems showed notable variations among varieties. The multifactor analysis suggested that the ZC and ZY varieties, with higher levels of Pro and GSH content, contribute to a decrease in the levels of MDA and ROS. Among all the Cd concentrations, ZC exhibited the lowest Cd accumulation, while YY showed the highest. Additionally, there were significant differences observed in Cd distribution and translocation factors among the four different varieties. In terms of Cd distribution, cell wall Cd accounted for the highest proportion of total Cd, and organelles had the lowest proportion. Among the varieties, ZC showed lower Cd levels in the cell wall, soluble fraction, and organelles. Conversely, YY exhibited the highest Cd accumulation in all tissues; K326 and ZY had intermediate levels. Translocation factors (TF) varied among the varieties under Cd stress, with ZC and ZY showing lower TF compared to YY and K326. This phenomenon mainly attributed to regulation of the NtNramp3 and NtNramp5 genes, which are responsible for the absorption and transport of Cd. This study provides a theoretical foundation for the selection and breeding of tobacco varieties that are resistant to or accumulate less Cd.

Deciphering morphology patterns of environmental microfibers: Insights into source apportionment.

Microfibers, a prevalent form of microplastics, undergo diverse environmental interactions resulting in varied morphological changes. These changes can offer insights into their environmental trajectories. Despite its importance, comprehensive studies on microfiber morphology are scarce. This study collected 233 microfibers from the East China Sea and South China Sea. Based on morphological features observed in microscopic images of microfibers, such as curvature, cross-sectional shapes, diameter variations, and crack shapes, we identified a general morphological pattern, classifying the environmental microfibers into three distinct morphological types. Our findings highlight noticeable differences in morphological metrics (e.g., length, diameter, and surface roughness) across three types, especially the diameter. Microfibers of Type I had an average diameter of 19.45 ± 4.93 µm, significantly smaller than Type II (263.00 ± 75.15 µm) and Type III (299.68 ± 85.62 µm). Within the three-dimensional (3D) space fully defined by these quantitative parameters, the clustering results of microfibers are also consistent with the proposed morphology pattern, with each category showing a potential correlation with specific chemical compositions. Type I microfibers correspond to synthetic cellulose, while 94.79 % of Types II and III are composed of polymers. Notably, we also validated the great applicability of the morphology categories to microfibers in diverse environmental compartments, including water and sediments in nearshore and offshore areas. This classification aids in the efficient determination of microfiber sources and the assessment of their ecological risks, marking a significant advancement in microfiber environmental studies.

A comparative survey between cascade correlation neural network (CCNN) and feedforward neural network (FFNN) machine learning models for forecasting suspended sediment concentration.

Suspended sediment concentration prediction is critical for the design of reservoirs, dams, rivers ecosystems, various operations of aquatic resource structure, environmental safety, and water management. In this study, two different machine models, namely the cascade correlation neural network (CCNN) and feedforward neural network (FFNN) were applied to predict daily-suspended sediment concentration (SSC) at Simga and Jondhara stations in Sheonath basin, India. Daily-suspended sediment concentration and discharge data from 2010 to 2015 were collected and used to develop the model to predict suspended sediment concentration. The developed models were evaluated using statistical indices like Nash and Sutcliffe efficiency coefficient (NES), root mean square error (RMSE), Willmott's index of agreement (WI), and Legates-McCabe's index (LM), supplemented by a scatter plot, density plots, histograms and Taylor diagram for graphical representation. The developed model was evaluated and compared with CCNN and FFNN. Nine input combinations were explored using different lag-times for discharge (Qt-n) and suspended sediment concentration (St-n) as input variables, with the current suspended sediment concentration as the desired output, to develop CCNN and FFNN models. The CCNN4 model with 4 lagged inputs (St-1, St-2, St-3, St-4) outperformed the other developed models with the lowest RMSE = 95.02 mg/l and the highest NES = 0.0.662, WI = 0.890 and LM = 0.668 for the Jondhara Station while the same CCNN4 model secure as the best with the lowest RMSE = 53.71 mg/l and the highest NES = 0.785, WI = 0.936 and LM = 0.788 for the Simga Station. The result shows the CCNN model was better than the FFNN model for predicting daily-suspended sediment at both stations in the Sheonath basin, India. Overall, CCNN showed better forecasting potential for suspended sediment concentration compared to FFNN at both stations, demonstrating their applicability for hydrological forecasting with complex relationships.

Extracellular vesicles-powered immunotherapy: Unleashing the potential for safer and more effective cancer treatment.

Cancer treatment has seen significant advancements with the introduction of Onco-immunotherapies (OIMTs). Although some of these therapies have received approval for use, others are either undergoing testing or are still in the early stages of development. Challenges persist in making immunotherapy widely applicable to cancer treatment. To maximize the benefits of immunotherapy and minimize potential side effects, it's essential to improve response rates across different immunotherapy methods. A promising development in this area is the use of extracellular vesicles (EVs) as novel delivery systems. These small vesicles can effectively deliver immunotherapies, enhancing their effectiveness and reducing harmful side effects. This article discusses the importance of integrating nanomedicines into OIMTs, highlighting the challenges with current anti-OIMT methods. It also explores key considerations for designing nanomedicines tailored for OIMTs, aiming to improve upon existing immunotherapy techniques. Additionally, the article looks into innovative approaches like biomimicry and the use of natural biomaterial-based nanocarriers (NCs). These advancements have the potential to transform the delivery of immunotherapy. Lastly, the article addresses the challenges of moving OIMTs from theory to clinical practice, providing insights into the future of using advanced nanotechnology in cancer treatment.

Development and evaluation of a pH-responsive Mimosa pudica seed mucilage/ß- cyclodextrin-co-poly(methacrylate) hydrogel for controlled drug delivery: In vitro and in vivo assessment.

In this comprehensive investigation, a novel pH-responsive hydrogel system comprising mimosa seed mucilage (MSM), ß-cyclodextrin (ß-CD), and methacrylic acid (MAA) was developed via free radical polymerization technique to promote controlled drug delivery. The hydrogel synthesis involved strategic variations in polymer, monomer, and crosslinker content in fine-tuning its drug-release properties. The resultant hydrogel exhibited remarkable pH sensitivity, selectively liberating the model drug (Capecitabine = CAP) under basic conditions while significantly reducing release in an acidic environment. Morphological, thermal, and structural analyses proved that CAP has a porous texture, high stability, and an amorphous nature. In vitro drug release experiments showcased a sustained and controlled release profile. Optimum release (85.33 %) results were recorded over 24 h at pH 7.4 in the case of MMB9. Pharmacokinetic evaluation in healthy male rabbits confirmed bioavailability enhancement and sustained release capabilities. Furthermore, rigorous toxicity evaluations and histopathological analyses ensured the safety and biocompatibility of the hydrogel. This pH-triggered drug delivery system can be a promising carrier system for drugs involving frequent administrations.

Transforming Pharmaceutical Synthesis with Sein-E-B Nanocomposite Photocatalyst through 1,4-NAD(P)H Cofactor Regeneration and C-N Bond Activation.

The need for sunlight chemical renewal and contemporary organic transformation has fostered the advancement of environmentally friendly photocatalytic techniques. For the first time, we report on the novel crafting of a bright future with selenium-infused Eosin-B (Sein-E-B) nanocomposite photocatalysts in this work. The Sein-E-B nanocomposite materials were created using a hydrothermal process for solar chemical regeneration and organic transformation under visible light. The synthesized samples were subjected to UV-DRS-visible spectroscopy, FT-IR, SEM, EDX, EIS and XRD analysis. The energy band gap of the Sein-E-B nanocomposite photocatalyst was measured using UV-DRS, and the result was around 2.06 eV. to investigate the generated Sein-E-B catalytic activity as a nanocomposite for 1,4-NADH/NADPH re-formation and C-N bond activation. This novel photocatalyst offers a promising alternative for the regeneration of solar chemicals and C-N bond creation between pyrrole and aryl halides.

Exosome-Based Macromolecular neurotherapeutic drug delivery approaches in overcoming the Blood-Brain barrier for treating brain disorders.

Delivering drugs to the brain is a complex challenge in medical research, particularly for disorders like Alzheimer's and Parkinson's. The blood-brain barrier restricts the entry of many therapeutic molecules, hindering their effectiveness. Nanoparticles, a potential solution, face issues like toxicity and limited approvals. A new avenue explores the use of small extracellular vesicles (sEVs), i.e., exosomes, as natural carriers for drug delivery. sEVs, tiny structures below 150 nm, show promise due to their minimal immune response and ability to precisely deliver drugs. This review focuses on the potential of sEVs-based drug delivery systems for treating neurological disorders, brain cancers, and other brain-related issues. Notably, bioengineered sEVs-carrying therapeutic compounds exhibit promise in early studies. The unique features of sEVs, such as their small size and natural properties, position them as candidates to overcome challenges in drug delivery to the brain. Ongoing clinical trials and research into sEVs behavior within the body further highlight their potential for revolutionizing drug delivery and addressing complex brain conditions.

Evaluate effect of 126 pre-processing methods on various artificial intelligence models accuracy versus normal mode to predict groundwater level (case study: Hamedan-Bahar Plain, Iran).

The estimation of groundwater levels is crucial and an important step in ensuring sustainable management of water resources. In this paper, selected piezometers of the Hamedan-Bahar plain located in west of Iran. The main objective of this study is to compare effect of various pre-processing methods on input data for different artificial intelligence (AI) models to predict groundwater levels (GWLs). The observed GWL, evaporation, precipitation, and temperature were used as input variables in the AI algorithms. Firstly, 126 method of data pre-processing was done by python programming which are classified into three classes: 1- statistical methods, 2- wavelet transform methods and 3- decomposition methods; later, various pre-processed data used by four types of widely used AI models with different kernels, which includes: Support Vector Machine (SVR), Artificial Neural Network (ANN), Long-Short Term memory (LSTM), and Pelican Optimization Algorithm (POA) - Artificial Neural Network (POA-ANN) are classified into three classes: 1- machine learning (SVR and ANN), 2- deep learning (LSTM) and 3- hybrid-ML (POA-ANN) models, to predict groundwater levels (GWLs). Akaike Information Criterion (AIC) were used to evaluate and validate the predictive accuracy of algorithms. According to the results, based on summation (train and test phases) of AIC value of 1778 models, average of AIC values for ML, DL, hybrid-ML classes, was decreased to -25.3%, -29.6% and -57.8%, respectively. Therefore, the results showed that all data pre-processing methods do not lead to improvement of prediction accuracy, and they should be selected very carefully by trial and error. In conclusion, wavelet-ANN model with daubechies 13 and 25 neurons (db13_ANN_25) is the best model to predict GWL that has -204.9 value for AIC which has grown by 5.23% (-194.7) compared to the state without any pre-processing method (ANN_Relu_25).

Carbon nanotubes in plant dynamics: Unravelling multifaceted roles and phytotoxic implications.

Carbon nanotubes (CNTs) have emerged as a promising frontier in plant science owing to their unique physicochemical properties and versatile applications. CNTs enhance stress tolerance by improving water dynamics and nutrient uptake and activating defence mechanisms against abiotic and biotic stresses. They can be taken up by roots and translocated within the plant, impacting water retention, nutrient assimilation, and photosynthesis. CNTs have shown promise in modulating plant-microbe interactions, influencing symbiotic relationships and mitigating the detrimental effects of phytopathogens. CNTs have demonstrated the ability to modulate gene expression in plants, offering a powerful tool for targeted genetic modifications. The integration of CNTs as sensing elements in plants has opened new avenues for real-time monitoring of environmental conditions and early detection of stress-induced changes. In the realm of agrochemicals, CNTs have been explored for their potential as carriers for targeted delivery of nutrients, pesticides, and other bioactive compounds. CNTs have the potential to demonstrate phytotoxic effects, detrimentally influencing both the growth and developmental processes of plants. Phytotoxicity is characterized by induction of oxidative stress, impairment of cellular integrity, disruption of photosynthetic processes, perturbation of nutrient homeostasis, and alterations in gene expression. This review aims to provide a comprehensive overview of the current state of knowledge regarding the multifaceted roles of CNTs in plant physiology, emphasizing their potential applications and addressing the existing challenges in translating this knowledge into sustainable agricultural practices.

A rare case of schwannomatosis with meningioma: a case report.

Introduction: Schwannomatosis is characterized by multiple schwannomas without vestibular schwannomas or any other stigmata of neurofibromatosis type 2 (NF2). Schwannomatosis is a rare disorder, with a reported incidence ranging from 1 in 40 000 to 1 in 1.7 million. Meningioma is also associated with schwannomatosis in around 5% of cases. Case presentation: We describe a case of a 20-year-old female presenting with progressive weakness of the right lower limb for 7 months with a tingling sensation and numbness of the same limb for 6 months and was found to have schwannomatosis with multiple spinal and right cerebellopontine angle (CPA) (9th/10th cranial nerve) schwannomas and left anterior cranial fossa meningioma. Discussion: Schwannomas in schwannomatosis are seen along the cranial, spinal, and peripheral nerves but not along the vestibular nerve, as is characteristically seen in NF2. The occurrence of meningiomas is about 5% in individuals with schwannomatosis, and the patient in our case also had an associated meningioma. The tumor was confirmed to be a schwannoma based on features on an MRI examination and histological examination. Conclusion: It is of great significance to identify the entire spectrum of the disease in a patient with schwannomatosis, and to differentiate it from related conditions in order to track and surgically manage the patient appropriately based on symptomatology and imaging findings.

Advancing Diabetes Management: The Future of Enzyme-Less Nanoparticle-Based Glucose Sensors-A Review.

BACKGROUND: Glucose is vital for biological processes, requiring blood sugar levels to be maintained between 3.88 and 6.1 mmol/L, especially during fasting. Elevated levels signal diabetes, a global concern affecting 537 million people, necessitating effective glucose-monitoring devices. METHOD: Enzyme-based sensors, though selective, are sensitive to environmental factors. Nonenzymatic sensors, especially those with nanoparticles, offer stability, high surface area, and cost-effectiveness. Existing literature supports their immediate glucose oxidation, showcasing exceptional sensitivity. RESULTS: This review details nonenzymatic sensors, highlighting materials, detection limits, and the promise of nanoparticle-based designs, which exhibit enhanced sensitivity and selectivity in glucose detection. CONCLUSION: Nanoparticle-based sensors, as reviewed, show potential for glucose monitoring, overcoming enzyme-based limitations. The conclusion suggests future directions for advancing these sensors, emphasizing ongoing innovation in this critical research area.

Chylolymphatic mesenteric cyst: A rare differential diagnosis of cystic mass in abdomen: A case report.

INTRODUCTION: Mesenteric cysts are the rare benign intraperitoneal tumor, which are common in the mesentery of the terminal ileum. Though mesenteric cysts are frequently seen, chylolymphatic mesenteric cysts in children are rare entities. CASE PRESENTATION: Our case is a case of a 3-year-old female child presenting to our center with a complain of abdominal pain. Ultrasonography (USG) of the abdomen revealed a cystic lesion in the right upper abdomen, and computed tomography (CT) scan showed a large homogenous fluid density lesion in the right upper abdomen, giving a provisional diagnosis of mesenteric cyst. She was managed surgically: the cyst was excised, the involved segment of bowel was resected and the remaining was anastomosed. On histopathology, the final diagnosis of a chylolymphatic mesenteric cyst was made. DISCUSSION: Clinical presentations may vary from asymptomatic abdominal lump to features of acute abdomen. Imaging modalities like ultrasonography and computed tomography scans are the mainstay of investigations. Surgical management with excision of cyst, and resection of the involved bowel segment is the treatment of choice, as done in our patient. The final diagnosis is made after the histopathologic examination of the excised specimen. CONCLUSION: Chylolymphatic mesenteric cysts are rare, and have varied clinical presentations. Although rare, chylolymphatic mesenteric cysts should be considered a differential diagnosis in patients presenting with cystic masses in the abdomen.

Unraveling the impact of digital transformation on green innovation through microdata and machine learning.

How to use digitalization to support the green transformation of organizations has drawn much attention based on the rapid development of digitalization. However, digital transformation (DT) may be hindered by the "IT productivity paradox." Exploring the influence of DT on green innovation, we analyze panel data encompassing A-share listed companies in Shanghai and Shenzhen spanning the period from 2010 to 2018. It tests the DT's non-linear impact, employing a random-forest and mediation effect models. The results reveal that (i) DT can promote green innovation; (ii) regarding heterogeneity, the promotion effect is mainly manifested in enterprises in non-state-owned and highly competitive industries; (iii) based on mechanism testing, DT relies on two routes to encourage green innovation: improving environmental information disclosure and reducing environmental uncertainty; and (iv) random-forest analysis shows that DT exhibits an inverted U-shaped non-linear effect on green innovation, including the "IT productivity paradox." This study enhances the existing discourse on DT and green innovation by furnishing empirical substantiation for the non-linear influence exerted by DT on green innovation. Furthermore, it imparts insights into the mechanisms and contextual limitations governing this association.

Targeting Pathways and Integrated Approaches to Treat Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic symmetrical systemic disorder that not only affects joints but also other organs such as heart, lungs, kidney, and liver. Approximately there is 0.5%-1% of the total population affected by RA. RA pathogenesis still remains unclear due to which its appropriate treatment is a challenge. Further, multitudes of factors have been reported to affect its progression i.e. genetic factor, environmental factor, immune factor, and oxidative factor. Therapeutic approaches available for the treatment of RA include NSAIDs, DMARDs, enzymatic, hormonal, and gene therapies. But most of them provide the symptomatic relief without treating the core of the disease. This makes it obligatory to explore and reach the molecular targets for cure and long-term relief from RA. Herein, we attempt to provide extensive overlay of the new targets for RA treatment such as signaling pathways, proteins, and receptors affecting the progression of the disease and its severity. Precise modification in these targets such as suppressing the notch signaling pathway, SIRT 3 protein, Sphingosine-1-phosphate receptor and stimulating the neuronal signals particularly efferent vagus nerve and SIRT 1 protein may offer long term relief and potentially diminish the chronicity. To target or alter the novel molecules and signaling pathway a specific delivery system is required such as liposome, nanoparticles and micelles and many more. Present review paper discusses in detail about novel targets and delivery systems for treating RA.

Exploring nanocarriers as innovative materials for advanced drug delivery strategies in onco-immunotherapies.

In recent years, Onco-immunotherapies (OIMTs) have been shown to be a potential therapy option for cancer. Several immunotherapies have received regulatory approval, while many others are now undergoing clinical testing or are in the early stages of development. Despite this progress, a large number of challenges to the broad use of immunotherapies to treat cancer persists. To make immunotherapy more useful as a treatment while reducing its potentially harmful side effects, we need to know more about how to improve response rates to different types of immunotherapies. Nanocarriers (NCs) have the potential to harness immunotherapies efficiently, enhance the efficiency of these treatments, and reduce the severe adverse reactions that are associated with them. This article discusses the necessity to incorporate nanomedicines in OIMTs and the challenges we confront with current anti-OIMT approaches. In addition, it examines the most important considerations for building nanomedicines for OIMT, which may improve upon current immunotherapy methods. Finally, it highlights the applications and future scenarios of using nanotechnology.

Comprehensive Investigation of Cu2+ Adsorption from Wastewater Using Olive-Waste-Derived Adsorbents: Experimental and Molecular Insights.

This study investigates the efficacy of adsorbents from locally sourced olive waste-encompassing olive skins, leaves, and pits, recovered from the initial centrifugation of olives (OWP)-and a composite with sodium alginate (OWPSA) for the removal of Cu2+ ions from synthetic wastewater. Experimental analyses conducted at room temperature, with an initial Cu2+ concentration of 50 mg/L and a solid/liquid ratio of 1 g/L, showed that the removal efficiencies were approximately 79.54% and 94.54% for OWP and OWPSA, respectively, highlighting the positive impact of alginate on adsorption capacity. Utilizing statistical physics isotherm models, particularly the single-layer model coupled to real gas (SLMRG), allowed us to robustly fit the experimental data, providing insights into the adsorption mechanisms. Thermodynamic parameters affirmed the spontaneity and endothermic nature of the processes. Adsorption kinetics were interpreted effectively using the pseudo-second-order (PSO) model. Molecular modeling investigations, including the conductor-like screening model for real solvents (COSMO-RS), density functional theory (DFT), and atom-in-molecule (AIM) analysis, unveiled intricate molecular interactions among the adsorbent components-cellulose, hemicellulose, lignin, and alginate-and the pollutant Cu2+, confirming their physically interactive nature. These findings emphasize the synergistic application of experimental and theoretical approaches, providing a comprehensive understanding of copper adsorption dynamics at the molecular level. This methodology holds promise for unraveling intricate processes across various adsorbent materials in wastewater treatment applications.

Isolated pancreatic injury following blunt trauma in a seven-year-old girl: A case report.

INTRODUCTION AND IMPORTANCE: Isolated pancreatic injury following blunt abdominal trauma is rare, and the absence of definite clinical signs and symptoms may delay diagnosis and management. CASE PRESENTATION: We present the case of a seven-year-old girl with a history of progressive, periumbilical abdominal pain and multiple episodes of non-bilious, non-blood mixed vomiting following a road traffic accident. Computed tomography (CT) imaging revealed an isolated grade three pancreatic injury managed conservatively. CLINICAL DISCUSSION: The patient usually presents with epigastric tenderness with or without a rise in pancreatic enzyme levels. CT grading of injury correlates with and guides the management approach, and CT abdomen with contrast is the preferred investigation for diagnosis. Management depends on the grade of injury, the hemodynamic status of the children, and the co-existence of other injuries. CONCLUSION: Isolated pancreatic injury, although rare, can go undiagnosed due to a lack of suspicion from the treating surgeon and may have dire consequences. Conservative management can be a suitable strategy for children with stable hemodynamic status.