Arthropods in soil reclamation and bioremediation: Functional roles, mechanisms and future perspective.

Soil arthropods are a diverse group of invertebrates that play pivotal roles in nutrient cycling, decomposition, soil structure formation, and regulation of soil biodiversity. Understanding the ecological significance of soil arthropods and their interactions with other soil organisms is crucial. This review paper examines the potential of arthropods in improving soil health and quality, with a specific focus on their relevance in acidic, saline/alkaline, and contaminated soils. The paper investigates the interactions between arthropods and their associated microbiomes, their contributions to soil physical and chemical properties, their influence on nutrient cycling and organic matter mineralization, as well as their role as indicators of soil health due to their sensitivity to environmental changes. Furthermore, the review explores how arthropods enhance the activities of microorganisms, such as bacteria, fungi, and yeast, which employ molecular mechanisms to remediate heavy metal contamination in soils. Lastly, the paper addresses key challenges and future directions for utilizing soil arthropods in the restoration of environmentally friendly soils.

Rational computational design and development of an immunogenic multiepitope vaccine incorporating transmembrane proteins of Staphylococcus lugdunensis.

Staphylococcus lugdunensis has emerged as a significant human pathogen, responsible for a range of infections from skin and soft tissue infections to endocarditis and bacteremia. Notably, abscess formation is a common manifestation, reflecting its potential shift from a benign skin commensal to a serious pathogen, akin to infective endocarditis. With the rising prevalence of antibiotic resistance, there is a pressing need for novel therapeutic strategies. This study addresses this need by exploring the development of an effective S. lugdunensis vaccine. Multiepitope vaccines, which incorporate various antigenic fragments from S. lugdunensis proteins, offer a promising approach to elicit a robust immune response. Computational tools are instrumental in selecting epitopes based on their predicted immunogenicity and non-toxicity. Molecular docking and molecular dynamics (MD) simulations further elucidate the interactions between vaccine constructs and immune system molecules, such as B-cell and T-cell receptors, providing detailed insights into binding affinity, specificity, and stability. This study highlights the potential of integrating multiepitope vaccine design with advanced computational methods to expedite and enhance vaccine development, addressing a critical gap amid escalating antibiotic resistance.

A Plasmacytoid Variant of Urothelial Carcinoma: A Rare Entity.

A rare histological variant of transitional cell urothelial carcinoma, the plasmacytoid variant, was recently included in the World Health Organization classification of urothelial tract tumors. This variant has a morphological resemblance to other tumors, which poses a diagnostic challenge for identifying this tumor and may often lead to misdiagnosis. Vigilant histopathological analysis and immunostaining are required to delineate the correct diagnosis. The plasmacytoid variant of urothelial carcinoma is an aggressive tumor with a poor prognosis, making correct diagnosis essential for early and appropriate treatment. This paper presents the case of a 46-year-old male with a plasmacytoid variant of high-grade urothelial carcinoma who underwent transurethral resection of a bladder tumor, received chemotherapy, and is currently undergoing follow-up.

Surface-enhanced Raman spectroscopy (SERS) for the diagnosis of acute myocardial infarction (AMI) using blood serum samples.

Acute myocardial infarction (AMI) is a serious medical condition generally known as heart attack, which is caused by the decreased or completely blocked blood flow to a part of the heart muscle. It is a significant cause of both mortality and morbidity throughout the world. Cardiac troponin-I (cTnI) is an important biomarker at different stages of AMI and is one of the most specific and widely used cardiac skeletal muscle proteins. Delays in medical treatment and inaccurate diagnosis might be the main cause of death of AMI patients. To overcome the death rate of AMI patients, early diagnosis of this disease is crucial. In the current study, surface-enhanced Raman spectroscopy (SERS) is employed for the characterization and diagnosis of this disease using blood serum samples from 49 clinically confirmed acute myocardial infarction (AMI) patients and 17 healthy persons. Silver nanoparticles (AgNPs) are used as the SERS substrate for the recognition of characteristic SERS spectral features, differentiating between healthy and AMI-positive samples. The acute myocardial infarction-positive blood serum samples reveal remarkable differences in spectral intensities at 534, 697, 744, 835, 927, 941, 988, 1221, 1303, 1403, 1481, 1541, 1588 and 1694 cm-1. For the differentiation and quantitative analysis of the SERS spectra, multivariate chemometric tools (including principal component analysis (PCA) and partial least squares regression (PLSR)) are employed. A PLSR model established on the basis of differentiating the SERS spectral features is found to be helpful in the prediction of the levels of cardiac troponin-I (cTnI) in the blood serum samples with the root mean square error of calibration (RMSEC) value of 2.98 ng mL-1 and root mean square errors of prediction (RMSEP) value of 3.98 ng mL-1 for S7.

Surface-enhanced Raman spectroscopy for the characterization of xylanases enzyme.

Xylanases are essential hydrolytic enzymes which break down the plant cell wall polysaccharide, xylan composed of D-xylose monomers. Surface-enhanced Raman Spectroscopy (SERS) was utilized for the characterization of interaction of xylanases with xylan at varying concentrations. The study focuses on the application of SERS for the characterization of enzymatic activity of xylanases causing hydrolysis of Xylan substrate with increase in its concentration which is substrate for this enzyme in the range of 0.2% to 1.0%. SERS differentiating features are identified which can be associated with xylanases treated with different concentrations of xylan. SERS measurements were performed using silver nanoparticles as SERS substrate to amplify Raman signal intensity for the characterization of xylan treated with xylanases. Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis (PLS-DA) were applied to analyze the spectral data to analyze differentiation between the SERS spectra of different samples. Mean SERS spectra revealed significant differences in spectral features particularly related to carbohydrate skeletal mode and O-C-O and C-C-C ring deformations. PCA scatter plot effectively differentiates data sets, demonstrating SERS ability to distinguish treated xylanases samples and the PC-loadings plot highlights the variables responsible for differentiation. PLS-DA was employed as a quantitative classification model for treated xylanase enzymes with increasing concentrations of xylan. The values of sensitivity, specificity, and accuracy were found to be 0.98%, 0.99%, and 100% respectively. Moreover, the AUC value was found to be 0.9947 which signifies the excellent performance of PLS-DA model. SERS combined with multivariate techniques, effectively characterized and differentiated xylanase samples as a result of interaction with different concentrations of the Xylan substrate. The identified SERS features can help to characterize xylanases treated with various concentrations of xylan with promising applications in the bio-processing and biotechnology industries.

Range aware message drop policy for delay tolerant networks.

In delay tolerant networks (DTNs) the messages are often not delivered to the destination due to a lack of end-to-end connectivity. In such cases, the messages are stored in the buffer for a long time and are transmitted when the nodes come into the range of each other. The buffer size of each node has a limited capacity, and it cannot accommodate the new incoming message when the buffer memory is full, and as a result network congestion occurs. This leads to a low delivery probability and thus increases the overhead ratio. In this research work, a new buffer management scheme called Range Aware Drop (RAD) is proposed which considers metrics such as message size and time to live (TTL). RAD utilizes TTL as an important metric and as a result, reduces the unnecessary message drop. Simulation results reveal that RAD performs significantly better than drop oldest (DOA) and size aware drop (SAD) in terms of delivery probability and overhead ratio. The obtained results also revealed that the hop-count average of SAD is 3.9 and DOA is 3.4 while the hop-count average of RAD is just 1.7. Also, the message drop ratio of the RAD is 36.2% while SAD and DOA have message drop ratios of 73.3% and 84.9% respectively.

Does trade policy uncertainty hurt renewable energy-related sustainable development goals in China?

Trade policy uncertainty might hamper trade flow, including the trade of green and renewable energy technologies. Therefore, this study aims to examine the asymmetric effects of trade policy uncertainty (TPU) on renewable energy consumption (REC) in China. To calculate the short- and long-term relationships between REC, TPU, national income, carbon footprints, and financial development, we used the nonlinear QARDL technique. The estimates reveal that an upsurge in TPU hurts REC in the short and long run. Conversely, a stable trade policy or a reduction in TPU increases REC in the long run. In the short run, a fall in TPU exerts no influence on REC. The findings further imply that various factors, including GDP, CO2 emissions, and financial development, contribute to long-term improvements in REC in China, both in the short and long run.

DFT, GC-MS analysis and biological evaluation of Limbarda crithmoides L. Dumort essential oil; an important edible halophyte grown in Pakistan.

Antimicrobial resistance is a major health burden in Pakistan, and therefore new herbal medicine-based therapeutic regimens are being largely investigated. Limbarda crithmoides essential oil was extracted by using hydrodistillation method. Chemical profiling of essential was evaluated by using FTIR and GC-MS analysis. A total of 20 components were identified including, p-xylene, o-xylene, ß-linalool, acetophenole and 3-isopropylphenyl methylcarbamate. The HOMO and LUMO analysis in DFT investigations presented that 3-isopropylphenyl methylcarbamate, p-xylene and o-xylene posess a substantial capacity to transfer charge through molecules. The antimicrobial potential of essential oil showed moderate inhibition against E. coli (MIC = 6.25 mg/mL), whereras a significant inhibition Staphylococos aureus was recorded (MIC = 3.12 mg/mL). Further, significant antioxidant activities were recorded in DPPH radical scavenging (IC50 = 80.5 µg/mL), H2O2 (64 ± 1.2%) and FRAP (60.3 µg ferrous equivalents) assays. It was therefore concluded that Limbarda crithmoides essential oil has potential antioxidant and anti-antimicrobial properties and can be used for further investigations.

Designing Nanocomposite-Based Electrochemical Biosensors for Diabetes Mellitus Detection: A Review.

This review will unveil the development of a new generation of electrochemical sensors utilizing a transition-metal-oxide-based nanocomposite with varying morphology. There has been considerable discussion on the role of transition metal oxide-based nanocomposite, including iron, nickel, copper, cobalt, zinc, platinum, manganese, conducting polymers, and their composites, in electrochemical and biosensing applications. Utilizing these materials to detect glucose and hydrogen peroxide selectively and sensitively with the correct chemical functionalization is possible. These transition metals and their oxide nanoparticles offer a potential method for electrode modification in sensors. Nanotechnology has made it feasible to develop nanostructured materials for glucose and H2O2 biosensor applications. Highly sensitive and selective biosensors with a low detection limit can detect biomolecules at nanomolar to picomolar (10-9 to 10-12 molar) concentrations to assess physiological and metabolic parameters. By mixing carbon-based materials (graphene oxide) with inorganic nanoparticles, nanocomposite biosensor devices with increased sensitivity can be made using semiconducting nanoparticles, quantum dots, organic polymers, and biomolecules.

Quantitative analysis of solid dosage forms of Atenolol by Raman spectroscopy.

OBJECTIVE: To develop a Raman spectroscopy-based analytical model for quantification of solid dosage forms of active pharmaceutical ingredient (API) of Atenolol.Significance: For the quantitative analysis of pharmaceutical drugs, Raman Spectroscopy is a reliable and fast detection method. As part of this study, Raman Spectroscopy is explored for the quantitative analysis of different concentrations of Atenolol. METHODS: Various solid-dosage forms of Atenolol were prepared by mixing API with excipients to form different solid-dosage formulations of Atenolol. Multivariate data analysis techniques, such as Principal Component Analysis (PCA) and Partial least square regression (PLSR) were used for the qualitative and quantitative analysis, respectively. RESULTS: As the concentration of the drug increased in formulation, the peak intensities of the distinctive Raman spectral characteristics associated with the API (Atenolol) gradually increased. Raman spectral data sets were classified using PCA due to their distinctive spectral characteristics. Additionally, a prediction model was built using PLSR analysis to assess the quantitative relationship between various API (Atenolol) concentrations and spectral features. With a goodness of fit value of 0.99, the root mean square errors of calibration (RMSEC) and prediction (RMSEP) were determined to be 1.0036 and 2.83 mg, respectively. The API content in the blind/unknown Atenolol formulation was determined as well using the PLSR model. CONCLUSIONS: Based on these results, Raman spectroscopy may be used to quickly and accurately analyze pharmaceutical samples and for their quantitative determination.

Morphometric and molecular characterization of Channa marulius from Riverine system of Punjab, Pakistan.

OBJECTIVE: Channidae family, are major freshwater fish species amongst the local aquatic fauna of Pakistan, while, there is limited availability of local data on their molecular identification and phylogenetic analysis. METHODS: Channa species were collected from four different geographical sites in the tertiary of Punjab province on the Indus and Chenab rivers of Pakistan. Morphometric records and molecular techniques were used to determine the intraspecific variations among populations of Channa marulius. Mitochondrial DNA was extracted from the flesh of C. marulius, while, COI gene was used for molecular identification and variation levels were estimated by using Principal Component Analysis. RESULTS: Data recorded on the basis of morphometric parameters clearly divided the C. marulius of different locations into two distinct categories, which accounted for a cumulative variability of 97.6%. Non-significance (P < 0.05) among the C. marulius showed that it contains a unique control haplotype localized within the sub-population. The intra-species distance ranged from 0.000 to 0.001 for four different populations, in contrast, the sequences retrieved from the NCBI database exhibited a range span of 0.000-0.003, while, sequence diversity ranged from 0.000 to 0.006 for this intra-specific comparison. The cladogram was also constructed for C. marulius of different geographical locations for observation of phylogenetic relationship. The conclusion drawn from the phylogenetic analysis of C. marulius populations used in this study, contributes significantly to the understanding of genetic variations within populations of this species. The findings provide valuable insight to devise conservation strategies in fisheries management programs in Pakistan.

Differentiation of different dibenzothiophene (DBT) desulfurizing bacteria via surface-enhanced Raman spectroscopy (SERS).

Fossil fuels are considered vital natural energy resources on the Earth, and sulfur is a natural component present in them. The combustion of fossil fuels releases a large amount of sulfur in the form of SO x in the atmosphere. SO x is the major cause of environmental problems, mainly air pollution. The demand for fuels with ultra-low sulfur is growing rapidly. In this aspect, microorganisms are proven extremely effective in removing sulfur through a process known as biodesulfurization. A major part of sulfur in fossil fuels (coal and oil) is present in thiophenic structures such as dibenzothiophene (DBT) and substituted DBTs. In this study, the identification and characterization of DBT desulfurizing bacteria (Chryseobacterium sp. IS, Gordonia sp. 4N, Mycolicibacterium sp. J2, and Rhodococcus sp. J16) based on their specific biochemical constituents were conducted using surface-enhanced Raman spectroscopy (SERS). By differentiating DBT desulfurizing bacteria, researchers can gain insights into their unique characteristics, thus leading to improved biodesulfurization strategies. SERS was used to differentiate all these species based on their biochemical differences and different SERS vibrational bands, thus emerging as a potential technique. Moreover, multivariate data analysis techniques such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were employed to differentiate these DBT desulfurizing bacteria on the basis of their characteristic SERS spectral signals. For all these isolates, the accuracy, sensitivity, and specificity are above 90%, and an AUC (area under the curve) value of close to 1 was achieved for all PLS-DA models.

SERS characterization of biochemical changes associated with biodesulfurization of dibenzothiophene using Gordonia sp. HS126-4N.

In this study, Gordonia sp. HS126-4N was employed for dibenzothiophene (DBT) biodesulfurization, tracked over 9 days using SERS. During the initial lag phase, no significant spectral changes were observed, but after 48 h, elevated metabolic activity was evident. At 72 h, maximal bacterial population correlated with peak spectrum variance, followed by stable spectral patterns. Despite 2-hydroxybiphenyl (2-HBP) induced enzyme suppression, DBT biodesulfurization persisted. PCA and PLS-DA analysis of the SERS spectra revealed distinctive features linked to both bacteria and DBT, showcasing successful desulfurization and bacterial growth stimulation. PLS-DA achieved a specificity of 95.5 %, sensitivity of 94.3 %, and AUC of 74 %, indicating excellent classification of bacteria exposed to DBT. SERS effectively tracked DBT biodesulfurization and bacterial metabolic changes, offering insights into biodesulfurization mechanisms and bacterial development phases. This study highlights SERS' utility in biodesulfurization research, including its use in promising advancements in the field.

Story of 20 Years of Triumph: A Case Report of Two Patients With Stage IV Granulosa Cell Tumor of the Ovary.

Ovarian granulosa cell tumors (GCTs) are rare neoplasms with a unique incidence pattern peaking in postmenopausal women. This case report presents two instances of stage 4 recurrent adult GCTs with a prolonged 20-year follow-up. Patient 1, diagnosed at 54 years, experienced multiple recurrences managed through surgery, hormonal therapy, and chemotherapy, culminating in hepatocellular carcinoma. Patient 2, diagnosed at 67 years, underwent various treatments, including surgery, chemotherapy, and hormonal therapy, demonstrating disease stability. Despite the generally favorable prognosis, these cases highlight the challenges of managing recurrent GCTs, emphasizing the need for tailored therapeutic approaches.

Surface-enhanced Raman spectroscopy for the study of interaction of an antibacterial agent ([bis(1,3-dipentyl-1H-imidazol-2(3H)-ylidene)silver(i)]bromide) with Bacillus subtilis bacterial biofilms.

Bacterial resistance towards antibiotics is a significant challenge for public health, and surface-enhanced Raman spectroscopy (SERS) has great potential to be a promising technique to provide detailed information about the effect of antibiotics against biofilms. SERS is employed to check the antibacterial potential of a lab synthesized drug ([bis(1,3-dipentyl-1H-imidazol-2(3H)-ylidene)silver(i)] bromide) against Bacillus subtilis and to analyze various SERS spectral features of unexposed and exposed Bacillus strains by observing biochemical changes in DNA, protein, lipid and carbohydrate contents induced by the lab synthesized imidazole derivative. Further, PCA and PLS-DA are employed to differentiate the SERS features. PCA was employed to differentiate the biochemical contents of unexposed and exposed Bacillus strains in the form of clusters of their representative SERS spectra and is also helpful in the pairwise comparison of two spectral data sets. PLS-DA provides authentic information to discriminate different unexposed and exposed Bacillus strains with 91% specificity, 93% sensitivity and 97% accuracy. SERS can be employed to characterize the complex and heterogeneous system of biofilms and to check the changes in spectral features of Bacillus strains by exposure to the lab synthesized imidazole derivative.

Predictors of quitting smoking behavior: evidence from Pakistan.

This study attempts to identify factors that significantly encourage the cessation of smoking in the context of Pakistan. The study distributes a modified questionnaire among 421 respondents (current as well as former smokers) in the capital city of Pakistan, Islamabad. The binary regression method was employed to data for analyzing predictors of making quit attempts and successful smoking cessation. The result indicates that respondents having strong intentions to quit, high socioeconomic status, low nicotine dependency, and past quit attempts, and those having no-smoking friends, are more likely to quit cigarette smoking successfully. On the other hand, factors like social pressure to quit smoking, religious information against smoking, intention to quit smoking, and public regulation on smoking are more likely to encourage smokers to make quit attempts. The study calls for community and school-wide smoking cessation campaigns involving officials, peers and parents, religious leaders, and other influential individuals to inform people about the dangers of smoking. In addition, religious leaders should be encouraged to issue rulings against smoking especially during "Friday Prayer." Furthermore, the government should pronounce more strict and comprehensive regulations on smoking by properly monitoring its implementation to encourage cessation of cigarette smoking.

Highly Stretchable Polyurethane Porous Membranes with Adjustable Morphology for Advanced Lithium Metal Batteries.

A highly flexible, tunable morphology membrane with excellent thermal stability and ionic conductivity can endow lithium metal batteries with high power density and reduced dendrite growth. Herein, a porous Polyurethane (PU) membrane with an adjustable morphology was prepared by a simple nonsolvent-induced phase separation technique. The precise control of the final morphology of PU membranes can be achieved through appropriate selection of a nonsolvent, resulting a range of pore structures that vary from finger-like voids to sponge-like pores. The implementation of combinatorial DFT and experimental analysis has revealed that spongy PU porous membranes, especially PU-EtOH, show superior electrolyte wettability (472%), high porosity (75%), good mechanical flexibility, robust thermal dimensional stability (above 170 °C), and elevated ionic conductivity (1.38 mS cm-1) in comparison to the polypropylene (PP) separator. The use of PU-EtOH in Li//Li symmetric cell results in a prolonged lifespan of 800 h, surpasing the longevity of PU or PP cells. Moreover, when subjected to a high rate of 5 C, the LiFePO4/Li half-cell with a PU-EtOH porous membrane displayed better cycling performance (115.4 mAh g-1) compared to the PP separator (104.4 mAh g-1). Finally, the prepared PU porous membrane exhibits significant potential for improving the efficiency and safety of LMBs.

Occurrence of fungal microbial contamination in drinking water of megacity of Karachi (Pakistan) and their physico-chemical control.

The water quality in Karachi (Pakistan) is uncertain due to the occurrence of fungi and other microorganisms. A total of twenty-five water samples were collected from public places, educational institutes, hospitals, water supply systems and surface water of the canal of Karachi (Pakistan). The different fungal species including Acremonium sp., Alternaria alternata, Aspergillus flavus, A. fumigatus, A. sulphureus, Cladosporium sp., Fusarium sp., Clonostachys (Gliocladium) sp., Macrophomina phaseolina, Mucor racemosus, Paecilomyces sp. Penicillium chrysogenum, P. citrinum, P. commune, P. expansum, Rhizoctonia sp. and Stachybotrys sp. were isolated from these drinking water samples. However, the bacteria, microalgae and some other microorganisms were present in low concentrations. The reason for fungi infection and production of mycotoxicity depends upon various factors and the availability of their nutrients in filtration plants. The major threats to human health are fungal mycotoxicity which is responsible for carcinogenic and other lethal diseases. Mostly, the genus Aspergillus was dominated and isolated with a maximum of 88-98% of occurrence in the different samples of drinking water by the direct plate-spread method. For the control of fungi, various Physico-chemical coagulation treatments were used, but Potassium alum, clay pot, and hot water treatment disinfected effectively 69-70% removal of the fungi and its spore or mycelia from the water. In addition, it is concluded that drinking water purifications such as chlorination, filtration and lime did not eliminate thermophilic fungal spores or mycelia including Penicillium, Paecilomyces and Mucor from the water.

Surface-Enhanced Raman Spectroscopy for Monitoring the Biochemical Changes Due to DNA Mutations Induced by CRISPR-Cas9 Genome Editing in the Aspergillus niger Fungus.

In this study, surface-enhanced Raman spectroscopy (SERS) technique, along with principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA), is used as a simple, quick, and cost-effective analysis method for identifying biochemical changes occurring due to induced mutations in the Aspergillus niger fungus strain. The goal of this study is to identify the biochemical changes in the mutated fungal cells (cell mass) as compared to the control/nonmutated cells. Furthermore, multivariate data analysis tools, including PCA and PLS-DA, are used to further confirm the differentiating SERS spectral features among fungal samples. The mutations are caused in A. niger by the clustered regularly interspaced palindromic repeat CRISPR-Cas9 genomic editing method to improve their biotechnological potential for the production of cellulase enzyme. SERS was employed to detect the changes in the cells of mutated A. niger fungal strains, including one mutant producing low levels of an enzyme and another mutant producing high levels of the enzyme as a result of mutation as compared with an unmutated fungal strain as a control sample. The distinctive features of SERS corresponding to nucleic acids and proteins appear at 546, 622, 655, 738, 802, 835, 959, 1025, 1157, 1245, 1331, 1398, and 1469 cm-1. Furthermore, PLS-DA is used to confirm the 89% accuracy, 87.7% precision, 87% sensitivity, and 88.9% specificity of this method, and the value of the area under the curve (AUROC) is 0.67. It has been shown that surface-enhanced Raman spectroscopy is an effective method for identifying and differentiating biochemical changes in genome-modified fungal samples.