Introduction- Chromium is the most prevalent metal present on earth in two valence states: hexavalent [Cr(VI)] and trivalent [Cr(III)]. Hexavalent chromium [Cr(VI)] is widely recognized as a teratogen, mutagen, and neurotoxin to humans. Chromium-induced autophagy is a novel avenue which involves a plethora of cellular and molecular intricacies, including the identification of the novel NPTX2 (neuronal pentraxin 2) as a critical mediator of chromium-induced autophagy dysregulation in CNS cells. NPTX2 has a broad expression pattern in the brain, with a principal role in synaptic plasticity and neuronal survival.

Material and Methods This review compiles the most recent research on the molecular processes of chromium-induced autophagy, with a particular emphasis on NPTX2 as a mediator in the cells of the CNS. Research on NPTX2 expression patterns in different brain areas and its role in autophagy dysregulation in response to chromium exposure was compiled. In addition, we looked at the signaling pathways and processes that were involved in the dysregulation of autophagy caused by chromium, such as the inhibition of mTOR, the activation of ULK1, and the interaction of NPTX2 with Beclin-1.

Results Abnormal autophagosome synthesis, lysosomal dysfunction, and improper autophagic substrate degradation are symptoms of disturbed autophagy, which is caused by an increase in NPTX2 expression in response to chromium exposure. The inhibition of mTOR, activation of ULK1, and interaction between NPTX2 and Beclin-1 are all components of the intricate signaling pathways that contribute to autophagy dysregulation. Furthermore, non-traditional pathways like peroxiphagy are involved; in this process, chromium-induced oxidative stress harms peroxisomes, which are then selectively engulfed by autophagosomes through PINK1/Parkin signaling, reducing cellular damage.

Conclusion Targeting peroxiphagy and pharmacological interventions which restore autophagic flux offer the potential to reduce chromium-induced neurotoxicity.

Aim:

1. To study the effect of food, drink, or pharmaceuticals on the action of drugs;
2. To study the result of interactions between medication molecules and secondary targets;
3. To study the effect of herbal extracts on drug absorption.

Objectives:

1. To identify the effects of different herbal extracts on the absorption of metronidazole;
2. To study in vitro and in situ herb–drug interactions;
3. To study the effect of different herbal extracts on the absorption of metronidazole.

Methodology: Take a sufficient amount of cold thyroid solution, place it in a Petri dish, transfer the ileum to it using forceps, and tie one end through the intestinal sac to a double-looped knot of a moistened thread. Fill a syringe with metronidazole alone or in combination with a herbal extract. Put the intestinal sac in a beaker, stir, take samples of the solution at particular time intervals, and assess the absorption of metronidazole.

Results and Discussion: Metronidazole is used as a treatment for amoebiasis or related diarrhea-like conditions which are also treated with home remedies like asafoetida, ginger, and lemon juice, given to the patient to correct electrolyte imbalances. However, these routine food items can affect the therapeutic effect of the synthetic drug when taken concomitantly, either by pharmacokinetic or pharmacodynamic mechanisms.

Conclusion: The results of this study are anticipated to provide valuable insights into the potential interactions between herbal extracts and metronidazole absorption. Herbal extracts, which are frequently used in conventional medicine and as food additives, might affect how synthetic medications like metronidazole are absorbed. Such interactions may affect the effectiveness of therapy and the results for patients. These results highlight the need of taking into account possible herb–drug interactions and modifying drug delivery schedules accordingly. For safe and effective medication administration, it is essential to comprehend these interactions.

Background: Over 90% of oral cancer deaths are due to metastases, facilitated by a mechanism, epithelial–mesenchymal transition (EMT), that demonstrates a mesenchyme-like phenotype of epithelial cells. Prompt metastasis prediction would navigatesurgeons in avoiding unwanted or aggressive treatment for low- and high-risk patients. Recently, the use of image processing is gaining popularity.

Aim: To assess the metastatic risk of Oral Squamous Cell Carcinoma (OSCC) by the quantification of tumor buds and epithelial–mesenchymal transition biomarker expression using MATLAB software

Objectives:

• To evaluate pan CK-stained tumor buds and the expression of epithelial–mesenchymal transition biomarkers, E-Cadherin, β-Catenin, MMP-2 and MMP-9, using immunohistochemistry;
• To quantify and correlate tumor buds and the protein expression of EMT biomarkers using MATLAB software.

Methodology: Pan CK-stained tumor buds and E-Cadherin, β-Catenin, MMP-2, and MMP-9 expression were evaluated immunohistochemically on 40 archival tissue samples of OSCC (20 metastatic and non-metastatic groups). Photomicrographs of immunostained OSCC cases were captured and subjected to texture and color segmentation using image processing in MATLAB software.

Statistical analysis: Statistical analysis using Statistical Package for the Social Sciences (SPSS) software was carried out for the mean scores.

Results: Metastatic OSCC showed a statistically significantly high number of tumor buds (90%). There was a significant decrease in the proportion and intensity of positive cells in E-Cadherin and β- Catenin (p=0.00) and an increase in MMP2 and MMP9 protein expression in metastatic OSCC (p=0.00).

Conclusion: This study is the first of its kind wherein image processing using texture and color segmentation in MATLAB has been used effectively to quantify the phenotypic protein expression of immunostained OSCC tumor buds and EMT markers. The correlation of tumor buds with EMT expression supports the mechanism of EMT responsible for OSCC metastasis, thereby facilitating surgeons in arriving at a definitive treatment plan.

Colorectal cancer is the third most common type of cancer and remains a significant global health challenge. The treatment of patients depends on the stage at which the cancer is diagnosed, but it is mostly based on chemotherapy. Regarding this, novel treatment strategies are essential for improving existing ones. This study examines the relationship between chemotherapeutic doses and the expression of caspase genes—specifically, caspases 3, 8, and 9—in colon cancer cell lines. Our study involves the application of various concentrations of 5-fluorouracil to clarify the potential upregulation of these apoptotic markers in treated cells. RNA was isolated from cells, and a qPCR analysis was performed. The results showed a heterogenous dose-dependent modulation of caspase expression, pointing out the potential mechanisms underlying cellular responses to treatment. Our findings indicate that both apoptotic pathways are activated upon the addition of the chemotherapy drug, as evidenced by the significant upregulation of both initiator and executioner caspases. This effect is most noticeable at larger dosages of 5-fluorouracil as the response of the cells to the chemotherapeutic drug, and this is in accordance with the previous literature review. This research not only advances our understanding of the molecular dynamics within colon cancer cells but also contributes to better therapy responses.

Industrial fish processing generates significant quantities of waste around the world, posing a risk to human health and the environment. It has been estimated that about two-thirds of the total amount of fish processed in industries is discarded as waste.
One of the promising ways for the industrial exploitation of industrial fish waste is the production of protein hydrolysates (FPH) which have a wide field of applications in different sectors, i.e., food industry, pharmaceutics, cosmetics and animal feed.
In this study, a protease enzyme was produced by Bacillus mojavensis FP2 and applied in the hydrolysis of industrial tuna waste. The hydrolysates obtained were tested for their antioxidant, antibacterial and anti-hyperglycemic activity. The hydrolysates were also characterized to determine their properties.
The protease produced showed a high enzymatic activity (105.94 ± 5.99 U/ml), which made it possible to achieve a high degree of hydrolysis (24.2 ± 1.69%) . Concerning antioxidant activity, a DPPH free radical scavenging activity of 96.9 ± 1.04% was achieved at a concentration of 10 mg/mL. Also, the protein hydrolysates from tuna waste presented a very high reducing power, ranging from 0.43 to 0.53 at 5 mg/ml.

Regarding antibacterial activity, the hydrolysates showed an inhibition of Staphylococcus aureus, Klebsiella pneumoniae and Escherichia coli. The hydrolyates also showed anti-hyperglycemic power. The hydrolysates which showed an inhibition of α-amylase activity were F45, F60 and F90, with an inhibition percentage of 15.97 ± 6.45%, 69.96 ± 1.34% and 14.16 ± 2.82%, respectively.
Finally, the tuna waste protein hydrolysates yielded peptides which had excellent solubility over a wide pH range, and good emulsifying and foaming capacities.

Abstract

Introduction: Diabetes mellitus, a metabolic disorder, elevates blood sugar levels, resulting in complications affecting various bodily systems such as nerves, eyes, kidneys, and other organs. The administration of oral antihyperglycemic medications can potentially induce adverse effects, especially when combined, leading to drug-drug interactions. To address these challenges, there's potential in introducing innovative antioxidant compounds targeted at specific organs for therapeutic action. Currently, metal nanoparticles have gained prominence in healthcare due to their exceptional biocompatibility, stability, cost-effectiveness, and environmentally friendly attributes.

Materials and Methods: In this study, green synthesis methods were employed to produce gold nanoparticles (AuNPs) using the Amaranthus gangeticus plant, known for its antidiabetic properties. The leaf extract of A. gangeticus was utilized to synthesize these green AuNPs using a 1 mM gold chloride solution. Various characterization techniques, including UV spectroscopy, FTIR analysis, X-ray diffraction analysis (XRD), transmission electron microscopy (TEM), and scanning electron microscopy (SEM), were employed to analyse the synthesized herbal-mediated AuNPs. Additionally, the in vivo antidiabetic efficacy of the produced AuNPs was evaluated.

Results: The induction of diabetes using STZ resulted in elevated levels of blood glucose, cholesterol, triglycerides, LDL, VLDL, and significant loss in body weight. However, these detrimental effects were mitigated after treating diabetic rats for 28 days, with significant improvements observed at a dosage range of 1 mg/kg of AuNPs compared to the group treated solely with the plant extract.

Conclusions: The findings suggest that the plant-mediated AuNPs demonstrate significant potential as antidiabetic agents compared to the crude extract alone.

Introduction. Osteoarthritis (OA) is the most common form of chronic joint disease characterized by the loss of cartilage as the primary site of the lesion. Both collagenous and non-collagenous proteins of the extracellular matrix (ECM) are dysregulated by the cellular component damage. Alterations in cartilage composition may manifest through variations in synovial fluid concentrations of C-terminal cross-linked telopeptides of type II collagen (CTX-II) and cartilage oligomeric matrix protein (COMP). This study seeks to decode histological alterations in the cartilage and establish a symbiotic relationship with concentrations of specific ECM proteins within the synovial fluid as potential OA biomarkers.

Methods. Twenty-five surgically obtained cartilage tissue samples were stained with toluidine blue and analysed using the OARSI grading system under a light microscope both quantitatively and semi-quantitatively. The presence of CTX-II and COMP proteins was measured in the synovial fluid samples using ELISA. The SPSS 28.0 program was used for statistical data analysis.

Results. The OARSI score median value was 4.0 (3.0;4.5), attributable to the delamination of the superficial cartilage zone. A greater number of single cells in comparison with cellular clusters was found: 60.00 (45.00;84.00) and 26.00 (22.00;48.00), respectively. Proteoglycan staining was 1.00 (1.00;2.00), attributable to low intensity. A negative correlation between ECM oedema and proteoglycan staining was found (r=-0.445; p=0.043). The mean levels of CTX-II and COMP in synovial fluid were 1092 pg/ml (SD 537.95) and 1262 ng/ml (SD 339.47), respectively. There was a positive correlation between CTX-II and OA severity (r=0.305; p=0.041); the COMP and OA severity correlation was negative (r=-0.286; p=0.049).

Conclusions. The identified positive correlation between OA severity and CTX-II levels in synovial fluid suggests that CTX-II may hold promise as a valuable biomarker for tracking OA progression. This implication opens up possibilities for early detection and targeted interventions in the management of the disease.

Introduction: Embark on a transformative journey into the heart of biomolecular complexity as we unravel the mysteries with the dynamic synergy of bioinformatics and computational biology. This review ignites curiosity by exploring how the digital realm has become a catalyst for groundbreaking insights, reshaping the landscape of biomolecular research.

Methods: In this digital odyssey, we unveil the cutting-edge methodologies propelling bioinformatics and computational biology to new heights. Immerse yourself in the world of algorithms and tools orchestrating the harmonious dance of data, predicting biomolecular interactions with unparalleled accuracy. Witness the magic of structural bioinformatics through molecular dynamics simulations, where biomolecules come to life in a virtual symphony of dynamic behaviors.

Results: Our review is a tapestry of recent triumphs, illustrating the impact of digital ingenuity on biomolecular exploration. From decoding the nuances of omics data to crafting intricate 3D portraits of biomolecules, the digital canvas reveals a deeper understanding of cellular processes. Experience the revelation of complex biomolecular networks through innovative systems biology approaches, offering a glimpse into the orchestrated chaos within cells.

Conclusions: As we venture into the digital frontier, this review culminates with a vision of transformative discoveries and innovations fueled by the dynamic duo of bioinformatics and computational biology. This is not just a journey of understanding; it is a gateway to personalized medicine, where biomolecular intricacies unlock bespoke therapeutic interventions. Amid challenges, the clarion call for collaborative exploration echoes, heralding a future where the digital canvas paints a vivid picture of biomolecular marvels.

Background: Glioblastoma Multiforme (GBM) presents significant diagnostic and therapeutic challenges due to its complex molecular pathogenesis. Current diagnostic methods often fail to detect early molecular signatures critical for timely intervention. This study integrates microarray and RNA-Seq datasets from both serum and tissue samples to explore differentially expressed genes (DEGs) and protein–protein interaction networks with the aim of identifying robust biomarkers and understanding the molecular underpinnings of GBM.

Methods: Utilizing microarray datasets (GSE116520 and GSE90604) and RNA-Seq datasets (GSE165595 and GSE228512) from both brain tissue and serum samples, this study conducted integrative differential gene expression analysis using limma and DESeq2 packages. Functional annotation and gene ontology analyses were performed using DAVID and ShinyGO tools. Protein–protein interaction (PPI) networks were constructed using the STRING database and analysed via Cytoscape to identify central hub genes.

Results: The analysis and cross-technology validation highlighted 1,051 common DEGs across tissue datasets where 87 were upregulated and 255 were downregulated. Notably, three genes, MAST3, ADAM11, and PTPRK, were consistent across tissue and serum datasets, suggesting their utility as non-invasive biomarkers. Functional annotation identified critical biological processes and pathways disrupted in GBM, such as cell division, angiogenesis, and cell adhesion. The PPI network analysis identified central hub genes, offering insights into the molecular interactions contributing to the pathophysiology of GBM.

Conclusion: This study underscores a complex network of molecular interactions pivotal to the pathophysiology of GBM. The identified DEGs and pathways provide a foundation for developing diagnostic panels and therapeutic targets, emphasizing the need for further research to translate these biomarkers from bench to bedside​​.

Background: DNA nanomachines were developed as highly accurate alternatives to costly and unreliable methods used for measuring gene expression levels. However, despite their potential, DNA nanomachines also come with several limitations. One major drawback is their tendency to interact with various biological molecules, which can compromise their functionality. Additionally, background noise often hampers their performance, leading to reduced sensitivity and less precise results.

Goal: The goal of our work was to create DNA nanomachines for the highly sensitive detection of RNA extracted from cell culture that can be used for assessing mRNA concentrations without amplification.

Methods: DNA nanomachines were partially preassembled to add more auxiliary structures and additional quenchers were added to the structure to decrease the background noise and increase the dynamic diapason and limit of detection. The pre-assembly was performed with the gradual cooling of samples after a short boiling period. The resulted structures were visualized via PAGE gel. Samples were incubated at 55^oC and different times of exposure were analyzed. The DNA nanomachines were characterized based on limits of detection and their activity was based on total RNA extracted from cell culture.

Results: The results of the optimization experiments showed that incorporating a specific amount of DNA nanomachine with quenchers effectively reduced the background noise and fluorescence, therefore leading to more accurate evaluation. The limit of detection experiments revealed that these engineered structures were capable of detecting their target at concentrations as small as picomolar. Notably, the machines equipped with quenchers exhibited even greater sensitivity, further enhancing their performance.

Conclusion: The optimization experiments conducted on DNA nanomachines have unequivocally demonstrated that their sensitivity can be significantly enhanced through the incorporation of new designs and additional elements. This breakthrough paves the way for the potential utilization of these advanced constructions as highly efficient point-of-care diagnostics in the future.