Determination of half-maximal inhibitory concentration using biosensor-based protein interaction analysis

Development of a prognostic model based on lysosome-related genes for ovarian cancer: insights into tumor microenvironment, mutation patterns, and personalized treatment strategies

BACKGROUND

Ovarian cancer (OC) is often associated with an unfavorable prognosis. Given the crucial involvement of lysosomes in tumor advancement, lysosome-related genes (LRGs) hold promise as potential therapeutic targets.

METHODS

To identify differentially expressed lysosome-related genes (DE-LRGs), we performed a matching analysis between differentially expressed genes (DEGs) in OC and the pool of LRGs. Genes with prognostic significance were analyzed using multiple regression analyses to construct a prognostic risk signature. The model's efficacy was validated through survival analysis in various cohorts. We further explored the model's correlation with clinical attributes, tumor microenvironment (TME), mutational patterns, and drug sensitivity. The quantitative real-time polymerase chain reaction (qRT-PCR) validated gene expression in OC cells.

RESULTS

A 10-gene prognostic risk signature was established. Survival analysis confirmed its predictive accuracy across cohorts. The signature served as an independent prognostic element for OC. The high-risk and low-risk groups demonstrated notable disparities in terms of immune infiltration patterns, mutational characteristics, and sensitivity to therapeutic agents. The qRT-PCR results corroborated and validated the findings obtained from the bioinformatic analyses.

CONCLUSIONS

We devised a 10-LRG prognostic model linked to TME, offering insights for tailored OC treatments.

Unleashing the future: The revolutionary role of machine learning and artificial intelligence in drug discovery

Drug discovery is a complex and multifaceted process aimed at identifying new therapeutic compounds with the potential to treat various diseases. Traditional methods of drug discovery are often time-consuming, expensive, and characterized by low success rates. Because of this, there is an urgent need to improve the drug development process using new technologies. The integration of the current state-of-art of artificial intelligence (AI) and machine learning (ML) approaches with conventional methods will enhance the efficiency and effectiveness of pharmaceutical research. This review highlights the transformative impact of AI and ML in drug discovery, discussing current applications, challenges, and future directions in harnessing these technologies to accelerate the development of innovative therapeutics. We have discussed the latest developments in AI and ML technologies to streamline several stages of drug discovery, from target identification and validation to lead optimization and preclinical studies.

Rapid discovery of Transglutaminase 2 inhibitors for celiac disease with boosting ensemble machine learning

Celiac disease poses a significant health challenge for individuals consuming gluten-containing foods. While the availability of gluten-free products has increased, there is still a need for therapeutic treatments. The advancement of computational drug design, particularly using bio-cheminformatics-oriented machine learning, offers promising avenues for developing such therapies. One promising target is Transglutaminase 2 (TG2), a protein involved in the autoimmune response triggered by gluten consumption. In this study, we utilized data from approximately 1100 TG2 inhibition assays to develop ligand-based molecular screening techniques using ensemble machine-learning models and extensive molecular feature libraries. Various classifiers, including tree-based methods, artificial neural networks, and graph neural networks, were evaluated to identify primary systems for predictive analysis and feature significance assessment. Boosting ensembles of perceptron deep learning and low-depth random forest weak learners emerged as the most effective, achieving over 90 % accuracy, significantly outperforming a baseline of 64 %. Key features, such as the presence of a terminal Michael acceptor group and a sulfonamide group, were identified as important for activity. Additionally, a regression model was created to rank active compounds. We developed a web application, Celiac Informatics (https://celiac-informatics-v1-2b0a85e75868.herokuapp.com), to facilitate the screening of potential therapeutic molecules for celiac disease. The web app also provides drug-likeness reports, supporting the development of novel drugs.

A comprehensive survey of drug-target interaction analysis in allopathy and siddha medicine

Effective drug delivery is the cornerstone of modern healthcare, ensuring therapeutic compounds reach their intended targets efficiently. This paper explores the potential of personalized and holistic healthcare, driven by the synergy between traditional and allopathic medicine systems, with a specific focus on the vast reservoir of medicinal compounds found in plants rooted in the historical legacy of traditional medicine. Motivated by the desire to unlock the therapeutic potential of medicinal plants and bridge the gap between traditional and allopathic medicine, this survey delves into in-silico computational approaches for studying Drug-Target Interactions (DTI) within the contexts of allopathy and siddha medicine. The contributions of this survey are multifaceted: it offers a comprehensive overview of in-silico methods for DTI analysis in both systems, identifies common challenges in DTI studies, provides insights into future directions to advance DTI analysis, and includes a comparative analysis of DTI in allopathy and siddha medicine. The findings of this survey highlight the pivotal role of in-silico computational approaches in advancing drug research and development in both allopathy and siddha medicine, emphasizing the importance of integrating these methods to drive the future of personalized healthcare.

Bile acid conjugated chitosan nanoparticles promote the proliferation and epithelial-mesenchymal transition of hepatocellular carcinoma by regulating the PI3K/Akt/mTOR pathway

Bile acids have been known to play significant roles at certain physiological levels in gastrointestinal metabolism. Yet, they are known to be carcinogenic and aid in tumor progression in most cases, although the roles remain uncertain. Hence, we tested the cytotoxic potential of cholic acid (CA) loaded chitosan nanoparticles (CNPs) on Hep3B cells. The physicochemical properties of the CNPs synthesized with CA load (CA-CNPs) were determined using standard techniques such as ultraviolet-visible spectrophotometry (UV-Vis), fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), dynamic light scattering (DLS) and transmission electron microscopy (TEM). The characteristic peak for chitosan nanoparticles were observed for plain CNPs (pCNPs) and CA-CNPs at around 300 nm as per UV-Vis analysis. FTIR analysis indicated the possible trapping of CA onto CNPs as certain peaks were retained and some peaks were shifted. XRD analysis determined that the peaks representing CA and pCNPs were collectively obtained in CA-CNPs. As per DLS analysis, the particle size, PDI and ζ-potential of the CA-CNPs were 259 nm, 0.284 and 30.4 mV. Further, the CA-CNPs were non-cytotoxic on Hep3B cells at the maximum tested concentration of 500 μg/mL. The viability at 500 μg/mL of CA-CNPs was two-fold higher than 500 μg/mL of pCNPs. Also, the pCNPs were not hemolytic and therefore could not have played a role in the increase of viability after treatment with CA-CNPs, which indicates that CA posed a major role in increased viability of Hep3B cells. As per quantitative PCR (qPCR), the upregulated gene expressions of PI3K, Akt, mTORC2, cMyc, Fibronectin, hVPS34, Slug and ZEB1 and the downregulated expression of the tumor suppressor PTEN indicates that PI3K/Akt/mTOR pathway mediated the induction of epithelial-to-mesenchymal transition (EMT) in response to CA-CNPs treatment on Hep3B cells.

Emerging Strategies to Prevent Bacterial Infections on Titanium-Based Implants

Titanium and titanium alloys remain the gold standard for dental and orthopedic implants. These materials are heavily used because of their bioinert nature, robust mechanical properties, and seamless integration with bone. However, implant-associated infections (IAIs) remain one of the leading causes of implant failure. Eradicating an IAI can be difficult since bacteria can form biofilms on the medical implant, protecting the bacterial cells against systemic antibiotics and the host's immune system. If the infection is not treated promptly and aggressively, device failure is inevitable, leading to costly multi-step revision surgeries. To circumvent this dire situation, scientists and engineers continue to develop novel strategies to protect the surface of medical implants from bacteria. In this review, details on emerging strategies to prevent infection in titanium implants are reported. These strategies include anti-adhesion properties provided by polymers, superhydrophobic, superhydrophilic, and liquid-infused surface coatings, as well as strategies and coatings employed to lyse the bacteria. Additionally, commercially available technologies and those under preclinical trials are examined while discussing current and future trends.

In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery

TBK1, or TANK-binding kinase 1, is an enzyme that functions as a serine/threonine protein kinase. It plays a crucial role in various cellular processes, including the innate immune response to viruses, cell proliferation, apoptosis, autophagy, and antitumor immunity. Dysregulation of TBK1 activity can lead to autoimmune diseases, neurodegenerative disorders, and cancer. Due to its central role in these critical pathways, TBK1 is a significant focus of research for therapeutic drug development. In this paper, we explore data from the CAS Content Collection regarding TBK1 and its implication in a large assortment of diseases and disorders. With the demand for developing efficient TBK1 inhibitors being outlined, we focus on utilizing a machine learning approach for developing predictive models for TBK1 inhibition, derived from the fragment-functional analysis descriptors. Using the extensive CAS Content Collection, we assembled a training set of TBK1 inhibitors with experimentally measured IC50 values. We explored several machine learning techniques combined with various molecular descriptors to derive and select the best TBK1 inhibitor QSAR models. Certain significant structural alerts that potentially contribute to inhibition of TBK1 are outlined and discussed. The merit of the article stems from identifying the most adequate TBK1 QSAR models and subsequent successful development of advanced positive training data to facilitate and enhance drug discovery for an important therapeutic target such as TBK1 inhibitors, based on an extensive, wide-ranging set of scientific information provided by the CAS Content Collection.

Silver nanoparticles mediated apoptosis and cell cycle arrest in lung cancer A549

The present study was aimed to synthesize the silver nanoparticles from Alangium salvifolium Wang. and evaluating its biomedical applications. The leaves of A. salvifolium collected and subjected for the standard procedure of Soxhlet extraction using distilled water as a solvent. With the help of an aqueous extract AgNPs were synthesized from silver nitrate using phyto-reduction method. Further, synthesized AgNPs were characterized using several analytical techniques such as UV, FTIR, SEM-EDX, XRD, particles size and zeta potential. Synthesized AgNPs were tested for antibacterial, antioxidant, anticancer for lung cancer cell line and flowcytometry-based pathway studies. The visual observation confirmed the formation of AgNPs from the aqueous extract by changing yellow to brown colour formation. Further, characterization techniques also confirmed the formation of AgNPs. Antibacterial activity results showed that the tested AgNPs were potent against bacterial pathogens with a higher zone of inhibition. Further, the antioxidant and anticancer activity of AgNPs revealed that the AgNPs have exhibited significant results with a good percentage of inhibition. Further, the flow cytometry studies confirmed that the AgNPs inducing apoptosis and cell cycle arrest in lung cancer. The phytochemicals of A. salvifolium plant have successfully synthesized AgNPs. In the case of performed biological activity, the synthesized silver nanoparticles exhibited potent activity. In future these AgNPs can be taken for molecular and in vivo studies to identify their efficacy using in vivo and molecular models.

Genistein and daidzein induce ferroptosis in MDA-MB-231 cells

OBJECTIVES

In recent years, there has been a growing interest in targeting ferroptosis for the treatment and prevention of multiple cancers. This study aimed to assess the contribution of ferroptosis to the antiproliferative effects of genistein (GN) and daidzein (DZ) in breast cancer cell lines.

METHODS

MDA-MB-231 and MCF-7 cells were employed as an in vitro model. The antiproliferative effects of GN and DZ were determined by WST-1 assay in the presence of specific inhibitors of different cell death pathways. The mRNA expressions of Gpx4 and Fsp-1, the levels of lipid peroxidation, glutathione (GSH)/glutathione disulfide (GSSG) ratio, and intracellular iron ion content were assessed in GN- or DZ-treated cells.

RESULTS

GN and DZ were found to cause ferroptotic cell death in MDA-MB-231, as confirmed by the reversal of viability when cells were pretreated with ferrostatin-1. Furthermore, both phytochemicals induced biochemical markers of ferroptosis, including lipid peroxidation and iron ions levels, and decreased GSH/GSSG levels. The mRNA expression levels of the main anti-ferroptotic genes, Gpx4 and Fsp-1, were diminished by the treatment of both phytochemicals. Surprisingly, ferroptosis did not play a role in GN- or DZ-induced cell death in MCF-7 cells.

CONCLUSION

Our findings highlight the potential of GN and DZ as ferroptosis inducers in triple-negative breast cancer cells.

Development of an automated high-content immunofluorescence assay of pSmads quantification: Proof-of-concept with drugs inhibiting the BMP/TGF-β pathways

INTRODUCTION

Bone morphogenetic proteins (BMPs) and transforming growth factors (TGF-β) are members of the TGF-β superfamily, known for their roles in several physiological and pathological processes. These factors are known to bind in vivo to BMP and TGF-β receptors, respectively, which induces the phosphorylation of Smad (pSmad) transcription factors. This pathway is generally studied with Western blot and luciferase bioluminescence assay, which presents some limitations.

PURPOSE

In this work, we developed and optimized a high-throughput assay to study pSmad pathways using immunofluorescence (IF) as an alternative to Western blot. We aimed to overcome the technical challenges usually faced in the classical IF assay in image acquisition, analysis, and quantification.

METHODS

We used C2C12 cells as a cellular model. The cells were stimulated with BMP-2 and TGF-β1 that were delivered either in solution (soluble) or via a biomaterial presenting the growth factor (GF), that is in a "matrix-bound" manner. Image acquisition parameters, analysis methods, and quantification of pSmads using IF were optimized for cells cultured on two types of supports: on bare glass and on a biomimetic coating made by self-assembly of the biopolymers hyaluronic acid and poly(l-lysine), which was crosslinked and then loaded with the GFs.

RESULTS

We performed high-content kinetic studies of pSmad expression for cells cultured in 96-well microplates in response to soluble and matrix-bound BMP-2 and TGF-β1. The detection limit of the IF-based assay was found to be similar to Western blot. Additionally, we provide a proof-of-concept for drug testing using inhibitors of BMP and TGF-β receptors, under conditions where specific signaling pathways are engaged via the ligand/receptor interactions. Altogether, our findings offer perspectives for future mechanistic studies on cell signaling and for studies at the single cell level using imaging methods.

SARS-CoV-2 Resistance to Small Molecule Inhibitors

Purpose of the Review

SARS-CoV-2 undergoes genetic mutations like many other viruses. Some mutations lead to the emergence of new Variants of Concern (VOCs), affecting transmissibility, illness severity, and the effectiveness of antiviral drugs. Continuous monitoring and research are crucial to comprehend variant behavior and develop effective response strategies, including identifying mutations that may affect current drug therapies.

Recent Findings

Antiviral therapies such as Nirmatrelvir and Ensitrelvir focus on inhibiting 3CLpro, whereas Remdesivir, Favipiravir, and Molnupiravir target nsp12, thereby reducing the viral load. However, the emergence of resistant mutations in 3CLpro and nsp12 could impact the efficiency of these small molecule drug therapeutics.

Summary

This manuscript summarizes mutations in 3CLpro and nsp12, which could potentially reduce the efficacy of drugs. Additionally, it encapsulates recent advancements in small molecule antivirals targeting SARS-CoV-2 viral proteins, including their potential for developing resistance against emerging variants.

A versatile dilution-treatment-detection microfluidic chip platform for rapid In vitro lung cancer drug combination sensitivity evaluation

Combination drug therapy represents an effective strategy for treating certain drug-resistant and intractable cancer cases. However, determining the optimal combination of drugs and dosages is challenging due to clonal diversity in patients' tumors and the lack of rapid drug sensitivity evaluation methods. Microfluidic technology offers promising solutions to this issue. In this study, we propose a versatile microfluidic chip platform capable of integrating all processes, including dilution, treatment, and detection, for in vitro drug sensitivity assays. This platform innovatively incorporates several modules, including automated discrete drug logarithmic concentration generation, on-chip cell perfusion culture, and parallel drug treatments of cancer cell models. Moreover, it is compatible with microplate readers or high-content imaging systems for swift detection and automated monitoring, simplifying on-chip drug evaluation. Proof of concept is demonstrated by assessing the in vitro potency of two drugs, cisplatin, and etoposide, against the lung adenocarcinoma A549 cell line, under both single-drug and combination treatment conditions. The findings reveal that, compared to conventional microplate approaches with static cultivation, this on-chip automated perfusion bioassays yield comparable IC50 values with lower variation and a 50 % reduction in drug preparation time. This versatile dilution-treatment-detection microfluidic platform offers a promising tool for rapid and precise drug assessments, facilitating in vitro drug sensitivity evaluation in personalized cancer chemotherapy.

Concomitant Administration of Ozanimod and Serotonergic Antidepressants in Patients With Ulcerative Colitis or Relapsing Multiple Sclerosis

BACKGROUND

Ozanimod, approved for the treatment of moderately to severely active ulcerative colitis (UC) and relapsing multiple sclerosis (RMS), is a weak in vitro monoamine oxidase B (MAO-B) inhibitor. MAO-B inhibitors can cause serotonin accumulation with concomitant use of selective serotonin reuptake inhibitors (SSRIs) or serotonin and norepinephrine reuptake inhibitors (SNRIs). We evaluated the incidence of treatment-emergent adverse events (TEAEs) potentially associated with serotonin accumulation during ozanimod and concomitant SSRI/SNRI use in this post hoc analysis of pooled UC studies and the open-label extension RMS DAYBREAK.

METHODS

Data for ozanimod 0.92 mg from pooled UC studies (n = 1158; cutoff: January 10, 2022) and RMS DAYBREAK (n = 2257; cutoff: February 1, 2022) were analyzed. Concomitant SSRI/SNRI use was allowed in the UC (n = 67) and RMS (n = 274) studies. A narrow Medical Dictionary for Regulatory Activities search ("serotonin syndrome," "neuroleptic malignant syndrome," and "malignant hyperthermia") and a broad search including terms potentially associated with serotonin accumulation were conducted. The percentages of patients with TEAEs in both searches were analyzed by concomitant SSRI/SNRI use when the TEAE occurred.

RESULTS

No patients had TEAEs matching the narrow search criteria. No differences were observed in the percentages of patients with ≥1 TEAE matching the broad search regardless of SSRI/SNRI use in UC (with: 25.4% [n = 17 of 67]; without: 15.0% [n = 164 of 1091]) and RMS (with: 12.4% [n = 34 of 274]; without: 15.6% [n = 310 of 1982]) studies.

CONCLUSIONS

No evidence of increased TEAEs potentially associated with serotonin accumulation was observed with concurrent use of ozanimod and SSRIs/SNRIs.

CLINICAL TRIAL REGISTRATION

NCT01647516, NCT02531126, NCT02435992, NCT02576717.

The function and mechanism of circRNAs in 5-fluorouracil resistance in tumors: Biological mechanisms and future potential

5-Fluorouracil (5-FU) is a well-known chemotherapy drug extensively used in the treatment of breast cancer. It works by inhibiting cancer cell proliferation and inducing cell death through direct incorporation into DNA and RNA via thymidylate synthase (TS). Circular RNAs (circRNAs), a novel family of endogenous non-coding RNAs (ncRNAs) with limited protein-coding potential, contribute to 5-FU resistance. Their identification and targeting are crucial for enhancing chemosensitivity. CircRNAs can regulate tumor formation and invasion by adhering to microRNAs (miRNAs) and interacting with RNA-binding proteins, regulating transcription and translation. MiRNAs can influence enzymes responsible for 5-FU metabolism in cancer cells, affecting their sensitivity or resistance to the drug. In the context of 5-FU resistance, circRNAs can target miRNAs and regulate biological processes such as cell proliferation, cell death, glucose metabolism, hypoxia, epithelial-to-mesenchymal transition (EMT), and drug efflux. This review focuses on the function of circRNAs in 5-FU resistance, discussing the underlying molecular pathways and biological mechanisms. It also presents recent circRNA/miRNA-targeted cancer therapeutic strategies for future clinical application.

A comprehensive in-vitro/in-vivo screening toolbox for the elucidation of glucose homeostasis modulating properties of plant extracts (from roots) and its bioactives

Plant extracts are increasingly recognized for their potential in modulating (postprandial) blood glucose levels. In this context, root extracts are of particular interest due to their high concentrations and often unique spectrum of plant bioactives. To identify new plant species with potential glucose-lowering activity, simple and robust methodologies are often required. For this narrative review, literature was sourced from scientific databases (primarily PubMed) in the period from June 2022 to January 2024. The regulatory targets of glucose homeostasis that could be modulated by bioactive plant compounds were used as search terms, either alone or in combination with the keyword "root extract". As a result, we present a comprehensive methodological toolbox for studying the glucose homeostasis modulating properties of plant extracts and its constituents. The described assays encompass in-vitro investigations involving enzyme inhibition (α-amylase, α-glucosidase, dipeptidyl peptidase 4), assessment of sodium-dependent glucose transporter 1 activity, and evaluation of glucose transporter 4 translocation. Furthermore, we describe a patch-clamp technique to assess the impact of extracts on KATP channels. While validating in-vitro findings in living organisms is imperative, we introduce two screenable in-vivo models (the hen's egg test and Drosophila melanogaster). Given that evaluation of the bioactivity of plant extracts in rodents and humans represents the current gold standard, we include approaches addressing this aspect. In summary, this review offers a systematic guide for screening plant extracts regarding their influence on key regulatory elements of glucose homeostasis, culminating in the assessment of their potential efficacy in-vivo. Moreover, application of the presented toolbox might contribute to further close the knowledge gap on the precise mechanisms of action of plant-derived compounds.

Bone morphogenetic protein signalling in pulmonary arterial hypertension: revisiting the BMPRII connection

Pulmonary arterial hypertension (PAH) is a rare and life-threatening vascular disorder, characterised by abnormal remodelling of the pulmonary vessels and elevated pulmonary artery pressure, leading to right ventricular hypertrophy and right-sided heart failure. The importance of bone morphogenetic protein (BMP) signalling in the pathogenesis of PAH is demonstrated by human genetic studies. Many PAH risk genes are involved in the BMP signalling pathway and are highly expressed or preferentially act on vascular endothelial cells. Endothelial dysfunction is recognised as an initial trigger for PAH, and endothelial BMP signalling plays a crucial role in the maintenance of endothelial integrity. BMPR2 is the most prevalent PAH gene, found in over 80% of heritable cases. As BMPRII protein is the major type II receptor for a large family of BMP ligands and expressed ubiquitously in many tissues, dysregulated BMP signalling in other cells may also contribute to PAH pathobiology. Sotatercept, which contains the extracellular domain of another transforming growth factor-β family type II receptor ActRIIA fused to immunoglobin Fc domain, was recently approved by the FDA as a treatment for PAH. Neither its target cells nor its mechanism of action is fully understood. This review will revisit BMPRII function and its extracellular regulation, summarise how dysregulated BMP signalling in endothelial cells and smooth muscle cells may contribute to PAH pathogenesis, and discuss how novel therapeutics targeting the extracellular regulation of BMP signalling, such as BMP9 and Sotatercept, can be related to restoring BMPRII function.

Pharmaceutical Potential of Remedial Plants and Helminths for Treating Inflammatory Bowel Disease

Research is increasingly revealing that inflammation significantly contributes to various diseases, particularly inflammatory bowel disease (IBD). IBD is a major medical challenge due to its chronic nature, affecting at least one in a thousand individuals in many Western countries, with rising incidence in developing nations. Historically, indigenous people have used natural products to treat ailments, including IBD. Ethnobotanically guided studies have shown that plant-derived extracts and compounds effectively modulate immune responses and reduce inflammation. Similarly, helminths and their products offer unique mechanisms to modulate host immunity and alleviate inflammatory responses. This review explored the pharmaceutical potential of Aboriginal remedial plants and helminths for treating IBD, emphasizing recent advances in discovering anti-inflammatory small-molecule drug leads. The literature from Scopus, MEDLINE Ovid, PubMed, Google Scholar, and Web of Science was retrieved using keywords such as natural product, small molecule, cytokines, remedial plants, and helminths. This review identified 55 important Aboriginal medicinal plants and 9 helminth species that have been studied for their anti-inflammatory properties using animal models and in vitro cell assays. For example, curcumin, berberine, and triptolide, which have been isolated from plants; and the excretory-secretory products and their protein, which have been collected from helminths, have demonstrated anti-inflammatory activity with lower toxicity and fewer side effects. High-throughput screening, molecular docking, artificial intelligence, and machine learning have been engaged in compound identification, while clustered regularly interspaced short palindromic repeats (CRISPR) gene editing and RNA sequencing have been employed to understand molecular interactions and regulations. While there is potential for pharmaceutical application of Aboriginal medicinal plants and gastrointestinal parasites in treating IBD, there is an urgent need to qualify these plant and helminth therapies through reproducible clinical and mechanistic studies.

Rational Approach toward COVID-19's Main Protease Inhibitors: A Hierarchical Biochemoinformatics Analysis

This study investigated the potential of selected compounds as inhibitors of SARS-CoV-2 Mpro through pharmacokinetic and toxicological analyses, molecular docking, and molecular dynamics simulations. In silico molecular docking simulations revealed promising ligands with favorable binding affinities for Mpro, ranging from -6.2 to -9.5 kcal/mol. Moreover, molecular dynamics simulations demonstrated the stability of protein-ligand complexes over 200 ns, maintaining protein secondary structures. MM-PBSA analysis revealed favorable interactions between ligands and Mpro, with negative binding energy values. Hydrogen bond formation capacity during molecular dynamics was confirmed, indicating consistent interactions with Mpro catalytic residues. Based on these findings, selected ligands show promise for future studies in developing COVID-19 treatments.

Investigating the Anticancer and Antioxidant Potentials of a Polymer-Grafted Sodium Alginate Composite Embedded with CuO and TiO2 Nanoparticles

In this study, we conducted the synthesis of a composite material by grafting an acrylonitrile-co-styrene (AN-co-St) polymer into sodium alginate and incorporating CuO (copper oxide) and TiO2 (titanium dioxide) nanoparticles. The primary objective was to investigate the potential anticancer and antioxidant activities of the composite material. First, CuO and TiO2 nanoparticles were synthesized and characterized for their size, morphology, and surface properties. Subsequently, these nanoparticles were integrated into the sodium alginate matrix, which had been grafted with the AN-co-St polymer, resulting in the formation of the composite material. To confirm successful nanoparticle incorporation and assess the structural integrity of the composite, various techniques such as X-ray diffraction analysis (XRD), scanning electron microscopy-energy dispersive X-ray analysis (SEM-EDX), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA) were employed. The composite material’s anticancer and antioxidant activities were then evaluated. In vitro cell viability assays using the HepG-2 cell line were performed to assess potential cytotoxic effects, while antioxidant (DPPH) assays were conducted to determine the composite’s ability to scavenge free radicals and protect against oxidative stress. Preliminary results indicate that the composite material demonstrated promising anticancer and antioxidant activities. The presence of CuO and TiO2 nanoparticles within the composite contributed to these effects, as these nanoparticles are known to possess anticancer and antioxidant properties. Furthermore, the grafting of the AN-co-St polymer into sodium alginate enhanced the overall performance and stability of the composite material.

Circadian transcriptome of pancreatic adenocarcinoma unravels chronotherapeutic targets

Pancreatic ductal adenocarcinoma (PDA) is a lethal cancer characterized by a poor outcome and an increasing incidence. A significant majority (>80%) of newly diagnosed cases are deemed unresectable, leaving chemotherapy as the sole viable option, though with only moderate success. This necessitates the identification of improved therapeutic options for PDA. We hypothesized that there are temporal variations in cancer-relevant processes within PDA tumors, offering insights into the optimal timing of drug administration - a concept termed chronotherapy. In this study, we explored the presence of the circadian transcriptome in PDA using patient-derived organoids and validated these findings by comparing PDA data from The Cancer Genome Atlas with noncancerous healthy pancreas data from GTEx. Several PDA-associated pathways (cell cycle, stress response, Rho GTPase signaling) and cancer driver hub genes (EGFR and JUN) exhibited a cancer-specific rhythmic pattern intricately linked to the circadian clock. Through the integration of multiple functional measurements for rhythmic cancer driver genes, we identified top chronotherapy targets and validated key findings in molecularly divergent pancreatic cancer cell lines. Testing the chemotherapeutic efficacy of clinically relevant drugs further revealed temporal variations that correlated with drug-target cycling. Collectively, our study unravels the PDA circadian transcriptome and highlights a potential approach for optimizing chrono-chemotherapeutic efficacy.

Establishment and characterization of NCC-DFSP5-C1: a novel patient-derived dermatofibrosarcoma protuberans cell line

Dermatofibrosarcoma protuberans (DFSP) is the most prevalent dermal sarcoma, characterized by the presence of the fusion of the collagen type I alpha 1 (COL1A1) gene with the platelet-derived growth factor beta chain (PDGFB) gene. Although PDGF receptor inhibitor imatinib mesylate was approved for the treating patients with unresectable or metastatic DFSP, disease progression was shown in 9.2% of the patients. Therefore, developing novel therapeutic strategies is crucial for improving the prognosis of DFSP. Patient-derived cell lines play a vital role in preclinical studies; however, only a limited number of DFSP cell lines are currently available in public cell banks. Here, we successfully established a novel DFSP cell line (NCC-DFSP5-C1) using surgically resected tumor tissue from a patient with DFSP. NCC-DFSP5-C1 cells were confirmed to carry the COL1A1-PDGFB translocation and maintain the same mutation as the original tumor tissue. They exhibited consistent growth, formed spheroids, and were invasive. By screening a drug library using NCC-DFSP5-C1 and four previously established DFSP cell lines, we identified anti-cancer drugs that inhibit DFSP cell proliferation. Our observations suggest that the NCC-DFSP5-C1 cell line holds promise as a valuable tool for conducting fundamental and preclinical studies for DFSP.

Spatial engineering of single-atom Fe adjacent to Cu-assisted nanozymes for biomimetic O2 activation

The precise design of single-atom nanozymes (SAzymes) and understanding of their biocatalytic mechanisms hold great promise for developing ideal bio-enzyme substitutes. While considerable efforts have been directed towards mimicking partial bio-inspired structures, the integration of heterogeneous SAzymes configurations and homogeneous enzyme-like mechanism remains an enormous challenge. Here, we show a spatial engineering strategy to fabricate dual-sites SAzymes with atomic Fe active center and adjacent Cu sites. Compared to planar Fe-Cu dual-atomic sites, vertically stacked Fe-Cu geometry in FePc@2D-Cu-N-C possesses highly optimized scaffolds, favorable substrate affinity, and fast electron transfer. These characteristics of FePc@2D-Cu-N-C SAzyme induces biomimetic O2 activation through homogenous enzymatic pathway, resembling functional and mechanistic similarity to natural cytochrome c oxidase. Furthermore, it presents an appealing alternative of cytochrome P450 3A4 for drug metabolism and drug-drug interaction. These findings are expected to deepen the fundamental understanding of atomic-level design in next-generation bio-inspired nanozymes.

Identification and Validation of a Novel Anoikis-Related Gene Signature for Predicting Survival in Patients With Serous Ovarian Cancer

Background

Ovarian cancer is an extremely deadly gynecological malignancy, with a 5-year survival rate below 30%. Among the different histological subtypes, serous ovarian cancer (SOC) is the most common. Anoikis significantly contributes to the progression of ovarian cancer. Therefore, identifying an anoikis-related signature that can serve as potential prognostic predictors for SOC is of great significance.

Methods

We intersected 308 anoikis-related genes (ARGs) and identified those significantly associated with SOC prognosis using univariate Cox regression. A LASSO Cox regression model was constructed and evaluated using Kaplan-Meier and receiver operating characteristic (ROC) analyses in TCGA (The Cancer Genome Atlas) and GSE26193 cohorts. We conducted quantitative real-time polymerase chain reaction (qPCR) to assess mRNA levels and applied bioinformatics to investigate the correlation between risk groups and gene expression, mutations, pathways, tumor immune microenvironment (TIME), and drug sensitivity in SOC.

Results

Among 308 ARGs, 28 were significantly associated with SOC prognosis. A 13-gene prognostic model was established through LASSO Cox regression in TCGA cohort. High-risk group had poorer prognosis than low-risk group (median overall survival (mOS): 34.2 vs. 57.1 months, hazard ratio (HR): 2.590, 95% confidence interval (CI): 0.159 - 6.00, P < 0.001). The area under the curve (AUC) values of 0.63, 0.65, and 0.74 reflected the predictive performance for 3-, 5-, and 8-year overall survival (OS) in GSE26193 validation cohort. Functional enrichment, pathway analysis, and TIME analysis identified distinct characteristics between risk groups. Drug sensitivity analysis revealed potential drug advantages for each group. Furthermore, qPCR validation once again confirmed the effectiveness of the risk model in SOC patients.

Conclusions

We developed and validated a robust ARG model, which could be used to predict OS in SOC patients. By systematically analyzing the correlation between the risk score of the ARGs signature model and various patterns, including the TIME and drug sensitivity, our findings suggest that this prognostic model contributes to the advancement of personalized and precise therapeutic strategies. Nevertheless, further validation studies and investigations into the underlying mechanisms are warranted.

Characterization of a Molecularly Engineered Banlec-Type Lectin (rBTL)

Lectins are proteins that reversibly bind to carbohydrates and are commonly found across many species. The Banana Lectin (BanLec) is a member of the Jacalin-related Lectins, heavily studied for its immunomodulatory, antiproliferative, and antiviral activity. In this study, a novel sequence was generated in silico considering the native BanLec amino acid sequence and 9 other lectins belonging to JRL. Based on multiple alignment of these proteins, 11 amino acids of the BanLec sequence were modified because of their potential for interference in active binding site properties resulting in a new lectin named recombinant BanLec-type Lectin (rBTL). rBTL was expressed in E. coli and was able to keep biological activity in hemagglutination assay (rat erythrocytes), maintaining similar structure with the native lectin. Antiproliferative activity was demonstrated on human melanoma lineage (A375), evaluated by 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT). rBTL was able to inhibit cellular growth in a concentration-dependent manner, in an 8-h incubation, 12 µg/mL of rBTL led to a 28.94% of cell survival compared to cell control with 100%. Through a nonlinear fit out log-concentration versus biological response, an IC50% of 3.649 µg/mL of rBTL was determined. In conclusion, it is possible to state that the changes made to the rBTL sequence maintained the structure of the carbohydrate-binding site without changing specificity. The new lectin is biologically active, with an improved carbohydrate recognition spectrum compared to nBanLec, and can also be considered cytotoxic for A375 cells.

Exploring the role of lactylation-related genes in osteosarcoma: A deep dive into prognostic significance and therapeutic potential

Osteosarcoma (OS), notorious for its complex pathogenesis and formidable prognosis, represents a significant medical quandary. This research embarked on a quest to unravel the implications of lactylation-related genes (LRGs) in OS, offering a novel lens through which to interpret its intricacies. A meticulous evaluation of 329 LRGs within the TARGET dataset spotlighted 27 paramount genes, intricately intertwined with survival. These genes highlighted metabolic processes-particularly amino acid metabolism-as key players, as evidenced in both GO and KEGG analyses. Utilizing consensus clustering and principal component analysis, the 93 OS samples were segmented into two distinct groups, differing notably in overall and event-free survival. Cluster 2 demonstrated a heightened immune response, contrasting the other cluster. Machine learning techniques, like generalized boosted model, CoxBoost, and RSF, spotlighted MYC and GOT2 as critical genes. Using multivariate Cox regression, a risk model was developed, categorizing patients into high and low-risk groups, each displaying varied survival patterns. Additionally, a contrast was observed between MYC and GOT2's associations with HLA molecules, emphasizing their distinct roles in antigen presentation. Potential therapeutic avenues were identified for each risk group, with special attention to mutations in MYC, particularly amplifications, hinting at its role in tumor progression. Finally, delving deeper into the role of MYC, Western blot analyses exhibited amplified myc protein levels in OS cells U-2 and MG-63 when juxtaposed against human osteoblastic cells Hfob1.19. A focused knockdown of myc in OS cells subsequently confirmed its influence on cell proliferation and migration, with reduced myc expression resulting in inhibited cell activities. Furthermore, immunofluorescence assays corroborated myc's heightened expression in OS cells relative to normal osteoblastic cells. In summary, this study accentuates the vital role of LRGs and specifically MYC in OS, ushering in a horizon of tailored therapeutic strategies.

Machine Learning Application for Medicinal Chemistry: Colchicine Case, New Structures, and Anticancer Activity Prediction

In the contemporary era, the exploration of machine learning (ML) has gained widespread attention and is being leveraged to augment traditional methodologies in quantitative structure-activity relationship (QSAR) investigations. The principal objective of this research was to assess the anticancer potential of colchicine-based compounds across five distinct cell lines. This research endeavor ultimately sought to construct ML models proficient in forecasting anticancer activity as quantified by the IC50 value, while concurrently generating innovative colchicine-derived compounds. The resistance index (RI) is computed to evaluate the drug resistance exhibited by LoVo/DX cells relative to LoVo cancer cell lines. Meanwhile, the selectivity index (SI) is computed to determine the potential of a compound to demonstrate superior efficacy against tumor cells compared to its toxicity against normal cells, such as BALB/3T3. We introduce a novel ML system adept at recommending novel chemical structures predicated on known anticancer activity. Our investigation entailed the assessment of inhibitory capabilities across five cell lines, employing predictive models utilizing various algorithms, including random forest, decision tree, support vector machines, k-nearest neighbors, and multiple linear regression. The most proficient model, as determined by quality metrics, was employed to predict the anticancer activity of novel colchicine-based compounds. This methodological approach yielded the establishment of a library encompassing new colchicine-based compounds, each assigned an IC50 value. Additionally, this study resulted in the development of a validated predictive model, capable of reasonably estimating IC50 values based on molecular structure input.

PIM Kinase Inhibitors as Novel Promising Therapeutic Scaffolds in Cancer Therapy

Cancer involves the uncontrolled, abnormal growth of cells and affects other tissues. Kinase has an impact on proliferating the cells and causing cancer. For the purpose of treating cancer, PIM kinase is a potential target. The pro-viral Integration site for moloney murine leukaemia virus (PIM) kinases is responsible for the tumorigenesis, by phosphorylating the proteins that control the cell cycle and cell proliferation. PIM-1, PIM-2, and PIM-3 are the three distinct isoforms of PIM kinases. The JAK/STAT pathway is essential for controlling how PIM genes are expressed. PIM kinase is also linked withPI3K/AKT/mTOR pathway in various types of cancers. The overexpression of PIM kinase will cause cancer. Currently, there are significant efforts being made in medication design and development to target its inhibition. A few small chemical inhibitors (E.g., SGI-1776, AZD1208, LGH447) that specifically target the PIM proteins' adenosine triphosphate (ATP)-binding domain have been identified. PIM kinase antagonists have a remarkable effect on different types of cancer. Despite conducting clinical trials on SGI-1776, the first PIM inhibitory agent, was prematurely withdrawn, making it unable to generate concept evidence. On the other hand, in recent years, it has aided in hastening the identification of multiple new PIM inhibitors. Cyanopyridines and Pyrazolo[1,5-a]pyrimidinecan act as potent PIM kinase inhibitors for cancer therapy. We explore the involvement of oncogenic transcription factor c-Mycandmi-RNA in relation to PIM kinase. In this article, we highlight the oncogenic effects, and structural insights into PIM kinase inhibitors for the treatment of cancer.

Tyrosine Kinase Inhibitors and their role in treating neovascular age-related macular degeneration and diabetic macular oedema

The advent of intravitreal anti-VEGF injections has revolutionised the treatment of both neovascular age-related macular degeneration (nAMD or wet AMD) and diabetic macular oedema (DMO). Despite their efficacy, anti-VEGF injections precipitate significant treatment burden for patients, caregivers and healthcare systems due to the high frequency of injections required to sustain treatment benefit. Therefore, there remains an unmet need for lower-burden therapies. Tyrosine kinase inhibitors (TKI) are a novel class of drugs that may have considerable potential in addressing this issue. This review will summarise and discuss the results of various pilot studies and clinical trials exploring the role of TKIs in treatment of nAMD and DMO, highlighting promising candidates and possible challenges in developments.

Cytotoxic activity of isoquinoline alkaloids and herbal extracts from selected plants against human cancer cell lines: harnessing the research potential in cancer drug discovery with modern scientific trends and technology

The increasing prevalence of cancer has led to a growing interest in alternative medicine methods and treatments. This study aimed to assess the cytotoxicity of isoquinoline alkaloids and herbal extracts from selected plants against human cancer cell lines, including melanoma and squamous cell carcinoma. The investigation involved in vitro cell viability assays using various cancer cell lines and normal skin fibroblasts as control cells. Additionally, a zebrafish model was employed for in vivo evaluation of cytotoxic activity. The results indicated that the tested alkaloids and extracts exhibited promising cytotoxic effects, showing higher potency than standard chemotherapeutic drugs. In comparison, these findings support the exploration of isoquinoline alkaloids and herbal extracts as potential candidates for developing novel anti-melanoma and anti-squamous cell carcinoma drugs. The primary inclusion criterion that was taken into consideration in this study effort was the therapeutic application of the cytotoxic effects of specific plant-based pharmacological components or chemicals produced from herbal extracts that are ordinarily cytotoxic.

First-Row Transition 7-Oxo-5-phenyl-1,2,4-triazolo[1,5-a]pyrimidine Metal Complexes: Antiparasitic Activity and Release Studies

Leishmaniasis and Chagas disease are still considered neglected illnesses due to the lack of investment in research, despite the fact that almost one million new cases are reported every year. Four 7-oxo-5-phenyl-1,2,4-triazolo[1,5-a]pyrimidine (HftpO) first-row transition complexes (Cu, Co, Ni, Zn) have been studied for the first time in vitro against five different species of Leishmania spp. (L. infantum, L. braziliensis, L. donovani, L. peruviana and L. mexicana) as well as Trypanosoma cruzi, showing higher efficacy than the reference commercial drugs. UV and luminescence properties were also evaluated. As a proof of concept, anchoring of a model high-effective-metal complex as an antiparasitic agent on silica nanoparticles was carried out for the first time, and drug-release behaviour was evaluated, assessing this new approach for drug vehiculation.

The Yin and Yang of Sodium Lauryl Sulfate Use for Oral and Periodontal Health: A Literature Review

Sodium lauryl sulfate (SLS) is an anionic surfactant, which has a wide range of usage in the health sector and in dental pharmaceutical products, especially in toothpastes. The objective of this review was to investigate the effects of SLS containing dentifrices on oral and periodontal health, possible side effects, and its benefits. A thorough literature search was done using databases of PubMed and Google Scholar and finally, 40 articles were included in the study. This narrative review revealed the sources of discrepancy and conflicting results regarding the impact of SLS on oral cavity as well as a lack of sufficient evidence in most topics. Hence, the evidence suggests improved drug bioavailability when used as a solubilizer, improved plaque control, and reduction in bad breath. On the other hand, SLS can serve as a risk indicator of prolonged oral wound healing time, recurrent aphthous stomatitis.

Current Principles, Challenges, and New Metrics in pH-Responsive Drug Delivery Systems for Systemic Cancer Therapy

The paradigm of drug delivery via particulate formulations is one of the leading ideas that enable overcoming limitations of traditional chemotherapeutic agents. The trend toward more complex multifunctional drug carriers is well-traced in the literature. Nowadays, the prospectiveness of stimuli-responsive systems capable of controlled cargo release in the lesion nidus is widely accepted. Both endogenous and exogenous stimuli are employed for this purpose; however, endogenous pH is the most common trigger. Unfortunately, scientists encounter multiple challenges on the way to the implementation of this idea related to the vehicles' accumulation in off-target tissues, their immunogenicity, the complexity of drug delivery to intracellular targets, and finally, the difficulties in the fabrication of carriers matching all imposed requirements. Here, we discuss fundamental strategies for pH-responsive drug delivery, as well as limitations related to such carriers' application, and reveal the main problems, weaknesses, and reasons for poor clinical results. Moreover, we attempted to formulate the profiles of an "ideal" drug carrier in the frame of different strategies drawing on the example of metal-comprising materials and considered recently published studies through the lens of these profiles. We believe that this approach will facilitate the formulation of the main challenges facing researchers and the identification of the most promising trends in technology development.

Analytical assessment of modulated electric flux triggered degradation of chlorfenapyr and deltamethrin pesticides in guava fruits

The purpose of this study was to explore the new effective method and investigate the dissipation of chlorfenapyr and deltamethrin (DM) pesticides used in the treatment of guava fruit from tropical and sub-tropical areas of Pakistan. Five different solutions of varying concentrations of pesticides were prepared. This study involved the in-vitro and in-vivo analysis of modulated electric flux-triggered degradation as an efficient method for the safer degradation of selected pesticides. The Taser gun was used as a tool for providing different numbers of electrical shocks of million voltages to the pesticides present in guava fruit at different temperatures. The degraded pesticides were extracted and analyzed by High-performance liquid chromatography (HPLC). The HPLC chromatograms verified that significant dissipation of pesticides took place when these were exposed to 9 shocks at 37 °C, which proved the efficiency of this degradation method. More than 50% of the total spray of both pesticides was dissipated. Thus, modulated electrical flux-triggered degradation is one of the effective methods for pesticide degradation.

Establishment of a human induced pluripotent stem cell derived alveolar organoid for toxicity assessment

Alveolar epithelial cells (AECs) are vulnerable to injury, which can result in epithelial hyperplasia, apoptosis, and chronic inflammation. In this study, we developed human induced pluripotent stem cell (hiPS) cell-derived AECs (iAECs) and the iAECs based organoids (AOs) for testing AEC toxicity after chemical exposure. HiPS cells were cultured for 14 days with differentiation medium corresponding to each step, and the iAECs-based AOs were maintained for another 14 days. SFTPC and AQP5 were expressed in the AOs, and mRNA levels of SOX9, NKX2.1, GATA6, HOPX, and ID2 were increased. The AOs were exposed for 24 h to nine chemical substances, and IC₅₀ values of the nine chemicals were determined using MTT assay. When the correlations between iAECs 2D culture and AOs 3D culture were calculated using Pearson's correlation coefficient r value, the nine chemicals that caused a significant decrease of cell viability in 3D culture were found to be highly correlated in 2D culture. The cytotoxicity and nitric oxide release in AO cultured with macrophages were then investigated. When AOs with macrophages were exposed to sodium chromate for 24 h, the IC₅₀ value and nitric oxide production were higher than when the AOs were exposed alone. Taken together, the AO-based 3D culture system provides a useful platform for understanding biological characteristics of AECs and modeling chemical exposures.

Hydrocinnamic Acid and Perillyl Alcohol Potentiate the Action of Antibiotics against Escherichia coli

The treatment of bacterial infections has been troubled by the increased resistance to antibiotics, instigating the search for new antimicrobial therapies. Phytochemicals have demonstrated broad-spectrum and effective antibacterial effects as well as antibiotic resistance-modifying activity. In this study, perillyl alcohol and hydrocinnamic acid were characterized for their antimicrobial action against Escherichia coli. Furthermore, dual and triple combinations of these molecules with the antibiotics chloramphenicol and amoxicillin were investigated for the first time. Perillyl alcohol had a minimum inhibitory concentration (MIC) of 256 µg/mL and a minimum bactericidal concentration (MBC) of 512 µg/mL. Hydrocinnamic acid had a MIC of 2048 µg/mL and an MBC > 2048 µg/mL. Checkerboard and time-kill assays demonstrated synergism or additive effects for the dual combinations chloramphenicol/perillyl alcohol, chloramphenicol/hydrocinnamic acid, and amoxicillin/hydrocinnamic acid at low concentrations of both molecules. Combenefit analysis showed synergism for various concentrations of amoxicillin with each phytochemical. Combinations of chloramphenicol with perillyl alcohol and hydrocinnamic acid revealed synergism mainly at low concentrations of antibiotics (up to 2 μg/mL of chloramphenicol with perillyl alcohol; 0.5 μg/mL of chloramphenicol with hydrocinnamic acid). The results highlight the potential of combinatorial therapies for microbial growth control, where phytochemicals can play an important role as potentiators or resistance-modifying agents.

Polyethyleneglycol-Betulinic Acid (PEG-BA) Polymer-Drug Conjugate Induces Apoptosis and Antioxidation in a Biological Model of Pancreatic Cancer

Pancreatic cancer (PC) is one of the most aggressive solid malignancies with poor treatment response and low survival rates. Herbal medicines such as betulinic acid (BA) have shown potential in treating various solid tumours, but with limitations that can be circumvented by polymer-drug conjugation. Polyethylene glycol-BA (PEG-BA) polymer-drug conjugate has previously shown selective anticancer activity against PC cells. Here, we elucidate the mechanism of cell death and the cell death pathway, anti-inflammatory and antioxidant activities of PEG-BA. PEG-BA induced apoptotic cell death by arresting MIA-PaCa-2 cells in the Sub-G1 phase of the cell cycle compared with BA and untreated cells (39.50 ± 5.32% > 19.63 ± 4.49% > 4.57 ± 0.82%). NFκB/p65 protein expression was moderately increased by PEG-BA (2.70 vs. 3.09 ± 0.42 ng/mL; p = 0.1521). However, significant (p < 0.05) overexpression of the proapoptotic genes TNF (23.72 ± 1.03) and CASPASE 3 (12,059.98 ± 1.74) compared with untreated cells was notable. The antioxidant potential of PEG-BA was greater (IC50 = 15.59 ± 0.64 µM) compared with ascorbic acid (25.58 ± 0.44 µM) and BA-only (>100 µM) and further confirmed with the improved reduction of hydroperoxide levels compared with BA-only (518.80 ± 25.53 µM vs. 542.43 ± 9.70 µM). In conclusion, PEG-BA activated both the intrinsic and extrinsic pathways of apoptosis and improved antioxidant activities in PC cells, suggesting enhanced anticancer activity upon conjugation.

A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease with complex pathogenesis, high mortality, and poor prognosis. Cuproptosis is a new type of programmed cell death triggered by copper accumulation that may play an important role in cancer. LncRNAs are becoming valuable prognostic factors in cancer patients. The effect of cuproptosis-related lncRNAs (CRlncRNAs) on LUAD has not been clarified. Based on the Cancer Genome Atlas database, CRlncRNAs were screened by co-expression analysis of cuproptosis- related genes and lncRNAs. Using CRlncRNAs, Cox and LASSO regression analyses constructed a risk prognostic model. The predictive efficacy of the model was assessed and validated using survival analysis, receiver operating characteristic curve, univariate and multifactor Cox regression analysis, and principal component analysis. A nomogram was constructed and calibration curves were applied to enhance the predictive efficacy of the model. Tumor Mutational Burden analysis and chemotherapeutic drug sensitivity prediction were performed to assess the clinical feasibility of the risk model. The novel prognostic signature consisted of 5 potentially high-risk CRlncRNAs, MAP3K20-AS1, CRIM1-DT, AC006213.3, AC008035.1, and NR2F2-AS1, and 5 potentially protective CRlncRNAs, AC090948.1, AL356481.1, AC011477.2, AL031600.2, and AC026355.2, which had accurate and robust predictive power for LUAD patients. Collectively, the novel prognostic signature constructed based on CRlncRNAs can effectively assess and predict the prognosis of patients and provide a new perspective for the diagnosis and treatment of LUAD.

The anti‐cancer effect of chitosan/resveratrol polymeric nanocomplex against triple‐negative breast cancer; an in vitro assessment

Herein, the authors synthesised chitosan nanoparticles (Cs NPs) as a resveratrol (RSV) carrier and evaluated their efficacy in stimulating apoptosis in MDA-MB 231 cells. Blank (Cs NPs) and RSV- Cs NPs (RSV-Cs NPs) were synthesised via ionic gelation and characterised by using fourier-transform infrared spectroscopy (FTIR), Scanning electron microscope, dynamic light scattering/Zeta potential and RSV release. MDA-MB 231 cells were treated with RSV, Cs NPs and RSV-Cs NPs (24, 48, and 72 h), followed by the 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide assay. Cell toxicity was evaluated using lactate dehydrogenase assay, and real-time polymerase chain reaction was performed to explore apoptosis induction. FTIR spectra confirmed the NPs via the formation of cross-linking bonds. Cs and RSV-Cs NPs sizes were about 75 and 198 nm with 14 and 24 mV zeta potentials. The RSV entrapment efficiency was 52.34 ± 0.16%, with an early rapid release followed by a sustained manner. Cs and RSV-Cs NPs inhibited cell proliferation at lower concentrations and IC50 values. RSV-Cs NPs had the most cytotoxic effect and stimulated intrinsic apoptotic pathway, indicated by increased Bcl-2-associated x (BAX), BAX/Bcl-2 ratio, P53 expressions, reduced Bcl-2 and upregulated caspases 3, 8 and 9. RSV-Cs NPs have a great potential to suppress invasive breast cancer cell proliferation by targeting mitochondrial metabolism and inducing the intrinsic apoptotic pathway.

Photodynamic inactivation of multidrug-resistant bacteria in wastewater effluent using green phytochemicals as a natural photosensitizer

The control of multidrug-resistant bacteria (MDRB) is a great challenge in the 21st century. Photodynamic treatment (PDT) is one of the promising approaches to control MDRB. In the process, powerful oxidants such as reactive oxygen species (ROS) are produced, which cause cytotoxic damage and cell death of bacteria. This study examined a new and environment-friendly strategy for the photodynamic inactivation of two MDRB (Escherichia coli and Staphylococcus aureus) and total coliform (TC) in wastewater effluent using two phytochemicals, pyrogallol (PGL) and terpinolene (TPN), along with white and blue light-emitting diode (LED) light. Fourier-transform infrared spectroscopy (FTIR) of the phytochemicals confirmed the presence of different phenolic and aromatic compounds, which can enhance the generation of ROS alongside inactivating the bacterial cells. In the PDT process, white LED light was more active in controlling MDRB than blue LED light. After 80 min irradiation with white LED light (17 mW/cm²), the MDRB bacteria were eradicated completely at a minimum inhibitory concentration (MIC) dose (0.156 mg/mL for E. coli and 0.078 mg/mL for S. aureus) of PGL. In addition, light intensity was an important parameter in photodynamic disinfection. The TC in the secondary effluent was inactivated completely by both phytochemicals after 60 min of exposure to white LED light with an intensity of 80 mW/cm². The photosensitizing activity of phytochemicals was analyzed by a bactericidal and imidazole-RNO assay. These assays showed that PGL contributed to the generation of •OH radicals, whereas TPN produced ¹O₂ in the PDT process. Transmission electron microscopy (TEM) confirmed bacterial cell disruption after treatment. Overall, PDT using the phytochemicals as PS is a sustainable approach to control the MDRB and TC in wastewater successfully.

StackPR is a new computational approach for large-scale identification of progesterone receptor antagonists using the stacking strategy

Progesterone receptors (PRs) are implicated in various cancers since their presence/absence can determine clinical outcomes. The overstimulation of progesterone can facilitate oncogenesis and thus, its modulation through PR inhibition is urgently needed. To address this issue, a novel stacked ensemble learning approach (termed StackPR) is presented for fast, accurate, and large-scale identification of PR antagonists using only SMILES notation without the need for 3D structural information. We employed six popular machine learning (ML) algorithms (i.e., logistic regression, partial least squares, k-nearest neighbor, support vector machine, extremely randomized trees, and random forest) coupled with twelve conventional molecular descriptors to create 72 baseline models. Then, a genetic algorithm in conjunction with the self-assessment-report approach was utilized to determine m out of the 72 baseline models as means of developing the final meta-predictor using the stacking strategy and tenfold cross-validation test. Experimental results on the independent test dataset show that StackPR achieved impressive predictive performance with an accuracy of 0.966 and Matthew's coefficient correlation of 0.925. In addition, analysis based on the SHapley Additive exPlanation algorithm and molecular docking indicates that aliphatic hydrocarbons and nitrogen-containing substructures were the most important features for having PR antagonist activity. Finally, we implemented an online webserver using StackPR, which is freely accessible at http://pmlabstack.pythonanywhere.com/StackPR . StackPR is anticipated to be a powerful computational tool for the large-scale identification of unknown PR antagonist candidates for follow-up experimental validation.

Proteochemometric Method for pIC50 Prediction of Flaviviridae

Viruses remain an area of concern despite constant development of antiviral drugs and therapies. One of the contributors is the Flaviviridae family of viruses causing diseases that need attention. Among other anitviral methods, antiviral peptides are being studied as viable candidates. Although antiviral peptides (AVPs) are emerging as potential therapeutics, it is important to assess the efficacy of a given peptide in terms of its bioactivity. Experimental identification of the bioactivity of each potential peptide is an expensive and time consuming task. Computational methods like proteochemometric modeling (PCM) is a promising method for prediction of bioactivity (pIC50) based on peptide and target sequence pair. In this study, we propose a prediction of pIC50 of AVP against the Flaviviridae family that may help make the decision to choose a peptide with desired efficacy. The peptides data was collected from a public database and target sequences were manually curated from literature. Features are calculated using peptide and target sequence PCM descriptors which consist of individual and cross-term features of peptide and respective target. The resultant R 2 and MAPE values are 0.85 and 8.44%, respectively, for prediction of pIC50 value of AVPs.

Effect of Cationic Groups on the Selectivity of Ternary Antimicrobial Polymers

Antimicrobial polymers (AMPs) have emerged as a promising approach to combat multidrug-resistant pathogens. Developed from binary polymers, which contain cationic and hydrophobic groups, ternary polymers are enhanced by adding neutral hydrophilic monomers to improve their biocompatibility. Cationic groups have attracted significant attention owing to their pivotal role in AMPs. Although many studies have investigated the effect of cationic groups on antimicrobial activity of binary AMPs, there is a lack of comprehensive and systematic evaluation for ternary AMPs. Therefore, a library of 31 statistical amphiphilic ternary polymers containing different cationic groups, including primary amine, guanidine and sulfonium groups was prepared to investigate the impact of cationic groups on antimicrobial activity and biocompatibility. We show that the cationic balance appears to be a critical factor influencing polymers' antibacterial activity and selectivity. Our results reveal that the polymers that have the ratio of the cationic groups ranging between 50-60%, coupled with a cationic/hydrophobic ratio in the range of [1.4-2] and an appropriate neutral hydrophilic/hydrophobic balance, exhibited the highest selectivity toward mammalian cells. Furthermore, selectivity can be improved with suitable cationic moieties and good neutral hydrophilic candidates. In the present study, a lysine-mimicking monomer and PEG chain were the best choices for cationic and hydrophilic sources to develop the most selective AMPs, displaying an impressive selectivity for HC₅₀ and IC₅₀ greater than 83 and 21, respectively. This study elucidates a structure-property-performance relationship for ternary AMPs, which contributes to the development of AMPs capable of selectively targeting gram-negative pathogens. This article is protected by copyright. All rights reserved.

Development of a Novel Sphingolipid Signaling Pathway-Related Risk Assessment Model to Predict Prognosis in Kidney Renal Clear Cell Carcinoma

This study aimed to explore underlying mechanisms by which sphingolipid-related genes play a role in kidney renal clear cell carcinoma (KIRC) and construct a new prognosis-related risk model. We used a variety of bioinformatics methods and databases to complete our exploration. Based on the TCGA database, we used multiple R-based extension packages for data transformation, processing, and statistical analyses. First, on analyzing the CNV, SNV, and mRNA expression of 29 sphingolipid-related genes in various types of cancers, we found that the vast majority were protective in KIRC. Subsequently, we performed cluster analysis of patients with KIRC using sphingolipid-related genes and successfully classified them into the following three clusters with significant prognostic differences: Cluster 1, Cluster 2, and Cluster 3. We performed differential analyses of transcription factor activity, drug sensitivity, immune cell infiltration, and classical oncogenes to elucidate the unique roles of sphingolipid-related genes in cancer, especially KIRC, and provide a reference for clinical treatment. After analyzing the risk rates of sphingolipid-related genes in KIRC, we successfully established a risk model composed of seven genes using LASSO regression analysis, including SPHK1, CERS5, PLPP1, SGMS1, SGMS2, SERINC1, and KDSR. Previous studies have suggested that these genes play important biological roles in sphingolipid metabolism. ROC curve analysis results showed that the risk model provided good prediction accuracy. Based on this risk model, we successfully classified patients with KIRC into high- and low-risk groups with significant prognostic differences. In addition, we performed correlation analyses combined with clinicopathological data and found a significant correlation between the risk model and patient’s M, T, stage, grade, and fustat. Finally, we developed a nomogram that predicted the 5-, 7-, and 10-year survival in patients with KIRC. The model we constructed had strong predictive ability. In conclusion, we believe that this study provides valuable data and clues for future studies on sphingolipid-related genes in KIRC.

A Novel and Robust Prognostic Model for Hepatocellular Carcinoma Based on Enhancer RNAs-Regulated Genes

Evidence has demonstrated that enhancer RNAs (eRNAs) play a vital role in the progression and prognosis of cancers, but few studies have focused on the prognostic ability of eRNA-regulated genes (eRGs) for hepatocellular carcinoma (HCC). Using gene expression profiles of HCC patients from the TCGA-LIHC and eRNA expression profiles from the enhancer RNA in cancers (eRic) data portal, we developed a novel and robust prognostic signature composed of 10 eRGs based on Lasso-penalized Cox regression analysis. According to the signature, HCC patients were stratified into high- and low-risk groups, which have been shown to have significant differences in tumor immune microenvironment, immune checkpoints, HLA-related genes, DNA damage repair-related genes, Gene-set variation analysis (GSVA), and the lower half-maximal inhibitory concentration (IC50) of Sorafenib. The prognostic nomogram combining the signature, age, and TNM stage had good predictive ability in the training set (TCGA-LIHC) with the concordance index (C-index) of 0.73 and the AUCs for 1-, 3-, and 5-year OS of 0.82, 0.77, 0.74, respectively. In external validation set (GSE14520), the nomogram also performed well with the C-index of 0.71 and the AUCs for 1-, 3-, and 5-year OS of 0.74, 0.77, 0.74, respectively. In addition, an important eRG (AKR1C3) was validated using two HCC cell lines (Huh7 and MHCC-LM3) in vitro, and the results demonstrated the overexpression of AKR1C3 is related to cell proliferation, migration, and invasion in HCC. Altogether, our eRGs signature and nomogram can predict prognosis accurately and conveniently, facilitate individualized treatment, and improve prognosis for HCC patients.