Despite the considerable decline of cervical cancer incidence in developed countries, the disease remains a public health problem in low-income and middle-income countries due to the low popularity of human papillomavirus vaccination and cervical cancer screening. Mainly treated with radiotherapy, the number of recurrences linked to radioresistance increases in women suffering from this disease and constitutes major obstacle. Here, we perform a combined proteomic and phosphoproteomic profiling of HeLa cervical cancer cells after in vitro treatment with X-rays and carbon ions. We observed differential and extensive alterations at the proteins and phosphoproteins levels. In total, we observed 96 and 102 differentially expressed proteins (DEPs) after X-rays and C-ions irradiation, respectively. For phosphoproteins, our results revealed 21 and 41 DEPs in response to C-ions and X-rays ionizing radiation respectively. Furthermore, our study revealed several mechanisms significantly activated by cells in response to ionizing radiation, potentially related to cancer radioresistance, including sister chromatid segregation, rRNA processing, ribosomal large subunit biogenesis, positive regulation of phagocytosis, engulfment, peptidase regulatory activity and negative regulation of ERK1/2 cascade. We also identified three proteins IPM3, DUSP3 and COQ7, oppositely expressed across the C-ions and X-rays groups while MX2 phosphorylation was downregulated in both radiation qualities. Finally, our study revealed a specific kinase signature, associated with Hela cells radioresistance: CDK5, MTOR and CDK2 kinases were predicted in the group of X-rays irradiation while CDK1, PLK1 SRC and MAPK1 kinases were predicted in the group of C-ions irradiation. Taken together, these findings could help to define new potential pathways and biomarkers to be targeted in the treatment of cervical cancer. Insight Box Statement of Integration, Innovation and Insight In this study, a robust proteomic and phospho-proteomic strategy was developed in order to display HELA cells responses to radiations. Two time points were selected to highlight the early responses of cells, following irradiation with low and high LET. CDK1, SRC, MAPK1 kinases were predicted to be activated in response to carbon ions irradiation, while CDK5, MTOR, ATM kinases were predicted in response to X-rays. Several accessions, playing pivotal role in cell proliferation and resistance, were upregulated in X-rays irradiated cells and down regulated in carbon ions irradiated cells. This study gives an accurate picture of molecular events linked with HELA cells radioresistance and offer potential drug targets for optimization of cervical cancer radiotherapy.

Fetal Bovine Serum (FBS) is one of the most commonly used media supplement for the maintenance of mammalian cell types, yet the expensive costs, ethical concerns, and lot-to-lot variation have provoked a clear need for a serum that is standardized and derived from non-animal sources. Several serum-free formulations have been developed in the past, however they are often cell type specific, contain animal-derived components, and lack long-term culture validation. In this study, we developed a novel animal component-free (ACF) media and investigated its effectiveness on four commonly used mammalian cell lines via long-term (up to 90 days) morphological, transcriptomic, and proliferative analyses. Cells cultured in our ACF medium exhibited comparable cellular morphologies and equal or greater growth rates compared with cells cultured with FBS. Additionally, differentially expressed genes between the FBS-grown and ACF-grown groups were predominantly associated with functions linked to proliferation and cell attachment. While the tested cells were initially derived using conventional methods and include non-human lines, this study demonstrates that our medium supports long-term culture without animal-derived supplements. The findings from this study indicate that this medium is a suitable replacement to FBS-containing medium for several common cell lines. Insight Box Traditional cell culture methods often rely on animal-derived components, which can pose ethical and economic challenges. The use of animal serum in vitro is needed to supply nutrients to cells but raises concerns about animal welfare and introduces variability and contaminants that can negatively affect downstream applications. This study presents a novel animal component-free medium designed to support the growth of adherent cell types, providing a sustainable alternative to serum. Here, we demonstrate long-term cell viability, normal morphology, and differential gene expression patterns indicative of enhanced proliferation and attachment in cells cultured in 2D environments. By addressing the demand for ethical and reproducible cell culture methods, this research aims to contributes to the broader adoption of sustainable practices in biotechnology.

Preeclampsia is a type of pregnancy complication that manifests as hypertension and albuminuria, associated with improper development of blood vessels in the placenta. However, the precise cause of preeclampsia is not well defined. Ferroptosis is a type of cell death involving abnormal accumulation of iron and lipid reactive oxygen species (ROS) in cells. Accumulating evidence indicates that ferroptosis may contribute to preeclampsia development, but the underlying mechanism remains unclear. Several ubiquitin-specific proteases (USPs) have been reported to repress ferroptosis, but whether other USPs regulate ferroptosis and preeclampsia development remains elusive. Here we identified USP46 as a potent regulator of erastin-induced ferroptosis in BeWo trophoblasts, which serve as an in vitro model to study preeclampsia. We found that overexpression of USP46 promoted erastin-induced ferroptosis in BeWo cells, while knockdown of USP46 led to resistance to erastin-induced ferroptosis. This resistance could be reversed by excessive cold-inducible RNA-binding protein (CIRBP). Immunoprecipitation experiments showed that USP46 interacts with CIRBP to inhibit its ubiquitination. These findings suggest that USP46 sensitizes BeWo cells to ferroptosis by stabilizing CIRBP. Insight Box Preeclampsia is a severe pregnancy complication with an unknown pathogenesis. Studies have shown that several ubiquitin-specific proteases (USPs) can inhibit ferroptosis and affect the occurrence of preeclampsia. However, given the numerous genes in the USP family, it remains unclear whether other USPs regulate ferroptosis and the development of preeclampsia. In this study, we identified USP46 as a strong regulator of ferroptosis in BeWo cells. USP46 interacts with CIRBP to reduce its ubiquitination and stabilize its expression, thereby promoting ferroptosis. This study reveals the key role of USP46 in regulating ferroptosis and provides a new target for etiological research and treatment of preeclampsia.

Hirschsprung's disease (HSCR) is a congenital intestinal disease characterized by the loss of enteric neural crest cells. BMI1 is demonstrated to be downregulated in HSCR tissues compared to normal intestinal tissues, but it is still unclear whether BMI1 is involved in the pathogenesis of HSCR. Here, we found that BMI1 expression was downregulated in HSCR-stenosed segments (HSCR-S) cases compared with HSCR-dilated segments (HSCR-D) or control cases. Pharmacological inhibition of BMI1 using PTC-209 significantly attenuated cell proliferation, migration, and cell cycle progression in both SH-SY5Y neuroblastoma cells and primary enteric neural crest cells (ENCCs), whereas BMI1 overexpression produced the opposite effects. BMI1 binds to the promoter region of the Wnt signaling pathway inhibitor Axin2 and suppressed its transcription by increasing H2AK119ub and reducing H3K4me3 at the Axin2 promoter, thereby hindering Wnt signaling. Moreover, overexpression of Axin2 decreased cell proliferation, migration and cell cycle progression. Treatment with HY-122816 (a Wnt signaling pathway agonist) reversed the inhibitory effects of PTC-209 on cell proliferation, migration, and cell cycle progression. Additionally, BMI1 upregulation promoted ganglion cell proliferation in Ednrb-/- mice. In conclusion: BMI1 facilitated Wnt signaling by mediating epigenetic silencing of Axin2, thereby promoting cell proliferation and migration in HSCR. Clinically, BMI1 expression was downregulated in HSCR-S cases compared with HSCR-D or control cases. Moreover, BMI1 was shown for the first time to promote cell proliferation, migration, and cell cycle progression in ENCCs. Molecular level probing revealed that BMI1 binds to the promoter region of Axin2, an inhibitor of the Wnt signaling pathway, and inhibited Axin2 transcription by increasing H2AK119ub and decreasing H3K4me3 in the Axin2 promoter, thereby hindering Wnt signaling. This study revealed that the BMI1/Axin2/Wnt axis may play an important role in the pathogenesis of HSCR.

Neurodegenerative disorders are characterised by progressive damage to neurons that leads to cognitive impairment and motor dysfunction. Current treatment options focus only on symptom management and palliative care, without addressing their root cause. In our previous study, we reported the upregulation of the CXC motif chemokine receptor 4 (CXCR4), in Alzheimer's disease (ad) and Parkinson's disease (PD). We reached this conclusion by analysing gene expression patterns of ad and PD patients, compared to healthy individuals of similar age. We used RNA sequencing data from Gene Expression Omnibus to carry out this analysis. Herein, we aim to identify natural compounds that have potential inhibitory activity against CXCR4 through cheminformatics-guided machine learning, to aid drug discovery for neurodegenerative disorders, especially ad and PD. Natural compounds are gaining prominence in the treatment of neurodegenerative disorders due to their biocompatibility and potential neuroprotective properties, including their ability to modulate CXCR4 expression. Recent advances in artificial intelligence (AI) and machine learning (ML) algorithms have opened new avenues for drug discovery research across various therapeutic areas, including neurodegenerative disorders. We aim to produce an ML model using cheminformatics-guided machine learning algorithms using data of compounds with known CXCR4 activity, retrieved from the Binding Database, to analyse various physicochemical attributes of natural compounds obtained from the COCONUT Database and predict their inhibitory activity against CXCR4. Insight Box This work extends our previous study published in Integrative Biology (DOI: 10.1093/intbio/zyad012). We aim to demonstrate the effectiveness of AI and ML in identifying potential treatment options for Alzheimer's and Parkinson's diseases. By analysing vast amounts of data and identifying patterns that may not be apparent to human researchers, AI-powered systems can provide valuable insight into potential treatment options that may have been overlooked through traditional research methods. Our study underscores the significance of interdisciplinary collaboration between computational and experimental scientists in drug discovery and in developing a robust pipeline to identify potential leads for drug development.

Angiogenesis is tightly regulated by the mechanical and biochemical cues of the microenvironment. To investigate the mechanobiological regulation of endothelial cells, we developed a 3D in vitro bioreactor that enables precise, leak-free application of hydrostatic pressure to endothelialized collagen I channels. Using this platform, we seeded primary human umbilical vein endothelial cells and primary human aortic endothelial cells at optimized densities and achieved reproducible channel endothelialization. We demonstrate that sufficient protein and RNA can be extracted from single channels, enabling downstream analysis such as Western blotting and RT-qPCR. Immunofluorescent staining revealed nuclear localization of YAP in angiogenic sprouts, a feature previously observed only in 2D cultures. This confirms this model ability to recapitulate pressure-induced YAP activation also in 3D. Our findings support the feasibility of this platform for mechanobiological studies and highlight its potential for investigating angiogenic signalling under controlled pressure conditions. Insight Box A reusable 3D bioreactor enables controlled hydrostatic pressure on endothelial cells within collagen I channels. This model reveals pressure-induced YAP nuclear localization in angiogenic sprouts and supports molecular analysis from single channels, bridging mechanobiology with in vitro vascular modelling.

Colorectal cancer is a highly prevalent malignant tumor of the digestive tract worldwide. Immunotherapy has emerged as a critical therapeutic approach for CRC patients. We observed that KCTD10 expression is significantly downregulated in colorectal cancer tissues compared to normal tissues, and patients with higher KCTD10 expression exhibited prolonged survival. To investigate its functional role, we established stable KCTD10-overexpressing CT26 and SW480 colorectal cancer cell lines. Both in vitro and in vivo experiments demonstrated that KCTD10 overexpression suppresses colorectal cancer progression and inhibits the EMT process. Notably, KCTD10 overexpression upregulated PD-L1 expression and synergistically enhanced the therapeutic efficacy of anti-PD-1 treatment. Our findings reveal that KCTD10 functions as a tumor suppressor in colorectal cancer pathogenesis. Mechanistically, KCTD10 potentiates the antitumor efficacy of anti-PD-1 immunotherapy by upregulating PD-L1 expression, thereby proposing a novel therapeutic target and suggesting a promising combination strategy for CRC treatment. Insight box KCTD10 can inhibit the development of colorectal cancer and the EMT process. And the over-expression of KCTD10 increased the expression of PD-L1, improved the efficacy of PD-1 treatment.

Small scale molecular network patterns and motifs are crucial for systems level understanding of cellular information transduction. Using randomizations, we statistically explored, previously overlooked basic patterns of mutually acting pairs, i.e. mutually positive (PP) or negative (NN) and positive-negative (PN) pairs, in two comprehensive and distinct large-scale molecular networks from literature; the human protein signaling network (PSN) and the human gene regulatory network (GRN). Only the positive and negative signs of all interacting pairs were randomized, while the gene pairs and the number of positive and negative signs in the original network were kept constant. While the numbers of NN and PN pairs were significantly higher, the number of PP pairs was significantly lower than randomly expected values. Genes participating in mutual pairs were more connected than other genes. NN genes were more connected than PP and PN in GRN for all types of degree values, including in, out, positive or negative connections, but less connected for in-degree and more connected for out-degree values in PSN. They also had significantly high number of intersections with each other and PN pairs than randomly expected values, indicating potential cooperative mechanisms. The three mutual interaction designs we examined had distinct RNA and protein expression correlation characteristics. NN protein pairs were uniquely over-represented across normal tissue samples, whose negative correlations were lost across cancer tissue samples. PP and PN pairs showed non-random positive RNA or protein expression correlation across normal or cancer tissue samples. Moreover, we developed an online tool, i.e. MGPNet, for further user specific analysis of mutual gene pairs. We identified SNCA with significantly enriched negatively correlated NN pairs. Unique non-random characteristics of mutual gene pairs identified in two different comprehensive molecular networks could provide valuable information for a better comparative understanding of molecular design principles between normal and cancer states. Insight Box/Paragraph Statement: This study provides a systems-level perspective on cellular information transduction by analyzing mutually acting pairs of genes. By examining mutually positive (PP), mutually negative (NN), and positive-negative (PN) pairs in the human protein signaling network (PSN) and the human gene regulatory network (GRN), we uncover significant variations in their connectivity and expression correlation. Our findings highlight the unique features of NN pairs across normal and cancer tissues and offer insights into molecular design principles. The development of the MGPNet tool further enhances user-specific analyses, enabling a deeper understanding of gene pair mechanisms and their potential cooperative roles in cellular processes.

Annexin A2 (ANXA2) is a Annexin family proteins member that plays a role in regulating cell growth and signal transduction pathways. However, its role in hepatocellular carcinoma (HCC) remains incompletely elucidated. We used bioinformatics methods to analyze the expression, diagnosis and prognostic value of ANXA2 in HCC using data from the TCGA, GTEx, GEO, HCCDB, HPA databases. Next, we predicted ANXA2-associated proteins and constructed a protein-protein interaction network via the STRING database. Furthermore, we obtained the biological processes associated with ANXA2 in HCC through GO, KEGG and GSEA enrichment analysis. Finally, CCK8, wound healing, and transwell were used to verify these biological processes in HCCLM3 cell lines. Insight box ANXA2 is highly expressed in a variety of tumors, with significantly higher levels in HCC than in normal tissues. ANXA2 expression is positively correlated with T stage, histologic grade, residual tumor, pathologic stage, tumor status and fibrosis ishak score in HCC, and high ANXA2 expression suggests a poorer prognosis. Additionally, ANXA2 has diagnostic value in HCC. Its expression is closely associated with S100A family proteins and immune infiltration. Enrichment analysis showed that high ANXA2 expression activates biological processes such as epithelial-mesenchymal transition (EMT), NF-κB and Wnt signaling pathways. The results of cell experiment were consistent with bioinformatics analysis. Our study explored the role of ANXA2 in the occurrence and development of HCC, which may provide reference for the treatment of HCC.

Metastasis is one of the leading factors of cancer-related deaths worldwide. New potential targets and treatment strategies are needed to extend survival and enhance the quality of life for these patients. We performed an in-depth bioinformatics analysis to identify potential genes and associated potential therapeutic compounds for metastasis of prostate adenocarcinoma. The differentially expressed genes (DEGs) were first identified using four datasets (GSE8511), (GSE3325), (GSE27616) and (GSE6919) present in the Gene Expression Omnibus (GEO) database and analyzed using the GEO2R. WGCNA was performed to find a significant gene cluster. Network analysis was performed using MCODE and Cytohubba plugins of Cytoscape to select hub genes. Moreover, expression validation of key genes was carried out using the TCGA dataset. Functional annotation and pathway enrichment analyses were conducted for validation, while survival analysis was applied to assess potential therapeutic effects. DEGs retrieved from the GEO were submitted to the Connectivity Map database to identify potentially related compounds. Molecular docking, ADMET analysis and drug-likeness properties, MD simulations and MM-GBSA analysis were performed to screen for the best potential drugs. We identified three compounds-Prunetin, Ofloxacin, and ALW-II-49-7 that may help extend disease-free survival in patients with tumor metastasis. Additionally, ACTA2, MYLK, and CNN1 were recognized as potential therapeutic targets for these compounds. These drugs' potential effectiveness and binding efficiency were screened using induced fit molecular docking followed by 100 ns MD-based Simulations and MM-GBSA analysis. However, further in vitro and in vivo studies are needed to confirm these findings. Insight box This study integrates microarray gene expression profiling with bioinformatics tools to identify differentially expressed genes (DEGs) and co-expression networks using WGCNA. Network analysis in Cytoscape was used to screen hub genes, and the Connectivity Map (cMAP) database was searched for potential candidate drugs. Binding efficiency of repurposed drugs was evaluated using molecular docking, molecular dynamics (MD) simulations, and MM-GBSA analysis. Our findings provide the potential therapeutic drugs and targets of prostate adenocarcinoma metastasis with possibilities for follow-up in vitro and in vivo validation.

Klebsiella pneumoniae (K. pneumoniae) has emerged as a prominent multidrug-resistant pathogen in healthcare settings and is ranked among the top three critical priority pathogens by the World Health Organization. Owing to the surge in antibiotic resistance and resulting treatment failures, there is an urgent need for alternative therapeutic approaches. N-succinyl-L, L-diaminopimelic acid desuccinylase (DapE), a crucial metalloenzyme in the lysine biosynthesis pathway in K. pneumoniae, is essential for protein synthesis and the cross-linking of the bacterial peptidoglycan cell wall. The remarkable conservation of DapE across diverse bacterial species makes it a promising target for combating drug resistance. In this study, 400 analogues were screened using virtual screening to evaluate their pharmacokinetic, toxicological, and bioactive properties. Fifty-two compounds meeting these criteria were selected for molecular docking analysis. Among these, five top-ranking compounds were identified based on docking scores, and two, ZINC262925003 (-7.1 kcal/mol) and ZINC237355153 (-7.0 kcal/mol), were selected due to their strong catalytic zinc-binding interactions at the active site. Extensive validation through 250 ns molecular dynamics simulation and Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) analysis revealed high structural stability and robust binding interactions for these complexes. These findings highlight their potential as therapeutic agents against DapE, necessitating further validation through in vitro and in vivo studies. Insight Box The study employs an integrated computational approach for identifying potential zinc-binding inhibitors against Klebsiella pneumoniae's DapE (KpDapE). In recent times, antimicrobial resistance has become a global challenge in treating bacterial infections. DapE, a metalloenzyme in the lysine biosynthesis pathway in K. pneumoniae, is essential for protein synthesis and the cross-linking of the bacterial peptidoglycan cell wall. DapE is a promising drug target to develop a new class of drugs. In this study, 400 L-Captopril analogues were screened, identifying two candidates as potent leads. Molecular docking and dynamics simulations revealed that ZINC262925003 and ZINC237355153 had significant binding affinity and stable interactions with KpDapE, supported by RMSD, RMSF, and binding-free energy analyses. This suggests that both these compounds could be potent inhibitors for KpDapE.

Ferroptosis plays a crucial role in inhibiting tumor progression. La Ribonucleoprotein 4B (LARP4B) is known to function as a pro-oncogenic factor in digestive tumors, but its specific role and potential mechanisms remain unclear in pancreatic cancer (PC). In this study, we found that LARP4B was upregulated in PC tissues and cells. Overexpression of LARP4B promoted PC cell proliferation and invasion, while knockdown of LARP4B inhibited PC cell proliferation and invasion. Furthermore, knockdown of LARP4B was associated with intracellular iron overload, increased levels of reactive oxygen species (ROS) and malondialdehyde (MDA), and decreased glutathione (GSH) content and superoxide dismutase (SOD) activity in PC cells. Mechanistically, LARP4B binds to mRNA of with-no-lysine kinase 1 (WNK1) and promotes its stability, and WNK1 competitively binds to the partial Kelch domain of Kelch-like ECH-associated protein 1 (Keap1) to promote the nuclear translocation of nuclear factor erythroid-2-related factor 2 (NRF2), thereby activating the NRF2/GCH1/BH4 pathway and inhibiting ferroptosis in PC cells. ML385, a NRF2 nuclear translocation inhibitor, partially rescued the inhibitory effect of WNK1 on ferroptosis in PC cells. Finally, in vivo experiments showed that knockdown of LARP4B suppressed tumor growth in PC xenograft mice. In conclusion, our study demonstrated that LARP4B inhibited ferroptosis by activating the WNK1-mediated NRF2/GCH1/BH4 pathway, thereby promoting PC progression. Insight Box This work provides evidence for LARP4B as a pro-oncogenic factor in pancreatic cancer, while also offers new insights into the further understanding of the biological functions of LARP4B and the oncological mechanisms of pancreatic cancer. We found that LARP4B is upregulated in PC tissues and cells, and its overexpression promotes the proliferation and invasion of PC cells. Additionally, we discovered that LARP4B binds to WNK1 mRNA and enhances its stability. WNK1 competitively binds to Keap1 to facilitate NRF2 nuclear translocation, thereby activating the NRF2/GCH1/BH4 pathway and inhibiting ferroptosis in PC cells. These findings provide significant insights for further research on PC and the development of therapeutic strategies.

Chronic obstructive pulmonary disease (COPD), multiple sclerosis (MS), and lung cancer are linked by shared inflammatory pathways and immune dysregulation. miRNAs regulate these processes by influencing gene expression, yet their roles in the molecular mechanisms across neurological and respiratory systems are not fully understood.

Vascular smooth muscle cells (VSMCs) play a crucial role in vascular growth and remodeling by adapting their phenotype in response to biomechanical cues. The Notch signaling pathway, known for its sensitivity to mechanical forces, is a regulator of strain-induced phenotypic plasticity of VSMCs. However, the impact of the intricate mechanical environment within the vessel wall on Notch signaling and VSMCs is not completely elucidated. In this study, we investigated the influence of strain anisotropy, which is important for understanding (patho)physiological mechanical conditions, on mechanosensitive Notch signaling and subsequent changes in VSMC phenotype. Using varying amplitudes of cyclic strain in the physiological range, we examined the effects of equibiaxial and uniaxial strain on Notch signaling and phenotypic transitions in synthetic and contractile VSMCs. Additionally, we compared cell responses between equibiaxial and uniaxial loading conditions by analyzing three different deformation characteristics to determine the primary strain measure governing Notch signaling and VSMC phenotype. Our findings reveal that both cyclic equibiaxial and uniaxial strain downregulate Notch signaling and contractile characteristics of VSMCs. Notably, these reductions are most similar for both loading conditions when the maximum principal strain values were compared. Overall, our results suggest that VSMCs respond in a comparable manner to equibiaxial and uniaxial strain, indicating that strain anisotropy may not significantly influence Notch signaling or phenotypic switching of VSMCs. Insight Box:  Vascular smooth muscle cells (VSMCs) adapt their phenotype during vascular growth and remodeling in response to mechanical cues. The Notch signaling pathway, sensitive to mechanical stimuli, regulates this phenotypic plasticity. However, the effect of strain anisotropy, which is important for understanding (patho)physiological mechanical conditions, on Notch signaling and subsequent changes in VSMC phenotype is not clear. Understanding this relationship is crucial to determine how VSMC phenotype, contributing to vascular growth and remodeling, is regulated in physiological and pathological hemodynamic environments. Here, we showed that both equibiaxial and uniaxial strain downregulate Notch signaling components and the contractile properties of VSMCs. Our findings further highlighted the maximum principal strain as the dominant mechanical parameter influencing Notch signaling and VSMC phenotypic changes.

Diabetes coexisting with infections (DCI) significantly increases the risk of severe outcomes and mortality in patients. This study proposes that RPL7P1, an uncharacterized pseudogene, plays a role in the pathogenesis of DCI.

Migration and scratch assays are helpful tools to investigate wound healing and tissue regeneration processes, especially under disease conditions such as diabetes. However, traditional migration (injury-free) assays and scratch (with injury) assays are limited in their control over cellular environments and provide only simplified read-outs of their results. On the other hand, microfluidic-based cell assays offer a distinct advantage in their integration and scalability for multiple modalities and concentrations in a single device. Additionally, in situ stimulation and detection helps to avoid variabilities between individual bioassays. To realize an enhanced, smarter migration assay, we leveraged our multilayered oxygen gradient (1%-16%) to study HaCaT migrations in diabetic conditions with spatial and metabolic read-outs. An analysis of spatial migration over time revealed a new dynamic between hypoxia (at 4.2%-9.1% O2) and hyperglycemia. Furthermore, in situ adenosine triphosphate (ATP) and reactive oxygen species (ROS) responses suggest that this dynamic represents a switch between stationary versus motile modes of metabolism. Thus, low glucose and hypoxia have synergistic effects promoting the migration of cells. These findings illustrate the benefits of spatial microfluidics for modeling complex diseases such as hypoxia and diabetes, where multimodal measurements provide a more deterministic view of the underlying processes.

Colorectal cancer (CRC) is a significant health challenge in the world, with incidence being increasingly reported among the young population. Machine learning, therefore, is revolutionizing care in CRC, including providing advancements in early detection, staging, recurrence prediction, and individualized medicine. Techniques for analysis include support vector machines, random forests, and neural networks, which allow complex analyses of datasets, including genetic profiles and imaging data, with an improvement in diagnostic accuracy and treatment outcomes. Machine learning-driven personalized treatment strategies empower clinicians to tailor therapies to individual patients, optimizing efficacy while reducing side effects. However, integration of Machine learning (ML) in CRC management faces challenges like data quality, validation, and smooth adaptation into clinical workflow. Overcoming these barriers through multi-institutional collaboration and strong validation frameworks will be essential to unlock the full potential of ML. Advancement in research will enable the transformation of CRC care to provide more accurate diagnoses and targeted treatments, ultimately changing patient outcomes. Insight box This review examines the transformative impact of machine learning (ML) in colorectal cancer (CRC) research and care. By integrating multi-omics, radiomics, and clinical data, ML models outperform traditional diagnostic and prognostic methods, enabling precise risk prediction, personalized treatment, and early recurrence detection. The amalgamation of supervised learning, neural networks, and deep learning yields actionable insights that improve patient outcomes and address unmet needs in CRC management. The review also discusses solutions to challenges such as data standardization, ethics, and clinical workflow integration, offering a roadmap for real-world ML adoption. This work highlights the synergy between computational advances and oncology, providing a forward-thinking framework for CRC care.

To develop efficient diagnostic and treatment approaches, gaining an in-depth knowledge of the molecular mechanisms and potential targets causing childhood asthma is of utmost significance.

We screened a random peptide phage display library using Russell's viper venom phospholipase A2 (RV-PLA2) as bait. Sequence information from the resulting set of bio-panned heptapeptides was analyzed and mined to determine likely sites of interaction between two subunits of RV-PLA2 homo dimers and between RV-PLA2 and the γPLA2 inhibitor PIP from Malayopython reticulatus. This was accomplished in part by sequence alignment of the affinity-selected peptides with the sequences of RV-PLA2 and PIP. Because similarity scores calculated from sequence alignments proved inadequate to determine interaction interfaces accurately for RV-PLA2 dimers, we explored the use of amino acid frequency-based interactions scores (SFI/SFIN) for a more accurate prediction of protein-protein interaction sites. Heptamers with elevated SFI(N) scores were compared to interfaces of interaction observed in crystal structures of RV-PLA2 homodimers and to sites of interaction predicted by protein-protein docking between structures of RV-PLA2 and model of PIP. Segments with a high density of protein-protein contacts coincided with heptamer sequences exhibiting SFI and/or SFIN scores significantly above average, in both RV-PLA2 homodimers and in RV-PLA2 γPLI heteromeric structures. Elevated SFI and SFIN scores were associated with peptide function since the heptamers with some of the highest SFI and SFI(N) scores, LPGLPLS, GLPLSLQ and SLQNGLY constitute the known PLA2 inhibitor P-PB.I (LPGLPLSLQNGLY) while KLGRVDI, and WDGVYIR, constitute PIP-17 (LGRVDIHVWDGVYIRGR), IC50 for hsPLA2: 5.3 μM. A graph showing the alignment of maxima between SFI scores and average solvent accessibility (per heptamer) suggests that solvent accessibility is a major driver of both protein-protein interaction and phage selection. Insights We show by computational methods that in sets of small phage-displayed peptides of the same length selected for binding to the same target protein, amino acids contributing to binding at a particular position occur at higher frequencies than in random peptides. This position-specific selection of particular amino acids can be detected in the position-specific amino acid frequency distribution of that set of selected peptides. Therefore, when this position-specific amino acid frequency is mapped back onto a particular amino acid sequence of the same length, the sum of these frequencies can function as a measure of enrichment of selected amino acids.

Integrins are transmembrane receptors that play a crucial role in cell adhesion and signaling by connecting the extracellular environment to the intracellular cytoskeleton. After binding with specific ligands in the extracellular matrix (ECM), integrins undergo conformational changes that transmit signals across the cell membrane. The integrin-mediated bidirectional signaling triggers various cellular responses, such as changes in cell shape, migration and proliferation. Irregular integrin expression and activity are closely linked to tumor initiation, angiogenesis, cell motility, invasion, and metastasis. Thus, understanding the intricate regulatory mechanism is essential for slowing cancer progression and preventing carcinogenesis. Among the four classes of integrins, the arginine-glycine-aspartic acid (RGD)-binding integrins stand out as the most crucial integrin receptor subfamily in cancer and its metastasis. Dysregulation of almost all RGD-binding integrins promotes ECM degradation in ovarian cancer, resulting in ovarian carcinoma progression and resistance to therapy. Preclinical studies have demonstrated that targeting these integrins with therapeutic antibodies and ligands, such as RGD-containing peptides and their derivatives, can enhance the precision of these therapeutic agents in treating ovarian cancer. Therefore, the development of novel therapeutic agents is essential for treating ovarian cancer. This review mainly discusses genes and their importance across different ovarian cancer subtypes, the involvement of RGD motif-containing ECM proteins in integrin-mediated signaling in ovarian carcinoma, ongoing, completed, partially completed, and unsuccessful clinical trials of therapeutic agents, as well as existing limitations and challenges, advancements made so far, potential strategies, and directions for future research in the field. Insight Box Integrin-mediated signaling regulates cell migration, proliferation and differentiation. Dysregulated integrin expression and activity promote tumor growth and dissemination. Thus, a proper understanding of this complex regulatory mechanism is essential to delay cancer progression and prevent carcinogenesis. Notably, integrins binding to RGD motifs play an important role in tumor initiation, evolution, and metastasis. Preclinical studies have demonstrated that therapeutic agents, such as antibodies and small molecules with RGD motifs, target RGD-binding integrins and disrupt their interactions with the ECM, thereby inhibiting ovarian cancer proliferation and migration. Altogether, this review highlights the potential of RGD-binding integrins in providing new insights into the progression and metastasis of ovarian cancer and how these integrins have been utilized to develop effective treatment plans.

Cancer-associated fibroblasts (CAFs)-derived exosomes promote tumor malignancy and confer chemotherapy resistance. However, their mechanistic roles in colorectal cancer (CRC) remain incompletely understood.