Biology subjects

Jalali, P.

Publications and source records attributed to Jalali, P..

3 recordsLinked to original sources

bioRxiv2026

Apidae BeeHavioural response to shape-neutral visual stimuli in natural setup

Floral displays attract pollinators through a finely tuned interplay of colour, pattern, shape, and scent. Yet, the question remains: how do bees respond when these traits are stripped to their simplest form, with only visual cues at play? In this field study, we examined the foraging behaviour of Apis mellifera on artificial flowers differing solely in background colour (white or yellow) and UV patterning, while shape and scent were held constant. Across three summer days, standardized stimuli were placed within a natural meadow, and bee-flower interactions were recorded and analyzed by Bayesian hierarchical models. The results reveal a clear preference for yellow over white backgrounds and prolonged visitation in the presence of ring-shaped UV patterns, whereas full UV coverage acted as a deterrent. These effects, though moderate, were consistently modulated by abiotic covariates, particularly radiation, temperature, and time of day. Negligible inter-individual variation and a substantial share of residual variance further underline the context-dependent complexity of foraging. In sum, our findings demonstrate that visual floral traits, while influential, are interpreted through the dual lens of environmental contingency and the bees inherent cognitive machinery.

animal behavior and cognition↗

bioRxiv2025

Hierarchical Machine Learning Uncovers Topological Signatures of Autophagy Regulation by Oral Bacteria in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) progression has been increasingly linked to dysbiosis of the oral microbiome. We hypothesized that pathogenic versus commensal bacteria differentially rewire host autophagy networks to either promote or inhibit OSCC progression. To test this, we constructed host-bacterium autophagy interactomes from KEGG, STRING, and curated databases, identifying key network hubs (e.g., MAPK1, STAT3) via graph-theoretic metrics. We then applied a hierarchical unsupervised machine learning pipeline, combining two-stage principal component analysis with permutation testing and linear discriminant analysis (LDA), to interrogate differences in network topology. This multi-layer approach revealed a clear separation between pro-cancer (pathogenic) and anti-cancer (commensal) bacterial network signatures, with Fusobacterium nucleatum and Streptococcus mitis emerging as dominant global outliers. Pathogenic taxa activated inflammatory-metabolic autophagy signatures (e.g., NFKB1, MYC, ACACA), whereas commensals stabilized kinase-homeostasis signaling (EGFR, PTEN, HSP90AA1). Permutation testing confirmed that these network differences were highly significant and non-random (p < 0.001). We also derived a Dysbiosis Index that robustly distinguished the pro- versus anti-cancer bacterial cohorts with high predictive power. Collectively, our findings highlight oral microbiota-autophagy network topologies as potential biomarkers of OSCC dysbiosis and as novel therapeutic targets. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/696881v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@13eb27forg.highwire.dtl.DTLVardef@138bccborg.highwire.dtl.DTLVardef@1f2e651org.highwire.dtl.DTLVardef@1eee140_HPS_FORMAT_FIGEXP M_FIG C_FIG Lay summaryHealthy mouth bacteria help cells stay balanced and protected. When harmful bacteria take over, they disrupt cell recycling (autophagy), increase inflammation, and causing cells to become more aggressive, which can promote oral cancer development.

cancer biology↗

bioRxiv2023

Mixed data analysis detected Endocrine Fibroblast Growth Factors (FGF19, FGF21, and FGF23) as Prognostic and Diagnostic Markers of Colorectal Neoplasia and Carcinoma

BackgroundEndocrine fibroblast growth factors (eFGFs) play important roles in various cellular signaling processes such as development and differentiation. These genes were also found to be significantly related to several cancer. However, little is known about the role of eFGFs in colon neoplasia and colon adenocarcinoma (COAD). MethodsWe performed systematically and comprehensively investigated the gene expression, DNA methylation, prognostic significance, genetic alteration, co-expressed genes, protein-protein interaction, small molecules pathway, and drug interactions of eFGFs based on the TIMER2.0, GEPIA2, UALCAN, OncoDB, cBioPortal, LinkedOmics, STRING, SMPDB, htfTarget, mirTarBase, circBank and DGIdb databases. Ultimately, the correlations of eFGFs expressions between polyp and COAD tissues compared to normal mucosa were validated using qRT-PCR as a cross-sectional part of our study. ResultsThe results indicated that eFGFs are highly expressed in COAD, and abnormal gene expressions may be related to promoter methylation. In this matter, methylation analysis revealed promotor hypermethylation of FGF19 and FGF21. Conversely, FGF23 was shown to have a tendency for promotor hypomethylation. Moreover, hypermethylation of FGF21 and FGF23 and downregulation of FGF23 were found to be detrimental to the survival of COAD patients. KEGG pathway analyses indicated that the co-expressed genes of eFGF family members were mainly related to the regulation of the actin cytoskeleton and, more notably, in Ras signaling, PI3k-Akt signaling, Rap1 signaling, and cancer pathways. Based on qRT-PCR results, FGF21 was significantly overexpressed in the colon polyps compared to normal mucosa. Additionally, RNA expression of FGF21 and FGF23 was markedly elevated in adenomatous polyps as opposed to hyperplastic polyps. ConclusionCollectively, these findings reveal the critical roles of eFGFs in COAD tumorigenesis and suggest eFGF family members as promising prognostic and diagnostic markers for CRC as well as discriminating markers for high-risk from low-risk polyps.

bioinformatics↗