HC102A

Infectious-disease experiments test how pathogens interact with host barriers, innate immune receptors, inflammatory signaling, pathogen replication, and tissue injury; pattern-recognition receptors such as TLRs, RIG-I-like receptors, NOD-like receptors, and inflammasomes detect microbial molecules and activate NF-κB, interferon, and cytokine responses. The central hypothesis is that infection severity reflects the balance between pathogen burden and host response: protective inflammation restricts pathogen growth, whereas excessive or mislocalized inflammation contributes to tissue damage and disease phenotype. Unresolved questions include which host pathways are protective versus pathogenic, why some infection models fail to translate to human disease, and which combined readouts best predict clinically relevant infection outcomes.

Cytotoxicity assays are usually based on the assessment of cell membrane damage, which can also be indirectly detected by measuring cell viability. Detection methods include MTT assay, CKK-8 assay, LDH assay and ATP assay, etc.

ROS/oxidative-stress fluorescent staining uses cell-permeant fluorogenic probes that become fluorescent after oxidation inside cells or tissues; commonly used examples include DCFH-DA/DCFDA for broad cellular oxidant detection, DHE for superoxide-related signal detection, MitoSOX for mitochondrial superoxide-related signal detection, and CellROX probes for oxidative-stress-associated fluorescence readouts. The assay detects probe oxidation rather than a single ROS species unless the probe and analysis method have been chemically validated for that species. DCFH-DA enters cells, is deacetylated by intracellular esterases to DCFH, and produces fluorescent DCF after oxidation, so the readout is used as an operational measure of total cellular oxidative stress rather than a species-specific ROS measurement. DHE and MitoSOX can report superoxide-related oxidation, but red fluorescence alone can include non-specific ethidium-like oxidation products; HPLC or optimized spectral approaches are